ORIGINAL ARTICLE

Knowledge sharing for sustainable development in civilengineering: a systematic review

Nicholas Meese • Chris McMahon

Received: 13 April 2011 / Accepted: 7 November 2011 / Published online: 3 December 2011

� Springer-Verlag London Limited 2011

Abstract Sustainable development (SD) knowledge in

civil engineering-related disciplines is evolving rapidly. As

such, it is increasingly important that engineers share SD

knowledge to allow them to systematically enhance the

environmental performance of engineered systems. This

systematic review identifies published primary data col-

lection studies of SD knowledge sharing (KS) approaches

in a civil engineering-related context with the aim of

understanding the KS concepts studied, the research strat-

egies used and the key KS findings. A predefined research

protocol guided the selection of relevant studies. Analysis

revealed that collaboration and education were the major

KS concepts and that most studies reside at the positivist

end of the research strategy spectrum. Practically all of the

identified studies emphasise the need for social interfacing,

which enhances the way engineers share complex SD

knowledge. The article concludes by describing the prac-

tical implications of the research.

Keywords Systematic literature review �Sustainable development � Knowledge sharing �Knowledge management � Civil engineering

1 Introduction

The aim of sustainable development (SD) is to create an

ecological harmony between our planet and the human

race. Over the past two decades, there has been increasing

awareness of environmental, social and economic unbal-

ance. Knowledge of how to achieve sustainability through

the harmonisation of these three components is evolving

and increasingly valuable (cf. Gullo and Haygood 2009).

Consequently, it is evermore important that we effectively

share SD insights and experience; if we do not, it is pos-

sible we will fail to innovate and adapt fast enough to

systematically enhance the way we interface with our

environment.

In response to this challenge, the authors have con-

ducted a systematic review to identify existing studies of

knowledge sharing (KS) for SD. Furthermore, as the built

environment plays such a major role in SD—controlling

the systems in which we live (Shelbourn et al. 2006)—this

article focuses solely on studies which exhibit civil engi-

neering aspects. Systematic reviews are unlike traditional

literature reviews in that they aim to minimise bias by

providing an audit trail of reviewers’ decisions, procedures

and conclusions (Cook et al. 1997; Petticrew and Roberts

2005). This increases methodological rigour and helps to

develop a reliable knowledge base from a range of sources

(Tranfield et al. 2003).

In this article, we aim to provide an overview of avail-

able KS for SD studies using this systematic review

approach, discussing concepts, major findings and research

methods employed. This article addresses the following

research questions:

1. Which KS concepts have been applied in a SD

context?

N. Meese (&)

School of Management, University of Bath,

Bath BA2 7AY, UK

e-mail: n.c.meese@bath.ac.uk

C. McMahon

Department of Mechanical Engineering, University of Bath,

Bath BA2 7AY, UK

e-mail: c.a.mcmahon@bath.ac.uk

123

AI & Soc (2012) 27:437–449

DOI 10.1007/s00146-011-0369-8

2. Which research strategies were applied to address

these concepts?

3. What were the key findings from the research?

This article does not address the following fields of

interest: rule-based decision support systems (e.g. Cortes

et al. 2001; Tseng 2011; Turon et al. 2007); regulatory and

legislative standards, such as BREAM, LEED and ISO

14001 (e.g. George and Jain 2008; Hamza and Greenwood

2009); environmental knowledge management systems

(e.g. EKAT 2007; Kraines et al. 2005); technological

development (e.g. solar panels); or the application of

knowledge itself.

The structure of the paper is as follows. It begins with a

brief overview of KS, SD and civil engineering. The sys-

tematic literature review methodology and findings are

then presented and discussed. Conclusions and implica-

tions of the review are outlined in the final section.

2 Background

This section provides an overview of the core topics sought

from the literature search.

2.1 Knowledge sharing

Knowledge management (KM) is concerned with devel-

oping and cultivating systems that enable organisations to

detect, leverage, distribute and improve their knowledge

assets (Nonaka 1998). In one form or another, KM com-

monly comprises of the following ‘steps’: knowledge

generation, knowledge sharing, knowledge adaptation,

knowledge application and knowledge modification (new

knowledge generation) (Gupta 2008). A common distinc-

tion of knowledge is the tacit–explicit dichotomy. Tacit

knowledge is highly complex in nature—personal, context-

specific, abstract and dynamic; it is difficult to transfer and

may be best shared using informal and interpersonal means

(Goh 2002); it is probably best understood by the assertion

that ‘we know more than we can tell’ (Polanyi 1966).

Explicit knowledge, on the other hand, can be readily

articulated and codified; it is easily transferred and is

reusable in a consistent and repeatable manner.

KS is often considered the most important facet of

knowledge management (KM) (Kalling and Styhre 2003).

