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Graduate Studies The Vault: Electronic Theses and Dissertations

2014-01-17

AUSIA Framework to Improve On-Site Communication

in the Commercial Construction Industry

Silva, Andarage

Silva, A. (2014). AUSIA Framework to Improve On-Site Communication in the Commercial

Construction Industry (Unpublished doctoral thesis). University of Calgary, Calgary, AB.

doi:10.11575/PRISM/25069

http://hdl.handle.net/11023/1271

doctoral thesis

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UNIVERSITY OF CALGARY

AUSIA Framework to Improve On-Site Communication in Commercial Construction

Industry

by

Andarage Lahiru Purna Silva

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF CIVIL ENGINEERING

CALGARY, ALBERTA

NOVEMBER, 2013

© ANDARAGE LAHIRU PURNA SILVA 2013

iv

Abstract

Information has the best value when it is delivered to the correct place at the

correct time in the required format. Many scholars have noted information and

communication chaos in the construction industry. Inadequate communication and non-

availability of information were well observed in almost all construction projects

reviewed in this study, which caused low productivity. Further, workers also emphasized

inadequate communication in their working environment as a cause for low productivity.

Construction companies, with the help of technology developers, are trying to incorporate

numerous software/hardware systems to improve on-site communication. However, these

isolated systems may create more confusion in construction projects, due to the mismatch

of the software and hardware systems. Site observations reveal that supervisory staff lose

more than two hours a day as a result of ineffective information management.

The AUSIA framework discussed in this PhD thesis is a communication platform

based on information integration and field automation with an information hub called the

i-Booth. This framework integrates several other information/communication

technologies. There have been extensive pilot site implementation for prolonged periods

in commercial construction settings with very satisfactory results. The AUSIA

framework has been developed to improve accessibility of information while enhancing

the end user satisfaction and usefulness of the data through information integration. This

automated system ensures that the site and office can communicate in real time to

minimise time wastage and productivity loss due to ineffective information management.

The framework was implemented in a commercial construction project for one

year and the level of communication was measured before and after implementation.

v

Field staff judged improvement in communication through a survey instrument.

Statistical analysis was performed to determine enhancements in communication.

Communication was judged according to ten information categories and analysis revealed

that research subjects overall perception on communication was improved compared to

the earlier state, while increasing their perception on information integration and field

automation significantly. Field staff appreciated that virtual design and construction were

integrated with the field level through an infrastructure to interact with models, with

minimal training. With the conclusion of the research the AUSIA framework was

successfully commercialized and the first kiosk was sold in early 2013 to a general

contractor.

vi

Acknowledgements

I would like express my gratitude for the guidance given to me by my supervisor,

Prof. Janaka Ruwanpura. I have been extremely lucky to have a supervisor who has

provided me with motivation, enthusiasm, and invaluable advice. I'd like to thank him for

allowing me the space and freedom I needed to work. I would also like to thank my co-

supervisor, Dr. Kasun Hewage, who guided me from the very beginning of my research

and who has been a source of inspiration to me. I'm very grateful for the numerous

discussions and arguments to reshape the research.

I would also like acknowledge Prof. George Jergeas and Prof. Frank Maurer of

my supervisory committee for providing me with insightful comments. A special thank

you to my fellow graduate students Gamini Weerasinghe, Jamal Siadat, Sulochana

Madanayake, and Tharindu Weerasinghe, and the technical staff of the Department of

Civil Engineering, especially Terry Quinn, Daniel Larson, and Mirsad Berbic for their

support. I would like to recognise the efforts of Dr. Kamal Ranaweera for his help in

developing the software platform. My sincere gratitude to members of CCA and

FIATECH, especially to Dave Smith, Dr. Richard Jackson, and Nicole Testa Boston for

the support and feedback provided throughout the research.

I'm grateful for the funding and support provided for this research project by Ellis

Don, Graham, PCL, and Ledcor companies, the Construction Research Institute of

Canada, the Canadian Construction Research Board, the Calgary Construction

Association, and the Natural Sciences Engineering Research Council (NSERC). My

sincere gratitude to Bruce White, Bruce Sonnenberg, and staff members of PCL

Construction, especially Derek Pearce, Ron Patterson, and Bob Genee.

vii

I would like to express my earnest gratitude to my parents for providing me with

an excellent foundation for life and for their unconditional support throughout my

studies. And last but not least I would love to thank my wife and daughter for believing in

me, and for the help and support they provided. The best outcome from these past seven

years is finding my best friend, soul mate, and wife. I married the best person out there

for me.

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Dedication

This thesis is dedicated to my parents, my wife, and my daughter for their endless love,

guidance, and encouragement.

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Table of Contents

Approval Page ..................................................................................................................... ii Abstract .............................................................................................................................. ivAcknowledgements ............................................................................................................ viDedication ........................................................................................................................ viiiTable of Contents ............................................................................................................... ixList of Tables ................................................................................................................... xivList of Figures and Illustrations ....................................................................................... xviList of Symbols, Abbreviations and Nomenclature ......................................................... xxi

CHAPTER ONE: INTRODUCTION ..................................................................................11.1 Background ................................................................................................................11.2 Problem Definition ....................................................................................................31.3 Research Question .....................................................................................................41.4 Research Goal and Objectives ...................................................................................41.5 Research Approach ....................................................................................................51.6 Thesis Structure .........................................................................................................6

1.6.1 Chapter One: Introduction .................................................................................61.6.2 Chapter Two: Literature Review .......................................................................61.6.3 Chapter Three: Conceptual Framework and Research Methodology ...............71.6.4 Chapter Four: Data Collection, Analysis, and System Development (Pre-

Implementation) .................................................................................................71.6.5 Chapter Five: Site Implementation and Testing ................................................71.6.6 Chapter Six: Data Collection and Analysis (During Implementation) ..............71.6.7 Chapter Seven: Data Collection, Analysis, Validation of Results, and

System Development (Post-Implementation) ....................................................71.6.8 Chapter Eight: Conclusion, Recommendations, and Future Research ..............8

CHAPTER TWO: LITERATURE REVIEW ......................................................................92.1 Construction Productivity ..........................................................................................92.2 Factors Affecting Construction Labour Productivity ..............................................112.3 Current Information Management and Drawbacks .................................................172.4 Classification and Design Guidelines for Information Kiosk Systems ...................19

2.4.1 Information Kiosks ..........................................................................................192.4.2 Advertising Kiosks ..........................................................................................192.4.3 Service Kiosks .................................................................................................192.4.4 Entertainment Kiosks ......................................................................................202.4.5 Information Dissemination & Advertising Kiosks ..........................................202.4.6 Interactive Information Kiosks ........................................................................202.4.7 Transaction Kiosks ..........................................................................................21

2.5 Information Integration, Field Level Automation, and Technology Usage in Construction ...........................................................................................................22

2.5.1 IT Automation .................................................................................................222.5.2 IT Integration ...................................................................................................23

2.6 Technology Readiness Level (TRL) and System Readiness Level (SRL) ..............272.7 Technology Readiness Index (TRI) .........................................................................27

x

2.8 Touch Screen Systems (Single Touch and Human Touch) .....................................292.9 Investments on Technology and Productivity .........................................................342.10 Supervision in Construction ...................................................................................352.11 User Acceptance of Mobile Technology in the Construction Industry .................362.12 Discussion and Conclusion ....................................................................................43

CHAPTER THREE: CONCEPTUAL FRAMEWORK AND RESEARCH METHODOLOGY ...................................................................................................46

3.1 Conceptual Framework of AUSIA ..........................................................................463.2 AUSIA Framework Mind Map ................................................................................483.3 Hypothesis ...............................................................................................................493.4 Research Methodology ............................................................................................52

3.4.1 Research Phases ...............................................................................................543.4.1.1 Phase I (Objectives I & II) .....................................................................543.4.1.2 Phase II (Objectives I, II & III) ..............................................................563.4.1.3 Phase III (Objectives III and IV) ...........................................................573.4.1.4 Phase IV (Objective IV) ........................................................................59

3.5 Sample Size Selection ..............................................................................................603.6 Techniques and Tools Utilized in the Research Study ............................................62

3.6.1 Literature Review ............................................................................................623.6.2 Questionnaire Survey ......................................................................................633.6.3 Interviews ........................................................................................................633.6.4 Document Analysis .........................................................................................643.6.5 Workshops .......................................................................................................643.6.6 Site Observations .............................................................................................643.6.7 Data Analysis ...................................................................................................65

3.7 Validation and Verification of Results ....................................................................653.8 Bias Associated with the Research ..........................................................................673.9 Limitations of the Study ..........................................................................................683.10 Problems Encountered and Solutions Provided .....................................................693.11 Conclusion .............................................................................................................70

CHAPTER FOUR: DATA COLLECTION, ANALYSIS AND SYSTEM DEVELOPMENT (PRE-IMPLEMENTATION) .....................................................72

4.1 State of Information Management in the Construction Industry in North America ..................................................................................................................72

4.2 AUSIA System Development ..................................................................................894.2.1 Zero Generation (Information Booth) .............................................................894.2.2 First Generation (i-Booth) ...............................................................................90

4.2.2.1 Shop Drawings .......................................................................................954.2.2.2 Changes ..................................................................................................98

4.2.3 First Generation AUSIA Framework System Architecture ...........................1004.3 Software Developers Contribution ........................................................................1064.4 Conclusion .............................................................................................................106

CHAPTER FIVE: SITE IMPLEMENTATION AND TESTING ...................................1085.1 Site Selection .........................................................................................................109

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5.2 Existing Information Handling ..............................................................................1115.3 Activity Monitoring ...............................................................................................1135.4 Integrating AUSIA Framework with Operational Level .......................................115

5.4.1 Location Selection .........................................................................................1155.4.2 Information & Communication Management ...............................................1165.4.3 Feedback Received & Modifications ............................................................118

5.5 Project Success ......................................................................................................1185.6 Main Objectives Satisfied By Site Implementation ...............................................1205.7 Conclusion .............................................................................................................120

CHAPTER SIX: DATA COLLECTION AND ANALYSIS (DURING IMPLEMENTATION) ...........................................................................................122

6.1 Hypothesis Testing ................................................................................................1226.2 Comparing the Site Group with the Online Group ................................................1376.3 Conclusion .............................................................................................................146

CHAPTER SEVEN: DATA COLLECTION, ANALYSIS, VALIDATION OF RESULTS, AND SYSTEM DEVELOPMENT (POST-IMPLEMENTATION) ...147

7.1 User Acceptance of AUSIA Framework ...............................................................1497.2 Validation of Site Implementation Results ............................................................1567.3 Modified AUSIA Framework (Second Generation i-Booth) ................................159

7.3.1 Types of Kiosks .............................................................................................1617.3.2 Hardware Components for the Kiosk ............................................................163

7.3.2.1 Touch Screen .......................................................................................1637.3.2.2 Key Board & Track Ball ......................................................................1637.3.2.3 Ruggedized Printer ..............................................................................1647.3.2.4 Capture Pen ..........................................................................................1647.3.2.5 BIM 3D Mouse ....................................................................................1657.3.2.6 Document Scanner ...............................................................................1657.3.2.7 GPS Tracking Device ..........................................................................165

7.3.3 Access Control Methods ................................................................................1667.3.4 Mobile Handheld Devices to Integrate with Kiosk .......................................1667.3.5 Software Components for the Kiosk .............................................................168

7.3.5.1 PDF Editor and Viewer ........................................................................1687.3.5.2 BIM Viewer/Autodesk Navisworks Freedom .....................................1707.3.5.3 DWF and DWG Viewers .....................................................................170

7.3.6 Information Arrangement in The System ......................................................1717.3.6.1 Design Drawings ..................................................................................1717.3.6.2 Shop Drawings .....................................................................................1727.3.6.3 Specifications .......................................................................................1737.3.6.4 Quality .................................................................................................174

7.4 Distribution Matrix ................................................................................................1747.5 Commercial AUSIA Framework (2nd Generation i-Booth) ...................................1757.6 Final Acceptance Testing .......................................................................................1787.7 BVG Sessions ........................................................................................................1817.8 Software Developers Contribution ........................................................................1817.9 Conclusion .............................................................................................................182

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CHAPTER EIGHT: CONCLUSIONS, RECOMMENDATIONS, AND FUTURE RESEARCH ............................................................................................................184

8.1 Research Summary ................................................................................................1848.2 Research Outcome/Findings ..................................................................................1858.3 Research Contribution ...........................................................................................1888.4 Research Limitations .............................................................................................1908.5 Future Research and Recommendations ................................................................191

REFERENCES ................................................................................................................193

APPENDIX I – COMBINED SUMMARY OF PRODUCTIVITY FACTORS .............204

APPENDIX II - SUMMARY OF HUMAN ASPECTS IN KIOSK DESIGN ................206

APPENDIX III – COMPLETE LIST OF HYPOTHESIS FOR AUSIA FRAMEWORK.......................................................................................................210

APPENDIX IV - CONFIDENTIALITY AGREEMENT................................................220

APPENDIX V - INFORMATION MANAGEMENT QUESTIONNAIRE (ONLINE) .227

APPENDIX VI - TECHNOLOGY READINESS INDEX (TRI) QUESTIONNAIRE ..230

APPENDIX VII – TIME WASTE DATA ENTRY SHEET ...........................................235

APPENDIX VIII - PRESENT STATE OF INFORMATION MANAGEMENT ...........236

APPENDIX IX – ERROR MARGIN CALCULATION FOR SAMPLE SIZE ..............240

APPENDIX X – TOOL TIME OBSERVATION SHEET ..............................................241

APPENDIX XI – DEMO SOFTWARE OVERVIEW ....................................................242

APPENDIX XII – PRESENT INFORMATION FLOW.................................................245

APPENDIX XIII - EVALUATION OF FIELD MANAGEMENT PERSONNEL ........249

APPENDIX XIV - INFORMATION MANAGEMENT AFTER IMPLEMENTATION .............................................................................................251

APPENDIX XV – KOLMOGOROV–SMIRNOV TEST STATISTICS ........................255

APPENDIX XVI – PREFERENCE CHANGE BEFORE AND AFTER IMPLEMENTATION .............................................................................................257

APPENDIX XVII – ACCEPTANCE TESTING WORKSHOP INSTRUMENT ..........262

APPENDIX XVIII - IMPLEMENTATION OF DIGITAL PEN ....................................263

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APPENDIX XIX - COST BREAKDOWN AND RECOVERY OF INVESTMENT FOR I-BOOTH SOFTWARE DEVELOPMENT ..................................................265

APPENDIX XXI – PERMISSION TO REUSE COPYRIGHTED MATERIAL ...........272

xiv

List of Tables

Table 2.1: Normalized Values for the Factors/Parameters (Modified .............................. 13

from Moselhi and Khan 2010) .......................................................................................... 13

Table 2.2: Characteristics of Technology Segments (Adopted from Parasuraman, 2000) ......................................................................................................................... 29

Table 2.3: Summary of Available Touch Screen Technologies ....................................... 31

Table 3.1: Null Hypothesis for Drawings ......................................................................... 51

Table 3.2: Alternative Hypothesis for Drawings .............................................................. 51

Table 4.1: Time Waste Due to Inappropriate Information Management/Communication ................................................................................... 88

Table 5.1: Tool-Time Observation Intervals .................................................................. 114

Table 5.2: Summary of Information Management ......................................................... 117

Table 6.1: Wilcoxon Signed Ranked Test Statistics Table ............................................. 124

Table 6.2: Wilcoxon Signed Ranks of Drawings ............................................................ 125

Table 6.3: Mann-Whitney U-Test Statistics Table for Drawings and Changes ............. 141

Table 6.4: Mann-Whitney U Test Statistics Table for Safety and Schedule .................. 142

Table 6.5: Mann-Whitney U Test Statistics Table for Material and 3D/4D Models ...... 143

Table 6.6: Mann-Whitney U Test Statistics Table for Weather and Technical .............. 144

Table 6.7: Mann-Whitney U Test Statistics Table for Quality and Certifications ......... 145

Table 7.1: Access Control Methods ................................................................................ 166

Table 7.2: Handheld Devices .......................................................................................... 167

Table 7.3: Acceptance Testing Survey - 2nd Generation i-Booth (AUSIA Framework) 180

Table A1: Null and Alternative Hypothesis for Drawings ............................................. 210

Table A2: Null and Alternative Hypothesis for Changes ............................................... 211

Table A3: Null and Alternative Hypothesis for Safety Information ............................... 212

Table A4: Null and Alternative Hypothesis for Schedule Information .......................... 213

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Table A5: Null and Alternative Hypothesis for Material Information ........................... 214

Table A6: Null and Alternative Hypothesis for 3D/4D Models ..................................... 215

Table A7: Null and Alternative Hypothesis for Quality Related Information ................ 216

Table A8: Null and Alternative Hypothesis for Certifications ....................................... 217

Table A9: Null and Alternative Hypothesis for Weather Information ........................... 218

Table A10: Null and Alternative Hypothesis for Technical Information ....................... 219

Table A11: K-S Test Before Implementation ................................................................. 255

Table A12: K-S Test After Implementation ................................................................... 256

Table A13: Wilcoxon Signed Ranks of Drawings .......................................................... 257

Table A14: Wilcoxon Signed Ranks of Changes (SI, RFI, PCN) .................................. 257

Table A15: Wilcoxon Signed Ranks of Safety ............................................................... 258

Table A16: Wilcoxon Signed Ranks of Schedule ........................................................... 258

Table A17: Wilcoxon Signed Ranks of Material ............................................................ 259

Table A18: Wilcoxon Signed Ranks of 3D/4D Models ................................................. 259

Table A19: Wilcoxon Signed Ranks of Quality ............................................................. 260

Table A20: Wilcoxon Signed Ranks of Certifications ................................................... 260

Table A21: Wilcoxon Signed Ranks of Weather ............................................................ 261

Table A22: Wilcoxon Signed Ranks of Technical ......................................................... 261

Table A23: Cash Flow Forecast for Next 3 Years .......................................................... 266

Table A24: AUSIA Framework Hardware Cost ............................................................. 267

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List of Figures and Illustrations

Figure 1.1: Labour Productivity Index: 2002-2011, Construction (NAICS 23) (Industry Canada, 2013) .............................................................................................. 2

Figure 2.1: Relative Contribution of Parameters in Daily Labour Productivity (Modified from Moselhi and Khan 2012) ................................................................. 12

Figure 2.2: Productivity as a Function of Individual Parameters/Factors (Moselhi and Khan 2010) ................................................................................................................ 13

Figure 2.3: Productivity as a Function of Temperature and Humidity (Moselhi and Khan 2010) ................................................................................................................ 15

Figure 2.4: Relationship Between Factors and Construction Productivity (Nasirzadeh and Nojedehi 2013) ................................................................................................... 16

Figure 2.5: Classification of Kiosk Systems ..................................................................... 21

Figure 2.6: Conceptual Diagram of Technology Readiness (Parasuraman, 2000) ........... 28

Figure 2.7: One-handed and Two-handed Interaction (Adopted from Song-Gook et al, 2007) ......................................................................................................................... 33

Figure 2.8: Total Time Distribution of a Typical Foreman (Modified from Gannoruwa 2008) ......................................................................................................................... 35

Figure 2.9: Breakdown of Survey Respondents According to Industry Sector (Modified from FIATECH, 2013) ............................................................................ 37

Figure 2.10: Value of Mobile Technologies for Design and Specifications in Field Reporting (Modified from FIATECH, 2013) ........................................................... 38

Figure 2.11: Value of Mobile Technologies for Project Control in Field Reporting (Modified from FIATECH, 2013) ............................................................................ 40

Figure 2.12: Value of Mobile Technologies for Quality in Field Reporting (Modified from FIATECH, 2013) .............................................................................................. 41

Figure 2.13: Value of Mobile Technologies for Safety in Field Reporting (Modified from FIATECH, 2013) .............................................................................................. 42

Figure 2.14: Value of Mobile Technologies for Material Management in Field Reporting (Modified from FIATECH, 2013) ........................................................... 42

Figure 2.15: Value of Mobile Technologies for Project Delivery in Field Reporting (Modified from FIATECH, 2013) ............................................................................ 43

Figure 3.1: Conceptual Framework .................................................................................. 47

xvii

Figure 3.2: AUSIA Mind Map .......................................................................................... 49

Figure 3.3: Research Flow Diagram ................................................................................. 53

Figure 4.1: Distribution of Research Subjects According to Industry Sector ................... 73

Figure 4.2: Distribution of Research Subjects According to Years of Experience .......... 73

Figure 4.3: Methods Used To Disseminate Information According to Research Subjects ..................................................................................................................... 74

Figure 4.4: Methods of Updating Information According to Research Subjects ............. 75

Figure 4.5: Issues/Problems Industry Faced with Information Integration, Updating, and Dissemination ..................................................................................................... 76

Figure 4.6: Participants’ Willingness to Deploy Soft Copies on Site ............................... 78

Figure 4.7: Reason for Deployment and Non Deployment of Soft Copies ...................... 78

Figure 4.8: Issues/Problems the Industry Faced when Deploying Soft Copies ................ 79

Figure 4.9: Organizational Expertise on 3D/4D Model Usage ......................................... 80

Figure 4.10: Methods of Using and Integrating 3D/4D Models at the Site Level ............ 81

Figure 4.11: Purposes of 3D/4D Models at Site Level ..................................................... 82

Figure 4.12: Infrastructure Available to Access 3D/4D Models at Site Level ................. 84

Figure 4.13: Issues/Problems Industry Faced with Deployment of 3D/4D Models ......... 85

Figure 4.14: Zero Generation (Information Booth) .......................................................... 90

Figure 4.15: First Generation i-Booth ............................................................................... 92

Figure 4.16: Demonstration Graphical User Interface (GUI) of First Generation i-Booth ......................................................................................................................... 93

Figure 4.17: Information Flow Chart for a Rebar Shop Drawing ..................................... 96

Figure 4.18: Information Flow Chart for a Formwork Shop Drawing ............................. 98

Figure 4.19: Information Flow Chart for a Request for Information (RFI) ...................... 99

Figure 4.20: Information Flow Chart for a Site Instruction (SI)..................................... 100

Figure 4.21: First Generation Framework (i-Booth) ....................................................... 102

xviii

Figure 4.22: Graphical User Interface (GUI) of First Generation i-Booth ..................... 103

Figure 4.23: Hierarchical Classification of First Generation i-Booth ............................. 104

Figure 4.24: Drawing Menu ............................................................................................ 105

Figure 5.1: Project Site Plan ........................................................................................... 108

Figure 5.2: Project Working Time Analysis ................................................................... 115

Figure 6.1: Research Subjects Perception Change Regarding AUSIA of Drawings Category after Implementation ............................................................................... 126

Figure 6.2: Research Subjects Perception Change Regarding AUSIA of Changes Category after Implementation ............................................................................... 127

Figure 6.3: Research Subjects Perception Change Regarding AUSIA of Safety Category after Implementation ............................................................................... 128

Figure 6.4: Research Subjects Perception Change Regarding AUSIA of Schedule Category after Implementation ............................................................................... 129

Figure 6.5: Research Subjects Perception Change Regarding AUSIA of Changes Category after Implementation ............................................................................... 130

Figure 6.6: Research Subjects Perception Change Regarding AUSIA of 3D/4D Models Category after Implementation .................................................................. 131

Figure 6.7: Research Subjects Perception Change Regarding AUSIA of Materials Category after Implementation ............................................................................... 132

Figure 6.7: Research Subjects Perception Change Regarding AUSIA Certifications Category after Implementation ............................................................................... 133

Figure 6.9: Research Subjects Perception Change Regarding AUSIA of Weather Category after Implementation ............................................................................... 134

Figure 6.10: Research Subjects Perception Change Regarding AUSIA of Technical Category after Implementation ............................................................................... 135

Figure 6.11: Research Subjects Overall Perception Change Regarding AUSIA after Implementation ....................................................................................................... 137

Figure 6.12: Distribution of Research Subjects According to Industry Sector ............... 138

Figure 6.13: Distribution of Research Subjects According to Years of Experience ...... 139

Figure 7.1: Distribution of Research Subjects According to Industry Sector ................ 147

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Figure 7.2: Distribution of Research Subjects According to Years of Experience ........ 148

Figure 7.3: Participants Awareness of i-Booth ............................................................... 148

Figure 7.4: Participants Willingness to Deploy i-Booth ................................................. 149

Figure 7.5: Participants preference on Best Location to Keep i-Booth .......................... 150

Figure 7.6: Methods to Encourage End-Users to Utilize i-Booth ................................... 150

Figure 7.7: Participants Preference of Access Control ................................................... 151

Figure 7.8: Participants Preference of Access Control Methods for i-Booth ................. 152

Figure 7.9: User Ratings on Value Addition from Input Devices .................................. 153

Figure 7.10: Categorization of Essential and Optional Hardware Items According to Online Participants Preference ................................................................................ 154

Figure 7.11: Categorization of Essential and Optional Hardware Items According to On-Site Participants Preference .............................................................................. 154

Figure 7.12: Online Participants Perception on Value Addition from Input Devices .... 155

Figure 7.13: On-Site Participants Perception on Value Addition from Input Devices ... 156

Figure 7.14: Online Participants Perception on Benefits of i-Booth .............................. 157

Figure 7.15: On-Site Participants Perception on Benefits of i-Booth ............................. 158

Figure 7.16: Conceptual AUSIA Framework (Second Generation i-Booth) .................. 160

Figure 7.17: Mobile Kiosk .............................................................................................. 162

Figure 7.18: Wall-mounted Kiosk .................................................................................. 162

Figure 7.19: Level 3 Concrete Beam Schedule Integrated with Site Instructions .......... 169

Figure 7.20: 3D Interactive PDF Model (Adobe, 2013) ................................................. 170

Figure 7.21: Classification of Design Drawings ............................................................. 172

Figure 7.22: Classification of Shop Drawings ................................................................ 173

Figure 7.23: Classification of Specifications .................................................................. 173

Figure 7.24: Classification of Quality ............................................................................. 174

Figure 7.25: Three 'I' Principles of AUSIA Framework ................................................. 176

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Figure 7.26: Integration in AUSIA Framework .............................................................. 177

Figure 7.27: GUI of Second Generation i-Booth ............................................................ 178

Figure 8.1: Digital Drawing Table .................................................................................. 192

xxi

List of Symbols, Abbreviations and Nomenclature

Abbreviation Definition AEC Architectural Engineering and Construction

ATM Automated Teller Machine

BIM Building Information Modeling

BVG Business Validation Group

CCA Calgary Construction Association

CO Change Order

CAD Computer-Aided Design

CII Construction Industry Institute

CLP Construction Labour Productivity

COAA Construction Owners Association of Alberta

CSI Construction Specifications Institute

CR Contemplated Revisions

DoD Department of Defence

D/IT Design/Information Technology

DWF Design Web Format

DWG DraWinG

EDI Electronic Data Interchange

EPC Engineering Procurement and Construction

ERP Enterprise Resource Planning

FIATECH Fully Integrated and Automated Technologies for Construction

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Abbreviation Definition GUI Graphical User Interface

HID Human Interface Devices

ICT Information and Communication Technology

IT Information Technology

IPD Integrated Project Delivery

IFC Issued for Construction

LEED Leadership in Energy and Environmental Design

MSDS Material Safety Data Sheets

NASA National Aeronautics and Space

Administration

NSERC Natural Sciences and Engineering Research

Council

PDA Personal Digital Assistant

PIN Personal Identification Number

PDF Portable Document Format

PDS Portable Document Solutions

PCN Project Change Notice

QA/QC Quality Assurance/Quality Control

QR Quick Reference

RFI Request for Information

ROI Return on Investment

SI Site Instructions

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Abbreviation Definition SIM Subscriber Identity Module

SRL System Readiness Level

TRI Technology Readiness Index

TRL Technology Readiness Level

3D Three Dimensional

TFP Total Factor Productivity

UPS Uninterrupted Power Supply

UofC University of Calgary

VDC Virtual Design and Construction

1

Chapter One: Introduction

This chapter briefly explains the nature of the construction industry in Canada and

the importance of construction productivity improvement. The rest of the chapter

discusses the structure of the thesis, the research approach, and the research objectives.

1.1 Background

The Construction Sector Council's (Build Force) forecast for 2011-2019 reports a

shortage of nearly 40,000 workers in Alberta. The construction industry in Alberta

employs about 140,000 workers and the Construction Sector Council report (2012)

predicts this will increase to 200,000 by 2019. The solution to this problem is to either

bring workers from outside into Alberta’s construction market or increase the

construction labour productivity of the existing work force. Industry associations such as

the Calgary Construction Association are trying to bridge the gap by introducing

programs to attract youth, women, and aboriginal communities to the construction

industry. As construction labour amounts to an average of 20% to 50% of the direct

capital cost of a project, the industry must find a method to arrest declining productivity

(Buchan et al., 1993; Hwang et al., 2013). Many researchers have reported a decline in

construction productivity across North America since the mid-1970’s (Heale, 1993).

