DEVELOPING A MATURITY MODEL FOR PRODUCT-SERVICE

SYSTEMS IN MANUFACTURING ENTERPRISES

Alexander A. Neff, Institute of Information Management, University of St.Gallen (HSG),

Switzerland, alexander.neff@unisg.ch

Florian Hamel, Institute of Information Management, University of St.Gallen (HSG),

Switzerland, forian.hamel@unisg.ch

Thomas Ph. Herz, Institute of Information Management, University of St.Gallen (HSG),

Switzerland, thomas.herz@unisg.ch

Falk Uebernickel, Institute of Information Management, University of St.Gallen (HSG),

Switzerland, falk.uebernickel@unisg.ch

Walter Brenner, Institute of Information Management, University of St.Gallen (HSG),

Switzerland, walter.brenner@unisg.ch

Abstract

The constantly rising fraction of industrial services reveals the structural economic change that is changing

the manufacturing industry landscape. Manufacturing firms have more and more problems to find the

appropriate information technology (IT) solution for planning and execution as they are confronted with the

strategic challenge of reducing operating costs while at the same time meeting ever-increasing industrial

service demands. Despite the existence of some standardization efforts dealing with product-related services,

there is no common understanding of product-service systems and the corresponding processes and IT

systems among manufacturing companies. This paper addresses this need by developing a maturity model

capturing the key requirements for the information systems (IS) support of product-service systems based on a

multiple case study. Further, we confronted these requirements with scientifically recognized maturity models

and standard specifications developed by the German Standards Institute. The development of the maturity

model is grounded in the design science research approach and is evaluated by managerial experts.

Keywords: Service Science, Information Systems, Product-Service Systems, Maturity Model, Design

Science Research.

1 INTRODUCTION

Nowadays, the manufacturing industry is undergoing significant structural economic changes (Vargo

& Lusch 2004; Wölfl 2005). In the German mechanical engineering sector, the total turnover related

to industrial services has made significant advancement from 16.8% in 1997 to 22.5% in 2000, while

the fraction in the electrical engineering industry has almost doubled in this period (Stille 2003). On a

European scale, services account for almost half of the profits of manufacturing companies with a

average annual profit growth of five percent (Strähle et al. 2012). The constantly rising fraction of

industrial services in all Organisation for Economic Co-operation and Development (OECD) countries

except Luxembourg (OECD 2011) results in the need for product-service systems to be supported with

the appropriate IT solution. Manufacturing firms have more and more problems to find the appropriate IT

solution for planning and execution as they are confronted with the strategic challenge of reducing operating

costs while at the same time meeting ever-increasing industrial service demands. (Dietrich 2006). While

legacy systems need to be replaced, expensive proprietary systems and highly customized standard

solutions must be maintained to serve the service component (Günther et al. 2009; Thomas et al.

2008). Notably, firms encounter problems in the maintenance function of product-service systems

(Thomas et al. 2008) and in supporting the managerial accounting (Dietrich et al. 2008). Moreover,

one of the major difficulties lies in the detail and accuracy of status information on the service

execution process, which is required by different hierarchy levels in the company.

The situation is even more challenging in business segments that are characterized by numerous and

strongly diverging production processes and highly versatile products. This holds particularly true for

the manufacturing industry, typically involving batch processes in press plant, highly automated

production lines, and assembling activities with load and balancing requirements. Service research has

traditionally concentrated on the front stage of service delivery, studying phenomena such as provider-

client relationships, co-creation of value, service quality, service encounters, and service experiences

(Glushko & Tabas 2009; Teboul 2006). However, there is a lack of research studies on the back stage

of service systems (Becker et al. 2011; Glushko & Tabas 2009). The authors apply an information

systems research perspective of service science. In view of the foregoing, a concept is needed allowing

a holistic support for such broad design and transformation tasks. Being successfully implemented in

the software engineering domain (Paulk et al. 1993), maturity models represent an established means

to support effective management for complex, heterogeneous phenomena (Ahern et al. 2004). Our

objective is to develop a maturity model that is capable of holistically assessing the IT support of

product-service systems in the manufacturing industry and that is based on highly relevant

requirements. Hence, we address the following research questions (RQ):

(1) What maturity models are capable of holistically assessing the IT support of product-service

systems in the manufacturing industry?

(2) What could a product-service system specific maturity model targeting key requirements of

multinational manufacturing enterprises look like?

In order to address these research questions, the authors conducted a multiple case study analysis with

leading manufacturing firms from the capital equipment goods industry. The authors contribute to the

body of knowledge by identifying requirements that are not covered holistically in existing maturity

models. Based on the identified requirements, the research gap is addressed with the development and

evaluation of a holistic maturity model. The following paper is divided into four parts. The first part

lays the foundation by considering the central terms and the research gap studied in this paper. The

second part describes the selected research approach. The third part answers RQ.1 by exploring

unaddressed requirements and analyzing existing maturity models and publicly available

specifications (PAS). The fourth part is concerned with the development and evaluation of the

maturity model (RQ.2). Finally, we conclude with our major contribution, supplemented with a critical

reflection and an outlook on future research.