KS is depicted as a set of behaviours regarding knowledge

exchange which involve the actors, knowledge content,

organisational context, appropriate media and a societal

environment (Yang and Chen 2007). The goal of KS can

either be to create new knowledge by differently combin-

ing existing knowledge or to become better at exploiting

existing knowledge (Christensen 2007). Nonaka and

Takeuchi’s (1995) SECI model implies that KS resides in

the socialisation phase, emphasising the tacit-to-tacit nat-

ure of the process (cf. Fernie et al. 2003). As such, open

communication underpins KS, enabling individuals to

explore and generate knowledge of the ‘problem domain’

in situ (Bakker et al. 2006). This differs to knowledge

transfer that implies knowledge externalisation (i.e. con-

verting tacit to explicit knowledge for exploitation)

(cf. Harris 1996).

Holtshouse (1998) realises three critical attributes that

encourage better KS; these are: social, cultural and tech-

nical. Cohen and Prusak (2001) state that social attributes

predominately consist of trust relationships, common

frames of reference and shared goals. Cultural attributes

govern our behaviour and can be cultivated to bring about

desired results (e.g. staff do not feel inhibitions about

sharing knowledge and consider it rewarding (Gupta 2008;

Bishop et al. 2008; McKenzie et al. 2001)). Finally, tech-

nical attributes consist of tools and technologies, such as

the Internet, which play a role in mobilising information

without creating ‘overload’ (Zhao et al. 2008). There is no

universal attribute configuration that will deliver equal KS

performance; all organisations exhibit different character-

istics and behaviours and, thus, are likely to require dif-

ferent emphases on the KS attributes.

KS approaches can be categorised as either formal or

informal (Paradise 2008). Formal approaches are instituted

by management and include mentorship programmes and

formal meetings (Taminiau et al. 2009; Fontaine and

Lesser 2002). Informal approaches, on the other hand,

often emanate from social networks (e.g. impromptu and

informal discussions) (Gluch and Raisanen 2009; Wenger

et al. 2002). However, whilst such approaches can deliver

benefits that enable organisations to create and sustain

competitive advantage, numerous barriers can impede

effective KS. These include (Gupta 2008; Bhirud et al.

2005; Davenport and Prusak 1998; Sveiby 2007; Meese

et al. 2010) attitudinal issues (lack of trust, silo mentality,

‘knowledge is power’, not invented here (NIH), fear of job

loss or embarrassment), management issues (lack of

knowledge sharing processes, poor leadership/top man-

agement support, inertia/bureaucracy, lack of encourage-

ment, intolerance for mistakes or need for help, poor status/

reward mechanisms), systems and resource issues (poor IT

systems, lack of meeting places, inadequate vocabularies

and so on).

2.2 Sustainable development

Organisations are under increasing pressure to apply SD

principles (Pojasek 2010). However, confusion still sur-

rounds SD and what it means in practice (Aras and

Crowther 2009; Brown et al. 1987; cf. Chaharbaghi and

438 AI & Soc (2012) 27:437–449

123

Willis 1999). Whilst this ‘fuzziness’ can be frustrating for

practitioners by generating a manifold of complex con-

siderations, some advocate that by not confining SD to one

definition avoids excluding perspectives on what SD

should entail (Robinson 2004). Nevertheless, Brundtland’s

(1987) SD definition remains one of the most cited:

‘development which meets the needs of the present without

compromising the ability of future generations to meet

their own needs’.

It is widely understood that SD requires the integration

and harmonisation of economic, environmental and social

aspects of products and product systems (Curran 2009).

These are often represented as the ‘triple bottom line’

model (Fig. 1) or the Russian doll model (Fig. 2). As in the

latter model, the research reported in this article places

particular emphasis on environmental aspects of SD.

Models such as these emphasise the need for a systems

thinking approach to understand complex inter- and intra-

system interactions (Seiffert and Loch 2005). Such

approaches can help alleviate the uncertainty associated

with SD, which ultimately affects the rate and degree of SD

activity (Stern 2006; Sage 1999). In response to this, SD

knowledge is evolving at an increasing rate. Thus, KS

approaches can help individuals identify and communicate

relevant SD knowledge, enabling communities to capitalise

on the continued exploration of SD practice (Tsai 2002;

Meer et al. 2009).

2.3 Civil engineering

The UK’s Institution of Civil Engineers (ICE) defines civil

engineering as: ‘creating, improving and protecting the

environment in which we live. It provides the facilities for

day-to-day life and for transport and industry to go about

its work. … [It is a] discipline that deals with the design,

construction and maintenance of the physical and naturally

built environment’ (ICE 2010). The civil engineering sec-

tor is responsible for creating and maintaining environ-

ments that, to a large extent, govern how we live and

behave (Shelbourn et al. 2006). Consequently, it is a major

player in SD as it also directly and indirectly affects SD

efforts in other industries.

Unfortunately, it is widely recognised that the civil

engineering sector has been slow to embrace environ-

mentally friendly practices (Myers 2005; Ofori 1998). This

is a likely result of the sector’s complex and fragmented

nature (Esmi and Ennals 2009; Myers 2005), creating a

tendency to resist change (Boddy et al. 2007). To push SD

within the sector, the UK government devised a strategy for

more sustainable construction (DETR 2000); its aim was to

act as a driver to change whilst negating detrimental

impacts associated with the construction sector. Key fac-

tors for action include: design for minimum waste; lean

construction; minimise energy in construction and use; do

not pollute; preserve and enhance biodiversity; conserve

water resources; respect people and local environment; and

setting targets, monitoring and reporting, in order to

benchmark performance (Addis and Talbot 2001; Cole

2000; Ofori et al. 2000).