Research studies conducted in different parts of the world have also reported declining or

stagnant construction productivity over the past few decades (Ganesan, 1984; The

Business Roundtable, 1989; Dozzi & Abourizk, 1993; McTague & Jergeas, 2003). A

recent study conducted by the Construction Industry Institute (CII), the Construction

Owners Association of Alberta (COAA), and Alberta Finance and Enterprise revealed

2

that construction productivity of concrete and instrumentation are worse than in the US

gulf coast, while structural steel productivity is comparable. As average wage rates in

Alberta are higher than in the US, improved productivity in Alberta will enhance the

competitive edge (Construction Industry Institute, 2009). According to Industry Canada,

from 2002-2011 labour productivity in the construction sector decreased 0.7% per year

on average while labour productivity (construction labour productivity is simply the time

taken to produce a unit amount or the amount made in a unit time) for the Canadian

economy increased 1.7% per year (see Figure 1.1 below).

Figure 1.1: Labour Productivity Index: 2002-2011, Construction (NAICS 23) (Industry Canada, 2013)

There was a positive trend reported in 2009, but compared to the increase in

Canadian economy this increase was negligible (in 2011 labour productivity in the

construction sector increased by 0.4%, compared to a 3.0% increase for the Canadian

economy).

3

1.2 Problem Definition

The University of Calgary (U of C) initiated a research project in collaboration

with leading construction companies in Alberta, and the Natural Sciences and

Engineering Research Council (NSERC) to find solutions for declining construction

productivity. This research team reported inadequate communication as a primary reason

for the decline in construction productivity (Hewage and Ruwanpura, 2006b). This

research team proposed and pilot tested an interactive information kiosk to bridge the

communication gap.

Significant value may be gained by the construction industry if technology could

be leveraged more effectively to improve its productivity (Goodrum et al., 2011).

Nonetheless the construction industry is lagging behind other industries in implementing

Design/Information Technology. O’Connor and Yang (2004) have investigated the

reasons for the construction industry’s reluctance to implement new technologies. They

indicated that lack of information and understanding regarding technological benefits

have contributed to the industry’s apparent technical stagnation. Hewage and Ruwanpura

(2009) conceptualized a novel solution to improve on-site communication called

‘information booth’. In order to validate this concept an information kiosk and software

infrastructure was required. Research work related to this thesis initiated with the

challenge of designing and implementing an information kiosk to improve

communication in the construction industry. The main objective of this thesis was to

design the hardware component of the kiosk and develop a high-level system architecture

(features and functions of the software).

4

1.3 Research Question

Improving both construction labour productivity and overall performance of a

construction company is the end goal of the U of C research team. According to

published literature, communication is a critical factor for improving construction

productivity. This communication deficiency in the construction industry might be

subdued by utilizing information and communication technologies.

The research question related to this thesis can be formulated as follows:

“Can an automated and integrated information system improve on-site

communication?”

1.4 Research Goal and Objectives

The main goal of this research is to develop and implement an automated and

integrated information system (AUSIA Framework) to improve on site communication in

commercial construction. The following are the defined research objectives:

Objective 1: Investigate the information flow and the bottlenecks in the

commercial construction industry in Alberta.

Objective 2: Investigate communication needs of construction workers and

field supervisors.

Objective 3: Develop an automated and integrated information management

system to improve on site communication.

Objective 4: Test and validate the automated and integrated information

management system in the actual construction field environment.

5

1.5 Research Approach

A brief description of the research evolution and research methodology is

discussed in this section. A detailed research methodology is presented in the Chapter

3.The research work in this thesis can be divided into four main phases, i.e. Phase I to

Phase IV. Phase I of the research work concentrated on investigating construction

productivity loss due to insufficient communication. Phase II dealt with finding solutions

for the issues identified in Phase I. The solutions identified in Phase II were implemented

in the Phase III. The final phase of the research focused on validating the findings from

site implementation.

Phase I of the research consisted of a comprehensive literature review before

conducting interviews and observations on construction sites. Interviews were carried out

to find the communication deficiencies in the operational level from office managers, site

managers, foremen, and lead hands. Observations were conducted to investigate

information handling and information management at the operational level. Finally, an

online survey was carried out to reinforce the findings from the interviews and

observations. Phase I of the research study revealed the deficiencies in on-site

communication.

In Phase II emphasis was on conceptualizing a framework (kiosk and software

infrastructure) to resolve the communication deficiencies. Interviews were conducted to

find suitable human interface devices (HIDs) for the proposed kiosk and user acceptance.

The next phase emphasized on site implementation of the proposed solution. Initially a

time motion study was conducted to assess the site conditions, then workshops were

conducted to evaluate the present level of communication. Another survey was conducted

6

to determine time wasted due to poor information management. The framework was

implemented for twelve months in a commercial construction site in Calgary. After

implementation of the framework was concluded workshops were conducted to evaluate

the change in level of communication.

The final phase focused on validating the outcomes from the previous phase. Two

workshops and one acceptance test was conducted to verify the results gathered from

implementation.

1.6 Thesis Structure

The thesis consists of eight chapters and each chapter is briefly discussed below.

1.6.1 Chapter One: Introduction

Chapter One consists of a brief overview of the research, research question,

research objectives, research approach, and structure of the thesis. This chapter discusses

the nature of the Canadian construction industry and rationale behind the research.

1.6.2 Chapter Two: Literature Review

Chapter Two provides an introduction to the productivity concepts and factors

affecting productivity. This chapter also discusses current information management

practices, design guidelines and kiosk classifications, information integration and

automation, touch screen systems, technology readiness level/index, and supervision in

construction.

7

1.6.3 Chapter Three: Conceptual Framework and Research Methodology

This chapter explains the development of the research methodology, conceptual

framework, research design, associated research tools, and techniques used to analyse and

validate the result. This also includes the constraints and limitations of the research study.

1.6.4 Chapter Four: Data Collection, Analysis, and System Development (Pre-Implementation)

This consists of the current state of information management based on results

from interviews and site observations. The latter half of the chapter consists of step by

step development of the first generation information system.

1.6.5 Chapter Five: Site Implementation and Testing

This chapter describes how the AUSIA framework was implemented, tools and

techniques adopted to collect data, and how testing was carried out.

1.6.6 Chapter Six: Data Collection and Analysis (During Implementation)

This chapter describes qualitative and quantitative analysis methods used to

investigate the real impact of the implemented AUSIA framework on communication and

construction productivity.

1.6.7 Chapter Seven: Data Collection, Analysis, Validation of Results, and System Development (Post-Implementation)

User acceptance of the AUSIA framework, validation of results, and development

of the second generation AUSIA framework based on lessons learned are discussed. A

8

briefing about the cost benefit analysis of the AUSIA framework from both solution

provider perspective and client perspective is included.

1.6.8 Chapter Eight: Conclusion, Recommendations, and Future Research

This chapter provides conclusions and recommendations for future research based

on the findings from the research project.

9

Chapter Two: Literature Review

This chapter consists of literature pertaining to this thesis in the following

knowledge areas: construction productivity, information management, information

technology, information integration and field automation, technology readiness, and

readiness of workforce.

Inadequate communication and management factors are critical issues that lead to

declining construction productivity (Dozzi and Abourizk, 1993). Liberda et al (2003)

identified fifty-one factors related to the decline in construction productivity in Alberta.

Thirty-five of those factors are significantly related to poor management practices in the

construction industry. Site management is directly responsible for more than 50% of the

time wasted due to poor management practices (Haas et al., 1999). Supervisory staff

plays a key role in communicating with workers and spends a significant amount of time

with them during a work day (Gannoruwa and Ruwanpura, 2008). Therefore, better

utilization of supervision time is a critical factor to improve efficiency and productivity

of construction work.

2.1 Construction Productivity

The terms related to productivity include construction productivity, labour

productivity, and on-site productivity. Many terms are used to describe productivity in

the construction industry: performance factor, production rate, unit person hour rate, and

so on. Construction Labour Productivity (CLP) can be simply defined as output generated

per unit input. However, the meaning of “productivity” varies with its application to

different areas of the construction industry. Definitions range from industry wide

10

economic parameters to the measurement of crews and individuals. Each of these

measures has its own unique purpose (Jergeas and McTague, 2002). In the construction

business, the inputs can be comprised of labour, materials, machinery, tools, time,

information and capital, etc., whereas the output includes the finished product (e.g. a

building) in a dollar value or specific unit of measurement. Method of measuring the

output will vary depending on the activity, for example by measuring the liner meters,

square meters, and cubic members or by weight. According to Dozzi and AbouRizk

(1993), traditionally, productivity is defined as a ratio of input/output, i.e. the ratio of the

input of an associated resource to a real output in creating economic value. Even though

productivity is generally accepted as the amount of output produced by one unit of input,

the above mentioned work by Dozzi and AbouRizk (1993), Thomas et al. (1999), and

Rowings Jr. and Sonmez (1996) analyzed productivity reciprocally, as the ratio of the

input of associated resources to output. Scholars emphasized that construction labour

productivity is essentially a single factor measure of productivity and it relates to an

output to only the labour work hours expended in the generation of that output. But Noor

(1992) and Thomas et al. (1990) expressed it mathematically:

(2.1)

Many scholars have discussed Total Factor Productivity (TFP) as a concept

gaining in importance because the more popular measure of labour productivity or value

added per unit labour suffers from the shortcoming that it does not reveal why the

productivity has risen or fallen. It could be due to fluctuations of input of capital

expenditure, or labour work hours. The TFP approach attempts to go into the “why” of

11

productivity changes and thus gives deeper insight into the underlying causes and

sustainability of growth or production. Overheads are the operating expenses of the

business (or simply the running cost.)

(2.2)

2.2 Factors Affecting Construction Labour Productivity

Construction productivity is influenced by many factors, thus many researchers

have tried to identity relationships between these factors. Based on the research work

conducted by the University of Concordia, researchers Moselhi and Khan (2012)

concluded that “temperature most significantly affects daily performance and the type of

work being executed is the second most important parameter affecting the daily outputs”.

Several researchers have worked on the effect of climate on productivity and Koehn and

Brown (1985) have reported that it is difficult to achieve efficient construction operations

below -10oF (-23.3oC) and above 110oF (43.38oC). Especially in Calgary, Alberta, during

the winter season, temperature changes significantly. As a result researchers cannot

isolate the productivity change due to the technology implemented. Figure 2.1 below

represents the contribution from each factor to construction labour productivity.

12

Figure 2.1: Relative Contribution of Parameters in Daily Labour Productivity (Modified from Moselhi and Khan 2012)

Many researchers around the world have investigated the factors affecting

construction labour productivity. Recent publications by Khaled and Remon (2013)

summarise factors affecting construction labour productivity worldwide. In this thesis,

information from Canada and other countries has been included with the summary

developed by Khaled and Remon (the combined summary is in Appendix –1). Moselhi

and Khan (2010) developed a set of equations to predict the influence of six different

factors (temperature, humidity, wind speed, gang size, labour percent, and floor level) on

construction labour productivity (see Figure 2.2 below). The six variables were

normalized between zero and one in the X axis, and daily productivities were normalized

in the Y axis. The normalized values for the six variables are given in Table 2.1 below.

The same normalized values are used for Figure 2.3 below.

13

Table 2.1: Normalized Values for the Factors/Parameters (Modified

from Moselhi and Khan 2010)

Parameter Normalised value Actual value

Temperature (oC) 0 -26 1 25

Humidity (%) 0 18 1 97

Wind Speed 0 3 1 43

Gang size 0 8 1 24

Labour (%) 0 29 1 47

Height (no. of floors)

0 1 1 17

Figure 2.2: Productivity as a Function of Individual Parameters/Factors (Moselhi and Khan 2010)

14

Based on these graphs, temperature has a positive correlation, and maximum daily

productivity is reported around twenty degrees Celsius. Gang size also has a positive

correlation as daily productivity has improved with the increase of gang size. On the

other hand work crew should be increased based on the available work space. Otherwise

site work may be affected due to congestion and this in turn will negatively affect labour

productivity (Chang et al., 2007). Daily labour productivity tends to increase with the

floor level until the eighth floor and afterwards the increase is drastically reduced.

Learning curve also plays a major role in increase in productivity (Couto & Teixeira,

2005) while an increase of number of floors reduces the worker efficiency. Increase in

humidity, labour percent, and wind speed have a slight negative effect on daily labour

productivity. On the other hand excessive wind speeds completely shut down the

construction sites for safety reasons.

Moselhi and Khan (2010) also developed a 3D function of productivity with

temperature and humidity (see Figure 2.3 below). The normalized values for the

factors/parameters are given above in Table 2.1. Temperature has a significant impact on

daily labour productivity in Calgary based on Figure 2.3 below (based on the assumption

that this model is transferable to Calgary). During the winter season, temperatures can

vary from -20oC to 20oC frequently. As a result productivity can vary more than 50%.

15

Figure 2.3: Productivity as a Function of Temperature and Humidity (Moselhi and Khan 2010)

Nasirzadeh and Nojedehi (2013) also developed a set of functions to establish the

relationship between labour productivity and three key parameters authors have identified

as important (see Figure 2.4 below). These parameters are temperature, skillfulness, and

site congestion (lack of work area). According to the graph, temperature has a positive

correlation to labour productivity while congestion has a negative correlation.

Skillfulness has a positive correction as well; with the increase of skillfulness labour

productivity tends to increase. In the last graph the authors show that with the increase of

labour productivity project duration reduces drastically until a certain level (eight units of

productivity), but thereafter reduction is very minimal.

16

Figure 2.4: Relationship Between Factors and Construction Productivity (Nasirzadeh and Nojedehi 2013)

Change orders are a regular occurrence in construction industry. These changes

are inevitable and necessary. The rework associated with these changes are costly, and

frustrating to the workforce. As a result rework has an adverse effect on productivity.

Thomas & Napolitan, (1995) reported a thirty percent loss of efficiency/productivity,

when changes were performed. They also stated that lower labour performance is

strongly correlated with change work, restrictions and rework. Hanna et al., (1999)

reported a significant difference in labour efficiencies between interrupted (due to

changes) and uninterrupted projects. Scholars have also reported a negative correction

between overtime and labour productivity. Thomas & Raynar (1997) revealed that short

term overtime leads to around ten to fifteen percent productivity loss, which is consistent

with studies conducted by Business Round Table in 1980.

17

All these factors and relationships identified by researchers worldwide can be

categorized into four main areas:

Environmental Factors: Temperature, Wind Speed, etc.

Management Factors: Overtime, etc.

Human Factors: Gang Size, Skill Level, etc.

Project Factors: Floor Level, Work Method/Type, Rework, etc.

2.3 Current Information Management and Drawbacks

The U of C’s ongoing research as well as other research have identified

inadequate communication as the critical factor contributing to low productivity (Hewage

and Ruwanpura, 2006a; Bowden et al., 2006). These findings led to the development of

an Information Technology (IT) roadmap for construction by Hewage and Ruwanpura

(2006b). Inadequate communication and non-availability of information were well

observed in almost all the construction projects, which caused low productivity and tool

time around 50% in high-rise building construction projects (Hewage and Ruwanpura,

2006b). Workers emphasized that “inadequate communication” in their working

environment causes low productivity and tool time. These workers believed that the

communication lags and unavailability of information were the main reasons for low

productivity. Use of information technology to overcome communication barriers was

extremely limited at the construction site level. Construction companies typically hesitate

to adopt new technologies. However, workers expressed their willingness and ability to

use new technologies at the construction site level. The present status of technology

usage in the construction industry and current communication practices were recently

18

investigated in Alberta, Canada to develop innovative solutions to improve

communication and productivity (Hewage and Ruwanpura, 2009). One of the main

findings in this investigation was the justification of “inadequate communication”

between the various parties involved in construction projects. Almost all workers blamed

managers for the insufficient “information flow” from the site/main office to the

operational (site) levels (Hewage and Ruwanpura, 2006a). Wachira (2001) too mentioned

that 50% of construction workers usually complain about inadequacy in communication.

Two-way radios were the main communication medium between site office and

work place in the last decade. The foremen had to visit the site office regularly for

clarifications and to refer to drawings. Therefore the foremen had less time to supervise

workers and provide instructions. Workers spend about 15% to 20% of their working

time moving around the site to locate material and tools (Hewage and Ruwanpura, 2006a;

Zhang and Ruwanpura, 2008; Liu and Ruwanpura, 2007). Some workers were not even

aware of their daily schedules and targets.

Information has the best value when it is delivered to the correct place at the

correct time in the required format. It is expected that the forthcoming decade will be

governed by information management. U of C’s productivity research team proposed an

automated information kiosk system called “information booth” to overcome the above

mentioned shortcomings. The proposed system was pilot tested in a commercial

construction setting to prove that this concept is economically viable enough to build a

prototype and carry out full scale site testing.

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2.4 Classification and Design Guidelines for Information Kiosk Systems

This subsection will focus on design guidelines and how to classify the kiosk

systems to gain an in-depth understanding. Brochers et al. (1995) proposed a

classification for information kiosk systems. There are four major categories based on the

major task.

2.4.1 Information Kiosks

Information kiosks provide information in a limited subject field, for example at

railway and bus stations. Users are not extensively motivated to use the system. They

simply use it to find information on connections to intended destinations, to buy tickets,

and to get route information.

2.4.2 Advertising Kiosks

Advertising kiosks are installed by companies to advertise services and products

to the public in an attractive and innovative way. Here, the content is presented in an

interesting and entertaining manner to motivate users to explore the system further. These

kiosks are designed in a visually attractive manner to catch the attention of potential

users.

2.4.3 Service Kiosks

Service kiosks are similar to information kiosks, with the addition of information

entry by the users: for example, airport terminals where data such as name, passport

number, and flight details have to be entered to get boarding passes.

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2.4.4 Entertainment Kiosks

Entertainment kiosks are intended to provide entertainment to potential end users.

According to Brochers et al. (1995) most of the information kiosk systems will

belong to two or more of the above mentioned categories.

Morris et al. (1995) developed another classification for kiosk systems. In this

classification kiosks were categorized into 3 main types.

2.4.5 Information Dissemination & Advertising Kiosks

These are utilized to advertise products and services and to offer information to

end users in a one-way communication setting. The commands for information are

entered through a touch screen monitor and also make use of videos, animation, and

sound to convey the message to users. Such kiosk systems are widely used in schools,

trades shows and conferences, museums, and visitor centers.

2.4.6 Interactive Information Kiosks

The main functions of these systems are to automate information access and to

collect information. These systems are regularly used in high pedestrian traffic areas such

as airports, stores, malls, and convention centers. End users may enter data via touch

screen or less frequently through a keyboard. Hard copy printouts such as boarding

passes, tickets, maps, or coupons can be obtained if the kiosk systems are equipped with a

printer.

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2.4.7 Transaction Kiosks

These systems are relatively more advanced compared to other kiosk systems,

because of more complex transactions and information exchange. Main data entry

mediums are touch screen, simple buttons, or keyboards. Since both privacy and money

are involved, security is a major concern for these kiosk systems. They are capable of

handling cash and credit card transactions.

Kiosk systems can be classified into two broad categories based on previous

classifications: Informative Kiosk Systems and Service Kiosk Systems (see Figure 2.5).

Informative kiosk systems can be further subdivided into three main categories:

information kiosk systems, advertising kiosk systems, and entertainment kiosk systems.

Service kiosk systems consist of two major components: interactive kiosk systems and

transaction kiosk systems.

Figure 2.5: Classification of Kiosk Systems

A literature survey was conducted on the limited literature available, to find

design guidelines for kiosk systems. The majority of kiosk system design literature deals

22

with public information kiosk systems. Kearsley (1994) listed several items such as

structure, location, material, operation, maintenance, and integration for consideration

when designing a kiosk system. Three simple guidelines were suggested to ensure

smooth and user friendly access and operation of kiosk systems. Those guidelines are as

follows:

Provide as much redundancy as possible in system operation

Allow as much user control of system as possible

Keep all screen displays and control options very simple

According to Maguire (1999), kiosk systems should be “walk up and use” based.

Maguire (1999) presented guidelines for the human aspect of kiosk design. Appendix II

summarizes design guidelines for kiosk systems based on Maguire’s work, literature, and

the researcher’s experience on kiosk prototype development.

2.5 Information Integration, Field Level Automation, and Technology Usage in Construction

Basic understanding of information integration and automation is a key to

identifying shortcomings of information management in construction. The following

definitions of integration and automation were developed by O’Connor and Yang (2004).

2.5.1 IT Automation

IT automation is the use of an electronic or computerized tool by a human being

in order to manipulate or produce a product. Hard automation, such as robotics, is not

included in this definition.

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In order to measure the present level of integration and automation there must be

a scale or a measuring system. Kang et al. (2006) developed a five point scale to measure

the level of automation.

Automation Levels

Level 1 (none/minimal): little or no utilization beyond e-mail

Level 2 (some): “office” equivalent software, 2D CAD for detailed design

Level 3 (moderate): stand-alone electronic/automated engineering discipline

(3D CAD) and project services systems

Level 4 (nearly full): some automated input/output from multiple databases

with automated engineering discipline design and project services systems

Level 5 (full): fully or nearly fully automated systems dominate execution of

all work functions.

2.5.2 IT Integration

IT integration is the sharing of information between project participants, or the

melding of information sourced from separate systems.

Kang et al. (2006) also developed a five point scale for the Construction Industry

Institute (CII) to measure the level of integration.

Integration Levels

Level 1 (none/minimal): little or no integration of electronic

systems/applications

Level 2 (some): manual transfer of information via hardcopy of email

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Level 3 (moderate): manual and some electronic transfer between automated

systems

Level 4 (nearly full): most systems are integrated with significant human

intervention for tracking inputs/outputs

Level 5 (full): all information is stored on a network system accessible to all

automation systems and users. All routine communications are automated.

The automated process and discipline design systems are fully integrated into

3D design, supply management, and project services systems (cost, schedule,

quality, and safety).

Griffis et al. (1995) found that 3D model usage was positively related to

improvement of cost, schedule performance, and reduction of rework. They observed

65% reduction in rework in projects that used 3D modeling. Balli (2002) demonstrated

how handheld electronics incorporated with wireless networking technologies could

provide accurate, reliable, and timely information to construction personnel (such as

foremen and lead workers). Balli (2002) concluded that handheld electronics may allow

construction personnel to access materials, tools, equipment, and drawing information,

which could reduce schedule delay and boost productivity. Back and Bell (1995)

indicated that fully exploiting electronic data management technologies to enhance

capabilities of automation and integration in the material management process resulted in

an 85% cost saving and 75% time saving respectively. Stiroh (2002) found that industries

that made largest investments in computer hardware, software, and telecommunication

equipment in the 1980’s and early 1990’s showed a larger productivity growth after 1995.

25

O’Connor and Yang (2004) established that automation and integration positively

correlated to project schedule and cost success. They also proved that schedule success

has a stronger relationship to technology than to project cost, via statistical analysis. El-

Mashaleh et al. (2006) encountered similar results when they analyzed the impact of

Information Technology (IT) on a construction firm’s performance. O’Connor & Yang

and El-Mashaleh et al. adopted a similar methodology to develop an IT index. These

analyses concluded that for every 1 unit of increase in IT index, construction companies

experienced a 5% and 3% increase in schedule and cost performance respectively. Zhai et

al. (2009) developed a similar methodology to O’Connor and Yang (2004) to measure the

IT/Automation/Integration Index.

Thomas et al. (2004) investigated the relationship between project performance

and use of Design/Information Technology (D/IT). Thomas et al. measured D/IT usage

specifically based on four technologies (Integrated databases, Electronic Data

Interchange (EDI), three dimensional (3D) and Computer-Aided Design (CAD), and bar

coding). They found that D/IT usage is positively correlated to project performance (cost

and schedule). Zhai et al. (2009) investigated the relationship between automation and

integration of construction information systems and labour productivity, observing four

trades: structural steel, electrical, piping, and concrete. These researchers concluded, via

statistical analysis, that information technology impacts construction productivity in a

positive manner and this trend is likely to continue in the future. Better construction

labour productivity is related to both automation and integration of project information

systems, but the analysis implied that a stronger relationship exists with integration. The

effectiveness of the automation and integration usage was different in the four trades.

26

Automation usage was more positively related to structural steel and electrical

productivity, but integration was more positively related to structural steel and concreting

productivity. According to the researchers, piping showed no significant impact from

either automation or integration technologies and they suggest further research to

examine this occurrence. Researchers observed average time saving per installed quantity

to be 30% and 45% when using a high versus low level of automation and integration

respectively.

Magdic et al. (2002) concluded that some important experience has already been

gained and the main building blocks for mobile computing in the construction industry

are already available in the market. Their final test showed that the efficiency of building

sites can be improved significantly even by using current, unmodified mobile computing

components (PDAs, mobile phones, and web services) for information interchange.

Despite the barriers to implementing IT at the site level, Daito Trust Construction

Company, a Japanese construction firm, developed a large-scale mobile computing

system called the DK Network. The company reported that the system made the process

of construction easier and greatly increased productivity (Daito, 2003). As projects

become more complex, the amount and detail of the information required increases. This

increase in turn makes the process of storing, retrieving, and analyzing the control

information more complicated. One commonly cited means to overcome labour shortages

and improve productivity, cost effectiveness, and competitiveness is through the use of

advanced technologies (Tatum, 1986; Johnson and Tatum, 1993).

27

2.6 Technology Readiness Level (TRL) and System Readiness Level (SRL)

TRL measures the maturity of an individual technology. The National

Aeronautics and Space Administration (NASA) has used Technology Readiness Level

(TRL), which is a nine point scale, since 1980. Level one is basic principles being

observed and reported, and level nine is actual system or “mission proven” through

successful mission operations (NASA, 2013). The Department of Defence (DoD) in 1999

adopted this concept from NASA and changed the definitions of some levels.

Sauser et al. (2006) developed a SRL to access systems based on TRL. The main

difference is that instead of focusing on the maturity of a single technology, SRL focuses

on the entire system. In this research project, acceptance testing workshops were

conducted to ensure that the system was ready for operational use. Acceptance testing is a

process to verify that the user requirements and system features and functionality are

compatible.

2.7 Technology Readiness Index (TRI)

Parasuraman and Rockbridge Associates developed the Technology Readiness

Index (TRI) to understand technology-related attitudes and behaviours of the client

companies’ customers. ‘Technology-readiness’ is a term that refers to “people’s

propensity to embrace and use new technology for accomplishing in home life and at

work” (Parasuraman, 2000). This is a good measure to find out a person’s preference

when using new technologies in terms of mental enablers and inhibitors. Parasuraman

also suggested that people could be arranged along a hypothetical technology-beliefs

continuum, which is strongly positive at one end and strongly negative at the other. The

28

position of this continuum can be correlated with people’s tendency to embrace and

employ technology. Technology-readiness consists of four components: optimism,

innovativeness, discomfort, and insecurity. Optimism and innovativeness are drivers of

technology-readiness but discomfort and insecurity are inhibitors. The definitions of

these components are as follows (Jaafar et al., 2007):

Optimism: Positive view of technology and a belief that it offers people

increased control, flexibility, and efficiency in their lives.

Innovativeness: Tendency to be a technology pioneer and thought leader.

Discomfort: Perceived lack of control over technology and a feeling of being

overwhelmed by it.

Insecurity: Distrust of technology and skepticism about its ability to work

properly.

Figure 2.6: Conceptual Diagram of Technology Readiness (Parasuraman, 2000)

Companies have the ability to utilize TRI to gain an in-depth understanding about

their employees’ and customers’ inclination to embrace computer/internet based

technologies. It is a general understanding that people with “high” TRI believe in the

29

benefits of technology and feel that they are in control of it. Employees’ technology

readiness is a critical success factor when making the right choice in terms of designing,

implementing, and managing the employee-technology link in the pyramid model. Jaafar

et al. (2007) mentioned that employees who rate high on interpersonal skills and

technology readiness are much more effective in tech support than those who are efficient

in only one of the above mentioned criteria. Table 2.2 below shows characteristics of

technology segments.

Table 2.2: Characteristics of Technology Segments (Adopted from Parasuraman, 2000)

Technology

SegmentOptimism Innovativeness Discomfort Insecurity

Explorers High High Low Low

Pioneers High High High High

Skeptics Low Low Low Low

Paranoids High Low High High

Laggards Low Low High High

2.8 Touch Screen Systems (Single Touch and Human Touch)

Touch screens became increasingly popular in other sectors such as industrial,

manufacturing, transportation, and health. Many kiosk systems have been developed in

these sectors using touch screen as the main input device. There are some challenges

when touch screen systems are adopted to the construction industry, such as weather

resistance, sunlight readability, durability, and ability to use with a gloved hand. A brief

30

summary of available touch screen technologies and advantages and disadvantages is

given below in Table 2.3. Following are the available touch screen technologies:

Resistive

Capacitive

Surface Wave

Infrared

Optical Imaging

Capacitive types of touch screens are popular in kiosk system designing

(electrostatic field-based touch screen technology), but unfortunately they can't be

operated with gloved hands or mechanical styluses. Capacitive systems are better for

applications requiring “finger touch”. Resistive technology is recommended for point of

sale systems such as in grocery stores, hotels, and restaurants. Surface-Wave technology

is utilized in ATMs, amusement parks, and financial institutions. The available touch

screen technologies are described in Table 2.3 and 2.4 below.