2 RELATED WORK AND RESEARCH GAP

Academics as well as practitioners hold an ongoing debate on services and related products. Scholarly

literature considers service science from distinct academic perspectives, e.g. information systems,

marketing, management and operations management (Bardhan et al. 2010; Beverungen 2011; Maglio

& Spohrer 2008; Rai & Sambamurthy 2006; Spohrer & Kwan 2009). Service concepts heavily depend

on the academic imprint of the researchers. In accordance to the service dominant logic (Vargo &

Lusch 2004), IS scholars define services as the application of competence and knowledge with the aim

of creating value between providers and receivers (Spohrer et al. 2007). Lately, the notion of the

“service system” has been put forward as the basic abstraction of the new discipline service science,

management, and engineering (SSME), representing “a dynamic value co-creation configuration of

resources, including people, organizations, shared information […], and technology, all connected

[…] by value propositions” (Maglio et al. 2009). In view of the broad conception of a service system,

extant literature in operations management tries to combine products and industrial services in terms

of bundles (Oliva & Kallenberg 2003), solutions (Davies et al. 2006; Tuli et al. 2007) and systems

(Goh & McMahon 2009).

The authors apply the definition of product-service systems, since it achieves most hits in a literature

search (among the three terms: bundles, solutions and systems) and fits best with the manufacturing

focus by adding the life cycle aspect (Neff et al. 2012). The definition recalls the “customer life cycle

oriented combinations of products and services, realized in an extended value creation network”

(Aurich et al. 2006). Although scholarly literature tries to consolidate the theoretical views on services

(Sampson & Froehle 2006), no consensus has been reached on a general definition of services

(Metters 2010). Present research in SSME focuses on customer value, such as value creation in service

economies, service marketing issues or service encounters, as well as value co-creation with customers

(Clarke & Nilsson 2008). Unfortunately, the existing research has not provided deeper insight into

business processes (Glushko & Tabas 2009), enterprise systems and software applications that are

required to integrate manufacturing and service processes in service systems. Although exchanging

information is accepted as one of the key challenges in SSME (Chesbrough & Spohrer 2006), the

literature falls short of outlining how IT artifacts have to be designed in order to make the appropriate

information accessible through the life cycle stages (Becker et al. 2011). In conclusion, there is a clear

need for an integrated solution with selected information exchange. Rather than analyzing transaction

cost economies, the authors focus on the requirements of product-service systems and the

corresponding IS / IT implementations. In particular, some producer stakeholders only supply physical

goods, whereas other producer stakeholders provide services in interaction with customers, thereby

fitting the front stage (i.e., services) and back stage (i.e., manufacturing carried out in the technical

core of operations) together into a seamless value network. Integrating service and manufacturing

processes is a challenging effort, as manufacturing processes and service processes require different

management approaches and are built upon different IT artifacts. For instance, service processes, as

opposed to manufacturing processes, are, due to their very nature, conducted in cooperation with the

customer as a co-creator of value (Tuli et al. 2007). Furthermore, customers often perceive “their

solution” to be inseparable (Bardhan et al. 2010), while manufacturers and service providers are faced

with the need to coordinate disparate business processes and resources to create this integrated service

experience.

Being defined as “the state of being complete, perfect or ready” (Simpson & Weiner 1989), the term

maturity implies an evolutionary progress in the demonstration of a specific ability or in the

accomplishment of a target from an initial to a desired end stage. IS scholars refer to a measure for the

evaluation of corporate capabilities (Rosemann & De Bruin 2005). Tying up in this line of

argumentation, Becker et al. (2009) explain that a maturity model serves as a tool for designing and

using IT effectively and efficiently. In essence, these models consist of multiple archetypal levels that

together represent the evolution of a certain domain (Fraser et al. 2002; Rosemann & De Bruin 2005).

The user, e.g. an organization, applies maturity models to benchmark and continuously improve

enterprise capabilities (Paulk et al. 1993). Assuming a strong link between the maturity level of a

particular capability and the effectiveness of the IT providing that capability, maturity models describe

how the value gained from IT increases along the evolutionary path (Urwiler & Frolick 2008).

3 RESEARCH APPROACH

In order to construct a maturity model and thereby address the RQs of this paper, we selected the

design science research (DSR) approach (Hevner et al. 2004; Peffers et al. 2007). This form of

research is widely accepted among IS scholars for addressing real-world problems and simultaneously

contributing to the body of scientific knowledge (Baskerville & Myers 2009). DSR strives to build and

evaluate “artifacts” with the aim of overcoming existing capability limitations (Hevner et al. 2004).

These artifacts represent the outcomes of the DSR process (Peffers et al. 2007). Using DSR, we argue

that maturity models are reference models (Herbsleb et al. 1997) and hence artifacts that show “an

anticipated, desired, or typical evolution path” (Becker et al. 2009).

Problem identification Iterative model development Model evaluation

· Problem identification and

motivation

· Conceptualization of maturity

levels (as in Paulk et al. 1993)

· Definition of structural dimensions

· Multi-perspective approach

(following Frank 2006)

· Multiple evaluation rounds

· Reflection on evaluation results

· Exploratory case studies

· Literature review

Pe

rfo

rme

d

ac

tiv

itie

s

Pe

rfo

rme

d

ac

tiv

itie

sU

se

d

tec

hn

iqu

es

Us

ed

tec

hn

iqu

es

1 3 4

· Section 2 (Related work and

research gap)

· Table 1 (Case study participants)

Ou

tpu

t &

rela

tio

n t

o

pa

pe

r

Ou

tpu

t &

rela

tio

n t

o

pa

pe

r

Comparison of existing maturity

models

· Deduction of maturity model

requirements

· Identification of existing maturity

models

· Evaluation of existing maturity

models

· Exploratory case studies

· Literature review (following vom

Brocke et al. 2009)