If civil engineering companies are to employ more

effective SD practices, it is vital that their engineers are

knowledgeable in SD topics (Rydin et al. 2007). As such,

knowledge management should be a core competency of

civil engineering companies (Dave and Koskela 2009;

Shelbourn et al. 2006). However, studies have shown that

civil engineering companies often fail to attain the benefits

associated with effective knowledge sharing (Esmi and

Ennals 2009). Relatively little published research addresses

the social aspects of sharing SD knowledge in a civil

engineering context (Newell et al. 2006). By contrast, a

large volume of SD KT research exists, often emphasising

the use of information technologies (Dave and Koskela

2009). Whilst the adoption of information technology may

be an attractive KS for SD solution, such systems often

overlook the social factors required for effective KS

(Rezgui et al. 2010) and may become cumbersome when

constantly re-codifying and re-assimilating variants of

rapidly evolving SD knowledge. KS, on the other hand,

emphases real-time duplex interpersonal communicationFig. 1 Triple bottom line SD model

Fig. 2 Russian doll SD model

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which is better suited to the highly integrated and dynamic

nature of SD knowledge (Chaharbaghi and Willis 1999).

3 Method

The aim of the study was to provide an overview of SD-

related KS within the civil engineering domain. Systematic

literature reviews take an unbiased and comprehensive

approach to answering specific research questions (Petticrew

and Roberts 2005). As aforementioned, the aim of this

research is to provide an overview of available KS for SD

studies, discussing concepts, major findings and research

methods employed. To achieve this aim, Tranfield et al.’s

(2003) stages of a systematic review were adopted. The

subsequent subsection headings directly relate to these stages.

3.1 Planning the review

At the beginning of the research, a group of seven subject

matter experts—five based in academic, two based in

industry—were invited to contribute to the foundation of

the study, the research protocol. A research protocol

specifies in advance the process of identifying relevant

research; that is, how the identified research is filtered. In

this case, it specified the research questions, the search

strategy, exclusion criteria and method of synthesis.

The exclusion criteria were developed to describe the

types of study that were eligible for in-depth review (Petti-

crew and Roberts 2005). As such, it directly related to the

research aim and the method described here. The criteria

itself are listed in Table 1, alongside the reasons for exclu-

sion. Inspiration for the criteria’s development was predom-

inately drawn from existing systematic review publications in

the knowledge management domain (e.g. Bjørnson Finn and

Dingsøyr 2008; Dawes and Sampson 2003).

3.2 Identification of research

A fundamental difference between a traditional narrative

review and a systematic review is that the latter encom-

passes a comprehensive, unbiased search (Tranfield et al.

2003). This process was initiated by the authors and subject

matter experts building a comprehensive set of search

terms that relate to KS and SD.1 These were concatenated

into a search string using a series of Boolean ‘AND’ and

‘OR’ operators.

Five online journal databases were queried: EBSCO;

Engineering Village; IEEE Xplore; ScienceDirect; and

Web of Knowledge. Where possible databases were

requested to query articles’ title, abstract and keyword list.

The search was conducted between 24th and 25th August

2010. A total of 17,469 citations were returned from the

search; the volume of results from each database is pre-

sented in Fig. 3. These citations were downloaded and

imported into Microsoft Excel for the selection of studies.

3.3 Selection of studies

The selection process began by eliminating duplicate

citations and citations that explicitly met the exclusion

criteria, e.g., non-journal studies and generic articles (e.g.

diary items, editorials). This reduced the overall number of

citations to 15,814, a reduction of 1,655 citations.

Due to the high volume of citations, it was agreed that

all citations would initially be assessed by their titles and

journal titles. The lead researcher conducted this, separat-

ing those which did and did not match the exclusion cri-

teria. This phase re-emphasised the differing perceptions of

SD. Although a large proportion of citations had ‘envi-

ronmental’ SD connotations, a significant proportion made

reference to business continuity, economic growth or other

disciplines outside the purview of this research (e.g.

astrophysics, chemical engineering). A total of 862 cita-

tions remained after the initial ‘title scan’ stage.

The remaining citations were then reassessed, consid-

ering their abstract and keywords list when comparing

them against the exclusion criteria. Of these citations,

70.1% did not resonate with our perception of SD, and

20.2% did not exhibit strong KS connotations; 87 citations

remained after this stage.

Full-text versions of the remaining citations were

downloaded from their respective databases and, where

necessary, the British Library. Once obtained, the full-text

articles were reviewed against the exclusion criteria.

Common reasons for exclusion at this stage included: lack

of theory application; lessons learned studies; hard rule-

based systems; knowledge codification techniques; poor

KS emphasis; and lack of civil engineering relevance. At

this late stage, these reasons brought into question two

concerns: the clarity and accuracy of citations’ title,

abstract and keywords; and the biases introduced by the

lead researcher during the selection process.