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Table 2.3: Summary of Available Touch Screen Technologies

Technology Description Advantages Disadvantages

Resistive Glass is layered with a

thin metallic sheet and a

conducting sheet. When

screen is touched layers

come into contact with

each other, coordinates are

used to locate the exact

region touched.

This technology

produces durable

touch screens.

High touch

resolution.

Not affected by dirt,

grease, light or

water.

Display clarity is

compromised

because of layers of

coatings used in the

screen.

Resistive layers can

be damaged by

objects.

Capacitive

(electrostatic

field)

These systems rely on

electrical charges stored in

the screen. Touches are

computed by analyzing a

small loss of charge in the

region.

High touch

resolution.

High image clarity.

Not affected by dirt,

grease and moisture

System can’t use

other pointing

devices such as

pens, styluses, or

other pointing

objects.

Surface-

Wave (sound

waves)

Ultrasonic waves and

transducers detect touch

inputs.

High touch

resolution.

Highest image

clarity.

No coating or

layers.

Have to use the

finger.

Can be affected by

environment.

32

Technology Description Advantages Disadvantages

Infrared

(light

interruption)

There are two types: one

reacts to heat, and the

other uses coordinated

sensors around the

perimeter of the display.

Surface

contaminants can

cause false

activation.

Thick border area

around display.

Optical

Imaging

Uses scanning optical

cameras to sense two-

dimensionally which is

interrupted when touched.

High image clarity.

Light touch and

whole screen

coverage.

Robust.

System does not

rely upon surface

coating, because of

that dirt or scratch

marks in the screen

will not affect the

touch function.

Possibility of two

point touch.

33

In the last decade, the majority of the touch screen systems produced had single

touch function. Recent progress in the area of touch hardware has accelerated towards

multi-touch function (human touch function).

There are several basic functions that touch screens should perform, such as

pointing, moving, left-rotation, right-rotation, zoom-in, and zoom-out. Human touch

function consists of two basic techniques: one-handed interaction and two-handed

interaction. When using the one-hand technique, the user can perform all the above-

mentioned basic moves. But with the two-handed interactions users can perform zoom-in,

zoom-out, tilt-up, and tilt-down functions only. Figure 2.7 below illustrates one-handed

and two-handed interactions graphically.

Figure 2.7: One-handed and Two-handed Interaction (Adopted from Song-Gook et al, 2007)

34

2.9 Investments on Technology and Productivity

Bart et al. (2003) concluded that the United States has benefited not only from

production in the Information and Communication Technology (ICT) industry but also

from adopting ICT in other industries. According to those authors most European

economies invest considerably lower funds in ICT goods and software than the US and as

a result productivity growth has accelerated in the United States while European

productivity growth has slowed down since mid-1990. Although new technologies claim

to improve construction productivity, they sometimes fail to deliver. McAfee and

Brynjolfsson (2008) found a clear correlation between levels of IT investments and a new

competitive dynamic in the market. Although since the mid-1990’s spending on IT has

risen sharply, the gap between the leader and laggards in the industry has widened. The

problem in the construction industry is identifying technologies with the maximum

competitive edge. Goodrum et al. (2011) built a model to predict the impact of a

technology on construction productivity. The authors concluded that mature technologies

have better performance and low risk while they may no longer be cutting edge. On the

other hand cutting edge technologies might have the potential to generate high rewards

with higher risk due to the unproven nature of the technology. Kang et al. (2008) also

found that increased use of technology correlates to better project performance. An

interesting finding was that smaller firms experience benefits of IT more than larger

firms. This can be because IT adaptation in smaller firms is relatively simple compared to

larger firms. Finally, the success of the acquired technology largely depends on top

managers and supervisory staff's ability to understand “which processes to make

consistent and which to vary locally” (McAfee & Brynjolfsson, 2008).

35

2.10 Supervision in Construction

Supervision time consists of three major components - direct work, instructions,

and ineffective time (Gannoruwa and Ruwanpura, 2008). Direct work is the time that

supervisory staff is physically engaged in the work. Instruction time consists of many

other sub-categories such as receiving instructions from senior management,

communicating instructions to the workers, and monitoring construction activities. Time

spent idling, out of sight, walking, within site office and socializing contributes to

ineffective time. Figure 2.8 illustrates the work time distribution of an average foreman in

the form work trade, and here ineffective time contributes to more than 30% of the

workday. This shows that the workers performed work without proper supervision for

approximately one third of the day.

Figure 2.8: Total Time Distribution of a Typical Foreman (Modified from Gannoruwa 2008)

36

The time spent by the supervisor while at the site office and out of sight can be

converted into instruction time by using the concept of “Virtual Supervision” (Silva et al.,

2009). In the construction site environment, engineering supervision and instructions are

critical in improving construction productivity since work can be held up due to

discrepancies or errors of interpretation in engineering details.

2.11 User Acceptance of Mobile Technology in the Construction Industry

Success of any technology adaptation (adoptability and adaptability) in the

construction industry depends on four factors:

need

user’s acceptance of technology

readiness of the technology

readiness of the work force

FIATECH conducted a survey within North America and Europe to find out end

user acceptance of mobile technology (FIATECH, 2013). FIATECH agreed to share the

raw data of this survey with the researcher. The mobile technologies considered were

iPhones, iPads, androids, tablets and Golden-i (described in table 7.2). These are very

similar to the mobile devices considered in the AUSIA framework.

The survey was undertaken by two hundred and twenty-four professionals, mostly

from the Architectural Engineering and Construction (AEC) and Engineering

Procurement and Construction (EPC) industries. A majority of the respondents were from

the construction industry while more than sixty percent had fifteen years or more

experience (see Figure 2.9).

37

Figure 2.9: Breakdown of Survey Respondents According to Industry Sector (Modified from FIATECH, 2013)

This survey instrument tested the major areas given below:

design and specification

project controls

quality

safety

material management

project delivery

Each major category was then subdivided into smaller areas. Then participants

were asked to rate each question on five levels based on the value mobile technologies

bring into these areas.

38

The design and specification area was divided into four major areas:

Distribution of design and specifications

Distribution of shop drawings

Access to 3D/4D BIM models

Version control of design and schedule

More than seventy percent of the respondents believed that mobile technology

would bring value to design and specifications in all four areas mentioned above (see

Figure 2.10 below).

Figure 2.10: Value of Mobile Technologies for Design and Specifications in Field Reporting (Modified from FIATECH, 2013)

The project control area was divided into fifteen different areas and some of the

important areas related to AUSIA framework are given below:

39

Track Request for Information (RFI)

Track change orders

Track project submittal

Work packaging

Document exchange between field and office personnel

Track labor productivity

Daily and weekly progress

More than fifty percent of the respondents believed that mobile technology would

be very valuable for tracking RFIs. Approximately eighty percent of the participants

trusted that mobile technology would bring value to the other area mentioned above.

Around seventy percent believed that mobile technology added value to construction

photo management, which was the least favourite choice (see Figure 2.11 below).

40

Figu

re 2

.11:

Val

ue o

f Mob

ile T

echn

olog

ies f

or P

roje

ct C

ontr

ol in

Fie

ld R

epor

ting

(Mod

ified

from

FIA

TE

CH

, 201

3)

41

Quality was subdivided into six different sub-areas and more than eighty percent

agreed that mobile technology would add value to quality field reporting. Only offsite

stakeholder inspection revealed less than eighty percent likeliness to bring value through

mobile technology (see Figure 2.12 below).

Figure 2.12: Value of Mobile Technologies for Quality in Field Reporting (Modified from FIATECH, 2013)

Safety is one of the important topics in the construction industry. Real-time field

reporting is critical for accurate statistics and injury prevention. The FIATECH survey

also reported data about using smart devices for real-time safety field reporting. Safety

consisted of five sub-areas, and three sub-areas reported that more than eighty percent

believed mobile technology would bring value (see Figure 2.13 below).

42

Figure 2.13: Value of Mobile Technologies for Safety in Field Reporting (Modified from FIATECH, 2013)

The final two areas were materials management and project delivery. These were

subdivided into five and three sub-areas respectively. Majority of users’ trusted that

mobile technology would bring value to both these areas (refer figure 2.14 and 2.15

below).

Figure 2.14: Value of Mobile Technologies for Material Management in Field Reporting (Modified from FIATECH, 2013)

43

Figure 2.15: Value of Mobile Technologies for Project Delivery in Field Reporting (Modified from FIATECH, 2013)

2.12 Discussion and Conclusion

There are opportunities for further research due to gaps/needs in the research and

developments in the commercial construction industry that need to be fulfilled.

Insufficient field level automation and integration, and information leakage in the

construction industry leads to inadequate two-way communication between project

stakeholders. Information double handling between stakeholder groups (Owner, engineer,

and constructor) and within stakeholder groups is observed. Most of the time owners,

engineers, and constructors use different standalone systems for information handling

without adequate integration between stakeholders. As a result, information is fed

manually from one system to another.

Infrastructure at the field/operational level is insufficient to gain advantage from

novel technologies and concepts such as Building Information Modeling (BIM) and work

44

face planning. Investments in the technology sector in the construction industry are low

when compared with other industries such as manufacturing, insurance, and banking

(Park, 2003). The proposed framework utilizes mobile technologies to communicate with

the operational level. The success of this framework largely depends on users’

willingness to accept mobile technologies on construction sites. The recently conducted

FIATECH survey concluded that construction professionals believe mobile technologies

will enhance real-time field reporting (FIATECH, 2013). Unavailability of established

tools and techniques to measure the readiness of tech tools, as well as an inability to

better understand benefits and risks associated with these tools before field-level

implementations led to a lack of investments in the technology area by construction

companies.

Based on researchers' experience during the last six years, construction companies

that participate in research work don’t want to reveal labour productivity because that

might affect their competitive advantage in the market. As a result, researchers focused

on measuring tool time as an alternative to construction labour productivity. Tool time is

one of the three components of working time. The other two components are supporting

time and non-tool-time.

Tool time: direct effective working time.

Supporting Time: time spent on activities that support the direct work (such as

safety, preparations etc.).

Non-tool-time: the rest of the time spent on activities other than direct work

and supporting time (such as idling, socializing, extra coffee breaks, random

walking etc.).

45

Researchers from the University of Alberta are working on developing a

relationship between tool time and supporting time, and labour productivity (Fayek and

Tsehayae, 2012; Tsehayae and Fayek, 2012). There is a correlation between supporting

time and tool time to achieve maximum productivity, but the academic community is still

unable to determine a relationship between tool time and construction labour

productivity. Researchers tend to measure tool time before and after implementing new

tools and techniques to measure the impact. If a positive impact on tool time is observed

this doesn't always guarantee a positive impact on construction labour productivity. The

reason for this is that tool time is only a measure of time workers spend on producing a

tangible output but doesn't measure the quality, efficiency, and effectiveness of the

product.

Therefore based on the literature and site experience, tool time might not be a

good measure of success of implemented tools/techniques. The best possible scenario is

to measure the TFP to gauge company performance, and to use CLP with tool time

investigations to assess worker performance. This will give researchers an overall

understanding on what sort of impact the tool/technique imparts on labour productivity

and company overheads.

46

Chapter Three: Conceptual Framework and Research Methodology

The detailed research methodology, which includes the conceptual framework,

hypothesis, and rationale behind the methodology adapted in each stage of the research

with reliability and validity of these methods, are presented in this chapter.

3.1 Conceptual Framework of AUSIA

The researcher has observed that information chaos in the construction industry is

a result of isolated information systems and poor system integration (Silva et al., 2008).

Construction companies, with the help of technology vendors and software developers,

are trying to incorporate numerous software/hardware systems to achieve better

productivity and gain a competitive advantage. However, these isolated systems may

create more confusion in the workforce, due to lack of information integration and

automation of software and hardware systems. The AUSIA framework will act as the

integration platform for different types of information management systems and act as a

field portal to integrate all these systems (see Figure 3.1 below). These information

management systems include contract management systems, scheduling software,

document management systems, Building Information Modeling (BIM), and Enterprise

Resource Planning (ERP). BIM and ERP are commercially developed software packages

by Autodesk, Bentley, Oracle, and SAP. The majority of research partners in the U of C

research study utilize these systems. One of the major complaints by the field staff was

the inability to interact with these models. There are several document control and

contract management systems general contractors utilise. These systems are either in-

house developments or commercial systems. Scheduling software is either MS Project or

47

Primavera. The integration between these systems enable field staff to access this

information quickly and much more effectively. This will also save a lot of time for both

management staff and field staff because it will reduce information double handling. As

an example schedulers and planners use Primavera P6 for scheduling construction

activities, but detailed construction planning needs to be done later by the foreman and

site superintendents, which they usually do in a white board or in Microsoft Excel. Better

performance can be achieved if there's a system to integrate these two methods, which

will enable two way communication between the schedulers and the foremen.

The AUSIA framework not only integrates these systems together but also

provides a platform to access information with ease. The data arrangement and Graphical

Interface Design (GUI) enable users to move back and forth very easily.

Figure 3.1: Conceptual Framework

48

3.2 AUSIA Framework Mind Map

AUSIA framework was designed by producing a second-generation i-Booth (see

chapters four and seven for the evolution of i-Booth) with ten, high-level information

categories:

Drawings: structural drawings, architectural drawings, mechanical drawings,

electrical drawings, and landscape drawings.

Changes: site instructions, requests for information (RFIs), change orders.

Safety information

Schedule information: master schedule, look ahead schedule, specific

schedules (room completion schedules etc.).

Material information: material locations, availability of materials.

3D/4D models

Quality information: quality checks, deficiency lists, quality plans.

Certification: LEED related information, permits, and regulatory information.

Weather information

Technical information: training videos, productivity related news letters.

The AUSIA framework is built on five main principles: Accessibility, Usefulness,

Satisfaction, Integration, and Automation.

Accessibility: ability to access particular information at the field/site level.

Usefulness: ability to use particular information at the field/site level.

49

Satisfaction: level of satisfaction on particular information at the field/site

level.

Integration: sharing of information between project participants or melding

of information sourced from separate systems.

Automation: the use of an electronic or computerized tool by a human being

in order to manipulate or produce a product.

Communication efficiency and effectiveness were measured based on the five

principles and ten information categories given above. Figure 3.2 below summarises

these ten information categories and five principles.

Figure 3.2: AUSIA Mind Map

3.3 Hypothesis

The research hypothesis was formulated with consideration for the research

design and the objectives of the AUSIA framework. The hypothesis can be broadly

formulated as “Implementation of AUSIA framework improves on-site communication”.

50

Hence the null hypothesis against which the research hypothesis is going to be

tested can be termed as follows:

H0 : Implementation of AUSIA framework does not improve on-site

communication

The null hypothesis can be tested against the alternative hypothesis which is:

HA : Implementation of AUSIA framework improves on-site communication

Communication is judged based on five criteria and ten information categories

explained in Chapter One: Introduction. These five criteria are Accessibility, Usefulness,

Satisfaction, Integration, and Automation (AUSIA). The ten information categories are

drawings, changes, safety information, schedule information, material information,

3D/4D models, quality related information, certification, weather information, and

technical information.

This derives fifty different null sub-hypotheses and fifty different alternative sub-

hypotheses. The null sub-hypothesis and alternative sub-hypothesis for the drawing

information category for all five criteria are given below in Tables 3.1 and 3.2. These

hypotheses will be tested for conditions given below.

(Before AUSIA)

(After AUSIA)

51

Table 3.1: Null Hypothesis for Drawings

Table 3.2: Alternative Hypothesis for Drawings

Hypothesis DescriptionNull Hypothesis

H0DA Implementation of AUSIA framework does not improve accessibility of

drawings on-site

H0DU Implementation of AUSIA framework does not improve usefulness of

drawings on-site

H0DS Implementation of AUSIA framework does not improve satisfaction

with drawings on-site

H0DI Implementation of AUSIA framework does not improve integration of

drawings on-site

H0DA Implementation of AUSIA framework does not improve automation

of drawings on-site

Alternative Hypothesis

HADA Implementation of AUSIA framework improves accessibility of

drawings on-site

HADU Implementation of AUSIA framework improves usefulness of drawings

on-site

HADS Implementation of AUSIA framework improves satisfaction with

drawings on-site

HADI Implementation of AUSIA framework improves integration of

drawings on-site

HADA Implementation of AUSIA framework improves automation

of drawings on-site

52

The full list of null hypothesis and alternative hypothesis are provided in

Appendix III.

3.4 Research Methodology

Quantitative and qualitative tools were utilized to fulfill the objectives of the

research stated above. These tools included interviews, questionnaire surveys, workshops

(lunch and learns), and observations, statistical analysis, and cost benefit analysis.

A summary of the research methodology, flow of the research, and how each

objective was achieved is illustrated in Figure 3.3 below. The main objectives of the

research are listed on top (from left to right) and the five main research stages are listed

in the left-hand side (from top to bottom). The research question, goals, and objectives

were developed with the aid of a literature survey, which will be continued until the end

of the research. Other main stages of the research are site observations and interviews,

pilot testing, user acceptance testing, and system development. All other stages other than

pilot testing cover all four objectives of the research, while pilot testing covers the last

two objectives. As explained above, the main reason for initial productivity and tool time

observation was to ensure that implementing the AUSIA framework would improve

communication while improving construction productivity. If the AUSIA framework

only improves communication without improving efficiency of the workforce, the system

will become an additional overhead for the construction companies.

53

Figu

re 3

.3: R

esea

rch

Flow

Dia

gram

54

3.4.1 Research Phases

Research work was divided into four major phases:

Phase I: investigate the problem

Phase II: design the solution

Phase II: implement the solution

Phase IV: validate the results

3.4.1.1 Phase I (Objectives I & II)

Under phase-I current industry practices were investigated to find out information flow,

the bottlenecks associated with the information flow, and the information needs of construction

workers and supervisors.

Conducted twenty unstructured interviews with office managers, site managers,

foremen, and lead hands. Interviews were conducted in a discussion style using open-

ended questions. These interviews dealt with types of information management

systems contractors utilized, issues and problems faced at the operational level due to

communication deficiencies, information types needed at the operation level, and

mobile technology devices they would like to utilize, etc. The researcher ensured that

the interviewee felt comfortable expressing the problems and issues they faced in

field operations due to information management. This was very critical because

unless field staff was comfortable, they wouldn’t express the drawbacks in current

information management systems as some of the research partners were using in-

house products for information management.

55

Observed construction operations to understand work practices and information flow

in three buildings (all three building projects were part of the same ABC

Polytechnic). Observations were carried out for 3 months (1 month each) in all three

building sites.

o identified effective information dissemination methods already practiced

at site level

o identified communication needs of construction workers

Conducted online surveys (see Appendix V for the survey instrument) to verify the

findings from interviews and site observations.

Survey and observation results of phase-I of the research work are included in Chapter

Four. Furthermore, a comprehensive literature survey was carried out throughout this research so

that the researcher was familiar with other research work related to on-site communication. The

researcher realised that without developing an actual system, the work force was unable to

express the information need.

The researcher attended several conferences and trade shows related to construction

technology and presented the findings of the research in several technology conferences and

tradeshows:

FIATECH Technology conference and tradeshow from 2009 to 2012

Construction Research Congress (CRC), 2009 and 2010

Canadian Civil Engineering Society (CSCE) construction speciality conference, 2008

and 2009

The sixth International Structural Engineering and Construction Conference, 2011

BUILDEX Calgary annual tradeshow, 2012

56

Alberta Center of Excellence for Building Information Modelling (aceBIM) annual

conference, 2013

The system was fine-tuned based on the input from experienced site superintendents,

construction managers, project managers, chief information officers, systems & technology

managers, technology vendors, and information technology professionals.

3.4.1.2 Phase II (Objectives I, II & III)

The first generation i-Booth was developed based on the input from Phase-I and from the

researcher's experience in the construction industry.

Conceptualized framework for the first generation i-Booth based on data from

interviews and observations.

Conducted eighteen phone interviews with technology vendors for Human Interface

Device (HID) selection, kiosk design, and prototype development (three vendors each

from the following areas: touch screen monitors, kiosk manufacturers, access control

system developers/providers, computer hardware providers, software

providers/developers, and kiosk system software developers). The main focus of these

interviews was to gain an understanding of the reception for these products in the

construction industry, the ruggedness of these technologies, the adverse effects if

exposed to sub-zero temperatures, and the possibility of integrating with other

hardware and software.

Assembled a prototype with the help of university technical staff based on interviews,

literature on kiosk system designing guidelines (given in Appendix II), and the

researchers’ experience in the construction industry.

57

Conducted pre-user acceptance testing for first generation i-Booth in three different

building construction sites in Calgary to check the functionality and usability of the

system.

Conducted ten interviews with higher managers/decision makers (during discussions

with research partners for status updates for Construction productivity improvement

research. Majority of the participants were Project Directors and Vice Presidents of

leading construction companies in Canada). Redesigned system software based on

end-user feedback and input from these interviews. This step was conducted to ensure

that technology readiness level of the i-Booth was sufficient for site testing. The main

factors discussed during these interviews were regarding new information categories

needed, willingness to pilot test the system in one of their jobsites, and likeliness to

purchase a unit in future.

3.4.1.3 Phase III (Objectives III and IV)

This phase dealt with implementation (site testing) of the first generation i-Booth. The

researcher conducted fifteen one-on-one interviews with supervisory and management staff after

showing an overview video of the first generation i-Booth. This helped the researcher to

understand the supervisor’s perception of the new technologies and willingness to implement the

proposed technologies. Other points discussed were site specific information requirements and

logistics of implementation. The researcher conducted a Technology Readiness Index (TRI)

survey to verify the findings. (The questionnaire used to assess TRI is attached in Appendix VI.)

The researcher initially planned to investigate TFP to assess company performance, and

conduct a time-motion study and measure construction labour productivity (planned verses

58

actual) to measure the worker performance. The researcher then planned to investigate the

impact on company overheads and the influence on construction labour productivity after

implementing the AUSIA framework. Unfortunately the research partner (general contractor)

refused to reveal any data related to productivity because of the competitive nature of the

business. As a result the researcher had to find other means to measure the impact.

Time-motion study was conducted to assess the present site conditions. Tool time

observations were performed for four weeks. Both the five-minute rating method and

the thirty minute continuous observation method were utilized for observations/work

sampling. In five minute rating method workers are observed every five minutes and

in thirty minutes continuous observation method observations are done for thirty

minutes continuously. Based on these observations activity analysis is conducted to

determine direct working time, supporting time and ineffective time.

Three workshops were conducted to investigate time wasted due to ineffective

information handling within all three building projects in ABC Polytechnic (the form

is attached in Appendix VII). Forty-six supervisory staff members participated in

these workshops.

A questionnaire survey was conducted to determine the present level of

communication under the above mentioned ten categories and five criteria (mentioned

in the Hypothesis section above). A questionnaire (Appendix VIII) with a five point

Likert scale (Extremely bad, slightly bad, undecided, slightly good, and extremely

good) was used in these workshops. Three workshops were carried out to ensure

supervisory staff could attend these without hindering site work. (Forty-seven people

participated in all three workshops.)

59

Above mentioned survey was also distributed online through SurveyMonkey to

generalize the sample selected to general population. FIATECH and CCA provided

assistance to the research by distributing the survey to construction professionals in

North America (twenty-four participated).

First generation i-Booth was implemented in the construction site for twelve months.

(Detailed discussion in Chapter 5: Site Implementation and testing)

A questionnaire survey (workshop) was conducted to assess level of communication

under above mentioned ten categories and five criterions after twelve months.

Questionnaire with five point Likert scale (Extremely bad, slightly bad, undecided,

slightly good and extremely good) was used in these workshops (forty-seven

participated in this survey).

After implementation, a questionnaire survey (Online and on-site) and user

acceptance workshop on i-Booth were conducted to understand user perceptions, the

impact of i-Booth, and optional and essential hardware items of the system. (Further

details in Chapter Seven: Data Collection, Analysis, Validation of Result and System

Development.)

3.4.1.4 Phase IV (Objective IV)

In phase IV the researcher validated the results, fine-tuned the first generation i-Booth,

developed the AUSIA framework (second generation i-Booth), and did business validation.

Two workshops were conducted in two construction sites to validate results collected

from implementation. These workshops were conducted to establish benefits from the

60

AUSIA framework and user acceptance of hardware. (Forty-four supervisory staff

members participated.)

The kiosk hardware was redesigned with the input from workshop data.

The kiosk was redesigned based on reviews and feedback from the workshops

conducted after site testing.

A final user acceptance workshop was conducted for software with the Calgary

Construction Association. A minimum of three supervisory staff members (one

foreman, one superintendent, and one senior manager) from six major general

contractors in Alberta participated. The researcher and software developer presented

the system and documented the feedback.

Four Business Validation Group (BVG) sessions were conducted with the CCA board

of directors at their annual general meeting, and two sessions were held with

Productivity Alberta with construction professionals from Edmonton.

Lessons learned through site testing and feedback were documented for future

research.

3.5 Sample Size Selection

Research samples were selected based on three basic principles:

Participants were from commercial construction companies; the majority were from

research partner companies in Alberta.

Participants had the right to withdraw at any time during the research study period,

but the data collected until the point of withdrawal were used for analysis and to

derive conclusions.

61

Samples were selected on a fully voluntary basis using random sampling technique.

Sample size is governed by the error margin, confidence level, and standard deviation of

the results. Sample size must be greater than 30 based on the central limit theorem. The required

sample size (n) was determined using the equation given below.

(3.1)

n = required sample size

(1- )% = error margin of the estimation

= standard deviation for the results

d = desired error margin

The difficulty with this pilot study was to satisfy the sample size needed to find a jobsite

with a large supervisory staff. As explained in the above section, getting agreement from a

general contractor to pilot test this type of system was a challenge. Time periods for setup and

testing also took ten to twelve months, so testing in multiple jobsites wasn’t a viable option. The

only possible solution was to test in this jobsite and calculate the error between sample mean and

population mean to ensure the error margin was acceptable.

(3.2)

Based on this equation the researcher calculated error for all fifty different variables

before and after implementation, for three different confidence intervals (ninety-nine, ninety-five

and ninety percent respectively (refer Appendix – IX)). Based on the calculations in the 90%

confidence interval, the error margin was acceptable because sample means were in the same

state the majority of the time. (As an example, if the sample mean of accessibility of drawings

62

was in the slightly bad state, in 90% confidence interval the sample mean falls into the same

state).

Qualitative research instruments such as interviews were not based on the above

equation, because only qualitative constructs were derived from the data collected. As an

example in the case of interviews, the number of interviews depended on the saturation point (the

researcher conducted interviews until the researcher was getting the same answer from the

research subjects).

3.6 Techniques and Tools Utilized in the Research Study

The research techniques and tools utilised in the research studies were a combination of

quantitative and qualitative techniques. The quantitative part consisted of what could be

measured. This involved collecting and analysing data that could be organised into statistical and

quantitative studies. The qualitative part consisted of investigating subjective data, in particular,

the perceptions of the people involved. The intention was to illuminate these perceptions of the

participants to derive conclusions.

3.6.1 Literature Review

Comprehensive and continuous literature review was carried out to narrow the research

topic and to find new state of the art, cutting edge research and development. Sources of the

literature review were based on electronic data sources, journals, books, conference and

symposium proceedings, industry reports, and masters and PhD theses.

63

3.6.2 Questionnaire Survey

Questionnaire surveys were structured with both open and closed questions, depending

upon the requirements. Survey instruments were pilot tested before being distributed online and

in workshops through participating research partner companies to fine tune (stability and

comprehensiveness) the instrument. Quantitative and some of the qualitative questions were

based on the five-point ordinal Likert scale given below. The researcher assigned a numerical

value for each level when analysing the data.

Extremely Bad (0)

Slightly Bad (1)

Undecided (missing)

Slightly Good (2)

Extremely Good (3)

3.6.3 Interviews

The researcher conducted both face to face and phone interviews. Face to face interviews

were carried out in closed rooms. Participation was voluntary and participants had the freedom to

walk away anytime without any consequences. The majority of the interviews were unstructured

and used open-ended discussions to encourage users to express their ideas. According to the

researchers' experience, field supervisory staff members weren’t comfortable with structured

interviews. The researcher conducted these interviews after spending several weeks in the jobsite

to make sure that field staff was familiar with the researcher and the research study to ensure

maximum participation.

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3.6.4 Document Analysis

Information was collected from secondary sources such as project execution documents

and contract documents. This was not conducted to derive any conclusions but to ensure that the

researcher was fully aware of project execution and other conditions before implementing the

system.