· Likert-scale ranking of MMs

2

· Section 4.1 (Analysis)

· Table 2 (Results of the keyword

search)

· Table 3 (Model fit assessment)

· Iteration 1: Content analysis of case

study reports

· Iteration 2: Model adoption

mechansims (vom Brocke 2007)

· Iteration 3: Focus group analysis

(Tremblay et al. 2010)

· Section 4.2 (Synthesis)

· Table 4 (Maturity model for

product-service systems)

· Focus group workshop

(Tremblay et al. 2010)

· Self-assessment of manufacturing

companies

· Section 4.3 (Evaluation)

· Table 5 (Profile of focus group

members)

· Table 6 (Self evaluation of

manufacturing companies)

· Iteration 1: Conceptualization of

maturity levels (as in Paulk et al.

1993) & definition of structural

dimensions

· Iteration 2: Integration of

requirements

· Iteration 3: Model refinement

Figure 1. Procedure model based on Becker et al. (2009)

We are aiming to investigate heterogeneous phenomena with a homogeneous model, and a maturity

model is well-suited for this analysis of product-service systems in the manufacturing industry. The

development of maturity models within the IS field is not new, and has been popular for quite some

time (De Bruin et al. 2005); literature scholars have counted numerous models (Becker et al. 2010b;

Mettler et al. 2010). In contrast to the large number of maturity models, the research on how to

develop these models is rather sparse (Becker et al. 2009). Additionally, most authors seldom

demonstrate their development process. During our literature review (Chapter 4.1), we encountered

only a few development procedure models, and the results suggest that there are two popular models

(Becker et al. 2009; De Bruin et al. 2005) among IS scholars. We decided to apply Becker et al. (2009)

to develop our maturity model, since this provides a stringent as well as a consistent development

process that is subject to the DSR guidelines (Hevner et al. 2004). Becker et al. (2009) propose an

eight-step development process for maturity models which we adapted slightly (Figure 1). In order to

reduce the complexity of the model and to align the procedure process with the structure of this paper,

we merged three process steps (conception of transfer and evaluation, implementation of transfer

media and finally the evaluation) into one, the evaluation step. Nevertheless, we follow the steps

proposed by Becker et al. (2009) within the evaluation step. Transfer media represent hereby the

media which are used to communicate and illustrate the maturity model. Since DSR refers to a

problem-oriented approach, the development of the maturity model is usually initiated either by a

“need and require” intention or by opportunity-based innovation (Järvinen 2007). In light of this, our

approach starts with problem identification (step 1). We specified the research problem, provided

practical relevance and justified the value of the artifact. Since the boundaries between service and

manufacturing processes and their contexts, i.e. the service systems in which they are embedded, are

not clear, case study research is well suited to guide our research (Yin 2009). Over a period of 3

months, from April 2012 till June 2012, a team of two researchers conducted seven exploratory case

studies at worldwide leading manufacturing firms (Table 1). Based in the high-wage countries of

Germany and Switzerland, the manufacturing firms rely heavily on innovation and customer service

for achieving efficiency synergies. Although data was collected using a variety of methods, semi-

structured interviews were our primary method of data collection. Scholarly literature emphasizes the

benefits of the multiple case study approach in terms of enhanced validity (Eisenhardt & Graebner

2007). Multiple researchers can improve the creative potential, while the convergence of observations

strengthens confidence in the findings (Eisenhardt 1989). After writing down the interview transcripts,

the authors complemented the interview-based data collection by further analyzing system landscapes

and process maps. The final results were documented and triangulated in a case study report, which

was consecutively reviewed and approved by the industry partners. The second step, comparison of

existing maturity models (2), builds on the problem identification (1) and the identification of

shortcomings or lack of transferability in the analysis of existing maturity models. As part of this step,

we conducted a structured literature review in accordance with vom Brocke et al. (2009) to identify

existing maturity models devoted to the same or similar domains. Subsequently, we analyzed the

maturity models according to their domain and functionality as well as their capability to address the

research problems we had outlined. During the iterative maturity model development (step 3), we used

model adoption mechanisms (i.e., configuration, instantiation, aggregation, specialization, analogy

(vom Brocke 2007)) in a rigorous creation of a maturity model (structure and content). For the next

step, model evaluation (step 4), we combined the conception of transfer and evaluation, the

implementation of transfer media and the evaluation into one step (Becker et al. 2009).

Case company

[Industry]

Employees

> 10k

Turnover €

> 5 Billion

Interview

partner

Number of

interviews

ALPHA

[Industrial]

Process Automation IS

Manager 2

BETA

[Industrial] -

Vice President Service

Division 2

GAMMA

[Construction] - - CIO & Head of Processes 2

DELTA

[Industrial] - CIO 1

EPSILON

[Industrial] -

Head of IT Strategy &

Transformation 1

ZETA

[Utility] CIO 2

ETA

[Industrial]

Head of Corporate

Solutions & Technology 1

Table 1. Profile of the case study participants; numbers are based on the fiscal year 2010

4 MATURITY MODEL DESIGN

During the interviews, the authors were confronted with a large number of specific challenges and

requirements for product-service systems. After analyzing all of our data thoroughly, the authors

aggregated and consolidated the aforementioned requirements and discussed them in workshops with

experts (Tremblay et al. 2010). This process resulted in the derivation of a list of seven highly relevant

requirements. In order to create a holistic perspective and to identify the critical levers, we structured

our findings according to three segments (strategy, process, and information systems) (Österle 2010).