3.4 Study quality assessment

Quality assessment is a major challenge in management

research (Tranfield et al. 2003). As such, only peer reviewed

journal published studies were considered. In accordance

with the research questions, all articles were mapped against

a research strategy framework to show the balance between

the positivistic and phenomenological research philosophies

applied within the selected studies. No two studies were

identified which were based on the same data; had this1 Keyword lists are available from corresponding author.

440 AI & Soc (2012) 27:437–449

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situation occurred, the corresponding authors would have

been contacted for further clarification; usually the data of

the later studies are used (Kitchenham 2004).

3.5 Data extraction

Data extraction was performed using a combination of

computerised spreadsheets and printed copies of the studies

with corresponding notes. Links between concepts within

studies were maintained by using unique identifiers for

each study. These registers maintained the following

extracted data: data collection method(s), process and

response rates; sampling process; subjects and setting; and

sources of information.

3.6 Data synthesis

A meta-ethnographic approach was used to synthesise the

studies in order to address the research questions. This

approach is akin to the grounded theory’s constant com-

parison approach, enabling researchers to identify and

compare themes emanating from the studies. This is

especially useful when there is little prior knowledge of the

structure of influences underlying the phenomenon (Ribe-

iro et al. 2010). According to Tranfield et al. (2003), there

Table 1 Exclusion criteriaNo. Criteria Reason for exclusion

1 Non-peer reviewed journal articles Validity of research and to reduce biased data synthesis

2 Research which doesn’t gather primary

data

Avoid problems associated with lessons learned reports

and discussion articles stemming from their lack of

scientific rigour

3 Non-civil engineering oriented articles Civil engineering is the focus of the study

4 Articles unavailable electronically Resources and time isn’t available to gather paper copies

5 Citations unavailable for download Citation analysis needs to be conducted on a computer

due to volume of data

6 ‘Sustainability’ as an organisation (i.e.

continued economic performance)

This does not refer directly to sustainable development as

described in this article

7 Foreign language Exclude articles not written in English because scholars

were not multi-lingual

8 Exclude if the focus of the article is

clearly not on knowledge sharing

KS is the focus of the study

9 Exclude if the focus of the article is

clearly not on sustainable development

SD is the focus of the study

10 Exclude if the focus of the article is on

domain knowledge

Not interested in the knowledge itself (e.g. knowledge

about SD techniques), rather how knowledge is shared

Table 2 Overview of research strategies

Positivism Phenomenology

Experiment Survey Case study Grounded theory Ethnography Action research Sum

Collaboration 2 2 2 6

Decision support 1 1

Education 3 2 5

Measurement 1 1

Public participation 1 1

Social learning 2 1 3

Social networks 1 1

Technology transfer 2 2

Sum 1 9 7 1 2 0 20

666

2,479

2,100

10,677

1,547

0 2,000 4,000 6,000 8,000 10,000 12,000

Web of Knowledge

Science Direct

IEEE Xplore

Engineering Village

EBSCO

Number of results

Fig. 3 Citation search results

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are three alternative meta-ethnographic synthesis tech-

niques: ‘refutational synthesis’ (used where studies provide

conflicting representations of the same phenomenon);

‘reciprocal translations’ (used where studies address simi-

lar issues); and ‘lines of argument synthesis’ (used where

studies examine different aspects of the same phenome-

non). From the selection of studies phase, it was clear the

selected studies exhibited clear KS concepts, and were

therefore organised as such. As little conflict emerged

during an initial pass of the selected studies, a ‘lines of

argument synthesis’ was used to understand how each

study approached its respective focus.

4 Findings

The systematic framework revealed twenty studies. Eight

KS concepts were identified by the meta-ethnographic

approach. These were aligned with Saunders et al.’s (2000)

research process model to address the second research

question (Table 2). The most common research strategies

were survey and case study. The subsequent sections pro-

vide an overview of the key findings from each of the

selected studies, with an overview provided in Table 4.

4.1 Collaboration

Margerum had published two studies that attempt to classify

the constraints and forms of SD-oriented collaboration. In

his earlier paper, Margerum (2001) classifies six types of

integrated environmental management constraints against a

set of six implementation strategies for gaining organisa-

tional commitment; Table 3 indicates which strategies were

found to be most useful in alleviating each constraint.

Margerum (2001) found the studied collaborations com-

monly relied on two implementation strategies: contractual

(i.e. a joint written agreement defining roles, responsibili-

ties, expectations and limitations) and interpersonal (i.e.

mutual trust and understanding amongst participants).

However, the weaknesses of these two strategies often

prevailed (e.g. agreements were unclear/unevaluated, per-

sonal commitments fluctuated), thus failing to fully negate

collaborative constraints. Margerum (2008) continued his

work in this area by classifying collaboratives along a

spectrum (action level—organisational level—policy

level). He found that to achieve their goals: action collab-

oratives needed to exploit social capital (i.e. the diffusion of

ideas and actions through social networks ultimately influ-

ence participants); organisational collaboratives needed

focus on inter-organisation capability (i.e. better integration

of programmes and activities); and policy collaboratives

needed negotiation to build strong and broad-based explicit

consensus. The principal finding of both papers was that

collaboratives will produce greater results should they seek

to alleviate commitment constraints and build shared

understanding through explicit management.