3.6.5 Workshops

Workshops were used to collect data through questionnaire surveys. The researcher

facilitated these workshops. This method was useful to collect information relatively quickly

compared to formal questionnaire surveys. This was beneficial for both the researcher and the

research subjects because the research subjects were able to get clarifications then and there and

the researcher had the ability to collect data relative quickly as mentioned above. Some of these

workshops were conducted as lunch and learns because it was easy to gather field staff and office

staff during lunch hour to ensure higher attendance. Most of the time the researcher conducted at

least two workshops for one survey because then field staff and office staff had the ability to

accommodate daily site work. This method was one of the best tools used to check user

acceptance of the i-Booth software and hardware (especially Human Interface Devices).

3.6.6 Site Observations

Observations at the construction sites were done by the researcher through direct

monitoring of construction site operations. The researcher conducted activity monitoring for

three weeks to figure out the current status of the jobsite. The research team has conducted

several activity monitoring studies in Alberta over the last several years. Activity monitoring was

conducted using observation forms and observation categories attached in Appendix X.

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3.6.7 Data Analysis

Extensive statistical and cost-benefit analysis was carried out in the quantitative domains

of data analysis. This was performed via SPSS (Statistical Package for Social Sciences)

statistical package and excel (data analysis and data processing). Hypothesis testing was

conducted using non-parametric tests (Conover and Iman, 1981):

Wilcoxon Signed Ranked test

Mann-Whitney U test.

The reasons for selecting non parametric tests instead of the parametric T Test are:

according to the K-S test, the assumption of normality was not satisfied.

the sample size was relatively small.

the instruments used were of ordinal nature.

After completing hypothesis testing, the researcher conducted qualitative analysis of the

data before and after implementation. This enabled researcher to compute research subjects

perception change before and after implementation of the AUSIA framework.

Qualitative analysis was performed using SPSS text analytics software package because

Natural Language Processing (NLP) and linguistics built into the package helped to analyse

open-ended answers much better than simple frequency calculations. Other qualitative answers

were analyzed with simple frequency calculations.

3.7 Validation and Verification of Results

Validity of the research depends upon validation, verification of research findings, and

reliability of the research data. The reliability of the research study is based on repeatability of

the research with a similar methodology to obtain similar results or observations. According to

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Kirk and Miller (1986) reliability is based on the stability of the measurement over time. A

mixed method approach, using two data collection methods and utilizing both qualitative and

quantitative research methods will increase the reliability of the outcome. Inter-item reliability

measures such as Cranach’s (alpha) don’t need to be calculated because no factor analysis was

performed and no interrelationship between variables was considered. One of the other issues

related to the reliability of data is the ‘Hawthorne Effect’ (Franke & Kaul, 1978). This is an

increase in worker productivity produced by the psychological stimulus of been singled out and

made to feel important due to being selected for the study. This phenomenon was proven by a

group of researchers in 1932. The researcher reduced this effect by collecting data after research

subjects were comfortable with the researcher. This was a judgement call based on experience in

the construction industry.

To improve the validity of the research, the following strategies were implemented:

triangulation, feedback, site observations, and comparisons. The researcher conducted two

workshops in two other construction sites of the same general contractor to triangulate the

findings from the pilot study (site testing). The main reason for selecting two jobsites of the same

general contractor was to ensure that the researcher wasn’t violating the agreement between the

research team and the general contractor. Based on the agreement, the research team needed to

completely erase the available data before showing the system to any other third party. The pilot

test was a very cumbersome and resource oriented exercise. The researcher let supervisory staff

of these two sites interact with the system for a week before the workshop to ensure that users

were familiar with the AUSIA framework.

External validity or establishing the domain of a study’s findings were generalised using

two methods. The research team conducted several BVG sessions with Canadian construction

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professionals to ensure the system was acceptable within the construction industry. Also the

researcher carried out a web-based survey to ensure that the perceptions of the sample population

is similar to the perceptions of the selected sample from construction community (majority of

respondents were from construction community in Alberta and members of FIATECH).

3.8 Bias Associated with the Research

As bias is unavoidable in the research setting, the researcher's only possibility was to

attempt to minimise the associated bias. There were several potential biases associated with this

research. Selection bias (sampling bias) is when the sample selected is not representative of the

population. The researcher made an effort to ensure samples were selected randomly and

independently, but this was somewhat restricted because the researcher needed to find a

construction site first. Recall bias occurs when the answer for a survey question is affected by the

respondent's memory (such as when research subjects fail to accurately recall events in the past),

for example when research subjects can’t recall how many projects used BIM before this project.

As a solution data triangulation, which is validation of data through cross verification from more

than two sources, was used. Confounding bias occurs when the factor under consideration is

related to other factors, so more than one explanation can be given for the results, for example

comparing the relationship between use of technology and construction productivity in two

samples (population) when one sample is young workers and other is older workers (due to the

ethics guidelines of CFREB, no analysis can be performed on age, sex, etc.). So multiple studies

were conducted to eliminate this bias. Design bias occurs when part of the research study does

not fit together to answer the question of interest. The solution is to make sure the control group

and the research group have the same randomness. To avoid this bias the researcher conducted

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the same survey for both site samples as well as for the general construction population of North

America. Non-respondent bias arises when some subjects choose not to respond to particular

questions and when the non-responders are different in some way (they are a non-random group)

from those who do respond. This was minimized in several ways: giving shorter surveys, sending

reminders, giving time to fill questionnaires during workshops, arranging workshops and

sessions during lunch hours, and holding more than one workshop when possible.

3.9 Limitations of the Study

There were certain limitations encountered by the researcher from inception to

completion of the research project. As this research is very technically advanced, several times

research partners refused to implement the AUSIA framework. One general contractor agreed to

implement the system but the site superintendent refused to implement the system stating that

they didn’t need additional technology. In another project, the construction manager wasn’t

comfortable with implementation, stating that to see benefits from tech tools we need to

implement them in a large project. Although the same general contractor agreed to pilot test the

system in a larger project, the researcher had to go through a very strict protocol before

disclosing information such as drawings, specifications, safety, quality, etc. The complete

information integration and systems integration was planned initially. The researcher and

software developer planned to directly access the contractors’ documents management system

(which was based on SharePoint) but the general contractors' Systems & Technology

Department refused the integration. So the researcher had to manually load the information to the

AUSIA framework. The agreement between the general contractor and the research team to

access information is attached in Appendix-IV. The contractor refused to reveal labour

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productivity data and TFP data because of its confidential nature. This was purely because of the

competitive nature of the Alberta market and the research team worked with five other general

contractors in this research project. As a result, verification and validation of benefits from the

AUSIA framework was investigated empirically through a questionnaire survey and qualitative

analysis.

3.10 Problems Encountered and Solutions Provided

Issues were encountered in the early stages of implementation of the AUSIA framework.

Researchers experienced three major problem categories: human, management, and automation

issues.

Human Issues

Human issues were the most influential factor in the success of the implementation stage.

Issues encountered were difficulty in coping with the technology, changes in workload, and the

inability to understand intended benefits. The problems related to the i-Booth were tackled by the

researchers from its inception. The i-Booth was designed in such a way that anybody with a

general understanding of a computer or an automated teller machine (ATM) was able to operate

this device.

Management Issues

In general, the construction sector offers stiff resistance to IT solutions (Mak, 2001). The

success of the i-Booth was dependant on management comfort and trust in the system.

Researchers encountered some resistance from management with the proposal to change internal

systems to IT solutions for better efficiency. Researchers carried out awareness sessions with

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management to convince them that IT tools are there to help, and systems are not intended to

replace the human brain.

Automation Issues

Automation issues came up during the early stages of the implementation of i-Booth. The

researcher and the Systems and Technology Department solved IT issues such as inter-

operability, data security, and compatibility.

The steps taken to solve the issues identified at the operational level were:

The worker or identifier of the problem immediately informed their supervisor of the

issue.

The supervisor informed the district systems administrator.

The systems administrator discussed the issue and its resolution with the

researchers/developers.

Reported issues were resolved with the help of general contractors' staff, the

researcher, and the software developer.

3.11 Conclusion

A conceptual framework was developed to enhance on-site communication based on ten

high level information categories and five main principles. The research study was divided into

four phases and initial two phases concentrated on identifying problems and proposing solutions.

Third phase dealt with site implementation of first generation i-Booth. Final phase focused on

validation of results. Observations, interviews, workshops with survey instruments were utilized

throughout the study. Statistical methods were utilised to analyse the impact from

implementation.

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Sample size was determined by indirect methods due to restrictions with site selection.

Instead of calculating the desired sample size with given error margin, the researcher calculated

the error margin for sample size of the selected job site. Exact Z values were calculated instead

of Z value approximation from the table because the sample size was small. Validation &

verification process relied on workshops, interviews and survey instruments, as another full

implementation of the framework in a new jobsite was not possible due to funding and time

restrictions.

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Chapter Four: Data Collection, Analysis and System Development (Pre-Implementation)

This chapter consists of data collected in phases I and II of the research project. Data

collected during these phases of the research was mostly qualitative data, which helped to

formulate the system and develop the initial version for site testing. Qualitative data was

analysed using a SPSS text analytics package and responses were summarized in frequency

tables.

4.1 State of Information Management in the Construction Industry in North America

The total number of participants in the initial stage was forty-six (both online and on-site)

but only thirty-three completed it. The demography of research subjects is given below in

Figures 4.1 and 4.2. The majority of participants (nearly two-thirds) were from the building

construction industry and close to fifty percent of the research subjects were very experienced

(more than 15 years of experience in the construction industry). The bulk of the research subjects

had both site and office experience. These qualities of research subjects enabled the researcher to

better understand the problems in communication.

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Figure 4.1: Distribution of Research Subjects According to Industry Sector

Figure 4.2: Distribution of Research Subjects According to Years of Experience

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These responses were based on the research subjects’ experience in the industry in 2009

and 2010 in North America. Everyone used hardcopies to disseminate information in the

construction industry, while soft copies were catching up fast. The problem was that supervisory

staff had a limited number of methods to take these soft copies to the site because a limited

number of users had smart phones or handheld devices (see Figure 4.3 below).

Figure 4.3: Methods Used To Disseminate Information According to Research Subjects

These soft-copy and hard-copy data needed to be updated regularly to ensure that

changes were incorporated into the current information. Most of the research subjects performed

this manually in hard copies or soft copies (see Figure 4.4 below). This created a bottleneck in

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information dissemination. Supervisory staff members were inclined to update their own set of

hard copies for two reasons (usually 11x17 size set):

Can easily carry that to the work site

Don’t have to rely on someone else to update the master set (trust issue)

Figure 4.4: Methods of Updating Information According to Research Subjects

Another objective was to find out if/why the site staff didn’t trust the master set, and

whether there were any problems or issues in updating. Nearly fifty-six percent of the research

subjects complained about problems in information updating.

Based on the interviews and surveys with construction professionals, the construction

industry faces some issues/problem in information integration, updating, and dissemination.

Nearly fifty-six percent thought that there were issues that needed to be solved to improve

communication/information management. Responses were analyzed with SPSS text analytics

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and are summarized in a frequency graph given below in Figure 4.5. The researcher further

investigated to reveal the nature of the problem. Lack of accessibility of information and a large

volume of information construction companies had to deal with were major problems. Field staff

complained about the lack of sunlight readability, ruggedness and durability, small screen sizes,

and heaviness of available devices. The management staff complained about the volume of data

they needed to handle and lack of acceptance from the field level. One of the other major

problems was dissemination barriers between the operational level and the office due to

insufficient technology and resources.

Figure 4.5: Issues/Problems Industry Faced with Information Integration, Updating, and Dissemination

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The researcher investigated willingness to deploy soft copies or soft data at the field level

because the AUSIA framework is based on soft data at field level (see Figure 4.6). The majority

of participants were enthusiastic about deploying soft-copy information at the field level.

According to responses from participants there were three main reasons to deploy soft

information at the operational level (Figure 4.7 below summarizes all responses from

participants):

cost effectiveness

ease of navigation and accessibility

real time information transferring capability

According to them there were two main reasons for not deploying soft copies:

lack of data security

issues with equipment and technology

Based on the responses, deployment of soft copies will reduce the cost of information

dissemination at field level and ensure timely delivery (real time) of information to field level.

Ease of navigation and accessibility will improve immensely by using soft copies instead of

printed hard copies. Some of the respondents were concerned that data might be accessible by

individuals without proper authority. Lack of infrastructure and technical knowledge that

prevents them from utilizing digital information in the field was another concern.

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Figure 4.6: Participants’ Willingness to Deploy Soft Copies on Site

Figure 4.7: Reason for Deployment and Non Deployment of Soft Copies

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Groups that deployed softcopies revealed some issues/problems they faced during

inception and deployment of soft-copies (information and data in a digital format) in the field.

The main drawbacks were a high volume of information and accessibility problems from field

level. Other issues were low reliability, inability to timely disseminate information, lack of

resources, and acceptance at the field level (see Figure 4.8 below). Lack of interoperability also

hindered successful deployment because the commercial construction industry didn’t have a set

of guidelines or standards to help engineers, architects, general contractors, and subcontractors to

share electronic data. These issues either prevented deployment or reduced the positive impact.

As a result supervisory staff members were inclined to depend more on hard copies.

Figure 4.8: Issues/Problems the Industry Faced when Deploying Soft Copies

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BIM is a good tool for both site and office, because it has a good potential to improve

communication (Dossick & Neff, 2011). The researcher explored the level of BIM usage within

research subjects' organizations. More than fifty percent of the research subjects believed their

organizations have a satisfactory level of BIM expertise (see Figure 4.9 below). Further inquiries

were made to these research subjects about success of BIM integration with the operational level

and any problems or issues they encountered.

Figure 4.9: Organizational Expertise on 3D/4D Model Usage

Another important aspect was methods of integrating BIM/3D models with the work site.

Initially the researcher explored the existing model dissemination approaches with the site level

(see Figure 4.10 below). The majority of the respondents didn’t integrate BIM models with the

site level and some only utilized BIM in the pre-construction stage and when estimating. An

equal number of respondents used printouts and screenshots as well as real models to integrate

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BIM with the field level. A minority used scaled down versions of BIM models in the field.

Contractors either used freely available programs such as SketchUp 3D or other model viewers.

These reduced models and free viewers enhanced the field staff's ability to navigate and interact

due to the simplified nature of controls. The researcher also used these reduced models with

multi-touch function and 3D BIM mouse (see Chapter Seven for more details) in the AUSIA

framework.

Figure 4.10: Methods of Using and Integrating 3D/4D Models at the Site Level

Respondents also commented on the purposes of these models in the field (see Figure

4.11 below). Most of the respondents used models for construction planning, and others used

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models for visualization and communication purposes. Field supervision staff used these models

to better communicate with the workforce and subcontractors. Design, clash detection, and

work/activity sequencing were some other purposes of 3D/4D models. Around fifteen percent of

respondents used models for coordination of construction work. Field supervision staff expressed

that models increase effectiveness of training, scheduling crane picks, design visualization

(concrete lift drawings), and early clash detection. During implementation the researcher noted

that field staff identified some of the clashes before construction as a result of workface planning

and better integration of BIM with the operational level.

Figure 4.11: Purposes of 3D/4D Models at Site Level

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Most of the organizations used computers in site trailers or printouts to deploy BIM

models in the field. As a result operational staff members at field level had limited access to

these models. Less than ten percent of the site staff had access to these models in an interactive

medium (see Figure 4.12 below). Even though field supervisory staff benefits from using BIM

models in the operational level, the majority of the contractors don’t have infrastructure to

support interactive models on site. There are a few reasons for this, one being no legal

framework to transfer the models to contractors. Another problem is lack of commitment from

all project participants to fully utilize BIM. So contractors create their models from 2D drawings

and as a result these models are not complete enough to properly conduct clash detection. The

researcher also observed this in the jobsite where the AUSIA framework was implemented. The

general contractor only modeled lift cores due to lack of available resources. Engineers,

architects and general contractors need to adopt either “The American Institute of Architects

(AIA) E202 BIM Protocol” or “The Associated General Contractors of America (AGC)

ConsensusDOCS 301 BIM Addendum” to facilitate the model data transfer between project

stakeholders.

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Figure 4.12: Infrastructure Available to Access 3D/4D Models at Site Level

Finally, inquiries were made about issues and problems with BIM model integration on

site (see Figure 4.13 below). The main complaint was unavailability of a proper protocol for

updating drawings or models. Engineers sometimes update shop drawings in the field with a

pencil or pen. They sometimes forget or do not have the time to go back and update the model.

Therefore, the models do not agree with the fabrication and installation. Other problems were

similar to those in soft-copy deployment.

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Figure 4.13: Issues/Problems Industry Faced with Deployment of 3D/4D Models

These results highlight that the construction industry needs an interactive communication

system to improve the communication between the field and the office. Supervisory staff suffers

due to the inability to take all required information with them to the field. Also there isn't a

proper procedure to update the master set of drawings, while information integration and

automation is minimal. As a result general contractors tend to have multiple copies updated in

multiple locations by several individuals. Supervisory staff tends to maintain their own copy

because of discrepancies in the information updating.

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This led the researcher to note time wasted due to poor information management and

communication. Time wastage was categorized into seven major areas:

Searching for Drawings

Supervisory staff spent time searching for drawings in the field/office. This was time

spent due to bad information management practices, lack of meta data to categorize information,

and poor version control. Time spent on studying drawings, referring to drawings, and other

construction and management related activities were excluded and only ineffective activities

were considered.

Searching for Site Instructions (SI), Requests for Information (RFI) and Contemplated Revisions

(CR)

Time that supervisory staff spent searching for SI, RFI, and CR as a result of poor

integration between drawings and changes and ineffective database practices was considered.

Supervisory staff studying changes for constructability, construction management, and other

field related activities were excluded.

Searching for Specifications and Technical Information

Time was spent ineffectively searching for technical information and specifications due

to lack of integration with addendums, lack of metadata for categorisation (CSI codes), and lack

of integration with drawings.

Searching for Material Safety Data Sheets (MSDS)

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Time was spent searching for MSDS, because most of the time these were available as

hardcopies in one binder.

Walking between Site and Site Office

Supervisory staff had to walk between the work site and the site office to refer to

drawings and other information, as they couldn’t carry all the information required.

Data Entry

Supervisory staff wasted time transferring information/data in paper to the computer in

the site office. Information such as near miss reports and incident reports that a foreman

completed on site needed to be entered into a system or a database by same/another staff

member.

Data Processing

Supervisory staff had to spend unnecessary time creating multiple copies of completed

forms and calculating work hours of the gang.

All above-mentioned issues led to unnecessary time waste that didn’t bring any value to

the contractor. Further, the majority of this time could be saved by better communication and

information management. A time waste summary of all forty-six respondents is given below in

Table 4.1. These values given below are based on the perceptions of field supervisors and as a

result actual values might be different.

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Table 4.1: Time Waste Due to Inappropriate Information Management/Communication

Sear

chin

g fo

r D

raw

ings

Sear

chin

g fo

r SI

, RFI

and

CR

Sear

chin

g fo

r Sp

ecifi

catio

ns a

nd

Tec

hnic

al In

form

atio

n

Sear

chin

g fo

r M

SDS

Wal

king

bet

wee

n Si

te a

nd S

ite O

ffic

e

Dat

a E

ntry

(H

ardc

opy

to S

oftc

opy)

Dat

a Pr

oces

sing

Tot

al T

ime

Was

te

(Min

/Day

)

Mean 37 26 23 4 28 36 30 184

Average Time Waste per Day per Person 166

The researcher calculated the average time wasted per day using two methods:

calculating the simple average time waste per person, per day

calculating the mean of each category separately and then adding up all means.

These were calculated separately because during this study, the research team developed

only part of the AUSIA framework (wall mount version and mobile version of the i-Booth).

Until the complete framework is developed with handheld applications, some of these time waste

categories can’t be minimized/eliminated. These are:

data entry

data processing

If these parts are eliminated from time wastage when the AUSIA framework is

implemented, the total time saving will be 114 min/day.

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4.2 AUSIA System Development

The AUSIA framework was developed in three generations, namely Zero generation,

First generation, and Second generation. Zero generation was the proof of concept phase and the

developed framework couldn’t be applied to the work site without further development. Because

of this, the researcher developed the first generation AUSIA framework for site testing (similar

to a beta version). This first generation framework underwent several changes before and during

site testing based on the inputs from acceptance tests and site feedback. The second generation

AUSIA framework is the final product developed after site testing and several acceptance tests

and BVG sessions.

4.2.1 Zero Generation (Information Booth)

The initial development and testing of the zero generation was conducted at Rocky View

General Hospital parkade with PQR Management Ltd, by the U of C productivity research team.

They used a LCD projector and a laptop to carry out toolbox meetings with the workforce (see

Figure 4.14 below), and then made a presentation with the aid of site supervision staff. This

presentation consisted of a few drawings, safety information, material locations, 3D renderings,

and work schedules. The foremen presented the content to the workforce. The research team

changed the presentation based on feedback from the workforce and input from supervisory staff.

Hewage and Ruwanpura (2006, 2009) developed this concept, pilot tested it for 3 weeks, and

concluded with a positive note.

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Figure 4.14: Zero Generation (Information Booth)

4.2.2 First Generation (i-Booth)

Based on the positive responses received from the workforce and supervisory staff, the

research team assembled a kiosk called Generation One i-Booth for extensive field testing, as the

initial setup used for the zero generation proof of concept phase wasn’t a practical solution.

During the interviews and observations the researcher realized that simply designing a kiosk with

a web interface wouldn’t bridge the communication gaps between site and office. The

construction industry needs an integrated platform to communicate between various systems

while providing an interactive portal for the supervisory staff on site. Before designing the full-

blown framework, the researcher designed the kiosk, which is the main communication hub of

the framework and one of the key components. This consisted of a single point touch-screen,

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rugged keyboard, mouse, and 3D BIM mouse. The kiosk was equipped with simple, web-based

software that communicated with the web server and the client's terminals in the construction

field and management offices. The first generation i-Booth was designed as a combination of an

information kiosk system and an interactive kiosk system. According to Maguire (1999), kiosk

systems should be “walk up and use” based, but special kiosk systems such as i-Booth need to

cater to specific end users (such as lead workers, foremen, trade and general superintendents, and

construction managers) so that minimal training is required to navigate the system.

The selection of an appropriate touch screen was a very critical aspect. Based on the

advantages/disadvantages and functionality, the best possible market-ready solution for i-Booth

is optical imaging technology. The following are advantages of the optical imaging technology:

No surface coatings, as a result no degradation in image quality and no dead areas, so

the whole screen is covered.

Gloved hands, mechanical styluses, or fingers can be used for touch function.

As they're robust systems, the screen is not affected by contaminants and scratch

marks.

System is easily sealable for dirt, moisture, and dust (environment resistant). As a

result it is ideal for demanding environments such as construction sites.

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Figure 4.15: First Generation i-Booth

The research team carried out user acceptance testing in three construction job sites and

interviewed higher managers to determine the feasibility of both hardware and software. Initially

the researcher and another graduate student in the program designed a dummy version of the

software with simple information categories such as drawings, safety, quality, schedule, etc.

These initial information categories were selected based on the researcher's industry experience

and inputs from the principal investigator. This version only consisted of a Graphical User

Interface (GUI) and some dummy data (see Figure 4.16 below). The researcher demonstrated

this demo system in a laptop connected to an LCD screen in a FIATECH conference, and in

several workshops given by the principal investigator to construction professionals on the 'Top

Ten Targets of Improving Construction Productivity'. More information on the dummy software

is attached in Appendix XI.

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Figure 4.16: Demonstration Graphical User Interface (GUI) of First Generation i-Booth

All the information in the demo system was in either PDF files, videos, or image files.

Based on the inputs from interviews and feedback, the researcher designed the first kiosk with a

touch screen, keyboard, and mouse with simple, web-based software (the research team hired a

graduate student from computer engineering for the software design). The researcher and

technical staff of the Department of Civil Engineering integrated a TV lift to protect the screen

during transportation. This lift enabled the screen to be lowered into the box when transporting.

Three acceptance tests were conducted to fine tune the data structure and user interface of the

kiosk. Users complained about pixel errors in the touch screen (Colle & Hiszem, 2004). The

researcher and software developer increased the button size and redesigned the software to

enhance fat finger functionality (Siek et al., 2005). Several other software features of the system

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were modified based on the input from users, such as integrating BIM models instead of 3D

illustrations. The number of supported file types was increased from three types to any number

of file types, but the kiosk needed software to read the files. As a result files were opened in the

native software instead of in the kiosk software. The kiosk end software only consisted of

information needed for the next two/three weeks based on the look-ahead schedule. This was

done based on the input from workshops to increase the performance.

The research team initially planned to integrate the in-house SharePoint-based document

management system of the general constructor with the kiosk system. The data and information

were uploaded based on two/three week look-ahead schedules. There were several shortcomings

identified during field testing in the last three years, which are relevant to many construction

contractors:

The document management system did not have some key features needed for

integration with the kiosk system. There was no amalgamation of information,

information was just populated into a list, searching for information was time

consuming, and a protocol for information uploading was unavailable.

Staff in the operational level couldn't work with information pertaining to the

subsequent two/three weeks, due to issues and problems in the drawings and other

information.

The integration of information [Site Instructions (SI), Requests for Information (RFI),

Contemplated Revisions (CR), Project Change Notices (PCN), etc.] was done

manually and needed to be updated to soft copies to streamline the process and

improve supervisory staff’s efficiency.

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New hardware components needed to be integrated with the kiosk to ensure better

utilization of BIM in the operational level.

The researcher conducted twenty interviews and developed tables, which are attached in

Appendix XII, to identify information flow within the construction site. This was a very

important step to understanding the current industry practice and inefficiencies in information

handling in construction sites. The general contractor receives all drawing packages as Issued for

Construction (IFC) after the project is awarded. Vital changes and other information necessary to

undertake construction are delivered as shop drawings, RFIs and SIs during the full project

duration. Timely delivery of the above-mentioned information is a critical factor for success. As

a result, the researcher focused mainly on drawings such as shop drawings, RFIs, and SIs and the

way these are handled by contractors and operational level personnel, and where the bottlenecks

occur.

4.2.2.1 Shop Drawings

As the general contractor was self-performing structural concrete, the researcher focused

mainly on rebar and formwork shop drawings. Figures 4.17 and 4.18 below illustrate the

generation and modification of this information. The blue circle represents the starting point of

the information and the green circle represents the final information. Generation of a rebar shop

drawing involves the following steps:

Architectural Consultant: Generation of architectural drawing

Structural Consultant: Generation of structural drawing (can be the same consultant)

General Contractor: Hand over the structural drawings to rebar subcontractor

Rebar Sub-Trade: Create and hand over the shop drawing to general contractor

96

General Contractor: Review the rebar shop drawings and resubmit to subcontractor

for revision and corrections (if needed) or else submit to detailing company (or in

some cases to architectural consultant) for approval

Detailing Company: Review and resubmit for corrections or else approve

General Contractor: Hand over the approved rebar shop drawing to subcontractor to

commence construction

Figure 4.17: Information Flow Chart for a Rebar Shop Drawing

97

Generation of formwork shop drawings ensues as follows:

Architectural Consultant: Generation of architectural drawing

Structural Consultant: Generation of structural drawing (can be the same consultant)

General Contractor: Hand over structural and architectural drawings to formwork

provider (or in-house engineering team) to design formworks

Formwork Provider: Create and hand over the shop drawing to general contractor

General Contractor: Review the formwork shop drawings and resubmit to formwork

provider for revisions (if needed) and corrections or else submit to structural

consultant (in some cases to architectural consultant) for approval

Structural Consultant: Review and resubmit for corrections or else approve

General Contractor: Commence construction based on approved shop drawing

Structural Consultant: Check the formwork before commencing concreting

General Contractor: Commence concreting

Structural Consultant: Give approval for stripping of formwork

General Contractor: Strip the formwork

98

Figure 4.18: Information Flow Chart for a Formwork Shop Drawing

4.2.2.2 Changes

Two other types of information (information handling) the researcher observed were

change RFIs and SIs (see Figures 4.19 and 4.20 below) because the majority of drawings

consisted of multiple RFIs and SIs. Timely delivery of changes to the operational level is critical

for successful project completion. Information contained in drawings inform the workforce of

what needs to be constructed, and changes provide what needs to be changed in the drawings and

other information to complete the project successfully. Generation of a RFI involves the steps

given below:

Subtrade: Generate a query based on requests from field level (this query may be

generated by subtrade or general contractor).

99

General Contractor: Review the query generated by field level; if general contractor

can't resolve the query, generate a RFI.

Trade Consultant: Resolve the RFI through a SI or a CO/ PCN, or else forward that to

Architectural Consultant.

Architectural Consultant: Resolve RFI through a SI or a CO/ PCN based on inputs

from Trade Consultant.

General Contractor: Distribute the SI or CO/PCN to field level/subtrade and execute

the work based on information and close the RFI.

Sub Trade: Execute the work based on information.

Figure 4.19: Information Flow Chart for a Request for Information (RFI)

Generation of a SI occurs as follows:

Trade Consultant: Generate a SI in response to a RFI or to resolve a site issue

identified by trade consultant or architectural consultant.