The intensive interviews with experts from different manufacturing corporations revealed the fact that

there is neither a common definition nor a standardized business model classification of the product-

service systems available. From a strategic perspective, these firms have developed their firm-specific

terminology, including classification approaches for business models. A similar thing holds true for

analytical objectives and performance indicators. The process perspective showed that mature

instantiations of installed base management and mobile solutions take advantage of valuable

operational and customer-centric data. Analyzing the cases from an information systems perspective,

we encountered a wide spectrum of system approaches. The system spectrum ranges from legacy

systems, through loosely coupled proprietary systems, to fully integrated enterprise systems. Applying

the most pragmatic approach of using proprietary systems was criticized by participants due to the

high level of software development and integration effort. Added to this problem, a high risk of low

data quality has a serious impact on the effectiveness and efficiency of the product-service system.

Furthermore, service processes need to be supported by a flexible and global service infrastructure.

According to our case study participants, the following aspects are not fully covered by existing

industry models and standards such as the PAS developed by the German Standards Institute (referred

to from here on as the DIN):

· (R1) Business model: The business model influences the service portfolio and hence the

business processes. However, all case study participants acknowledge that keeping capital

equipment goods operating at the customer site is essential to succeed in the service business.

The IS manager of ALPHA stated that “the ALPHA group distinguishes three business model

stereotypes: spare parts, life cycle service and full service. Each of them requires different

business processes for realization.”

· (R2) Service quality: Since the value of industrial services arises when the business customer

applies it, the service quality has to be ensured along the entire value chain, including external

vendors. For that reason, the following methods have been applied: roll-out global service

processes, establishing audits and certifications, and performance indicators. The CIO of

DELTA outlined that “we rolled out standardized service processes worldwide. Once a year,

the service locations are checked in a comprehensive audit program.”

· (R3) Installed base management: Managing the installed base is salient as it presents valuable

customer knowledge and creates critical insights about the machines in operation. The

following elements characterize this requirement: collecting and updating historic data after

repair and maintenance events, use of condition monitoring for preventive maintenance, and

optimizing the customer processes including equipment investment goods from competitors.

As stated by the manager of BETA, “the application of emerging technologies such as remote

setup, repair, and maintenance can help to keep up the operation condition with efficient

resources.”

· (R4) Mobile solution: There is a clear need to support service technicians during the customer

visit. The main purpose is to provide master data, historical data, service catalogues, access to

the knowledge base, and to trigger the billing and accounting processes. The manager at

EPSILON reported “on a mobile solution that guides the service technicians during repair

and maintenance activities. However, expensive proprietary systems serve as a technical basis

for the mobile support of our service technicians.”

· (R5) Enterprise integration: Most of the case companies primarily produce in their European

home market, while local entities are responsible for sales and service activities. Larger

production entities, smaller service entities and local subcontractors form a comprehensive

service network that requires appropriate architectural solutions. The resulting complexity

provides additional challenges to the IT architecture. As specified by the manager of ALPHA,

“locations with production and service hubs require substantially more information systems

support than smaller locations with a smaller budget. Cloud-based information systems

present a contemporary approach for such small entities.” The manager of GAMMA refers to

expensive customization projects for adapting enterprise systems to the service-specific needs.

· (R6) Data quality & integration: Ensuring high efficiency in the service processes requires

substantial investment in corporate data quality to establish standards. A set of profound and

reliable master data is crucial for automated service processes. Five case study participants

clearly indicated that service and product businesses are separated organizationally and that is

reflected in a separation of the adjacent information systems. As a result, product and service

components are covered by distinct data models. However, efficient contract management

requires an integrated view of product and service objects. The manager of BETA mentioned

that “the service level is specified as long text in the product object.”

4.1 Analysis

Based on the exploratory findings, we analyzed the existing literature that seemed promising for

addressing the discussed requirements. The selection of existing maturity models and DIN PAS was

based on the structured literature review approach (vom Brocke et al. 2009). We present below (Table

2) the results of the keyword search in which, using relevant keywords from literature reviews

(Bardhan et al. 2010; Berkovich et al. 2011; Beverungen 2011; Neff et al. 2012; Spohrer & Kwan

2009), we performed the searches of certain databases (EBSCOhost, ProQuest (ABI/INFORM),

Emerald, ScienceDirect, Web of Science, and AISeL) (vom Brocke et al. 2009). We limited our search

to title, abstract, and keywords, and it resulted in 57 matches for in-depth analysis. After the actual

content analysis, 53 articles were excluded, since they did not include maturity models in the targeted

domain or they referred to previous models instead. The findings can be narrowed down to four

articles. Since these maturity models do not even mention two of the relevant requirements (R4 and

R6), we continued the literature search with a forward / backward search that yields four DIN PAS;

deriving, in total, 8 articles for analysis.

Database

AN

D

“Stage model” OR “maturity model”

“Information technology” OR “information systems”

“Service

science”

“Product

service

bundle”

“Product

service

system”

“Product

service

solution”

Net

hits*

EBSCOhost 7 (33) 0 (9) 2 (8) 0 (1) 9

ProQuest 6 (73) 0 (8) 4 (37) 0 (5) 10

Emerald 6 (70) 2 (16) 6 (28) 1 (6) 15

ScienceDirect 0 (2) 0 (12) 1 (12) 0 (3) 1

Web of Science 3 (42) 1 (2) 3 (82) 1 (10) 8

AISeL 12 (49) 0 (0) 3 (3) 1 (7) 16

Net hits* 57

Legend: *) Double counts are removed manually

Table 2. Results of the keyword search (before in-depth analysis)

The keyword search yields four existing maturity models. This selection was also confirmed by two

conceptual publications in the product-service context (Becker et al. 2010a; Pöppelbuß et al. 2009).