Three identified studies employed explicit approaches to

managing action collaboratives as defined by Margerum

(2008). First, Yao and Steemers’ (2009) present an EU-

China partnership that promoted collaborative activities

(e.g. training, conferences, visit lectures) through an explicit

approach. This enabled the development of good cross-

boundary relationships, resulting in numerous benefits

including: upgraded SD knowledge and the identification of

technology transfer opportunities. Second, Garde-Bentaleb

et al. (2002) developed a reference document that helped

build shared understanding between architects and thermal

engineers in an intra-organisational setting. The reference

document acted as a KS mechanism by making explicit

collaborative opportunities, advocating its use through an

‘eco’ accreditation scheme. Finally, Cooper (2002) reported

the performance of an electronically mediated collaboration

system for SD. A communications framework used an

online platform and face-to-face meetings to promote

interdisciplinary and cross-cultural knowledge sharing and

negotiations that surround issues such as the definition of

SD. This study emphasised the need for cross-boundary KS

for SD and suggested that this KS framework acts as a

Table 3 Matching strategies to constraints (Margerum 2001)

Constraint Strategies to overcome constraints

Strategies focusing on organisation Strategy focusing on both Strategies focusing on the individual

Hierarchical Financial Contractual Coordination Facilitation Interpersonal

Legal and legislative x x

Resources x

Organisational power x x x x x x

Organisation perception x x x x

Organisational guidance/training x x x

Personal commitment x x x

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coordination strategy, alleviating resource, organisational

perception and personal commitment constraints. It was also

recognised that electronically mediated KS systems are no

panacea; regular face-to-face contact is still necessary to

build effective relationships.

Whilst the previously mentioned three collaboratives

reported positive outcomes, Lyver’s (2005) study on two

traditional ecological knowledge partnerships reported

several issues which hampered effective collaboration. A

contractual and interpersonal collaborative strategy was

implemented, but did not prevent a series of barriers

encompassing the following constraints: resource (e.g. not

enough time to develop relationships); organisational per-

ception (e.g. biased collaborative agenda); organisational

guidance and training (e.g. capability assumptions); per-

sonal commitment (e.g. high turnover of staff, career

measurement approach conflicts with collaborative

agenda).

4.2 Technology transfer

Technology transfer (TT) is often referred to as ‘a broad set

of processes covering the flows of know-how, experience

and equipment’ (IPCC 2000). KS is rooted in the TT lit-

erature (Cummings 2003), where it is predominately an

enabler for enhancing partners’ absorptive and emitting

capacities (Amesse and Cohendet 2001). Schneider et al.

(2008) and Forsyth (2005), amongst others (e.g. UNFCCC

2007), believe TT can act as a catalyst to combating SD

issues, such as climate change.

The two TT-related papers identified here corroborate

two findings. First, successful TT is often an organic pro-

cess that requires long-term partnerships that deliver reli-

able cost recovery. Second, TT cannot succeed without an

appreciation of the socio-economic needs and concerns of

recipient communities (UNFCCC 2004). Schneider et al.

(2008) found the TT programme presented in their study

increases commercially viable low-carbon TT and lowers

information and financial barriers; however, it was also

recognised that the programme was failing to improve the

institutional frameworks of receiving countries—a vital

requirement for attracting TTs.

Both Forsyth (2005) and Schneider et al. (2008) pro-

posed considerations for conducting TTs. Forsyth (2005)

advocates the following critical success factors: minimi-

sation of transaction costs; maximisation of assurance

mechanisms (e.g. contracts, rules of engagement); and

maximisation of trust and accountability. Whilst Schneider

et al. (2008) proposed a more comprehensive set of three

‘parameters’: barriers (lack of: commercial viability;

information; access to capital; institutional framework);

dimensions (geographical, technology, firm); and quality

(the degree to which the transfer enhances the recipient’s

know-how and their capacity to generate new knowledge

as a result of the transfer) (Mansfield 1975)—the type of

technology and nature of the ‘deal structure’ were key

quality determinants.

4.3 Social learning

Social learning (SL) refers to the generation of new

knowledge through deliberate social interaction; its aim is

to build shared understanding and a basis for joint action

(Schusler et al. 2003). Three studies demonstrated SL using

various approaches. Selin et al. (2007) studied a National

Forest Trail search conference (a collective planning

approach that the participants themselves will implement).

Al-Jayyousi (2004) studied how poor communities created

greater benefits from greywater systems through sociali-

sation. Whilst Measham (2009) conducted focus groups

and workshops to help overcome knowledge barriers.

Furthermore, Measham (2009) proposed five principals for

fostering SL through an evaluation process: iteration

(learning is fostered at each step and often reinforced when

repeated); feedback and discussion (a platform for building

individual understanding); group deliberation (to develop

shared understanding); flexibility (ad hoc adaption of the

SL programme’s design to meet participants needs and

expectations); and integration (linking all aspects of the

system to build richer understanding and to identify gaps,

anomalies and differing perspectives). All three studies

revealed positive SL outcomes, which were determined to

be a result of enabling groups of individuals/stakeholders

to tackle complex environmental issues through the soci-

alisation of knowledge.