100

Architectural Consultant: Generate a SI or approve SI issued by trade consultant.

General Contractor: Execute work based on SI or distribute SI to subtrade.

Sub Trade: Execute work based on SI.

Figure 4.20: Information Flow Chart for a Site Instruction (SI)

4.2.3 First Generation AUSIA Framework System Architecture

The first generation AUSIA framework (i-Booth) software system was designed with a

simple architecture (see Figure 4.21 below). The system consisted of three main components:

Office-End Computer: Any computer with i-Booth software installed in the site

office, management office, and home office of the contractor, and computers in the

client's and consultant's offices can act as an office end computer in the system.

Office computers had read-write access to the i-Booth system.

Server: The basic network drive in the system acted as the storage solution. After

installing the software, the network drive was configured such that all the computers

and kiosks in the system could access a specific folder in the network drive. The

101

researcher and software development team utilized the web drive provided by the

University of Calgary during site implementation. There were several reasons to

select the University web drive over commercially available solutions:

o Web drive was available free of charge

o Web drive can be easily accessed by configuring any computer or kiosk

o Support and customizations are available conveniently in the university, free

of charge

Site-End Kiosk: The kiosk developed by the researcher and university technical staff

was used as the site end kiosk. This kiosk was designed with a single point touch

screen, TV lift, laptop, water resistant keyboard, and wireless mouse. These

components were assembled inside a wooden cabinet with a steel frame.

102

Figu

re 4

.21:

Fir

st G

ener

atio

n Fr

amew

ork

(i-B

ooth

)

103

The laptop was equipped with a Windows operating system, PDF professional,

DWF/DWG viewer, Autodesk Navisworks Freedom, and MS office. Software was a basic web

based database. Users accessed information through the GUI (Figure 4.22). Users had read-only

access to information through the kiosk.

Figure 4.22: Graphical User Interface (GUI) of First Generation i-Booth

Other than productivity tool box all other modules were operational during site

implementation. Information was arranged in a pre-determined hierarchical order in the first

generation i-Booth. Hierarchical browsing is called a similarity pyramid. The similarity pyramid

clusters similar information together, which allows users to view the database at varying levels

(Chen et al., 2000). The researcher and software development team decided to incorporate ten

information categories (see orange colour boxes in Figure 4.23 below). Drawings were further

categorized into 8 sub-categories (see yellow colour boxes in Figure 4.23 below). Thereafter the

users had the ability to subdivide based on their preference (for example, based on the number of

104

levels or by area). The schedule was further divided into 4 sub-categories (see yellow colour

boxes in Figure 4.23 below). Thereafter the users had the ability to subdivide based on their

preference (for example, based on the area). The detailed classification used in the first

generation i-Booth is summarized in Figure 4.23 below.

Figure 4.23: Hierarchical Classification of First Generation i-Booth

This predetermined hierarchical browsing technique had some drawbacks: when users are

deep in one folder they have to come back to the home page or go back by the same route if they

want to access other information. As an example, if users were viewing a level one structural

drawing and wanted to view a mechanical drawing in level two, they either had to go back to the

home screen (Figure 4.22) or go back two steps to mechanical (Figure 4.24 below) and go to

level two, which is time consuming.

Information was populated to the system based on the folder structure in the network/web

drive. The information needed, such as a description and version number, was determined based

on the file name. Version history was handled manually and if the file already exists in the

105

system then that file will be superseded with the newer file. Users need to input the version

number when uploading the file.

Figure 4.24: Drawing Menu

After acceptance tests and system modifications, the researcher started site

implementation of the first generation AUSIA framework. Before commencing implementation

the researcher showed a video overview of the system to field and office management staff to

ensure readiness of the technology and readiness of the workforce. This helped to ensure the

kiosk was pre-populated with information needed for field staff. At that time the general

contractor requested that work packages and shop drawings be added to the system.

The researcher initially incorporated these into the drawings section and documented

changes needed for the final version. These changes were incorporated in the second generation.

106

4.3 Software Developers Contribution

A graduate student from the computer science department helped researcher in software

development. The main contributions from the software developer was to develop the basic

software for first generation i-Booth. The researcher provided the complete list of requirements

for the program and functionality required for field testing. Development was done based on

web drive as a central data repository and interface to upload and download information

(Access).

4.4 Conclusion

This chapter analyses data collected from phases I and II of the research study. When

analysing current level of information management the majority of research subjects used hard

copies to disseminate information to the operational level. Updates were done manually in both

hard copies and soft copies. As a result the research subjects encountered problems such as poor

accessibility, inability to handle large volume of information and lack of reliability. Some

general contractors focused on deployment of soft copies to bridge the communication gap

between office and operational level. According to the research subjects there were reasons to

both discourage (data insecurity, lack of infrastructure, and inadequate technology) and

encourage (ease of navigation and accessibility, cost effectiveness, and real time data transferring

capabilities) contractors to deploy soft copies. BIM models have the capability to improve

communication at the field level but updating and integration problems prevented general

contractors from deploying models in the field. This ineffective information management cost

nearly two hours of each supervisory person’s time (nearly seventy dollars per head).

107

The first generation AUSIA framework was designed based on input from site

observations and interviews. Initially it consisted of a kiosk equipped with a single point touch

screen, rugged key board, mouse and 3D BIM mouse with a simple web based software. Later

the system was modified based on input from acceptance tests.

108

Chapter Five: Site Implementation and Testing

This chapter describes on-site implementation and full scale site testing of the first

generation i-Booth at the TTC complex in ABC Polytechnic, from Dec. 2010 to Dec. 2011. This

chapter also deals with site selection, existing information handling methods, activity

monitoring, feedback and modifications requested by the general contractor, and objectives

fulfilled by implementation. The TTC complex included construction of three new buildings

(South Wing, Centre Wing, and West Wing) and providing a major renovation to a fourth

building. The three new buildings added over 700,000 square feet of new class, lab, office, and

common space and consisted of four stories that were built with a self-performed concrete

structure, steel roof structure, and unitized curtain wall cladding. This was a two hundred and

fifty million dollar guaranteed maximum price contract, with a profit sharing model of forty

percent to sixty percent between the general contractor and client if total cost of the project was

less than two hundred and fifty million.

Figure 5.1: Project Site Plan

109

The organizational structure of the project consisted of a management office and a field

office. Three new building projects and a renovation project were carried out by one senior

superintendent and two superintendents. This setup enabled smooth functioning of site

supervision, contract administration, and cost and schedule control.

5.1 Site Selection

The selection of a proper location for site implementation is a critical factor for success

because pilot testing is a time and money consuming exercise. Success of field level systems

largely depends on the attitude of onsite personnel towards technology and their willingness to

try something new.

The field level management team was the most important factor considered when

selecting a site to implement the system. Site implementation can fail for two reasons:

Inadequate readiness level of technology for site testing.

This can be measured using two methods:

o Technology Readiness Level and System Readiness Level (TRL & SRL) -

TRL was developed by NASA and SRL was develop by Sauser et al. (2006)

(discussed further in Chapter Two: Literature Review).

o Acceptance Tests- The researcher conducted three acceptance testing

workshops at three different job sites before site testing, to ensure the readiness

level of the technology (further discussed in Chapter Three: Objectives and

Research Methodology).

110

Workers propensity to embrace new technology also determines successful site

implementation. This can be measured by TRI, developed by Parasuraman (2000).

(Discussed further in Chapter Two: Literature Review.)

Based on researchers’ observations and input from field and office management,

construction personnel have a tendency to resist system/procedure changes. As a result these

technologies should be tried and tested thoroughly before implementation.

The summary of the field level management teams' willingness to embrace and try new

technology is given in Appendix XIII (only the West Wing and Centre Wing were considered

because South Wing was not a feasible option to implement the system). According to this

summary, Center Wing staff had medium TRI scores and a positive attitude regarding new

communication technology.

The South Wing superstructure was completed and the finishing stage had already started

when the researcher first came to the site. The researcher preferred to implement the system with

the general contractors' crew because subtrades were not part of the collaborative research and

development project. The South Wing would have been an ideal place to implement if the

researcher had had the chance one year earlier, because it was a small, compact building. As the

West Wing superstructure was under way (only two floors were completed from a total of five

floors), the learning curve influence was minimal so it was a benefit (Wong & Cheung, 2008).

The researcher had to manage this project by himself because of the confidentiality

agreement between the general contractor and the researcher to release the information. The size

of the Center Wing was too large for this kind of implementation because the time and effort

needed for site implementation is directly proportionate to project size. Based on the researchers’

experience, technically advanced systems and tools need not be implemented in large projects to

111

reap benefits. The effort needed to implement an information management system is directly

proportionate to the project size but the benefits don’t depend on project size. So the size of the

West Wing was ideal for testing.

Another reason for selecting this site was ease of accessibility, as it was closer to the

university. Based on the above rationale the researcher decided to pilot test the system in the

West Wing.

5.2 Existing Information Handling

The researcher conducted some observations initially to understand the current

information handling practices. Also some interviews were done with the project manager, senior

superintendent, trade superintendents, document coordinator, field engineers, and foremen to

validate and reinforce the observations (see earlier chapter for details).

The general contractor used an in-house, web-based information management system

called “Portable Document Solutions (PDS)” for information/document handling, contract

administration, and construction management. This system was good for contract administration

and construction management, but using this for information management had several down

sides:

Information and data (such as drawings, specifications, RFI, SI, and CR) were

populated into a web-based database without any integration between these

information. As a result extra time was needed when searching for particular

information. This was compensated by two hardcopy drawing sets kept in the

management office and field office. These were updated manually by two separate

field engineers.

112

There was a lack of integration and automation in the document management system.

As an example, when a user wanted to find drawing number S40.00 he had to go to

the structural (IFC) section and download the PDF of the drawing, but there was no

proper procedure for finding the latest revision of the drawing. (This was a major

drawback when the researcher wanted to integrate the existing PDS with the

framework).

Constructability and accuracy of the information were not verified when uploading

information into the existing system. (Because of this the researcher was unable to

directly connect the framework with PDS.)

There were a few issues raised by field supervisory staff that needed solutions in order to

prevent productivity loss due to inadequate communication at the field level. Schedulers and

planners used Primavera P6 for scheduling construction activities, but detailed construction

planning had to be done by a foreman and site superintendents, which was usually done on a

white board or in Microsoft Excel. A solution was needed to integrate these two methods for

better performance. Field staff also complained that information delay led to rework and on some

occasions the approved shop drawing was issued only after construction was completed.

The general contractor used Workface Planning and prepared work packages beforehand,

which were either paper binders or PDF files. Workface planning is the process of organizing

and delivering all the elements necessary, before work is started, to enable craft persons to

perform quality work in a safe, effective and efficient manner (Construction Owners Association

of Alberta, 2013). The main purpose of these packages was to ensure that field staff had all the

relevant information in an easily accessible mode. As an example, a package prepared for second

floor slab concrete might consist of:

113

Grade of the concrete and mix design

Final Quality Assurance/Quality Control (QA/QC) of the formwork

Drawings for floor finishing levels, etc.

These packages needed to be updated regularly due to constant changes, but this rarely

happened and as a result field staff of the general contractor and subcontractor had to search for

all of this information in the document control system. This was a waste of resources for both the

general contractor and subcontractor.

5.3 Activity Monitoring

Activity monitoring was conducted to understand the present site condition. The research

team had conducted several activity monitoring sessions in Calgary during the last six years.

This helped the researcher to get a preliminary understanding of labour productivity. The

researcher used the following observation periods and methods for conducting tool time. These

time periods were selected based on the breaks on the site for tea (10:00am – 10:30am) and

lunch (1:30pm – 2:00pm). The researcher only concentrated on carpentry (flyer striping, flyer

placing, and wall forms) and concreting activities because the general contractor self-performed

only these two trades.

114

Table 5.1: Tool-Time Observation Intervals

Time Interval Method Remarks

08.30 – 09.00 am 30min Continuous

09.00 – 09.30 am 30min Continuous Backup Slot

11.00 – 11.30 am 30min Continuous

11.30 – 12.00 am 30min Continuous Backup Slot

02.30 – 03.00 pm 30min Continuous

03.00 – 03.30 pm 30min Continuous Backup Slot

Very high tool times were observed during this observation period; as an example, in

some weeks the researcher observed around seventy percent of direct working time. This project

had higher tool time compared to other projects the research team had previously observed

(Hewage and Ruwanpura, 2006a). Based on discussions with the project director and the

operations manager, productivity of the general contractor had increased significantly during the

last six years. Unfortunately they weren’t willing to reveal the actual figures due to the

competitive nature of the construction industry.

115

Figure 5.2: Project Working Time Analysis

5.4 Integrating AUSIA Framework with Operational Level

The researcher had to integrate the i-Booth with the operational level carefully because

there were several key steps to consider after selecting the West Wing as the location for site

testing. These steps are explained in detail below.

5.4.1 Location Selection

The researcher considered several options within the West Wing for placement of the i-

Booth. The locations considered were:

Workface/Job Site

Site Office

Lunch Room

Foremen Trailers

116

These locations were identified based on the researcher’s experience and input from the

acceptance tests. The factors considered when selecting the location were accessibility,

availability of power and data connections, and security. The main factor considered was easy

accessibility to the kiosk. Though the ideal location to easily access the i-Booth was

workface/job site, there were a few issues to consider such as security and availability of power

and data. The researcher initially positioned the kiosk in the lunch room/work trailer as requested

by the senior superintendent and West Wing superintendent, due to security issues.

Uninterrupted Power Supply (UPS) for the kiosk was also a factor because the initial first

generation version tested wasn't equipped with a UPS. For these reasons the lunch room trailer,

which was adjacent to the structure under construction, was selected as the location for the kiosk.

After three months the kiosk was moved to the first floor of the West Wing. The kiosk was

equipped with a third generation air card to provide data connection (wireless 3G connection).

5.4.2 Information & Communication Management

After the logistics were finalized, the researcher planned the rest of the implementation.

Both the researcher and the management team agreed to consider the hardcopy drawing set in the

field office as the most current and up-to-date version of the drawings for contractual purposes.

Site management and the researcher agreed that field supervisory staff and lead hands always

had to refer to the hardcopy drawing set in the morning before checking the kiosk. This protocol

was practiced to prevent discrepancies between the hard copy and soft data, as the researcher was

uploading information to the kiosk system manually. Table 5.2 below summarizes the

information management during field testing.

117

Tab

le 5

.2: S

umm

ary

of In

form

atio

n M

anag

emen

t

R

esea

rche

r M

anag

emen

t Sta

ff

Fiel

d St

aff

Upl

oadi

ng

Info

rmat

ion

Prim

arily

resp

onsi

ble

for u

ploa

ding

info

rmat

ion

Prov

ide

acce

ss to

PD

S an

d co

ordi

nate

with

field

staf

f to

prov

ide

acce

ss to

softc

opie

sPr

ovid

e ac

cess

to so

ftcop

ies

Typ

e of

Info

rmat

ion

Prov

ide

ratio

nale

beh

ind

reas

ons

for i

nclu

ding

this

info

rmat

ion,

and

purp

oses

it se

rves

Prim

arily

det

erm

ine

type

s of i

nfor

mat

ion

to

incl

ude

in th

e ki

osk

(Dra

win

gs, S

afet

y,

Mee

ting

Min

utes

, and

BIM

)

Influ

ence

rese

arch

er a

nd

man

agem

ent

Ret

riev

ing

Info

rmat

ion

Prov

ide

hard

war

e an

d so

ftwar

e to

help

retri

eval

-

Prim

arily

resp

onsi

ble

to

retri

eve

info

rmat

ion

Tra

inin

gPr

imar

ily re

spon

sibl

e fo

r tra

inin

g C

oord

inat

e w

ith re

sear

cher

and

fiel

d st

aff

-

Han

dlin

g

Issu

es

Prim

arily

resp

onsi

ble

for

docu

men

ting

the

issu

es a

nd

prov

idin

g so

lutio

ns

Coo

rdin

ate

with

rese

arch

er

Res

pons

ible

for r

epor

ting

the

issu

es a

nd te

stin

g th

e

solu

tions

pro

vide

d

118

The researcher communicated one-to-one with management office staff and field office

staff before implementing the kiosk system. Supervisory staff provided inputs, comments, and

concerns on information needed, in which format, at what level of integration, and how

frequently updates were needed. The researcher provided individual training to all the field

supervision and management staff. The researcher was present on the job site during site testing

and was able to give necessary training and information.

5.4.3 Feedback Received & Modifications

Several modifications were done to the kiosk and software based on feedback received

from site implementation. The software was modified by including the following functions and

features:

ability to integrate information

work packages

create a separate section for shop drawings

These modifications were done primarily based on requests from lead hands and

foremen. Kiosk hardware also underwent several modifications based on the input from site

staff, such as adding a forklift ready base and multi-touch display. The prototype unit consisted

of a single-touch rugged display but supervision staff wanted to perform multi-touch functions

such as pan, zoom, etc. through the screen (Song-Gook et al., 2007).

5.5 Project Success

The general contractor monitored project success every week in a systematic manner.

They performed labour cost reporting every week and foremen reported worker time sheets

119

every day. This procedure resulted in a very successful structural completion of the project (West

Wing 2.5 weeks ahead of schedule and Centre Wing 2.5 weeks behind schedule), especially

considering the project size and cost. As well, a smart contracting strategy was used and a profit-

sharing model was adopted by the client.

Another interesting factor was that everybody from the lead-hand to the senior project

manager worked as one well-oiled machine. In particular the site superintendent and assistant

superintendent of the West Wing had a lot of construction experience, which resulted in

identifying errors such as constructability, incorrect sizing before the construction of that

particular item commenced. Deployment of four field engineers and a BIM draftsman resulted in

a positive outcome. Because of that, the work force got the opportunity to benefit from cutting

edge technology such as work packaging and BIM. Field engineers were able to identify some

constructability issues through BIM modeling. Upper management of the general contracting

firm had taken smart steps in the right direction:

Integrating BIM with the field level despite some limitations due to unavailability of

infrastructure to access models.

Hiring a BIM draftsman for the project. Modeling, however, was limited to service

core and staircases due to resource scarcity.

Site management shared the BIM models in work packages but unfortunately workers

and field level supervision staff didn’t have the ability to interact with the model as it was given

to them in printed and PDF formats.

120

5.6 Main Objectives Satisfied By Site Implementation

The researcher fulfilled five objectives through field implementation (the details are

discussed in chapter six):

Improved two-way communication between operational/site level, site management,

and the management office (office management). Enhanced the efficiency and

effectiveness of the information flow between operational/site level, site

management, and management office to augment the information dissemination and

collection process.

Delivered information in a format that the field level could easily understand.

Improved information integration to enhance efficiency and effectiveness of

information dissemination to operational/site level.

Increased the field level automation to enhance information collection and

dissemination.

Selected essential hardware items and optional hardware items for the kiosk system

based on end-user input.

5.7 Conclusion

First generation i-Booth was implemented in TTC complex in Calgary for twelve months.

This complex consisted of three different buildings, which enabled the researcher to select one of

the best possible locations to implement. As systems may fail due to resistance from site staff,

site selection was one of the critical factors for success of implementation. TRI and interviews

assisted the researcher in understanding field supervisory staff’s perspective on leading edge

121

technology and willingness to implement new technology (how adaptive to change). Readiness

of technology for site implementation was tested with acceptance tests.

A major hurdle encountered during site implementation was attaining drawings, contract

documents, and other information from the general contractor. The confidentiality agreement

between the general contractor and the researcher enabled the release of information.

Information management practices of the contractor prevented the researcher from completely

integrating the document management system with the AUSIA framework, so the information

was manually updated to the kiosk by the researcher. The information was delivered in a format

which could be easily accessible through a touch screen kiosk. Implementation improved worker

satisfaction and two-way communication between site and office.

122

Chapter Six: Data Collection and Analysis (During Implementation)

This chapter consists of hypothesis testing and analysis of qualitative and quantitative

data collected during site implementation. The latter half of the chapter contains a comparison of

data collected during implementation (on-site survey) and North American perspective (online

survey).

The researcher collected both qualitative and quantitative data during site

implementation. The researcher conducted workshops to collect data to investigate the level of

communication change before and after implementing the AUSIA framework. The researcher

conducted three workshops each before and after implementation. Survey instruments, listed in

Appendix VIII and Appendix XIV, were used to measure the level of communication. Initially

the researcher conducted Kolmogorov-Smirnov tests to examine the normality of the data (see

Appendix XV for results of K-S test). Based on the results the majority of the variables rejected

the normality assumption. As a result the researcher had to use the nonparametric Wilcoxon

Signed ranked test for hypothesis testing. Other reasons for selecting this statistical method were

explained in earlier chapters.

6.1 Hypothesis Testing

The following are the null hypothesis (H0) and alternative hypothesis (HA) tested:

H0 : Implementation of AUSIA framework does not improve on-site communication

HA : Implementation of AUSIA framework improves on-site communication

Hypothesis can be subdivided into fifty different sub-hypotheses based on AUSIA and

ten information categories (full list of sub-hypotheses are in Appendix III). The researcher

conducted the Wilcoxon Signed Ranked Test for before and after implementation data sets using

123

the IBM SPSS Statistics package. The results of the Wilcoxon Signed Ranked Test are given

below in Table 6.1. As there were only forty-seven research subjects who participated, exact p

values were calculated to prevent errors in approximation. The majority (forty-seven) of sub-

hypotheses p values were less than 0.05. This enabled the researcher to conclude that the AUSIA

framework made a change in the level of on-site communication in a majority of the areas.

124

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ct S

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els

Z -3

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37-3

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p (E

xact

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(Exa

ct S

ig.)

.000

.000

.000

.000

.000

Cer

tific

atio

ns

Z -2

.460

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42-1

.890

-2.6

40-2

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p (E

xact

Sig

.) .0

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80.0

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eath

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65-1

.795

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02p

(Exa

ct S

ig.)

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.001

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nica

lZ

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75p

(Exa

ct S

ig.)

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.000

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125

The frequency tables generated by the Wilcoxon Signed Ranked test enabled the

researcher to investigate the research subjects’ change of perception on communication before

and after implementation. Each individual information types’ preference change before and after

implementation are summarized in Appendix XVI. According to these frequency tables, the

majority of the time after implementation the respondents’ statuses were either neutral or

positive. In only a few instances the preference level became negative. As an example, in the

drawings frequency table, only two responses were negative from more than forty responses

while a majority of the responses were positive (see Table 6.2 below).

Table 6.2: Wilcoxon Signed Ranks of Drawings

Research subjects’ perceptions change (positive, tie and negative responses) was

analyzed according to these ten information categories in five areas of AUSIA.

ID Information Rank

Dra

win

gs

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 27

Tie After = Before 13

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 20

Tie After = Before 18

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 19

Tie After = Before 13

Integration Negative Rank After < Before 0 Positive Rank After > Before 28

Tie After = Before 7

Automation Negative Rank After < Before 0 Positive Rank After > Before 27

Tie After = Before 3

126

In the drawings information category nearly seventy percent of respondents reported a

positive change in accessibility after implementing AUSIA framework, while nearly thirty

percent of respondents didn’t experience any difference. Integration and automation areas in

drawing information category imparted nearly eighty & ninety percent positive change

respectively, while usefulness and satisfaction received more than fifty percent positive change.

Cumulative negative experience was less than ten percent in all five AUSIA areas. Overall more

than fifty percent of the field supervisory staff experienced positive change in drawings

information category (see Figure 6.1 below).

Figure 6.1: Research Subjects Perception Change Regarding AUSIA of Drawings Category after Implementation

127

In the changes information category nearly eight five percent of the respondents reported

a positive change in integration and automation areas after implementing AUSIA framework,

while nearly fifteen percent of respondents didn't experience any difference. Satisfaction area in

changes information category imparted more than seventy five percent positive change, while

accessibility and usefulness received around fifty percent positive change. Cumulative negative

experience was zero percent. Overall more than fifty percent of the field supervisory staff

experienced positive change in changes information category (see Figure 6.2 below).

Figure 6.2: Research Subjects Perception Change Regarding AUSIA of Changes Category after Implementation

128

In the safety information category more than seventy percent of respondents reported a

positive change in automation area after implementing AUSIA framework, while nearly thirty

percent of the respondents didn’t experience any difference. Satisfaction and integration areas in

safety information category demonstrated nearly fifty & forty percent positive change

respectively while accessibility and usefulness received more than thirty percent positive change.

Cumulative negative experience was less than ten percent. Overall more than thirty percent of

the field supervisory staff experienced positive change in safety information category (see Figure

6.3 below). The main reason for less percentage increase in safety compared to others is due to

the great emphasis on safety in construction industry.

Figure 6.3: Research Subjects Perception Change Regarding AUSIA of Safety Category after Implementation

129

In schedule information category nearly eighty percent and seventy percent of

respondents reported a positive change in integration and automation areas after implementing

AUSIA framework, while nearly fifteen percent of respondents didn’t experience any difference.

Satisfaction, usefulness and accessibility areas in schedule information category imparted around

fifty percent positive change, while forty percent of the respondents didn’t experience any

difference in those areas. Cumulative negative experience was around eighteen percent. Overall

more than fifty percent of the field supervisory staff experienced a positive change in schedule

information category (see Figure 6.4 below).

Figure 6.4: Research Subjects Perception Change Regarding AUSIA of Schedule Category after Implementation

130

In quality information category seventy five percent of the respondents reported a

positive change in automation area after implementing AUSIA framework, while twenty five

percent of the respondents didn’t experience any difference. Satisfaction and integration area in

quality information category reported more than sixty percent positive change, while

accessibility and usefulness received more than sixty and fifty percent positive change

respectively. Cumulative negative experience was less than ten percent. Overall more than fifty

percent of the field supervisory staff experienced a positive change in changes information

category (see Figure 6.5 below).

Figure 6.5: Research Subjects Perception Change Regarding AUSIA of Changes Category after Implementation

131

In 3D/4D model information category nearly eighty five percent respondents reported a

positive change in accessibility area after implementing AUSIA framework, while nearly fifteen

percent of respondents didn’t experience any difference. Automation and integration areas in

3D/4D model information category imparted nearly eighty percent positive change, while

usefulness and satisfaction reported more than fifty and sixty percent positive change

respectively. Cumulative negative experience was less than ten percent. Overall more than fifty

percent of the field supervisory staff experienced a positive change in 3D/4D model information

category (see Figure 6.6 below).

Figure 6.6: Research Subjects Perception Change Regarding AUSIA of 3D/4D Models Category after Implementation

132

In the materials information category nearly eighty percent of the respondents reported a

positive change in integration area after implementing AUSIA framework, while nearly fifteen

percent of respondents didn’t experience any difference. Satisfaction and automation areas in

materials information category showed nearly seventy percent positive change while

accessibility and usefulness received more than sixty and forty percent positive change

respectively. Cumulative negative experience was around thirty percent. Overall more than forty

percent of the field supervisory staff experienced a positive change in 3D/4D model information

category (see Figure 6.7 below). The reason behind the more negative response was because the

researcher only electronically presented available material information.

Figure 6.7: Research Subjects Perception Change Regarding AUSIA of Materials Category after Implementation

133

In the certifications information category nearly eighty percent of the respondents

reported a positive change in automation area after implementing AUSIA framework, while

nearly twenty percent of respondents didn’t experience any difference. Integration and

accessibility areas in certifications information category imparted nearly seventy & sixty percent

positive change respectively while usefulness and satisfaction received more than twenty and

thirty percent positive change respectively. Cumulative negative experience was less than ten

percent. Overall more than twenty five percent of the field supervisory staff experienced a

positive change in certifications information category (see Figure 6.8 below). Compared to other

categories here more respondents didn’t experience any difference because LEED and other

certifications systems weren’t applicable to the jobsite.

Figure 6.7: Research Subjects Perception Change Regarding AUSIA Certifications Category after Implementation

134

In the weather information category nearly sixty percent of respondents reported a

positive change in automation area after implementing AUSIA framework, while nearly thirty

five percent of respondents didn’t experience any difference. Satisfaction and integration areas in

weather information category imparted nearly forty & fifty percent positive change respectively,

while accessibility and usefulness reported more than forty and twenty percent positive change

respectively. Cumulative negative experience was around thirty percent. Overall more than

twenty percent of the field supervisory staff experienced positive change in weather information

category (see Figure 6.9 below). The reason behind less increase in weather is because the

research team only linked Weather Canada and Weather Network websites to AUSIA framework

which are accessible through any smart phone (supervision staff had rugged cell phones with

only voice and text capabilities).

Figure 6.9: Research Subjects Perception Change Regarding AUSIA of Weather Category after Implementation

135

In the technical information category nearly eighty percent of the respondents reported a

positive change in automation area after implementing AUSIA framework, while nearly twenty

percent of the respondents didn’t experience any difference. Accessibility and integration areas

in technical information category imparted nearly sixty percent positive change, while usefulness

and satisfaction received more than thirty and fifty percent positive change respectively.

Cumulative negative experience was less than ten percent. Overall more than thirty five percent

of the field supervisory staff experienced a positive change in technical information category

(see Figure 6.10 below).