Hildenbrand et al. (2006) break down the strategic service management of industrial organizations into

five stages, each of which reflects a distinct degree of service orientation. While Nägele and Vossen

(2006) focus on the integration of the customer into the service development, Oliva and Kallenberg

(2003) outline the transition of the corporate focus from product to service in a procedural model.

They claim that new organizational structures and business processes become necessary for the

adequate support of this transition. Spath and Demuß (2006) describe in their maturity model the

different roles that industrial service can obtain through the combination with physical goods in the

manufacturing industry.

The forward / backward search provides four standard specifications (i.e., DIN PAS) that outline

particular requirements. Special requirements are given through the integration of heterogeneous

service and product components, properties of the life cycle management, innovative business models,

customer integration and regulatory compliance. In accordance with DIN PAS 1094 (2009b), three

additional DIN PAS have been developed to deepen particular aspects. While DIN PAS 1082 (2008)

presents a standardized process for the development of industrial services in networks, DIN PAS 1091

(2010) encompasses interface specifications for the integration of product-service systems. DIN PAS

1090 (2009a) is concerned with IS requirements that are developed for the mobile support of the

technical customer service.

In order to derive the appropriate dimensions for the maturity model, the authors mapped the explored

requirements with the identified maturity models and the DIN PAS (Table 3). We used a five point

Likert scale to rank every article for every requirement according to the degree of coverage from 1

(very low) to 5 (very high). This method has been widely applied to IS research, e.g. by Alavi (1984).

The evaluation of coverage was conducted by the research team focusing on quantifying the

conceptual differences of the analyzed models. In the next paragraphs, we will outline examples that

illustrate the ranking process and the mentioned imperfect coverage of the requirements by the

existing industry models. None of the existing models covers can be called holistic as no model

addresses all requirements at the same time.

Framework [Source] Orientation Requirements

Standard Maturity R1 R2 R3 R4 R5 R6

Hildenbrand et al. (2006) - 4 3 1 1 3 1

Nägele & Vossen (2006) - 4 3 1 1 1 1

Oliva & Kallenberg (2003) - 5 1 4 1 2 1

Spath & Demuß (2006) - 4 3 3 1 1 1

DIN PAS 1082 (2008) - 3 1 1 2 2 3

DIN PAS 1090 (2009a) - 1 1 1 4 4 1

DIN PAS 1091 (2010) - 3 3 1 1 1 3

DIN PAS 1094 (2009b) - 4 3 3 1 1 2

Average 3.5 2.3 1.9 1.5 1.9 1.6

Legend: Degree of coverage: 1 very low; 2 low; 3 medium; 4 high, 5 very high

Table 3. Model fit assessment

The business model requirement (R1) achieves the highest average of all the requirements

investigated. Most attention in literature is directed towards the strategic debate about the appropriate

business model in the “servizitation” (Neely 2008) of the manufacturing industry, resulting in seven

articles for analysis. After dealing with transaction-based services, manufacturing firms recalibrate

their focus towards relationship-based activities such as professional services and sophisticated

maintenance (Oliva & Kallenberg 2003). They claim that new business models such as spare parts, life

cycle service and full service become necessary to support this strategic transition. Hildenbrand et al.

(2006) break down the strategic service management of industrial organizations into five stages, each

of which reflects a distinct degree of service orientation, but neglect the full service conception.

Nägele and Vossen (2006) posit a customer-oriented view from a purchaser to a partnering role in the

service development and hence they lack the provisioning function of a manufacturing firm. Spath and

Demuß (2006) consider the organizational capabilities to realize customer-individual solutions that

arise in the transition from product to service business. However, they focus on design and mechanical

engineering issues. DIN PAS 1082 emphasizes the development phase of product-service systems in

networks, while the need to develop an innovative business model is only outlined. DIN PAS 1091

addresses component-based interface specifications for supporting controlling, sales and organization

but neglects the implications for business models. DIN PAS 1094 rather provides an overview and

remains on a very generic level. Summing up, although particular publications achieve a relatively

high coverage of R1, the average resides on a medium to high level (3.5).

The lowest coverage was achieved by the mobile solution requirement (R4). The IS requirements

specified by DIN PAS 1090 are based merely on a particular case study analysis and, hence, lack

validity (Thomas et al. 2007). Furthermore, the document does not address billing transactions, refers

to custom-built software for the service technicians of the construction industry and does not

incorporate the latest technological shifts such as cloud computing. The authors, hence, conclude with

a very low to low coverage (1.5) of the mobile solution requirement that is addressed in three articles.

Summing up, the analysis revealed that the majority of maturity models only partially address these

requirements, while the DIN specifications make up a broader set but remain very generic.