Social learning differs from education in its form; edu-

cation is often more formal, centralised and has predeter-

mined outcomes; social learning, on the other hand, often

occurs in informal communities where individuals explore

and evolve potential outcomes (Wenger 2000). Despite the

studies being strictly categorised as being either education

or social learning, the studies did exhibit elements of both.

4.4 Education

Morgenroth et al. (2004) investigated the current and future

requirements of environmental engineering education (E3).

Soliciting international responses from universities, com-

panies, municipalities and government agencies, it was

found the majority of E3 programmes in 2004 were asso-

ciated with the civil engineering discipline and that can-

didates with an E3 background were in demand. A series of

core E3 professional competencies are outlined, compris-

ing of: the need for universities remain focused on deliv-

ering fundamental science and engineering education—

industry will provide job-specific training to fit individual

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SD needs, and E3 students should exhibit superior inter-

disciplinary and interpersonal skills and an ability to deal

with ill defined, wicked problems.

Two articles reported on programmes which educate

professionals in SD matters. The first article (Huisingh and

Mebratu 2000) was concerned with educating university

educators to improve preventative environmental manage-

ment education. The second (Sage 2000) details a programme

which provides support for cleaner production (i.e. work-

shops, consultation sessions, award process). Commonalities

exist between these studies; it was believed that the respective

educational platforms perpetuate effective change agents

whilst emphasising a need for cross-boundary interaction

between organisations, countries and economic sectors.

Gao et al. (2006) applied a holistic educational approach

to shift personal attitudes towards protective environmental

management and to bring about a sustainable society. The

application of a three-tiered education framework ensured

content and activities were targeted at specific stakeholder

groups (top company managers and government policy

makers; company and government representatives; and the

public). Results were encouraging in all stakeholder

groups, including: greater KS activity; proactive SD atti-

tudes; improved management support; strategic advantage;

environmental and economic benefits; and public promo-

tion of SD thinking.

Finally, Pohl et al. (2009) present an e-learning system for

vocational education. Distance education can provide

advantages for professionals, despite Morgenroth et al.

(2004) finding that new teaching tools are ‘not expected to

provide much benefit’. Nonetheless, Pohl et al. present a

system which delivers a form of ‘blended learning’; the

course is made up of 30% face-to-face interaction, with the

remainder being conducted online. To overcome technical

barriers, the system uses real-life online tutors and metaphors

to enable users to affiliate the system with real-world situa-

tions (e.g. uses the notion of rooms to depict each directory’s

contents, such as ‘library’). Communication was considered

a very important feature; a combination of scheduled and ad

hoc interaction provided a good course structure. A social

barrier was that some students found it difficult to interact in

online discussions; e.g., asking ‘intelligent’ questions

despite the best efforts of the tutor. A long-term benefit of the

system is the social network that emerged from the course;

participants continued to regularly meet to exchange per-

sonal experiences with eco-design.

4.5 Social networks

Social networks play a fundamental role in how individuals

share knowledge and share information (Wang et al. 2006).

Instances of social networks are evident in the education

section, where self-perpetuating social network groups

organically stemmed from participation in education pro-

grammes (Huisingh and Mebratu 2000; Sage 2000; Pohl

et al. 2009), enabling longer-term KS. Lauber et al.’s

(2008) studies of collaborative resource management found

that such social structures are formed to: exchange ideas

during the development of a project; share knowledge;

exert influence; and provide fiscal or tangible resources. It

also reinforces Huisingh and Mebratu’s (2000) and Sage’s

(2000) message that cross-boundary sharing is important

for environmental management.

4.6 Public participation

Public participation (PP) is an important source of exper-

tise. With numerous participatory processes falling short of

their objectives, Gonzalez et al. (2008) approached inter-

national experts to test the assumption that geographical

information systems (GIS) can be used as a novel com-

munication channel which enhances understanding (e.g. to

help people spatially comprehend situations). It was found

that whilst PP was considered valuable to decision-making,

it only occurred in a few cases. A number of factors were

reported to affect the effectiveness of PP; it was generally

felt clear guidance would help facilitate public engagement

and tackling the listed set of identified issues (e.g. pro-

moting two-way communication, building trust, demon-

strating an openness and willingness to engage with the

public, and so on). Gonzalez et al. (2008) found that

Internet access and literacy (i.e. the ‘digital divide’), cou-

pled with information management challenges, would

hinder the success of PP systems. In conclusion, it was felt

that a combination of social–technical PP systems could

provide richer knowledge to decision makers.

4.7 Decision support

Boddy et al. (2007) emphasise that project engineers are

required to make critical decisions which affect a project’s

SD performance. Thus, decision makers require timely

knowledge to encourage more informed SD-related deci-

sions, with the subsequent results being recorded for future

use. Boddy et al. (2007) consequently report on the inte-

gration of a knowledge management environment and a

decision support system (DSS), whose aim was to bring

people and information together for knowledge informed

decision-making (KIDM). A laboratory case experiment

suggests that the KIDM system was capable of delivering

real-time, relevant decision support. However, it was also

recognised that information is distributed in its raw format

(i.e. there is no guarantee that suggested decisions are the

‘right ones’), thus poor decisions could be used to inform

future decisions, spawning a cycle of poor decisions.