Figure 6.10: Research Subjects Perception Change Regarding AUSIA of Technical Category after Implementation

136

The researcher divided the ten information categories into two sub-groups:

Primary Information: Drawings, Changes, Safety, Schedule, and Quality

Secondary Information: 3D/4D Models, Materials, Certification, Weather, and

Technical

Researcher assumed all information categories have equal weights and calculated the

perception change of overall AUSIA for primary and secondary information categories (see

Figure 6.11 below). In both primary and secondary information categories more than fifty

percent of the respondents reported a positive change in accessibility area after implementing

AUSIA framework, while less than five percent of the respondents experienced a negative

change. Automation and integration areas in both information categories imparted more sixty

percent positive change. More respondents haven’t experienced any change in usefulness and

satisfaction areas compared to other areas.

Based on the assumption that all five areas of AUSIA have equal weights, more than

sixty percent of the respondents reported a positive change, while thirty seven percent of the

respondents didn’t experience any difference. Only less than three percent experienced a

negative change.

137

Figure 6.11: Research Subjects Overall Perception Change Regarding AUSIA after Implementation

6.2 Comparing the Site Group with the Online Group

The researcher conducted an online version of the ‘present state of information

management’ survey instrument (Appendix V) to demonstrate that perception on field level

communication of the site sample is similar to that of the general population. The online survey

was distributed to the construction community in Calgary through CCA, and in North America

through FIATECH. The researcher received twenty-four total responses after circulating the

survey several times through the construction community in North America. The summary of

demographic information of survey participants is given below in Figure 6.12 and Figure 6.13.

138

Figure 6.12: Distribution of Research Subjects According to Industry Sector

The majority of participants were from the building construction industry and more than

fifty percent of the participants had more than fifteen years of experience. Participants had both

site and office experience to refer to when commenting on/assessing management practices in

the construction industry. The researcher conducted the Mann-Whitney U Test on both online

and onsite data sets. Reasons for selecting the Mann-Whitney U test instead of an independent T

Test were that both groups’ independent and dependent variables were ordinal, and a majority of

onsite samples were not normally distributed (Conover & Iman, 1981). The following are the

null hypothesis and alternative hypothesis tested.

H0 : Online and on-site groups have similar perceptions on field level communication

HA : Online and on-site groups have different perceptions on field level communication

139

Figure 6.13: Distribution of Research Subjects According to Years of Experience

The hypothesis can be subdivided into fifty different sub-hypotheses based on AUSIA

and ten information categories (similar to the full list of sub-hypothesis in Appendix III). The

researcher analysed both on-site and online samples using the IBM SPSS Statistics package. The

researcher conducted the Mann-Whitney U-Test for both groups, and results are given below in

Table 6.3 to Table 6.7. As the online group consisted of twenty-five participants, exact p values

were calculated to prevent errors in approximation. A majority (forty-one/more than 80%) of

sub-hypotheses p values were more than 0.05, so the researcher can conclude that the majority of

the sub-null hypotheses can't be rejected. This enabled the researcher to derive that the majority

of the site sample's perception was similar to the perception of construction professionals in

North America.

140

For an example in the Table 6.3 below, which considers research subjects perception on

drawings and changes, all of the p values were more than 0.05 except in one circumstance

(automation of drawings). From this we can deduce that both the selected online research group

and onsite research subjects have similar perceptions on present level of accessibility,

usefulness, satisfaction and integration of drawings, and accessibility, usefulness, satisfaction,

integration and automation of changes. Similarly Tables 6.4 to 6.7 conclude that other than

accessibility, satisfaction, integration and automation of 3D/4D models, automation of technical

information, and accessibility and usefulness of quality information, both research groups have

similar perceptions on all other categories. This concludes that majority of onsite research

subjects perceptions are comparative to perspective of selected online research subjects.

141

Tab

le 6

.3: M

ann-

Whi

tney

U-T

est S

tatis

tics T

able

for

Dra

win

gs a

nd C

hang

es

Info

rmat

ion

Gro

up

AU

SIA

N

R

ank

Ave

rage

Sum

of

Ran

ks

U

Z

P

Dra

win

gs

On-

site

Acc

essi

bilit

y 41

27

.94

1145

.50

284.

500

-1.3

68

.165

U

sefu

lnes

s 39

26

.72

1042

.00

262.

000

-1.1

94

.261

Sa

tisfa

ctio

n 34

21

.76

740.

00

145.

000

-2.0

66

.053

In

tegr

atio

n 36

23

.42

843.

00

177.

000

-1.7

59

.081

A

utom

atio

n 31

18

.08

560.

50

64.5

00

-2.8

75

.003

Onl

ine

Acc

essi

bilit

y 25

33

.26

565.

50

U

sefu

lnes

s 24

31

.13

498.

00

Sa

tisfa

ctio

n 20

29

.85

388.

00

In

tegr

atio

n 21

30

.86

432.

00

A

utom

atio

n 19

30

.05

300.

50

Cha

nges

On-

site

Acc

essi

bilit

y 42

29

.14

1224

.00

321.

000

.770

.7

26

Use

fuln

ess

39

26.1

9 10

21.5

0 24

1.50

0 .2

59

.313

Sa

tisfa

ctio

n 33

24

.36

804.

00

219.

000

.754

.7

84

Inte

grat

ion

30

22.0

0 66

0.00

19

5.00

0 .1

51

.169

A

utom

atio

n 30

19

.70

591.

00

126.

000

.013

.0

12

Onl

ine

Acc

essi

bilit

y 24

30

.44

487.

00

U

sefu

lnes

s 23

30

.90

463.

50

Sa

tisfa

ctio

n 21

23

.14

324.

00

In

tegr

atio

n 24

27

.53

468.

00

A

utom

atio

n 20

29

.60

444.

00

142

Tab

le 6

.4: M

ann-

Whi

tney

U T

est S

tatis

tics T

able

for

Safe

ty a

nd S

ched

ule

Info

rmat

ion

Gro

up

AU

SIA

N

R

ank

Ave

rage

Sum

of

Ran

ks

U

Z

P

Safe

ty

On-

site

Acc

essi

bilit

y 41

27

.95

1146

.00

285.

000

-.885

.4

00

Use

fuln

ess

42

27.6

4 11

61.0

0 25

8.00

0 -1

.606

.0

90

Satis

fact

ion

36

23.8

5 85

8.50

19

2.50

0 -1

.553

.1

37

Inte

grat

ion

35

24.6

6 86

3.00

23

3.00

0 -.2

95

.823

A

utom

atio

n 30

20

.35

610.

50

145.

500

-1.6

97

.094

Onl

ine

Acc

essi

bilit

y 23

31

.69

507.

00

U

sefu

lnes

s 23

34

.38

550.

00

Sa

tisfa

ctio

n 20

29

.75

416.

50

In

tegr

atio

n 19

25

.86

362.

00

A

utom

atio

n 19

27

.11

379.

50

Sche

dule

On-

site

Acc

essi

bilit

y 38

27

.97

1063

.00

210.

000

-1.2

85

.220

U

sefu

lnes

s 39

27

.18

1060

.00

280.

000

-.650

.5

35

Satis

fact

ion

31

23.2

3 72

0.00

11

7.00

0 -1

.691

.0

96

Inte

grat

ion

33

23.5

0 77

5.50

21

4.50

0 0.

000

1.00

0 A

utom

atio

n 29

19

.50

565.

50

130.

500

-1.6

60

.104

Onl

ine

Acc

essi

bilit

y 22

22

.50

315.

00

U

sefu

lnes

s 23

30

.00

480.

00

Sa

tisfa

ctio

n 18

16

.64

183.

00

In

tegr

atio

n 20

23

.50

305.

50

A

utom

atio

n 20

25

.96

337.

50

143

Tab

le 6

.5: M

ann-

Whi

tney

U T

est S

tatis

tics T

able

for

Mat

eria

l and

3D

/4D

Mod

els

Info

rmat

ion

Gro

up

AU

SIA

N

R

ank

Ave

rage

Sum

of

Ran

ks

U

Z

P

Mat

eria

l

On-

site

Acc

essi

bilit

y 32

22

.00

704.

00

176.

000

-1.8

69

.065

U

sefu

lnes

s 30

22

.27

668.

00

203.

000

-1.2

66

.215

Sa

tisfa

ctio

n 29

21

.16

613.

50

178.

500

-1.0

29

.314

In

tegr

atio

n 29

20

.91

606.

50

171.

500

-.864

.3

99

Aut

omat

ion

26

17.9

4 46

6.50

11

5.50

0 -1

.650

.1

13

Onl

ine

Acc

essi

bilit

y 22

29

.50

472.

00

U

sefu

lnes

s 24

27

.06

460.

00

Sa

tisfa

ctio

n 21

25

.10

376.

50

In

tegr

atio

n 21

24

.25

339.

50

A

utom

atio

n 18

24

.12

313.

50

3D/4

D M

odel

s

On-

site

Acc

essi

bilit

y 23

15

.22

350.

00

74.0

00

-2.0

24

.049

U

sefu

lnes

s 28

18

.27

511.

50

105.

500

-1.9

40

.057

Sa

tisfa

ctio

n 23

14

.35

330.

00

54.0

00

-2.1

54

.030

In

tegr

atio

n 25

15

.28

382.

00

57.0

00

-2.2

44

.026

A

utom

atio

n 23

14

.63

336.

50

60.5

00

-2.2

06

.028

Onl

ine

Acc

essi

bilit

y 16

22

.27

245.

00

U

sefu

lnes

s 19

25

.71

308.

50

Sa

tisfa

ctio

n 15

22

.00

198.

00

In

tegr

atio

n 13

23

.67

213.

00

A

utom

atio

n 15

22

.45

224.

50

144

Tab

le 6

.6: M

ann-

Whi

tney

U T

est S

tatis

tics T

able

for

Wea

ther

and

Tec

hnic

al

Info

rmat

ion

Gro

up

AU

SIA

N

R

ank

Ave

rage

Sum

of

Ran

ks

U

Z

P

Wea

ther

On-

site

Acc

essi

bilit

y 39

27

.78

1083

.50

281.

500

-.233

.8

52

Use

fuln

ess

40

28.1

8 11

27.0

0 29

3.00

0 -.1

48

.897

Sa

tisfa

ctio

n 35

24

.06

842.

00

212.

000

-.401

.7

15

Inte

grat

ion

32

22.9

7 73

5.00

20

7.00

0 -.4

46

.670

A

utom

atio

n 27

19

.28

520.

50

142.

500

-.991

.3

37

Onl

ine

Acc

essi

bilit

y 21

26

.77

401.

50

U

sefu

lnes

s 22

27

.53

413.

00

Sa

tisfa

ctio

n 19

25

.69

334.

00

In

tegr

atio

n 21

24

.71

346.

00

A

utom

atio

n 19

23

.04

299.

50

Tech

nica

l

On-

site

Acc

essi

bilit

y 36

25

.17

906.

00

240.

000

-1.1

12

.222

U

sefu

lnes

s 39

27

.96

1090

.50

310.

500

-.031

1.

000

Satis

fact

ion

30

19.8

7 59

6.00

13

1.00

0 -1

.117

.2

67

Inte

grat

ion

32

22.5

3 72

1.00

19

3.00

0 -.7

99

.433

A

utom

atio

n 27

17

.85

482.

00

104.

000

-2.1

42

.033

Onl

ine

Acc

essi

bilit

y 23

29

.50

472.

00

U

sefu

lnes

s 24

28

.09

449.

50

Sa

tisfa

ctio

n 17

24

.09

265.

00

In

tegr

atio

n 20

25

.71

360.

00

A

utom

atio

n 22

26

.00

338.

00

145

Tab

le 6

.7: M

ann-

Whi

tney

U T

est S

tatis

tics T

able

for

Qua

lity

and

Cer

tific

atio

ns

Info

rmat

ion

Gro

up

AU

SIA

N

R

ank

Ave

rage

Sum

of

Ran

ks

U

Z

P

Qua

lity

On-

site

Acc

essi

bilit

y 35

23

.59

825.

50

195.

500

-2.0

97

.030

U

sefu

lnes

s 39

24

.59

959.

00

179.

000

-2.8

21

.004

Sa

tisfa

ctio

n 31

21

.74

674.

00

178.

000

-1.1

44

.273

In

tegr

atio

n 31

20

.77

644.

00

148.

000

-1.0

88

.304

A

utom

atio

n 25

17

.94

448.

50

123.

500

-1.5

60

.124

Onl

ine

Acc

essi

bilit

y 24

31

.28

500.

50

U

sefu

lnes

s 24

36

.31

581.

00

Sa

tisfa

ctio

n 22

25

.79

361.

00

In

tegr

atio

n 19

25

.17

302.

00

A

utom

atio

n 20

23

.68

331.

50

Cer

tific

atio

ns

On-

site

Acc

essi

bilit

y 20

15

.03

300.

50

89.5

00

-.026

1.

000

Use

fuln

ess

20

15.5

0 31

0.00

80

.000

-.5

43

.626

Sa

tisfa

ctio

n 16

11

.44

183.

00

47.0

00

-.649

.5

73

Inte

grat

ion

17

12.3

2 20

9.50

45

.500

-.4

05

.677

A

utom

atio

n 12

9.

83

118.

00

40.0

00

-.654

.5

32

Onl

ine

Acc

essi

bilit

y 12

14

.94

134.

50

U

sefu

lnes

s 12

13

.89

125.

00

Sa

tisfa

ctio

n 10

13

.29

93.0

0

Inte

grat

ion

09

11.0

8 66

.50

A

utom

atio

n 11

11

.50

92.0

0

146

6.3 Conclusion

Non-parametric statistical analysis and qualitative analysis of research data were

conducted to ensure that the benefits of the AUSIA framework were calculated properly. As

explained above, the majority of the on-site data set did not satisfy the normality assumption, so

hypothesis testing was conducted using non-parametric tests. The researcher established that the

AUSIA framework has a positive impact on communication through hypothesis testing and then

used qualitative analysis to quantify the actual perception change of research subjects. Analysis

revealed that in the primary information category (other than safety) research subjects perception

of integration and automation categories have changed positively by seventy and eighty percent

respectively. In the 3D and 4D models category research subject’s perception of accessibility

has changed positively by more than eighty percent, while their perception of automation and

integration of these models have increased by eighty and eighty two percent respectively. The

analysis concluded that the implementation of AUSIA framework has increased research

subject's overall perception of communication at the operational level by around sixty percent.

The other challenge was to ensure that the selected TTC complex was not an anomaly,

because the impact of the framework depends on the perception of field staff. The researcher

conducted an online survey through CCA and FIATECH to make sure the perspective of site

staff and the perspective of other selected construction professionals from FIATECH and CCA

are similar. Hypothesis testing revealed the majority of the on-site sample’s perspectives are

similar to the selected online sample's viewpoint.

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Chapter Seven: Data Collection, Analysis, Validation of Results, and System Development (Post-Implementation)

This chapter consists of results from acceptance tests conducted after site implementation

was completed. Two workshops were conducted to validate the results from implementation. The

framework was modified based on the input from acceptance tests and site testing. The latter half

of the chapter focuses on hardware and software components of the framework, distribution of

information, the commercial framework, and the final acceptance tests and BVG session.

After completing site implementation the researcher conducted two user acceptance

workshops and an online survey through SurveyMonkey. Online surveys were distributed to the

construction community through CCA and FIATECH. Job site workshops were done by taking

the kiosk to the job site for a week and concluding with a workshop. The online survey was

completed by forty individuals and the on-site survey was done by fifty-two individuals. A

majority of the respondents were from the building construction industry while more than fifty

percent had fifteen years or more construction experience (see Figures 7.1 and 7.2 below).

Figure 7.1: Distribution of Research Subjects According to Industry Sector

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Figure 7.2: Distribution of Research Subjects According to Years of Experience

Participants were also questioned about their previous awareness of the AUSIA

framework or i-Booth. Nearly eighty-five percent of on-line participants had heard about the

system before and more than fifty percent of the on-site participants had also heard about the

system (see Figure 7.3 below). This was done to ensure that most of the participants were aware

about the AUSIA framework (second generation i-Booth) before proceeding with the survey

instrument.

Figure 7.3: Participants Awareness of i-Booth

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7.1 User Acceptance of AUSIA Framework

The researcher provided on-site research subjects the opportunity to try the system

beforehand. The online community was given a description and a picture of the system to find

out their willingness to utilize the system. All of the on-site participants were willing to utilize

the system, while over eighty percent of the online community was willing to deploy the system

in their job site or organization (see Figure 7.4 below).

Figure 7.4: Participants Willingness to Deploy i-Booth

Research participants were asked to provide input on the ideal location to keep the i-

Booth to maximize the usage and benefits. A majority of the online community wanted to keep it

on the work site while a majority of the on-site community wanted to keep it in the site office for

security reasons (see Figure 7.5 below).

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Figure 7.5: Participants preference on Best Location to Keep i-Booth

When asked to provide methods to encourage end users to use i-Booth, research subjects

believed that the best possible scenario was to conduct workshops before implementing the

system. Self-running demonstrations on screen was also a preferred choice (see Figure 7.6).

Figure 7.6: Methods to Encourage End-Users to Utilize i-Booth

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Research subjects were asked to select their preferred method for access control of the

system in the field (access to i-Booth). Two options given were free access to all or limited

access (only foremen and up in the organization having access to the kiosk). The reason for this

was that general contractors were concerned that the workers might concentrate more on the

information given rather than on the work at hand. A majority of the research subjects preferred

limited access while a minority proposed a hybrid solution, namely to allow workers to have free

access to limited portions of the system, mainly work assignments, safety (emergency response

plan), and weather information (see Figure 7.7 below).

Figure 7.7: Participants Preference of Access Control

The most popular choice for access control methods was a traditional user name and

password, while an access card was the second best choice (see Figure 7.8). Research subjects

were not that comfortable with a biometric scan and retinal scan for privacy reasons.

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Figure 7.8: Participants Preference of Access Control Methods for i-Booth

A majority of the users liked the touch screen as the main input device, while a keyboard

was the second option (see Figure 7.9 below). Both online and on-site research subjects chose a

rugged document scanner, rugged printer, and capture pen as essential hardware items, while

proximity scanners and GPS tracking devices were selected as optional hardware items. A 3D

mouse was rated by both groups at just above fifty percent as an essential hardware item (see

Figures 7.10 and 7.11 below).

153

Figu

re 7

.9: U

ser

Rat

ings

on

Val

ue A

dditi

on fr

om In

put D

evic

es

154

Figure 7.10: Categorization of Essential and Optional Hardware Items According to Online Participants Preference

Figure 7.11: Categorization of Essential and Optional Hardware Items According to On-Site Participants Preference

155

Research subjects were also asked to comment on value addition from each hardware

item. More than ninety percent of the online community believed a rugged printer would bring

good value addition to the kiosk. In the online community more than sixty percent believed other

hardware items such as a 3D mouse, rugged document scanner, and capture pen would bring

good value addition to the kiosk. Only fifty percent of the online community believed a

proximity scanner and GPS tracking device would add value to the kiosk (see Figure 7.12

below).

Figure 7.12: Online Participants Perception on Value Addition from Input Devices

A majority (more than eighty percent) of the on-site community believed a rugged

document scanner, rugged printer, and capture pen would add value to the kiosk. A GPS tracking

device and a proximity scanner came next in value addition (more than sixty percent). A 3D

156

mouse was last in value addition (less than fifty percent) from the on-site community (see Figure

7.13 below).

Figure 7.13: On-Site Participants Perception on Value Addition from Input Devices

7.2 Validation of Site Implementation Results

The latter part of the instrument focused on the areas that the AUSIA framework has an

impact on. This was asked to validate the findings from field implementation. Both communities

believed that the system has a very positive impact on information integration, quality, and BIM

integration with the field level. All research subjects believed that all other categories have more

than seventy percent positive impact (see Figures 7.14 and 7.15) on the construction industry.

157

Figu

re 7

.14:

Onl

ine

Part

icip

ants

Per

cept

ion

on B

enef

its o

f i-B

ooth

158

Figu

re 7

.15:

On-

Site

Par

ticip

ants

Per

cept

ion

on B

enef

its o

f i-B

ooth

159

7.3 Modified AUSIA Framework (Second Generation i-Booth)

The research team developed a new, totally integrated solution to improve

efficiency and effectiveness of information management in the construction industry

based on the feedback from site implementation and workshops.

The conceptual framework of the second generation i-Booth consists of the job

site end and the office end. This framework is designed as a distributed computer system.

The AUSIA framework has a server to communicate between the various information

systems of the general contractor, engineer, and architect. Construction personnel have

direct access to the system through a web portal. Depending on roles and responsibilities,

users have read-only or read-write access to the system. Field personnel are equipped

with handheld devices and the construction site is equipped with one or more mobile and

wall-mounted kiosk units. The general contractor can decide the number of kiosk units

needed based on the number of workers on the job site, the nature of the construction, and

financial capability. BIM models are integrated with the framework through the kiosk

and handheld devices on the work site, while in the field office BIM is integrated through

virtual reality and augmented reality. The research team is developing another concept

called a digital plan room, which is explained in the final chapters.

160

Figu

re 7

.16:

Con

cept

ual A

USI

A F

ram

ewor

k (S

econ

d G

ener

atio

n i-B

ooth

)

161

The second-generation kiosk can be summarized as:

An advanced information kiosk designed to improve information integration between

office and site, and on-site communication between different project personnel and

the construction workers.

A large-scale, multi-touch, high-definition display with the latest advancements in

distributed data warehousing and security technologies.

7.3.1 Types of Kiosks

The second generation i-Booth system consists of two main types of kiosks: mobile

(Figure 7.17) and wall mounted (Figure 7.18) systems. The mobile kiosk consists of a multi

touch sunlight readable display, rugged industrial grade key board (function, delete, alter, control

keys were removed to enhance software security) and trackball, rugged letter sized printer,

magnetic strip card reader, proximity scanner, signature capture device and UPS. The wall

mounted kiosk includes a multi touch display, rugged industrial key board and trackball. The

mobile unit is updated overnight (online synchronisation) or through a USB key (offline

synchronization), and the wall mounted unit is updated in real time. If critical updates occur

during work hours, supervisory staff will receive a short text message via their mobile phones so

they can go to a wall mounted unit and update their handheld devices. Field engineers are

responsible for updating the system and integrating the new information with existing

information in the system. This includes updating new drawings to the system; integrating SI,

RFI, CO, and PCN with existing drawings; and creating work packages. The site

superintendent/construction manager has to check the information before releasing it to the work

site.

162

Figure 7.17: Mobile Kiosk

Figure 7.18: Wall-mounted Kiosk

163

7.3.2 Hardware Components for the Kiosk

The researcher identified key hardware components during the site implementation.

These key components for smooth operation are the touch screen, keyboard, and track ball. Other

components identified are ruggedized printer, capture pen, BIM mouse, document scanner and

GPS tracking device. Only a selected number of hardware components were integrated with the

kiosk, but all other mentioned hardware components can be incorporated to the system.

7.3.2.1 Touch Screen

The touch screen is the most important hardware item of the kiosk. The minimum size of

the recommended screen is thirty-two inches. The important features associated with the screen

are sunlight readability, dust resistance, and cold weather resistance.

7.3.2.2 Key Board & Track Ball

The keyboard and mouse are washable and fully sealed industrial grade items. The

researcher used a track ball with left and right mouse buttons because during pilot testing some

problems were encountered when using a wired or wireless standard mouse. These problems

were:

connectivity issues between wireless mouse and the kiosk

due to dust and harsh nature of construction, wireless and wired mouses don't last

long

the ease of use heavily depends on the mouse pad but due to the rugged nature of

construction it's hard to keep a mouse pad in good condition

164

The researcher identified several other hardware components to make the

implementation process easier for field level and management level personnel. These

components are ruggedized printer, capture pen, BIM 3D mouse, document scanner, and GPS

tracking device.

7.3.2.3 Ruggedized Printer

This rugged 10 x 17 letter sized printer enables users to make printouts of

the information they need at field level.

7.3.2.4 Capture Pen

The capture pen is a new device that helps the field level to integrate

with the kiosk system without much difficulty. This capture pen works as a normal pen at field

level and management personnel can do the mark-ups and form filling in regular hardcopy

printouts, and later can synchronise with the computer to digitize these. This costs approximately

one thousand CAD per pen and a general contractor needs only a four-colour laser printer. This

enables the field level to do their work in a normal manner without using a computer, and later

on convert the data into soft data to share with others. This is a very good solution for

information integration (integrating RFI, SI, and CR to drawings and doing mark-ups in

drawings). This can reduce the need to maintain two separate hardcopy drawing sets in the field

office and management office. Later on these can be easily integrated with the kiosk system after

some modifications.

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7.3.2.5 BIM 3D Mouse

The BIM 3D mouse is a specially designed mouse that can be used for BIM

model navigation. This makes it very easy for the field level personnel to navigate

the model without learning the software. This is a very good investment for

contractors because by making tasks easier for field level personnel, they will use BIM more and

that will increase the return on investment.

7.3.2.6 Document Scanner

The industrial document scanner increases two-way communications between

the field level and management. All day-to-day forms and other documents filled

by field level personnel can be scanned quickly and sent to upper management

easily. This allows site personnel with limited ability with computers to adapt to the system

quickly.

7.3.2.7 GPS Tracking Device

A GPS tracking device can be installed in the kiosk system to find the location of the

kiosk in the case of theft. The construction site should be geofenced. If the kiosk is moved from

the site, management will receive a short text and they can monitor movement of the unit online.

This will only cost thirty to forty CAD per month, which is worthwhile considering the capital

cost of the kiosk.

166

7.3.3 Access Control Methods

Access control is done through magnetic strip cards or SIM cards with PIN numbers.

Several access control mechanisms were identified such as user name and password, biometric

scanner, card access, and retinal scanners. But field level personnel were more comfortable with

username and password or card access with PIN. The researcher favours card access because it is

more convenient for field use as users only need to remember a 4 or 5 digit pin number.

Table 7.1: Access Control Methods

Retinal Scanner:

enables users to log

into the kiosk using

retina.

Chip ID Card:

enables users to log

into the kiosk using

the chip ID card and a

unique PIN number

for each individual.

Biometric Scanner:

enables users to log

into the kiosk using

biometrics (finger

scanner).

User Name and

Password: enables

users to log into the

kiosk using user

name and password.

7.3.4 Mobile Handheld Devices to Integrate with Kiosk

Supervision staff will be equipped with handheld devices such as iPads, androids, and

Golden-i. Handheld devices enable staff at the operational level to use new technologies such as

167

Quick Reference (QR) codes for Material Safety Data Sheet (MSDS), playing training videos,

and to display messages/photos and company contact details.

Table 7.2: Handheld Devices

Rugged Handheld:

enables users to

access certain

information from the

kiosk. This also

increases the two-way

communication

between site and

office.

Golden-i: enables

users to access the

kiosk through this

device via Bluetooth

(users can view a 15”

monitor through the

eye piece). This helps

end users to access

information while on

site without going to

the kiosk.

Androids: enables

users to access some

information through

an android. This

helps end users to

access the

information while on

site without going to

the kiosk.

iPad: enables users to

access some

information through an

iPad. This helps end

users to access

information while on

site without going to

the kiosk.

168

7.3.5 Software Components for the Kiosk

There are a few key software items that the researcher has identified as essential for

smooth operation of the kiosk. These are a PDF editor and viewer, BIM viewer, and Design Web

Format (DWF) and DWG (DraWinG) viewers. All these software components are included in

both types of kiosks. Other types of software can also be included as required without any

restrictions.

7.3.5.1 PDF Editor and Viewer

The researcher used a Professional PDF editor and viewer to integrate various

sources of information into one source. Drawings were integrated mainly

through PDF. Drawings were integrated with SI, RFI, CR, and other related

drawings. Examples:

Mechanical drawing of the lift-core was integrated with related structural drawings,

architectural drawings, electrical drawings, and changes (RFI, SI and CR).

Architectural drawings were integrated with cross sections, levels, and details.

Integrated relevant concrete spec sections were integrated with structural concrete

drawings.

The researcher secured the PDF file with a password after integration was completed.

Figure 7.19 below represents the integration of a structural drawing with a site

instruction.

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Figure 7.19: Level 3 Concrete Beam Schedule Integrated with Site Instructions

3D models and BIM models are integrated with the field level through a 3D interactive

PDF model. Interactive 3D PDFs are easy to operate by field supervision staff for several

reasons:

No infrastructure is needed to view models through the kiosk (only Adobe Acrobat

Reader)

Models can be easily secured through PDF

Plug-ins to convert BIM models to PDF are inexpensive compared to BIM software

Field supervisory staff only need limited training to operate 3D PDF models

Field supervisory staff has the ability to check dimensions and identify elements just

by clicking on the elements.

Figure 7.20 below shows a sample 3D PDF.