4.2 Synthesis

In view of the unsatisfactory coverage of the relevant requirements, the development of a new

maturity model is preferable to the evolution of an existing model. Nonetheless, our maturity model

adopts the well-established dimensions, elements, levels, and functions of the investigated maturity

models. We developed the maturity model in three iterations. In the first iteration, we defined the basic

characteristics and structure of the model. Drawing from popular maturity models such as the

capability maturity model (CMM) (Paulk et al. 1993), we conceptualized five levels: prepared,

engaged, established, managed and optimized. For structural purposes, we employed the dimensions

strategy, process and information systems (Österle 2010) to collect together the exploratory identified

requirements. Whilst the first iteration satisfies the need for relevance through the content analysis of

the case study reports, the second iteration ensures rigour by assessing the requirements against

existing models and standards. As a result, we integrated the elements of analytical objectives (based

on R1 & R2), installed base management (based on R3), mobile solutions (based on R4), data

integration (based on R5 & R6) and data quality (based on R6). The element data integration

addresses R5 implicitly, since e.g. [C.1.4] refers to “data integration with major business entities”. In

this light, the second iteration is concerned with the alignment and specification of the maturity model.

Confronted with the lack of coverage of the analyzed maturity levels, we extended the scope to the

DIN PAS to specify the maturity levels further. The third iteration, which refers to a focus group

analysis, yielded the element business model (R1) as well as the specifications for the installed base

management and mobile solution maturity levels. The focus group (comprising a senior researcher and

two case study participants) allowed us to slightly adapt and balance the model in terms of details and

wording. Finally, we consolidated the contributions of the discussion and aligned the model (Table 4).

Since it lies beyond the scope of this paper to describe all the maturity levels in detail, we focus on the

two extreme levels of the developed model. Level 1, product-service systems prepared, implies that, in

addition to the capital equipment goods, only rudimentary services such as spare parts sales are offered

[A1.1]. There are no key performance indicators (KPIs) in place [A.2.1]. Regarding the business

processes, neither an installed base management [B.1.1] nor a mobile solution [B.2.1] is adequately

covered in the IS landscape. The data necessary for the analytical functions and sophisticated business

processes are gathered on an ad hoc basis [C.1.1], while a consistent quality assurance has not been

implemented [C.2.1]. Forming a clear contrast to Level 1, Level 5, product-service systems optimized,

describes a customer-driven, highly integrated and real-time organization. Instead of managing

particular functions associated with the installed base, the firm extends the business model by

managing the entire customer operation [A.1.5]. In order to integrate the customer’s needs, the

organization gathers a balanced set of financial, non-financial and customer-oriented KPIs [A.2.5].

Efficient processing and velocity in managerial decision-making is ensured by permanent and real-

time monitoring of the customer’s operation [B.1.5]. Moreover, fully integrated mobile devices are

deployed for the service technicians’ use, allowing them to perform create, delete, update and insert

(CRUD) operations for the installed base management, to trigger billing transactions, and to access the

knowledge database [B.2.5]. These aforementioned business processes require substantial investments

into the information systems landscape. Data from the production and service divisions need to be

automatically integrated on a real-time basis [C.1.5]. However, efficiency and effectiveness in the

product-service system depend on consistent data quality (e.g. master data, operational data,

transaction data, and knowledge base data) encompassing vertical and horizontal reconciliation

[C.2.5]. Intermediate levels are designed to be clearly distinguishable, so that a higher level

corresponds to additionally offered features. In the mobile solution element, e.g., this translates into a

clear add-on criteria sequence. On Level 2, access to customer data is provided [B.2.2], on level 3 the

access extends to a knowledge database (including CADs, construction plans, experience reports, etc.)

[B.2.3] and on level 4, the system allows for automatic billing of the service provided [B.2.4].

Dimension Element Level 1 Level 2 Level 3 Level 4 Level 5

[A]

Str

ate

gy

[A.1

.]

Bu

sin

ess

mo

del

[A.1.1]

Rudimentary

spare parts

sales

[A.1.2]

In addition

to[A.1.1],

reactive

maintenance

[A.1.3]

In addition to

[A.1.2], predictive

maintenance

[A.1.4]

In addition to

[A.1.3],

performance

contracting

[A.1.5]

In addition to

[A.1.4],

managing the

customer’s

operations

[A.2

.]

An

aly

tica

l

ob

ject

ives

[A.2.1]

There are no

specific KPIs

in place

[A.2.2]

Focus on

financial KPIs

[A.2.3]

In addition to

[A.2.2], non-

financial KPIs are

added

[A.2.4] In addition

to [A.2.3],

financial and non-

financial KPIs are

balanced

[A.2.5] In

addition to

[A.2.4], KPIs are

adjusted

regularly to

customer needs

[B]

Pro

cess

[B.1

.]

Inst

all

ed b

ase

ma

na

gem

ent

[B.1.1]

No

coordinated

interaction

[B.1.2] Basic

electronic

reports are

exchanged

[B.1.3] In addition to

[B.1.2], remote calls

on machines are

supported

[B.1.4] In addition

to [B.1.3],

continuous

monitoring based

on sensory data is

established

[B.1.5] In

addition to

[B.1.4],

maintenance for

competing

brands is done

[B.2

.]

Mo

bil

e

solu

tio

n

[B.2.1]

No mobile

support

[B.2.2]

Access to

customer data

is provided

[B.2.3] In addition to

[B.2.2],

access to knowledge

database is provided

[B.2.4] In addition

to [B.2.3],

transactions of

billing are

provided

[B.2.5] In

addition to

[B.2.4], full

integration of

mobile devices

is given

[C]

Info

rma

tio

n

Sy

stem

s

[C.1

.]