Modern systems often allow users to annotate or approve

444 AI & Soc (2012) 27:437–449

123

information based on criterion; this feature was not avail-

able in the integrated systems.

Boddy et al. (2007) also found that adaptation of KM

systems is often inhibited in construction organisations due

to their bureaucratic and hierarchical structure; this structure

and culture work against systems similar to the proposed

KIDM tool, which flourish in flat management structures,

with open communication channels and an opportunity to

inform decision-making processes where appropriate.

4.8 Measurement

Mackley and Milonas (2001) measured KS against an

environmental performance assessment (EPA) pro-

gramme’s learning objectives on an international scale.

Intra-national teams’ responses varied, predominately

dependant on teams’ knowledge prior to the EPA pro-

gramme: those who had prior EPA knowledge felt the

learning objectives had not been met and exhibited resis-

tance to EPA tools; those without prior EPA knowledge

felt methodological knowledge had been transferred and

had benefitted from the lessons of more experienced teams.

At an international level, teams associated value with

collaborative processes which exposed them to diverse

issues and solutions. However, collaborative barriers were

also identified, including: difficulties in physical meetings

due to distance or funding; time limitations in conferences

or meeting sessions; and cultural barriers.

5 Conclusion

The aim of this research was to provide an overview of

existing KS for SD studies. A discussion of basic SD and

KS concepts emphasised the need for improved KS for SD

within civil engineering organisations. Consequently, a

systematic literature review was conducted to locate and

synthesise KS for SD-related studies which exhibit civil

engineering-related contexts. This revealed that dominant

KS concepts centred around SD collaboration and educa-

tion (Table 4) and that most studies adopted a survey or

case study research strategy (Table 2).

This research suggests that there is a dearth of published

KS for SD-related studies. The work reported here is the

first systematic review aimed at KS for SD and is one of

few studies investigating KS for SD in the civil engineering

sector.

5.1 Implications

The findings have practical implications for those who

recognise the need for greater KS for SD in civil engi-

neering contexts.

First, whilst technical systems are often perceived as

easy to implement and measure, practically all of the

identified studies emphasise that organisations cannot dis-

miss the importance of face-to-face interaction when

sharing SD knowledge. This interaction allows participants

to develop relationships and build trust; a widely under-

stood requirement for successful KS (Davenport and Pru-

sak 1998; Abrams et al. 2003). The importance of social

interfacing when dealing with complex SD situations was

reinforced by Morgenroth et al. (2004). This is somewhat

understandable as technical systems often advocate

knowledge externalisation (i.e. codification of knowledge),

rather than knowledge socialisation. Of course, there are

exceptions; the technical system studies reviewed here, for

example, whose purpose is to act as a socialisation mech-

anism rather than to capture and disseminate knowledge

and information. It is noteworthy that it was found that

social interfacing cannot be left to serendipity alone;

developing and maintaining an explicit understanding of

how parties are to engage seems to reduce conflict and

enhance outcomes.

Second, collaboration is necessary to deal with SD’s

multidisciplinary requirements. Collaboration played a

noteworthy role in all of the identified studies. Most col-

laboration-centric studies present scenarios that involved

KS between diverse parties, which are believed to enhance

knowledge creation and problem solving (Fong 2005).

However, it was perceived that this cross-boundary KS

may generate conflict; relevant studies suggest that more

explicit collaborative activities may reduce such conflict

(cf. Margerum 2001, 2008; Lauber et al. 2008) or by using

prescribed interfaces (cf. Schneider et al. 2008, Yao and

Steemers 2009; Cooper 2002).

Third, education is a vital aspect of SD that allows par-

ticipants to expand their appreciation of SD topics and

issues. It can help individuals build consciousness, knowl-

edge and skills for the process of SD (Jansen 2003; UNCED

1993), thus helping organisations to overcome KS issues,

such as silo mentalities that are common in civil engineer-

ing organisations. Further, the educational environments

reported by applicable studies endorse open two-way

communication to encourage new knowledge generation

through KS; they did not advocate the traditional form of

knowledge transfer (i.e. a lecturer ‘transfers’ knowledge to

students in a one-way format).

Finally, social networks are powerful organisational

assets. Civil engineering-related organisations should seek

to identify and cultivate these informal structures as they

can provide many KS benefits, especially when dealing

with SD’s complex and interdisciplinary nature. SNA

techniques can help organisations map informal structures

to determine how they can be better supported (cf. Scott

2000; Cross et al. 2002).

AI & Soc (2012) 27:437–449 445

123

5.2 Directions for further research

Systematic literature reviews also allow researchers to

recognise areas of uncertainty and where little research has

been conducted (Petticrew and Roberts 2005). Whilst this

is true, the field of KS is expansive, thus there is too much

to list here. However, the frameworks used to classify the

identified studies are used to provide an indication of how

KS for SD research could be expanded.

It is evident that only a small number of KS concepts are

addressed in the identified studies. Concepts which exhibit

few studies suggest the greatest opportunity for further

research in this area; although with such few identified

studies, any research that explores KS for SD is potentially

valuable. For example, despite a strong emphasis on col-

laboration and social networks, only one identified study

attempted to map KS interactions. SNA techniques could

help organisations understand and improve the effective-

ness of collaborative relationships, especially in the civil

engineering domain which is often considered to be highly

fragmented (Myers 2005).