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Figure 7.20: 3D Interactive PDF Model (Adobe, 2013)

7.3.5.2 BIM Viewer/Autodesk Navisworks Freedom

The researcher utilized freely available Autodesk Navisworks Freedom software (BIM

viewer) to access BIM models through the kiosk. The BIM viewer enables users to interact with

the model while providing security needed by engineers to prevent users from editing the model.

This viewer is highly intuitive and easily accessible through the touch screen. This allows

workers who are not comfortable with the keyboard and mouse to utilize models through the

touch screen with ease.

7.3.5.3 DWF and DWG Viewers

Autodesk DWF and DWG file viewers were used in the second generation i-Booth to

access 2D CAD drawings. These 2D drawings were used as an alternative to PDF files. The

CAD file format was integrated with the system at the request of the foremen. They mentioned

that they can access missing information and interact with the CAD file format more easily than

171

with PDFs. At present the construction industry integrates with Bluebeam software (Bluebeam,

2013), which enables users to interact with 2D drawings similar to CAD files. However there are

some issues with accuracy of the measurements, whereas measurements are exact with CAD

files.

7.3.6 Information Arrangement in The System

In the second generation i-Booth the researcher and software development team decided

to enable faceted browsing in the system rather than the hierarchical browsing used in first

generation i-Booth. Faceted browsing or faceted navigation is a technique for accessing

information organized according to a faceted classification system. A faceted classification

system allows assignment of multiple characteristics to an object. This enables users to apply

multiple filters in a search. The information in the system was categorized based on the

classifications in the following sections to enable faceted browsing. These classifications were

developed during a two day workshop with construction industry professionals. The

classifications given below were developed for a four-storey building project at the University of

Calgary. These classifications can be customized to suit the client’s needs and the project

requirements.

7.3.6.1 Design Drawings

Design drawings were classified based on five different criteria:

Type-drawings were classified into eight subtypes (Figure 7.21) based on the

discipline.

Location: This depends on project type and nature of the construction. As mentioned

above, the subtypes given below were developed for a four-storey building project

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but if this was for a bridge project these subtypes would change to

substructure/foundation, pillars, deck, and abutments.

View: This was developed based on the views in 2D IFC drawings.

Element: Element sections will differ based on the selection of the eight ‘types’

mentioned above. The elements given below are structural elements.

Stage: Depends on the stage of the project.

Figure 7.21: Classification of Design Drawings

7.3.6.2 Shop Drawings

Shop drawing classification consists of three subtypes:

Master format: This was based on 2011 Master Format (CSI, 2013).

Trade: Depends on the job function.

Location: This depends on project type and nature of the construction.

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Figure 7.22: Classification of Shop Drawings

7.3.6.3 Specifications

The classification below was developed based on the 2011 Master Format. Sections will

be arranged according to spec section.

Figure 7.23: Classification of Specifications

174

7.3.6.4 Quality

This classification consists of four main subtypes:

Check list: This consists of all the check lists related to quality.

Quality plan: This is divided into two main categories, namely subcontractor and

general contractor.

Deficiency list

Other: Can include anything related to quality other than items mentioned above.

Figure 7.24: Classification of Quality

7.4 Distribution Matrix

Distribution of information in the AUSIA framework is based on a distribution matrix or

a distribution list. This matrix is based on the site organization structure. One of the major

concerns of research participants and other workshop participants was the need to ensure the

accuracy of the information in the AUSIA framework. The researcher decided to introduce the

distribution matrix concept to resolve the accuracy issues. Accuracy of information will be

checked by individuals appointed by the general contractor. These individuals (one or more) are

175

appointed based on the trade, and they have the authority to approve or reject the information in

the AUSIA framework. Supervisory staff members below the grade of the responsible authority

will not have access to information until approval is given. This ensures the accuracy of the

information before its release to the operational level.

After a handheld application of the AUSIA framework is developed, supervisory staff

will have the ability to make queries from the optional level. The information flow from the field

level depends on the supervisory relationship. As an example, when a lead hand or a foreman

makes an inquiry from the field, the AUSIA framework will notify the immediate supervisor of

that particular individual about the issue. This enables the individual and supervisor to resolve

the issue if possible, or the supervisor may choose to report it to upper management. If the

general contractor isn’t able to resolve the issue in-house then a RFI can be initiated through the

AUSIA framework to resolve the issue.

7.5 Commercial AUSIA Framework (2nd Generation i-Booth)

The second generation i-Booth was formally introduced to the construction indsutry at

the launching ceremoney in April, 2012 at the University of Calgary.

The commercial system (2nd generation i-Booth) was designed based on three principles

(known as three I’s):

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Figure 7.25: Three 'I' Principles of AUSIA Framework

Interaction: The success of the 2nd generation i-Booth largely depends on how the

system interacts with users and other systems. The researcher selected hardware items

such as a touch screen, track ball, and card access to enhance the user interaction and

user experience. The software system/platform was designed to interact and integrate

seamlessly with other systems such as ERP, Contract Management, Schedule, Cost

Control, etc.

Integration: Information integration was the key aspect of the AUSIA framework.

As explained in earlier chapters, information integration has a positive correlation

with construction productivity. The researcher and software development team

enabled users from the office end to integrate information and access integrated

information from the kiosk. Previous versions of i-Booth utilized professional PDF

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files to integrate information. These files don’t have the ability to update linked

information automatically so the users have to manually update the links. The second

generation i-Booth system was designed so that after initial relationships were built,

when source information gets updated users don’t need to update the links again

(Figure 7.26).

Figure 7.26: Integration in AUSIA Framework

Interface: GUI of the second generation i-Booth was designed by a special team with

background in human behavior studies. The GUI was designed such that users can

access any information in three clicks (Figure 7.27). There is a certain level of skill

needed when touch screens are utilized due to overly sensitive or unresponsive

buttons. In the i-Booth the size of the buttons and check boxes were designed to

enhance the touch screen experience. These buttons and check boxes were designed

for a fat finger, and as a result these buttons are not overly sensitive but are very

responsive (Siek, Rogers, & Connelly, 2005; Colle & Hiszem, 2004).

178

Figure 7.27: GUI of Second Generation i-Booth

7.6 Final Acceptance Testing

The researcher, software developer, and supervisor conducted an acceptance test at CCA.

Six general contractors participated in six different workshops to describe the changes and

modifications they wanted in the system. This was done in six workshops because contractors

had more freedom to express their needs without their competitors present. These sessions were

videotaped and user stories were later transferred to features and functions. Finally, research

subjects rated the system on eleven different categories in a 1-7 Likert scale. The survey

instrument used for rating in these workshops is given in Appendix XVII. The responses were

aggregated and summarized in table 7.5 below. Based on the aggregates all the categories

179

showed seventy percent positive responses. Percentages were calculated as follows (e.g. Overall

reaction to the System):

Total Number of Responses: 26

Total Possible Score: 7x26

182

Earned Score: 1x0 + 2x0 +3x1+4x1+ 5x11+

6x13+7x0

140

Percentage: 140/182x100

76.92%

180

Tab

le 7

.3: A

ccep

tanc

e T

estin

g Su

rvey

- 2nd

Gen

erat

ion

i-Boo

th (A

USI

A F

ram

ewor

k)

Item

1

2 3

4 5

6 7

Perc

enta

ge

1 O

vera

ll re

actio

n to

the

Syst

em

0101

1113

Te

rrib

le

W

onde

rful

2 Te

rmin

olog

y an

d Sy

stem

Info

rmat

ion

05

1506

C

onfu

sing

Ver

y cl

ear

3 Sy

stem

Com

patib

ility

with

Exi

stin

g

Syst

ems a

nd P

roce

sses

01

0613

0201

Bad

Goo

d

4 G

raph

ical

Use

r Int

erfa

ce/S

cree

n

Des

ign

0410

12

Con

fusi

ng

V

ery

clea

r

5 Sy

stem

Nav

igat

ion

0307

15

Con

fusi

ng

V

ery

clea

r

6 Pe

rcei

ved

Ease

of U

se

0104

1011

B

ad

G

ood

7 Pe

rcei

ved

Use

fuln

ess

01

04

1011

B

ad

G

ood

8 Su

bjec

tive

Satis

fact

ion

05

1307

B

ad

G

ood

9 Ef

ficie

ncy

0202

1406

B

ad

G

ood

10

Con

sist

ency

01

0708

09

Bad

Goo

d

11

Lear

n-ab

ility

01

0408

13

Bad

Goo

d

181

7.7 BVG Sessions

The researcher conducted four BVG sessions with Canadian construction

professionals to measure acceptance of the AUSIA framework within the construction

industry. These sessions were conducted at the following events:

Calgary Construction Association board of directors’ annual general meeting

held in Banff, Alberta.

Canadian Construction Association's annual general meeting held in Jasper,

Alberta.

Two sessions organized by Productivity Alberta for construction professionals

in Edmonton.

Events started with an overview and demonstration of the AUSIA framework and

concluded with open-ended discussions. A majority of the attendees expressed positive

feedback about the system and the research team is negotiating with a few of these

attendees to transfer the system.

7.8 Software Developers Contribution

A postdoctoral fellow helped the researcher in software development. Based on

availability of resources only the front-end GUI was modified. The main contribution

from the software developer was to develop a GUI to demonstrate the capabilities of

second generation i-Booth. Researcher provided all information required for faceted

classification and also provided a data set with required relationships and meta data for

faceted classification. Based on these input software developers designed the GUI to

demonstrate the capabilities of the kiosk.

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7.9 Conclusion

The researcher conducted two workshops on two job sites and an online survey to

validate the findings from site implementation. Data collected from on-site and online

samples were analysed separately because the on-site sample had the opportunity to

interact with the kiosk for a week while the online group only had some pictures and a

description. The first part of the survey focused on logistics, setup, and hardware

components of the kiosk and the second half emphasised validating the impact on

communication. Both online and on-site groups wanted limited access to the kiosk, while

the on-site group wanted to make some portions of the system with unrestricted access

(such as safety, weather, and work assignments). A popular access control method was

username and password, even though the researcher expected the biometric scanner and

retinal scanner to be popular because of ease of use. But research subjects were not

comfortable with these due to privacy concerns.

The touch screen was a very successful interactive media for both the tech savvy

work force and the technologically challenged workforce. The majority of on-site and

online research subjects rated the touch screen as an extremely good input device. While

the document scanner, printer, and capture pen were essential hardware items, the

researcher included only a printer because the AUSIA framework in fully implemented

construction sites will be paperless. Both research groups believed that the framework

will have a very positive impact on information integration.

Finally, the researchers manufactured a market-ready information kiosk based on

the feedback received. The researcher and software developer changed the information

183

arrangement to support faceted browsing instead of hierarchical browsing to enhance user

experience.

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Chapter Eight: Conclusions, Recommendations, and Future Research

This chapter briefly describes the specific observations and objectives achieved in

previous chapters, and conclusions derived from analysing data. The latter part of the

chapter further discusses limitations of the research study. Lastly, recommendations for

future development and research are included.

8.1 Research Summary

The main objective of this study was to improve on-site communication in the

construction industry. The researcher observed construction practices and issues faced by

field staff and workers due to poor communication. Workers faced problems such as

rework due to information delay, and time waste due to poor information management.

Looking at these issues, information technology seemed to be an ideal solution to bridge

the communication gap. But a few technology vendors and software developers so far

had limited success in implementing these solutions in the construction industry. This

insight from discussions with field staff led the researcher to develop an integrated

platform to communicate with different systems performed in isolation. This lead the

researcher to think beyond a simple information kiosk and develop a totally integrated

platform that would work with multiple systems across multiple operating systems.

Hand-held application for AUSIA framework will be developed in the next phase of the

research project.

Thereafter, the researcher designed and manufactured a prototype information

kiosk, which is part of the AUSIA framework. The research team, with the help of a

software developer, field tested the alpha version of the software platform with manual

185

integration capabilities. The researcher conducted several acceptance testing workshops

to investigate the features and functions of the software. At these workshops research

partners were keen to see Virtual Design and Construction (VDC) or Integrated Project

Delivery (IPD) with the system but the main drawback in early 2010 to late 2011 was that

field staff didn’t have a mechanism to communicate/interact with these models. The other

major complaint was the lack of integration between data: inability to move from one

data type to another without going back to the root menu (hierarchical browsing).

The researcher then conducted twelve months of field testing after modifying the

system based on feedback from the above acceptance tests . Several changes were done

to the AUSIA framework during site implementation, the main one being that the number

of information categories changed as a result of introducing new categories such as shop

drawings, work packages, etc. Also the researcher introduced integration between

drawings, changes, and specifications to enhance the efficiency and effectiveness of

communication. Workshops were conducted before, during, and after implementation to

prove that the AUSIA framework improved communication in the construction industry.

Finally, two more workshops were conducted on another two jobsites to validate

the research findings, and an acceptance test was done in CCA to determine the level of

acceptance of the system in the construction industry.

8.2 Research Outcome/Findings

Initial site observations and literature validated that there's a communication gap

in the construction industry. Supervisory staff waste more than two hours per day due to

ineffective information handling. This time waste can be minimised by using a better

186

communication system such as the AUSIA framework. According to the Project

Management Institute, “highly effective communicators are five times more likely than

minimally effective communicators to be high performers to complete their projects on

time, on budget and having met original goals and business intent” (PMI, 2013).

The hypothesis testing concluded that the AUSIA framework has increased the

overall communication at the operational level. Majority (around sixty percent) of the

research subjects experienced a positive change after implementation. The most

significant impact was reported in the automation and integration categories. Analysis

revealed that in the primary information category around seventy and eighty percent of

the research subjects experienced a positive change in integration and automation areas

respectively. In the secondary information category, around seventy percent of research

subjects experienced a positive change in integration and automation areas. Many

scholars in the past (Zhai et al., 2009; O'Connor & Yang, 2004; Zhai & Goodrum, 2009)

have established that automation and integration have a positive correlation to

construction productivity.

Overall around fifty percent of the respondents experienced a positive change in

accessibility of information compared to pre-implementation in all categories except for

safety and weather. Especially, eighty four percent of the research subjects have noted a

positive change in the accessibility of 3D and 4D models. Field supervisory staff was

impressed with the improved accessibility to BIM models, and the proposed framework

provided supervisory staff with HIDs to better interact with VDC and IPD models. Due

to the distributed architecture of the AUSIA framework, field staff don’t need to click

and wait for models to load. This was a major complaint from field staff initially when

187

the kiosk was fully web based, which led the researcher to update the system so the

information would synchronize overnight. Improved accessibility to drawings and

integration of information was a major success. As an example, when a foreman looks up

a structural drawing of the service core, information integration provides access to all

mechanical, electrical, changes (SI, RFI & CR), and spec sections relevant to that

drawing without having to go back and forth in the system. The redundancy of the

AUSIA framework and ability to perform offline is an added bonus to the field staff

because the majority of the information systems available don’t perform offline. The

AUSIA framework enabled the general contractor and other stakeholders to integrate

information systems, which enabled both site staff and office staff to better manage the

information. As a result of integration and automation, office staff can create a virtual

work package in the system and let field staff populate that with relevant information.

The faceted browsing function provides the field staff with an edge when searching for

information. The meta data and the classifications enable field staff to search for any

information relatively quickly. This drastically cuts down the time waste in searching for

information.

One of the major obstacles that needed to be overcome was to earn the trust of the

experienced supervisory staff in relying on information technology instead of printed

copies. Pen and paper was the main mode of red-lining drawings for generations. Red-

lining drawings in a softcopy wasn’t a concept they were willing to accept. The digital

pen was an intermediate solution to overcome this by offering the best of both hard copy

and soft copy. (See Appendix XVIII for detailed implementation of digital pen or capture

pen.) The general contractor maintained two master sets of drawings in the site office and

188

management office, which were manually updated by two different individuals. After

introducing the AUSIA framework the general contractor has the option to release one

staff member to more important work such as constructability reviews, detailed

construction planning, and supervision work.

This research concluded that the AUSIA framework improves communication in

the construction industry significantly, while bringing positive benefits to construction

productivity and reducing rework due to information delay.

8.3 Research Contribution

The most important contribution from this research is the market-ready hardware

solution with high-level software architecture. This research project recognised and field

tested several potential technologies to overcome communication issues in site level. The

research team has already sold one kiosk unit while several potential buyers are

negotiating with i-Booth Inc. to purchase more units.

The AUSIA framework and information distribution matrix enable higher

managements and other supervisory staff members to communicate real-time with

operational level more clearly and effectively. Also identification of suitable hardware

items and HIDs enhance the information retrieval while improving communication.

The drawbacks in current information management and communication systems

in commercial construction industry were clearly identified by this research. This clear

problem identification and analysis of drawbacks enable future researchers to better adopt

technology tools in commercial construction industry.

189

The site implementation of AUSIA framework revealed that the research subjects

believe the use of an integrated and automated system significantly improves

communication in operational level. Successful site implementation changed the attitude

of field supervisory personnel's' perception on construction technology.

There are several more contributions from this research. The research community

and the Calgary construction industry have experienced positive benefits from improved

communication between field and office. The research community has the opportunity to

integrate novel mobile technologies such as Golden-i and, maybe in future, Google Glass.

This system was pilot tested extensively in the construction environment; as a result,

developing the remaining parts of the system is not much of a challenge for the research

community.

The construction community and the Calgary construction industry will benefit as

this novel solution points general contractors towards paperless construction. The general

contractor who agreed to pilot test the system was very enthusiastic and had several

discussions with the researcher and the principal investigator to purchase the system. As a

result of financial barriers, however, the general contractor used his extensive knowledge

of the system to build an in-house version.

The kiosk developed during this research project was successfully tested in an oil

sands project in Northern Alberta for six months, with a different software platform

developed for industrial construction. This proves the versatility of the hardware in

different types of construction.

190

Penetrating the construction market with technology tools was a big challenge for

the researcher, and this successful market reception will pave the way for future

researchers.

8.4 Research Limitations

The major limitation of the research was unavailability of productivity data to

prove a direct benefit from increase in communication. As explained earlier, improving

communication without improving construction productivity will be an extra financial

burden for construction industry. The researcher used empirical means to suggest that the

framework generates positive construction productivity.

Another limitation was the inability to fully test the system with the general

contractor as a result of a confidentiality agreement that prevented integration with

contractor's information management system. This prevented full implementation and as

a result the researcher had to manually integrate the AUSIA framework. Other limitations

are summarized below.

The AUSIA framework was implemented with the general contractor who

was only self-performing formwork and concreting. As a result findings can’t

be generalized for other trades such as mechanical, electrical, and finishes.

The findings of the research are predominantly based on workshops,

interviews, and observations on a construction site in Calgary. It might not be

possible to generalize the findings to different regions because of differences

in workers’ skill levels, market conditions, and climate conditions. The

191

researcher investigated the level of communication across North America to

ensure that the selected job site isn’t an anomaly.

The proposed AUSIA framework was developed based on expectations and

opinions of construction professionals in Calgary. General contractors in other

regions might need to modify the framework based on the type of

construction, the region, and the needs of supervisory staff.

Success of the proposed framework largely depends on continuous

improvements. Devices and types of information need to be changed to suit

the needs of the construction industry.

8.5 Future Research and Recommendations

The researcher and i-Booth Inc. plan to design a digital drawing table and digital

drawing room for incorporation with the AUSIA framework. The digital drawing table

will be similar to the mobile i-Booth but the table angle, height, and width will be

determined by ergonomics. Table width will depend on the size of the door in trailers.

The digital plan room will consist of several digital drawing tables, mobile i-Booths, and

augmented, reality-based systems to visualize models. An augmented reality-based

system consists of several headsets that will enable users to have an actual walk-through

experience in the structure.

192

Figure 8.1: Digital Drawing Table

193

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Appendix I – Combined Summary of Productivity Factors

Country

Total

Number of

Studied

Factors

Major Factors

United

Kingdom

(UK)

13

Skill of labour; Buildability; Quality of supervision;

Method of working; Incentive scheme; Site layout;

Complexity of construction information; Crew size and

composition; Length of working day; Availability of

power tools; Absenteeism; Total number of operatives on

site; and Proportion of work subcontracted (Horner,

Talhouni, & Thomas, 1989).

Singapore 17

Difficulty in recruitment supervisors; Difficulty in

recruitment workers; High rate of labour turnover;

Absenteeism at worksite; Communication problems with

foreign workers; and Inclement weather that requires

work stoppage for one day or more (Lim & Alum, 1995).

Iran 13

Material shortage; Weather and site conditions;

Equipment breakdown; Drawing deficiencies/change

orders; and Lack of proper tools and equipment (Zakeri,

Olomolaiye, Holt, & Harris, 1996).

Country Total Major Factors

205

Number of

Studied

Factors

Indonesia 11

Lack of materials; Rework; Absenteeism of operatives;

Lack of suitable tools and Equipment; and Crew

interference (Kaming, Olomolaiye, Holt, & Harris, 1997).

Thailand 23

Lack of material; Incomplete drawings; Incompetent

supervisors; Lack of tools and equipment; Absenteeism;

Poor communication; Instruction time; Poor site layout;

Inspection delay; and Rework(Makulsawatudom, Emsley,

& Sinthawanarong, 2004).

Canada 51

Thirty five of those factors were significantly related to

poor management practices in the construction industry.

Management factors, such as lack of detail planning,

inadequate supervision, and lack of information.

USA 81

CII identified 81 factors which narrow down to ten by

research group in 2009 to factors such as “I have to wait

for people and/or equipment to move the material I need”,

“There are errors in the drawings that I use”, etc. (Dai et

al., 2009)

206

Appendix II - Summary of Human Aspects in Kiosk Design

Item Recommendations

Defining user requirements Determine the end-user population for the

Kiosk. Obtain user feedback on system

content and concept.

Location and encouraging use Provide a bright attractive screen, and if

possible a self-running demonstration to

indicate purpose of system and how to use

it.

Place logically in the work area depending

upon the following: nature of the job site,

type of construction, complexity and total

project cost.

Physical access and number of kiosks Place the kiosk in a well-lit area with

adequate physical access.

Number of kiosks per construction job site

will be determined by job complexity, type

of construction, total project cost and

number of workers.

207

Item Recommendations

Introduction and instructions Workshops which target end users to

introduce the system.

On screen, short, free running

demonstration can save time on lengthy

instructions.

Proximity scanner to sense users and popup

the login screen.

Privacy SIM card access control system, finger print

scanner, or retinal scanning system will be

utilized to identify users.

User log file will record user activities.

Users will have different levels of access

(read-write and read-only) to different

contents depending upon job function.

Input to the kiosk (General) Trackball/Mouse and a touch screen can be

used as the pointing device.

Keyboard and speech input for content

input.

Mobile kiosk systems (open air system)

designed to withstand weather, vandalism

and continuous use.

208

Item Recommendations

Keyboard Generic keyboard or specific keyboard

depending upon user requirement.

Touch Screen Minimum button area 2.6cm2 (allowing for

gloved hands).

Feedback for users when button is pressed

(change of button colour, pressing action or

clicking/pressing sound)

Speech Input Noise robust speech input system.

Knowledge among users about keywords to

be used.

Data Capture Bar Code Scanners and RFID readers

depending on end-user requirement.

Communication (Optional Feature) Webcam & Microphone to communicate

with off-site management and supervision

staff. This feature is optional and can be

included depending upon end-user

requirement.

Text and Colour Minimum font Size 16point.

Font style simple.

209

Item Recommendations

Feedbacks When system is delayed more than 3s

display a message indicating that

processing is taking place.

Allow users to give anonymous feedback

on system performance.

Images and Graphics When reducing the image size make sure

user can see the details.

Ensure users can see the image or graphic

in one screen without scrolling.

Audio and Video Output Natural speech is generally preferred to

synthetic.

Optimum resolution for clear viewing

without hampering file size.

Structure and navigation Simple, clear and consistent structure

throughout the system.

Show users current position in the structure

and navigation keys to go one step back and

to main menu/sub-menu.

Menu Limit number of menu options to 12 or less.

Avoid splitting a menu in to two pages.

210

Appendix III – Complete List of Hypothesis for AUSIA Framework

Table A1: Null and Alternative Hypothesis for Drawings

Hypothesis Description Null Hypothesis

H0DA Implementation of AUSIA framework does not improve accessibility of drawings on-site

H0DU Implementation of AUSIA framework does not improve usefulness of drawings on-site

H0DS Implementation of AUSIA framework does not improve satisfaction with drawings on-site

H0DI Implementation of AUSIA framework does not improve integration of drawings on-site

H0DA Implementation of AUSIA framework does not improve automation of drawings on-site

Alternative Hypothesis

HADA Implementation of AUSIA framework improves accessibility of drawings on-site

HADU Implementation of AUSIA framework improves usefulness of drawings on-site

HADS Implementation of AUSIA framework improves satisfaction with drawings on-site

HADI Implementation of AUSIA framework improves integration of drawings on-site

HADA Implementation of AUSIA framework improves automation of drawings on-site

211

Table A2: Null and Alternative Hypothesis for Changes

Hypothesis Description Null Hypothesis

H0ChA Implementation of AUSIA framework does not improve accessibility of changes on-site

H0ChU Implementation of AUSIA framework does not improve usefulness of changes on-site

H0ChS Implementation of AUSIA framework does not improve satisfaction with changes on-site

H0ChI Implementation of AUSIA framework does not improve integration of changes on-site

H0ChA Implementation of AUSIA framework does not improve automation of changes on-site

Alternative Hypothesis

HAChA Implementation of AUSIA framework improves accessibility of changes on-site

HAChU Implementation of AUSIA framework improves usefulness of changes on-site

HAChS Implementation of AUSIA framework improves satisfaction with changes on-site

HAChI Implementation of AUSIA framework improves integration of changes on-site

HACAh Implementation of AUSIA framework improves automation of changes on-site

212

Table A3: Null and Alternative Hypothesis for Safety Information

Hypothesis Description Null Hypothesis

H0SaA Implementation of AUSIA framework does not improve accessibility of safety information on-site

H0SaU Implementation of AUSIA framework does not improve usefulness of safety information on-site

H0SaS Implementation of AUSIA framework does not improve satisfaction with safety information on-site

H0SaI Implementation of AUSIA framework does not improve integration of safety information on-site

H0SaA Implementation of AUSIA framework does not improve automation of safety information on-site

Alternative Hypothesis

HASaA Implementation of AUSIA framework improves accessibility of safety information on-site

HASaU Implementation of AUSIA framework improves usefulness of safety information on-site

HASaS Implementation of AUSIA framework improves satisfaction with safety information on-site

HASaI Implementation of AUSIA framework improves integration of safety information on-site

HASaA Implementation of AUSIA framework improves automation of safety information on-site

213

Table A4: Null and Alternative Hypothesis for Schedule Information

Hypothesis Description Null Hypothesis

H0SchA Implementation of AUSIA framework does not improve accessibility of schedule information on-site

H0SchU Implementation of AUSIA framework does not improve usefulness of schedule information on-site

H0SchS Implementation of AUSIA framework does not improve satisfaction with schedule information on-site

H0SchI Implementation of AUSIA framework does not improve integration of schedule information on-site

H0SchA Implementation of AUSIA framework does not improve automation of schedule information on-site

Alternative Hypothesis

HASchA Implementation of AUSIA framework improves accessibility of schedule information on-site

HASchU Implementation of AUSIA framework improves usefulness of schedule information on-site

HASchS Implementation of AUSIA framework improves satisfaction with schedule information on-site

HASchI Implementation of AUSIA framework improves integration of schedule information on-site

HASchA Implementation of AUSIA framework improves automation of schedule information on-site

214

Table A5: Null and Alternative Hypothesis for Material Information

Hypothesis Description Null Hypothesis

H0MaA Implementation of AUSIA framework does not improve accessibility of material information on-site

H0MaU Implementation of AUSIA framework does not improve usefulness of material information on-site

H0MaS Implementation of AUSIA framework does not improve satisfaction with material information on-site

H0MaI Implementation of AUSIA framework does not improve integration of material information on-site

H0MaA Implementation of AUSIA framework does not improve automation of material information on-site

Alternative Hypothesis

HAMaA Implementation of AUSIA framework improves accessibility of material information on-site

HAMaU Implementation of AUSIA framework improves usefulness of material information on-site

HAMaS Implementation of AUSIA framework improves satisfaction with material information on-site

HAMaI Implementation of AUSIA framework improves integration of material information on-site

HAMaA Implementation of AUSIA framework improves automation of material information on-site

215

Table A6: Null and Alternative Hypothesis for 3D/4D Models

Hypothesis Description Null Hypothesis

H0MoA Implementation of AUSIA framework does not improve accessibility of 3D/4D models on-site

H0MoU Implementation of AUSIA framework does not improve usefulness of 3D/4D models on-site

H0MoS Implementation of AUSIA framework does not improve satisfaction with 3D/4D models on-site

H0MoI Implementation of AUSIA framework does not improve integration of 3D/4D models on-site

H0MoA Implementation of AUSIA framework does not improve automation of 3D/4D models on-site

Alternative Hypothesis

HAMoA Implementation of AUSIA framework improves accessibility of 3D/4D models on-site

HAMoU Implementation of AUSIA framework improves usefulness of 3D/4D models on-site