Da

ta i

nte

grati

on

[C.1.1] Data

is collected

on an ad-hoc

basis without

an integrated

approach

[C.1.2] Data

collection is

done manually

with basic

integration

applications

[C.1.3] In addition to

[C.1.2], data

collection is partially

automated with

partial data

integration (e.g.

intranet-based web

tool)

[C.1.4] In addition

to [C.1.3], data

collection is fully

automated, data

integration with

major business

entities (e.g. MIS)

[C.1.5] Data

integration is

fully automated

and optimized as

real-time

integration for

the whole

enterprise

[C.2

.]

Da

ta q

ua

lity

[C.2.1] No

data quality

assurance in

place

[C.2.2]

Rudimentary

quality

assurance

(plausibility

checks)

[C.2.3] In addition to

[C.2.2], quality

assurance includes

horizontal integration

(e.g. between

product and service

division)

[C.2.4] In addition

to [C.2.3], quality

assurance involves

vertical integration

(e.g. between

operative &

analytical systems)

[C.2.5] In

addition to

[C.2.4], data

quality is part of

a continuous

improvement

process

Table 4. Maturity model for product-service systems (after iteration 3)

4.3 Evaluation

A substantial element of DSR is the evaluation step that demonstrates the “utility, quality, and efficacy

of a design artefact” (Hevner et al. 2004). To conform to these requirements, we followed a multi-

perspective approach. As previously outlined, maturity models are particular instances of reference

models. Hence, we employed the four evaluation perspectives of Frank (2006) to structure and

document our evaluation findings. Further, we conducted a focus group workshop with representatives

of four additional manufacturing companies in order to make a confirmatory investigation of the

maturity model (Tremblay et al. 2010). The focus group was asked about comprehensiveness, validity

in self-assessment and the capability of supporting the development of a roadmap. The results were

structured according to the aforementioned evaluation perspectives.

The economic perspective suggests an evaluation based on the criteria of cost, benefit, and

coordination. Cost and benefits have rarely been measured due to the lack of cases in which the model

has been applied. The model by itself does not generate direct benefits. However, it helps to align the

service initiatives of manufacturing firms by framing the analysis of the situation and outlining the

required activities for advancement in maturity. The maturity model can also foster inter-

organizational standardization, since it supports the establishment of a unified terminology that is

compatible with the DIN PAS and existing maturity models. Further, it provides a better

understanding of the requirements of product-service systems not only for the industry but also for

software vendors to allow them to develop standardized support tools. Since improvement activities

can be easily identified by analysing the capabilities at the next higher level, the maturity model was

found particularly useful as a foundation for the development of a preliminary roadmap serving as a

basis for investment decisions.

The deployment perspective is subject to understandability and appropriateness criteria that are

confirmed by the managerial practitioners. Applying the business engineering framework (Österle

2010) and the DIN PAS, they agreed that the model presents a holistic and integrated approach to

assessing and improving organizations that implement product-service systems. Moreover, it provides

the first insights into developing a reference model to map the functional requirements with the

appropriate IT support.

From an engineering perspective, the intended purpose of the maturity model (defining and

explaining) and the application domain (capital investment goods industry) are aligned with the

research approach. The requirements are mapped to the elements of the maturity model. The model

was confirmatory investigated in a focus group workshop with representatives of four additional

manufacturing companies (Tremblay et al. 2010). The two hour focus group workshop took place in

October 2012 and was made up of five managerial practitioners as participants (see profile in Table

5), a senior researcher as moderator, and a junior researcher as observer. The focus group was asked

about comprehensiveness, validity in self-assessment and the capability of supporting the development

of a roadmap. Summing up, the general reactions to the presented model were positive. The mix of

business-related and technical items supports the comprehensiveness of the model. Nonetheless, two

managerial practitioners criticized the absence of a human-centred dimension. In particular, they

argued for addressing factors such as skill or specialisation.

Regarding the self-assessment, all participants were able to position their organisation by applying the

maturity model. Most of the managers located their product-service systems between maturity levels 2

and 4 (see Table 6). As a result, the total average across all manufacturing companies was 2.6. The

individual elements of the maturity model varied between a maturity level of 1.8 and 3.3. [B.1]

“installed base management” turned out to be difficult to implement and hence achieved the lowest

average of 1.8. However, one managerial expert in the focus group positioned his company at level 4.

He justified that self-assessment level by stating that “today, we are able to remotely monitor the

installed base at the customers’ plants. Our solution continuously analyses the sensory data and

informs the service staff, when problems occur. By doing so, we are not only able to ensure an

immediate replacement of the correct defect product [one assembly line can be driven by dozens of

capital equipment goods], but also provide accurate predictions on the remaining lifetime. The

customer value lies in the reduced downtimes of production facilities. As a consequence our sales went

up, while the company saved money by streamlining and accelerating the service processes”. [C.1]

“data integration” had the highest average of 3.3. One of the focus group participants put this down to

the large data warehousing and business intelligence projects which had happened in recent years. In

this light, he outlined that “we realized that our databases contain much valuable information on the

products deployed at the customer's place when we consolidate our services and systems. By means of

combining pieces of data from several data warehouses, it is possible to find out which customer

possesses which product at which location.”