It is also evident that a gap exists for the application of

particular research strategies; studies generally resided on

the positivistic end of the research strategy spectrum.

Whilst survey and case study strategies are widely adopted,

other research strategies may also prove insightful to the

Table 4 Summary of studies’ KS concepts and main findings

Concept Dominant

attribute

Main findings Reference

Collaboration Cultural Approach to encourage cross-functional collaboration Garde-Bentaleb

et al. (2002)

Cultural Creating successful partnerships with tribes requires significant resources to develop a

shared understanding and awareness, and a high level of continuity to develop effective

relationships

Lyver (2005)

Social Stakeholder commitments and constraints must be explicitly addressed Margerum (2001)

Social Benefits of using a typology to reduce confusion between collaboration efforts Margerum (2008)

Social Approaches to developing a practical and intellectual knowledge partnership between

European and Chinese institutions

Yao and Steemers

(2009)

Technical Electronically mediated approach to tackling the contentious issues of SD, interdisciplinary

working, and the design and management of virtual organisations

Cooper (2002)

Decision

support

Technical Emphasises potential process benefits of integrating a decision support tool with a

knowledge management environment

Boddy et al.

(2007)

Education Cultural Approaches to educating different stakeholder groups Gao et al. (2006)

Cultural Universities should remain focused on providing fundamental education in basic sciences

and related engineering fields, whilst enhancing students’ interpersonal skills necessary for

social learning activities

Morgenroth et al.

(2004)

Social Educational programmes can be important contributors to societal changes Huisingh and

Mebratu (2000)

Social Participation in educational programmes facilitates implementation of long-term activities Sage (2000)

Technical Considerations for employing an e-learning course Pohl et al. (2009)

Measurement Cultural The Green Building Challenge process accelerates KS at a team and national level Mackley and

Milonas (2001)

Public

participation

Technical Technology-aided methods can improve traditional public participation processes Gonzalez et al.

(2008)

Social

learning

Social Impacts of KS in poor communities using sustainable technologies Al-Jayyousi

(2004)

Social Social learning can identify and address key constraints to complex SD issues Measham (2009)

Social Search conference format can be adopted to explore diverse perspectives of issues and

identify concerns

Selin et al. (2007)

Social

networks

Social Reasons why stakeholders interact in collaborative processes Lauber et al.

(2008)

Technology

transfer

Social Successful technology transfers depend on minimising transaction costs, strengthening

collaborative mechanisms, and in maximising public trust and accountability of

partnerships

Forsyth (2005)

Social The Clean Development Mechanism does contribute to technology transfer by lowering

barriers and raising transfer quality

Schneider et al.

(2008)

446 AI & Soc (2012) 27:437–449

123

complex interactions and perspectives that are inherent in

both SD and KS; for example, the application of a groun-

ded theory techniques are well suited to KS for SD due to

its systematic approach to building understanding of

complex social phenomenon (Ribeiro et al. 2010). Further,

examples of these strategies in wider KS literature dem-

onstrate the benefits of such approaches.

Finally, the studies predominately report inter-organi-

sational KS for SD scenarios. Intra-organisational KS for

SD, however, is also important where valuable knowledge

is often ‘locked-in’ strategic business units (Willem et al.

2006). This is especially true when dealing with large

international organisations where KS can ‘enhance overall

organisational capabilities through collective learning and

synergistic benefits generated from the processes of

exchanging information, know-how, or local expertise’

(Tsai 2002).

5.3 Limitations

This study is not without limitations. There are four note-

worthy limitations that should be considered when drawing

on this work.

First, whilst subject matter experts were consulted at the

beginning of the study, the filtering process was done by

the authors. This potentially introduces a self-selection bias

which may limit the reliability of the conclusions. In rec-

ognition of this limitation, the authors strictly adhered to

the comprehensive set of exclusion criteria in a bid to

improve the reliability of the study.

Second, the study’s conceptual categorisation may suf-

fer from construct validity. However, the purpose of the

categorisation was to indicate where research efforts had

been focused, not provide a taxonomy. Further, there was

also a lack of empirical data presentation in the identified

studies, which may compound this issue; a common diffi-

culty when extracting data from management studies

(Tranfield et al. 2003).

Third, the journal databases selected did not include all

journal publications, and some potentially relevant articles

were excluded as a result. However, five leading online

databases that are publicly available were queried to reduce

this issue.

Finally, the low number of identified studies is a limi-

tation in itself. As such, it was difficult to draw a rich

understanding of what does and does not work in KS for

SD. This is accentuated by a disproportionate number of

‘success stories’; the identified literature seems to suffer

from publication bias, where positive results are more

frequently reported. For example, Lauber et al.’s (2008)

study specifically selected ‘sites’ where previous projects

were considered successful.

Acknowledgments The authors gratefully acknowledge the support

of the Engineering and Physical Sciences Research Council (EPSRC),

through the Bristol/Bath Engineering Doctorate Centre in Systems

Engineering, for the work reported in this paper.

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