HAMoS Implementation of AUSIA framework improves satisfaction with 3D/4D models on-site

HAMoI Implementation of AUSIA framework improves integration of 3D/4D models on-site

HAMoA Implementation of AUSIA framework improves automation of 3D/4D models on-site

216

Table A7: Null and Alternative Hypothesis for Quality Related Information

Hypothesis Description Null Hypothesis

H0QuaA Implementation of AUSIA framework does not improve accessibility of quality related information on-site

H0QuaU Implementation of AUSIA framework does not improve usefulness of quality related information on-site

H0QuaS Implementation of AUSIA framework does not improve satisfaction with quality related information on-site

H0QuaI Implementation of AUSIA framework does not improve integration of quality related information on-site

H0QuaA Implementation of AUSIA framework does not improve automation of quality related information on-site

Alternative Hypothesis

HAQuaA Implementation of AUSIA framework improves accessibility of quality related information on-site

HAQuaU Implementation of AUSIA framework improves usefulness of quality related information on-site

HAQuaS Implementation of AUSIA framework improves satisfaction with quality related information on-site

HAQuaI Implementation of AUSIA framework improves integration of quality related information on-site

HAQuaA Implementation of AUSIA framework improves automation of quality related information on-site

217

Table A8: Null and Alternative Hypothesis for Certifications

Hypothesis Description Null Hypothesis

H0QuaA Implementation of AUSIA framework does not improve accessibility of certifications on-site

H0QuaU Implementation of AUSIA framework does not improve usefulness of certifications on-site

H0QuaS Implementation of AUSIA framework does not improve satisfaction with certifications on-site

H0QuaI Implementation of AUSIA framework does not improve integration of certifications on-site

H0QuaA Implementation of AUSIA framework does not improve automation of certifications on-site

Alternative Hypothesis

HAQuaA Implementation of AUSIA framework improves accessibility of certifications on-site

HAQuaU Implementation of AUSIA framework improves usefulness of certifications on-site

HAQuaS Implementation of AUSIA framework improves satisfaction with certifications on-site

HAQuaI Implementation of AUSIA framework improves integration of certifications on-site

HAQuaA Implementation of AUSIA framework improves automation of certifications on-site

218

Table A9: Null and Alternative Hypothesis for Weather Information

Hypothesis Description Null Hypothesis

H0WeaA Implementation of AUSIA framework does not improve accessibility of weather information on-site

H0WeaU Implementation of AUSIA framework does not improve usefulness of weather information on-site

H0WeaS Implementation of AUSIA framework does not improve satisfaction with weather information on-site

H0WeaI Implementation of AUSIA framework does not improve integration of weather information on-site

H0WeaA Implementation of AUSIA framework does not improve automation of weather information on-site

Alternative Hypothesis

HAWeaA Implementation of AUSIA framework improves accessibility of weather information on-site

HAWeaU Implementation of AUSIA framework improves usefulness of weather information on-site

HAWeaS Implementation of AUSIA framework improves satisfaction with weather information on-site

HAWeaI Implementation of AUSIA framework improves integration of weather information on-site

HAWeaA Implementation of AUSIA framework improves automation of weather information on-site

219

Table A10: Null and Alternative Hypothesis for Technical Information

Hypothesis Description Null Hypothesis

H0TecA Implementation of AUSIA framework does not improve accessibility of technical information on-site

H0TecU Implementation of AUSIA framework does not improve usefulness of technical information on-site

H0TecS Implementation of AUSIA framework does not improve satisfaction with technical information on-site

H0TecI Implementation of AUSIA framework does not improve integration of technical information on-site

H0TecA Implementation of AUSIA framework does not improve automation of technical information on-site

Alternative Hypothesis

HATecA Implementation of AUSIA framework improves accessibility of technical information on-site

HATecU Implementation of AUSIA framework improves usefulness of technical information on-site

HATecS Implementation of AUSIA framework improves satisfaction with technical information on-site

HATecI Implementation of AUSIA framework improves integration of technical information on-site

HATecA Implementation of AUSIA framework improves automation of technical information on-site

220

Appendix IV - Confidentiality Agreement

221

222

223

224

225

226

227

Appendix V - Information Management Questionnaire (Online)

228

229

230

Appendix VI - Technology Readiness Index (TRI) Questionnaire

231

232

233

234

235

Appendix VII – Time Waste Data Entry Sheet

236

Appendix VIII - Present State of Information Management

237

238

239

240

App

endi

x IX

– E

rror

Mar

gin

Cal

cula

tion

for

Sam

ple

Size

Information

AU

SIA

Err

or

99%

Err

or

95%

Err

or

90%

Mean

99%

Con

fiden

ce

Lev

el

95%

Con

fiden

ce

Lev

el

90%

Con

fiden

ce

Lev

elU

pper

Lim

it

Low

er

Lim

it

Upp

er

Lim

it

Low

er

Lim

it

Upp

er

Lim

it

Low

er

Lim

it

Drawings

Acc

essi

bilit

y (B

efor

e)

.478

10.

189

0.14

2 0.

118

2.00

0 2.

189

1.81

1 2.

142

1.85

8 2.

118

1.88

2 A

cces

sibi

lity

(Afte

r)

.500

00.

198

0.14

8 0.

124

2.75

0 2.

948

2.55

2 2.

898

2.60

2 2.

874

2.62

6 U

sefu

lnes

s (B

efor

e)

.398

40.

158

0.11

8 0.

099

2.11

1 2.

269

1.95

3 2.

229

1.99

3 2.

210

2.01

2 U

sefu

lnes

s (A

fter)

.4

871

0.19

3 0.

144

0.12

1 2.

639

2.83

2 2.

446

2.78

3 2.

495

2.76

0 2.

518

Satis

fact

ion

(Bef

ore)

.5

884

0.23

3 0.

175

0.14

6 1.

710

1.94

3 1.

477

1.88

5 1.

535

1.85

6 1.

564

Satis

fact

ion

(Afte

r)

.569

90.

226

0.16

9 0.

141

2.48

4 2.

710

2.25

8 2.

653

2.31

5 2.

625

2.34

3 In

tegr

atio

n (B

efor

e)

.718

40.

284

0.21

3 0.

178

1.36

7 1.

651

1.08

3 1.

580

1.15

4 1.

545

1.18

9 In

tegr

atio

n (A

fter)

.5

724

0.22

7 0.

170

0.14

2 2.

500

2.72

7 2.

273

2.67

0 2.

330

2.64

2 2.

358

Aut

omat

ion

(Bef

ore)

.8

000

0.31

7 0.

237

0.19

8 1.

000

1.31

7 0.

683

1.23

7 0.

763

1.19

8 0.

802

Aut

omat

ion

(Afte

r)

.485

20.

192

0.14

4 0.

120

2.65

4 2.

846

2.46

2 2.

798

2.51

0 2.

774

2.53

4

Changes

Acc

essi

bilit

y (B

efor

e)

.603

60.

239

0.17

9 0.

149

2.08

3 2.

322

1.84

4 2.

262

1.90

4 2.

232

1.93

4 A

cces

sibi

lity

(Afte

r)

.467

20.

185

0.13

9 0.

116

2.69

4 2.

879

2.50

9 2.

833

2.55

5 2.

810

2.57

8 U

sefu

lnes

s (B

efor

e)

.447

80.

177

0.13

3 0.

111

2.26

5 2.

442

2.08

8 2.

398

2.13

2 2.

376

2.15

4 U

sefu

lnes

s (A

fter)

.4

478

0.17

7 0.

133

0.11

1 2.

735

2.91

2 2.

558

2.86

8 2.

602

2.84

6 2.

624

Satis

fact

ion

(Bef

ore)

.5

509

0.21

8 0.

163

0.13

6 1.

800

2.01

8 1.

582

1.96

3 1.

637

1.93

6 1.

664

Satis

fact

ion

(Afte

r)

.546

70.

216

0.16

2 0.

135

2.66

7 2.

883

2.45

1 2.

829

2.50

5 2.

802

2.53

2 In

tegr

atio

n (B

efor

e)

.689

50.

273

0.20

5 0.

171

1.34

6 1.

619

1.07

3 1.

551

1.14

1 1.

517

1.17

5 In

tegr

atio

n (A

fter)

.5

084

0.20

1 0.

151

0.12

6 2.

538

2.73

9 2.

337

2.68

9 2.

387

2.66

4 2.

412

Aut

omat

ion

(Bef

ore)

.8

771

0.34

7 0.

260

0.21

7 1.

333

1.68

0 0.

986

1.59

3 1.

073

1.55

0 1.

116

Aut

omat

ion

(Afte

r)

.465

30.

184

0.13

8 0.

115

2.70

4 2.

888

2.52

0 2.

842

2.56

6 2.

819

2.58

9

241

App

endi

x X

– T

ool T

ime

Obs

erva

tion

Shee

t

242

Appendix XI – Demo Software Overview

243

244

245

Appendix XII – Present Information Flow

Abbreviations used for each designation are given below

CM Construction Manager

RM Risk Manager

SPM Senior Project Manager

PM Project Manager

APM Assistant Project Manager

GS General Superintendent

BSM Building Systems Manager

ES Estimator

PC Project Coordinator

C Coordinator

FE Field Engineer

S Supervisor

QMC Quality Management Coordinator

O Operator

DC Document Control

S Superintendent

AS Assistant Superintendent

GF General Foremen

Su Surveyor

SS Summer Student

IS Intern Student

246

Symbol Description

Information initiated by the person

Information process intimately by the person

Information end up with the person

247

Initi

ated

By

(IB

)

Info

rmat

ion

or D

ocum

ent

Initi

ated

(I/D

I) fr

om

Off

ice-

End

SS

AS

HSE

C

M &

E C

A

PM

PC

Stru

ctur

al/

Arc

hite

ctur

al

/LE

ED

C

FE

ST

Info

rmat

ion

or

Doc

umen

t

Initi

ated

(I/D

I)

from

fiel

d-E

nd

Initi

ated

By

(IB

)

Su

perin

tend

ents

Dai

ly R

epor

t

Ass

ista

nt

/Tra

de

Supe

rinte

nden

t

W

eekl

y

Prog

ress

Rep

ort

Fiel

d

Engi

neer

s/

Fore

men

Seni

or

Supe

rinte

nden

t

Look

Ahe

ad

Sche

dule

Seni

or

Supe

rinte

nden

t

Cha

nge

Ord

er

R

FI/R

RFI

Su

b Tr

ades

Es

timat

e fo

r

Extra

Wor

k

Sub

Trad

es

248

IB

I/D

I

from

Off

ice-

End

PM

(Str

uctu

re)

PM

(Env

elop

e/

Site

)

GS

GS

(Str

uctu

re)

PCH

SE SQ

MC

C

M

SPM

A

S FE

G

F

I/D

I

from

Fiel

d-E

nd

IB

FE

Wor

k

Pack

ages

GS

(Stru

ctur

e)

Look

Ahe

ad

Sche

dule

Req

uest

for

Info

rmat

ion

GF

GS

Site

Inst

ruct

ions

PM

Cha

nge

Ord

er

HSE

S

Safe

ty

Rec

ord

Job

Haz

ard

Ana

lysi

s

GF

Supe

rvis

ors

Dai

ly R

epor

t

GF

249

Appendix XIII - Evaluation of Field Management Personnel

The summary below consists of field personnel's propensity to embrace new

technology using TRI and their willingness to participate in this research project. A brief

description about individual's perception on advanced communication and information

management tools are also given.

StructureSupervision

PersonalTRI Attitude Details

West

Wing

Site

SuperintendentMedium High

Mature person with lot

of construction

experience. Willing to

utilize cutting edge

technologies such as

rugged tablets and BIM.

Assistant

SuperintendentMedium High

Not a tech savvy guy but

was willing to try

something new.

Acknowledges the

advantages of rugged

tablets, BIM and kiosks

in the field level

250

StructureSupervision

PersonalTRI Score Attitude Details

Centre

Wing

Site

SuperintendentLow Medium

Mature person closer to

retirement age, believes

extra effort needed to

learn new technology is

not beneficial for him.

Proposes proper training

program before

implementing new

technologies

Assistant

Superintendent

(Area A and

B)

Medium Medium

Relies on hard skills but

is willing to try new

technology

Assistant

Superintendent

(Area C)

High Low

Tech savvy guy but

believes everything he

needs is in in-house

solution

251

Appendix XIV - Information Management after Implementation

252

253

254

255

App

endi

x X

V –

Kol

mog

orov

–Sm

irno

v T

est S

tatis

tics

Tab

le A

11: K

-S T

est B

efor

e Im

plem

enta

tion

Info

rmat

ion

V

alue

A

cces

sibi

lity

Use

fuln

ess

Satis

fact

ion

Inte

grat

ion

Aut

omat

ion

Dra

win

gZ

2.38

32.

871

1.82

41.

724

1.28

8p

(Exa

ct S

ig.)

.000

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.005

.072

Cha

nges

Z 2.

158

2.81

02.

008

1.69

61.

226

p (E

xact

Sig

.) .0

00.0

00.0

01.0

06.0

99Sa

fety

Z 2.

632

2.90

52.

635

1.89

31.

206

p (E

xact

Sig

.) .0

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00.0

00.0

02.1

09Sc

hedu

leZ

1.86

21.

853

1.53

91.

486

1.48

2p

(Exa

ct S

ig.)

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.002

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.024

.025

Mat

eria

lZ

1.51

01.

736

1.37

91.

205

1.22

9p

(Exa

ct S

ig.)

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.110

.098

3D/4

D M

odel

s Z

1.02

31.

284

.917

1.22

2.9

84p

(Exa

ct S

ig.)

.246

.074

.369

.101

.287

Qua

lity

Z 2.

611

2.34

82.

175

1.32

31.

021

p (E

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.) .0

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49C

ertif

icat

ions

Z

1.70

31.

669

1.02

1.9

23.8

24p

(Exa

ct S

ig.)

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.248

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Wea

ther

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1.83

61.

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25Te

chni

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Z 2.

276

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.) .0

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21.2

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256

Tab

le A

12: K

-S T

est A

fter

Impl

emen

tatio

n

Info

rmat

ion

V

alue

A

cces

sibi

lity

Use

fuln

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Satis

fact

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Inte

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Aut

omat

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Dra

win

gZ

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592

2.09

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257

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Safe

tyZ

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353

2.23

52.

116

2.35

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ct S

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.000

.000

.000

.000

Sche

dule

Z 2.

671

2.37

72.

223

2.49

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526

p (E

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.) .0

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ater

ial

Z 2.

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1.89

21.

589

1.71

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p (E

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/4D

Mod

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Z 2.

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2.40

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563

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ualit

y Z

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62.

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Cer

tific

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ns

Z 2.

197

1.91

21.

673

1.71

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898

p (E

xact

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.) .0

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06.0

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eath

erZ

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02.

248

1.98

81.

821

1.89

0p

(Exa

ct S

ig.)

.000

.000

.001

.003

.002

Tech

nica

lZ

2.69

22.

692

2.38

62.

452

2.43

9p

(Exa

ct S

ig.)

.000

.000

.000

.000

.000

257

Appendix XVI – Preference Change Before and After Implementation

Table A13: Wilcoxon Signed Ranks of Drawings

Table A14: Wilcoxon Signed Ranks of Changes (SI, RFI, PCN)

ID Information Rank

Dra

win

gs

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 27

Tie After = Before 13

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 20

Tie After = Before 18

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 19

Tie After = Before 13

Integration Negative Rank After < Before 0 Positive Rank After > Before 28

Tie After = Before 7

Automation Negative Rank After < Before 0 Positive Rank After > Before 27

Tie After = Before 3

ID Information Rank

Cha

nges

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 22

Tie After = Before 18

Usefulness Negative Rank After < Before 0 Positive Rank After > Before 18

Tie After = Before 20

Satisfaction Negative Rank After < Before 0 Positive Rank After > Before 23

Tie After = Before 9

Integration Negative Rank After < Before 0 Positive Rank After > Before 24

Tie After = Before 6

Automation Negative Rank After < Before 0 Positive Rank After > Before 26

Tie After = Before 4

258

Table A15: Wilcoxon Signed Ranks of Safety

Table A16: Wilcoxon Signed Ranks of Schedule

ID Information Rank Sa

fety

Accessibility Negative Rank After < Before 1 Positive Rank After > Before 14

Tie After = Before 23

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 15

Tie After = Before 21

Satisfaction Negative Rank After < Before 0 Positive Rank After > Before 14

Tie After = Before 16

Integration Negative Rank After < Before 0 Positive Rank After > Before 17

Tie After = Before 15

Automation Negative Rank After < Before 0 Positive Rank After > Before 20

Tie After = Before 7

ID Information Rank

Sche

dule

Accessibility Negative Rank After < Before 1 Positive Rank After > Before 17

Tie After = Before 16

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 18

Tie After = Before 16

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 14

Tie After = Before 12

Integration Negative Rank After < Before 3 Positive Rank After > Before 20

Tie After = Before 4

Automation Negative Rank After < Before 0 Positive Rank After > Before 20

Tie After = Before 4

259

Table A17: Wilcoxon Signed Ranks of Material

Table A18: Wilcoxon Signed Ranks of 3D/4D Models

ID Information Rank M

ater

ial

Accessibility Negative Rank After < Before 1 Positive Rank After > Before 17

Tie After = Before 7

Usefulness Negative Rank After < Before 2 Positive Rank After > Before 11

Tie After = Before 10

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 15

Tie After = Before 5

Integration Negative Rank After < Before 1 Positive Rank After > Before 19

Tie After = Before 3

Automation Negative Rank After < Before 1 Positive Rank After > Before 16

Tie After = Before 3

ID Information Rank

3D/4

D M

odel

s

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 19

Tie After = Before 3

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 15

Tie After = Before 11

Satisfaction Negative Rank After < Before 0 Positive Rank After > Before 15

Tie After = Before 6

Integration Negative Rank After < Before 0 Positive Rank After > Before 18

Tie After = Before 5

Automation Negative Rank After < Before 0 Positive Rank After > Before 16

Tie After = Before 4

260

Table A19: Wilcoxon Signed Ranks of Quality

Table A20: Wilcoxon Signed Ranks of Certifications

ID Information Rank Q

ualit

y

Accessibility Negative Rank After < Before 1 Positive Rank After > Before 22

Tie After = Before 11

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 23

Tie After = Before 14

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 21

Tie After = Before 9

Integration Negative Rank After < Before 0 Positive Rank After > Before 21

Tie After = Before 9

Automation Negative Rank After < Before 0 Positive Rank After > Before 19

Tie After = Before 5

ID Information Rank

Cer

tific

atio

ns

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 7

Tie After = Before 4

Usefulness Negative Rank After < Before 1 Positive Rank After > Before 4

Tie After = Before 9

Satisfaction Negative Rank After < Before 0 Positive Rank After > Before 4

Tie After = Before 7

Integration Negative Rank After < Before 0 Positive Rank After > Before 8

Tie After = Before 3

Automation Negative Rank After < Before 0 Positive Rank After > Before 5

Tie After = Before 1

261

Table A21: Wilcoxon Signed Ranks of Weather

Table A22: Wilcoxon Signed Ranks of Technical

ID Information Rank W

eath

er

Accessibility Negative Rank After < Before 3 Positive Rank After > Before 16

Tie After = Before 17

Usefulness Negative Rank After < Before 4 Positive Rank After > Before 10

Tie After = Before 24

Satisfaction Negative Rank After < Before 2 Positive Rank After > Before 16

Tie After = Before 15

Integration Negative Rank After < Before 1 Positive Rank After > Before 16

Tie After = Before 13

Automation Negative Rank After < Before 0 Positive Rank After > Before 15

Tie After = Before 9

ID Information Rank

Tec

hnic

al

Accessibility Negative Rank After < Before 0 Positive Rank After > Before 21

Tie After = Before 13

Usefulness Negative Rank After < Before 0 Positive Rank After > Before 14

Tie After = Before 23

Satisfaction Negative Rank After < Before 1 Positive Rank After > Before 16

Tie After = Before 12

Integration Negative Rank After < Before 0 Positive Rank After > Before 19

Tie After = Before 12

Automation Negative Rank After < Before 0 Positive Rank After > Before 21

Tie After = Before 4

262

Appendix XVII – Acceptance Testing Workshop Instrument

263

Appendix XVIII - Implementation of Digital Pen

The researcher encountered some resistance from research subjects when moving

from hardcopy to softcopy due to their lack of confidence in a completely paperless

system. Tech savvy workforce was willing to implement a completely paperless solution,

but the rest of the supervisory staff wanted to maintain hardcopy sets and update

manually. The researcher had to find a solution to satisfy both groups to ensure

successful implementation. The researcher introduced the ‘digital pen’ to merge hardcopy

and softcopy.

The digital pen has the ability to transfer written markings from a hardcopy onto a

softcopy. The digital pen can transfer redlines from hardcopy drawings to PDFs, and

DWG and DWF files. Another application is transferring hardcopy forms to MS excel

files.

The hardcopy (e.g. a drawing or a form) should be printed utilizing the digital pen

software, which overlays a unique dot pattern on each individual page printed. The pen

has an optical and pressure sensor; the pressure sensor activates the digital pen and the

optical sensor simultaneously reads the overlaid dot pattern to identify the particular page

(drawings) and the specific location in that page. The pen has an ink cartridge and any

writing done on the drawing is physically marked (in ink) on the hardcopy.

Cost

Hardcopies need to be printed with a colour laser printer to enable the digital pen

to read the drawings or forms. The cost of a digital pen is around fifteen hundred dollars

and printing cost with dot patterns can be done in house or in a production company. Cost

264

of a colour printout is $2.99/ft2 or $35.88/sheet (Arch E Large Format Sheet 36”x48”)

and a black and white printout costs $0.99/ft2 or $11.88/sheet (Arch E).

The researcher implemented the digital pen in the TTC complex. This project

utilized 550 drawings (Architectural, Structural, Mechanical, and Electrical). The general

contractor had printed two sets of hardcopies for the site office and management office,

and individual field supervisory staff members had reduced size copies (11”x17”). The

cost breakdown is given below:

Cost of colour printing with dots : 19,734.00 CAD

Cost of the pen : 1,500.00 CAD

Total cost for digital pen implementation : 21,234.00

Cost for printing two black and white sets : -13,068.00 CAD

Extra Cost : 8,166.00 CAD

This extra eight thousand dollars is offset by the direct cost saving of reducing the

number of field staff members needed to update multiple copies. Also the number of

11x17 copies needed by field supervisor staff can be reduced (cost of one set of 11x17

black and while hardcopy is around 700 CAD).

There are a few disadvantages of the digital pen, such as the pen might not

identify redlining over some dark hatched areas on drawings. This can be avoided by not

writing over dark shaded areas on the drawings. There might be a learning curve for the

printing company when printing the dotted drawings for the first time, however once they

are set up further printing will be seamless.

265

Appendix XIX - Cost Breakdown and Recovery of Investment for i-Booth Software Development

The research team spoke with several software developers to find out

development costs associated with the AUSIA framework; a feasible estimate was

500,000CAD - 750,000CAD. Calculation was done assuming i-Booth Inc. can generate

500,000CAD and the Industrial Research Assistance Program by National Research

Council of Canada will match the balance money. i-Booth Inc. plans to recover the

investment in 3 years with at least 15% ROI. i-Booth Inc. will engage in agreements with

6 potential clients to raise the 500,000CAD. These six clients don’t need to pay for site

license or enterprise license for 7 years (initial investment of 100,000CAD each). Cash

flow forecast is based on the following assumptions:

Initial investment : 750,000

Software Development : 500,000

Operating Cost : 250,000

AUSIA framework software will cost 5000CAD/month for site license or

20,000CAD/month for enterprise license.

Five clients for the first year with a one-year site license (5,000x12x5 =

300,000) will generate 300,000. The operating cost for the first year will be

150,000, assuming that this is only for support and server maintenance. A

one-time setup and training fee will be paid by the clients in the initial setup.

During the second year there will be one enterprise license for a year, and

three and a half site licenses (assuming one client terminates contract after six

months) for one year (20,000x12x1 + 5,000x12x3.5), amounting to 450,000.

266

The operating cost for the second year will increase to 250,000, assuming that

this is only for support, server upgrade, and server maintenance. A one-time

setup and training fee will be paid by the new clients in initial setup.

During the third year there will be one and a half enterprise licenses and four

site licenses for one year (20,000x12x2 + 5,000x12x4), amounting to

600,000. The operating cost for the second year will reduce to 200,000

because old projects in the server will be archived and server space will be

free for new projects. Operating cost will only be for support, server upgrade,

and server maintenance. A one-time setup and training fee will be paid by the

new clients in initial setup.

Table A23: Cash Flow Forecast for Next 3 Years

Year Cash-In Cash-Out

1 300,000 150,000

2 450,000 250,000

3 600,000 200,000

Net Present Value (NPV) [10% Discounted Rate] : 852,178.82

Profitability Index : 1.2044

Internal Rate of Return (IRR) : 19.5

Based on the calculations i-Booth Inc. will be able to recover the investment with

around 20% return on investment within 3 years.

267

AUSIA Framework Site Implementation Cost and ROI

The hardware costs of two versions of i-Booth are given below.

Table A24: AUSIA Framework Hardware Cost

Sales Option Wall-mount

VersionMobile Version

Mobile Version

(Sun-Light

Readable Screen)

Direct Purchase

(One Year Return to

Deport Warranty)

17,500.00 21,500.00 25,000.00

Direct Purchase

(48 Hrs. On-Site

Support)

19,700.00 24,500.00 28,000.00

Lease

(48 Hrs. On-Site

Support)

2,450.00 3,100.00 3,500.00

Operating Cost of the i-Booth for a General Contractor

Four-storey building project with a simple organization chart. The site

management and operations staff consists of

One Construction Manager (Half Time)

One Site Superintendent

268

One Assistant Superintendent

Two General Foremen

One Field Engineer/Coordinator

One Lead Hand

The contractor can recover the operating expense of the system by direct time

savings of supervision staff. Assuming a flat charge out rate of 35$/hr. (0.60 per minute)

for above mentioned staff, benefit calculation will be as follows:

(As mentioned in chapter four, minutes saved per head/day due to i-Booth is

114.3mins)

Cost saving per person : 114.3x0.60

: 068.4

Cost saving for this site : 68.4*6.5

: 444.6/Day

Operating cost of the system was calculated with the following assumptions:

Site license for the software will cost 5000.00 CAD/Month

Site management will only have to lease a wall-mount unit for the project

because management trailer is located on-site and all site staff is equipped

with handheld devices (iPads or Windows Tablets)

Cost of the handheld devices per month is 66.67CAD (assuming unit cost is

1000 CAD and operational life is 15 months)

Cost of cellular data connection for a handheld device is 50.00CAD/month

Wired data connection costs 500.00CAD per month with Wi-Fi access points

269

Site License : 5000.00

Wall-mount Unit Lease : 2450.00

Cost of Handhelds : 66.67x6.5

: 0433.34

Cellular Data : 50.00x6.5

: 0325.00

Hardwire Connections with Wi-Fi : 0500.00

Total Cost for a Month : 8708.34

Number of Days to Recover the Cost : 8708.34/444.6

: 20 Days

Contractor can recover the operating expense of the system by direct time saving

of supervision staff.

Option II

Twenty storey building project with a midsize organization structure. The site

management and operations staff consists of

One Project Manager

One Construction Manager

One Site Superintendent

Two Assistant Superintendents

Four General Foremen

Two Field Engineers/Coordinators

270

Six Lead Hands

Assuming flat charge out rate of 36$/hr. (0.60 per minute) for the above

mentioned staff, the benefit calculation will be as follows:

Cost saving per person : 114.x0.60

: 068.4

Cost saving for this site : 68.4x17

: 1162.8/Day

Operating cost of the system was calculated with the following assumptions:

Site license will cost 5000.00 CAD/Month

Site management will lease three wall-mount unit and two sunlight readable

mobile units for the project because management trailer is located away site

and field trailer is located on-site. All site staff is equipped with handheld

devices (iPads or Windows Tablets)

Cost of the handheld devices per month is 66.67CAF (assuming unit will 1000

CAD and operational life is 15 months)

Cost of cellular data connection for a handheld devices is 50.00CAD/Month

Wired Data connections 1000.00CAD per month with Wi-Fi access points

Site License : 5000.00

Wall-mount Unit Lease : 2450.00s3

: 7350.00

Sunlight Readable Mobile Unit Lease : 3500.00x2

271

: 7000.00

Cost of Handhelds : 66.67x17

: 1133.33

Cellular Data : 50.00x17

: 0850.00

Hardwire Connections with Wi-Fi : 1000.00

Total Cost for a Month : 22333.33

Number of Days to Recover the Cost : 22333.33/1162.80

: 20 Days

The contractor can recover the operating expense of the system by direct time

savings of supervision staff.

The research team also spoke with solution provider about marketing the AUSIA

framework as a Software as a Service (SaaS) model. Further details about this option are

discussed in the Future Research section.

272

Appendix XXI – Permission to Reuse Copyrighted Material

273

274

275