Company

[Industry]

Employees

> 10k

Turnover €

> 5 Billion Function of the participant

Number of

participants

THETA

[Industrial] -

Head of IT Services for Sales

Head of Customer Service 2

IOTA

[Industrial] - - Director of ERP Systems 1

KAPPA

[Industrial] CIO 1

LAMBDA

[Industrial] - Head of IT Strategy 1

Table 5. Profile of the focus group participants; numbers are based on the fiscal year 2010

The epistemological perspective is concerned with the scientific value and the fulfilment of scientific

requirements. The development of the maturity model uses a combination of numerous scientifically

accepted approaches. The literature review is based on an established literature review framework and

ensures sufficient coverage of the existing maturity models. The research methodology takes case

study research to explore the requirements, follows an established procedural model for the

development of maturity models that is embedded into the design science approach, and critically

evaluates the artifact in accordance with approved evaluation perspectives and approaches. The

contribution to the scientific body of knowledge comprises the application of the maturity model

approach to the IS support of product-service systems in the manufacturing industry. For managerial

practitioners, in turn, the contribution lies in the assessment of their organization and the identification

of capabilities that serve as levers for corporate improvement. Managers are able to draw a preliminary

roadmap to increase the performance of the product-service systems within their organizations

according to their individual requirements.

Dimension Element Level

Average 1 2 3 4 5

[A]

Strategy

[A.1] - #2 #1 #1 - 2.8

[A.2] - #3 #1 - - 2.3

[B]

Process

[B.1] #1 #2 - #1 - 1.8

[B.2] - #3 #1 - - 2.3

[C]

Information

System

[C.1] - - #3 #1 - 3.3

[C.2] - #2 #1 #1 - 2.8

Total 2.6

Table 6. Self-assessment of four manufacturing firms

5 CONCLUSION

This paper aims to develop a maturity model for the IS support of industrial product-related services.

Contrary to the traditional focus on customer value such as co-creation with customers in SSME, we

adopt the perspective of manufacturing firms offering an integrated product-service portfolio. The

maturity model can be used as a management instrument to analyze the current set-up in order to

determine the key levers for improvement. The overall goal is the reduction of the effort needed to

unleash the full potential of the product-service system and the corresponding information systems

support. Accordingly, this paper addresses this need by answering two RQs in line with the DSR

approach. The first part of this paper investigates “what maturity models are capable of holistically

assessing the IT support of product-service systems in the manufacturing industry” [RQ.1]. For that

reason, the authors conducted a multiple case study to elaborate key requirements which serve as a

reference baseline for investigating whether existing maturity models are capable of holistically

assessing the IT support of product-service systems in the manufacturing industry. Using a structured

literature review framework (vom Brocke et al. 2009), we analyzed the coverage of those requirements

in current managerial and scientific frameworks. The findings indicate that existing maturity models

and DIN PAS only partially address the exploratory identified requirements, and hence that none of

the models is capable of assessing the problem holistically. For that reason, the authors develop a

maturity model in the second part of this paper. The model and its evaluation address the second

research question “what could a product-service system specific maturity model targeting key

requirements of multinational manufacturing enterprises look like” [RQ.2]. The model we developed

is based on the structure of existing maturity models and inherits conceptualizations and

methodologies from extant literature in IS, operations management, marketing, and general

management. Consistent with the fundamental principle in DSR of addressing real-world problems

and simultaneously contributing to the scientific and practitioners’ body of knowledge, it was the

researchers’ aim to produce consumable results for literature scholars and managerial practitioners.

Moreover, the maturity model benefited from a multi-perspective evaluation according to a

scientifically well-accepted approach (Frank 2006). The focus group workshop outlines the model’s

capability in terms of comprehensiveness, validity in self-assessment and supporting the development

of a roadmap. In particular, the self-assessment then offers further insights into the current state of four

additional manufacturing companies. The model is differentiated from existing maturity models not

only through its holistic coverage of the requirements, but also through its exclusive focus in the IS

domain.

The case selection might be described as a possible limitation of the study presented. A generalization

of the results could be enhanced by examining more cases and more industries. The utilization of a

quantitative research design might help to validate the findings. Another limitation is the focus on

multinational German and Swiss companies. The requirements derived are influenced by the

multinational setting of the firms which have, for example, a strengthening effect on the global service

infrastructure requirement. Additionally, the success of knowledge management initiatives heavily

depends on the managerial ability to make customers and employees contribute (Kankanhalli et al.

2005). Future research can investigate the validity of the model for local firms. The maturity model

presents an important step in understanding to what extent manufacturing firms struggle with the IS

implementation of product-service systems and how they apply proprietary systems. Following this

line of argument, we posit the development of a functional reference model (mapping the functions

with the IS support) with the aim of forming building blocks and identifying the standardization

potential of existing solutions.

References

Ahern, D., Clouse, A. and Turner, R. (2004). CMMI distilled: a practical introduction to integrated

process improvement. 2nd Edition. Addison-Wesley Professional, Boston.

Alavi, M. (1984). An assessment of the prototyping approach to information systems development.

Communications of the ACM, 27 (6), 556-563.

Aurich, J., Fuchs, C. and Wagenknecht, C. (2006). Life cycle oriented design of technical Product-

Service Systems. Journal of Cleaner Production, 14 (17), 1480–1494.

Bardhan, I.R., Demirkan, H., Kannan, P., Kauffman, R.J. and Sougstad, R. (2010). An

interdisciplinary perspective on IT services management and service science. Journal of

Management Information Systems, 26 (4), 13–64.

Baskerville, R.L. and Myers, M.D. (2009). Fashion waves in information systems research and

practice. MIS Quarterly, 33 (4), 647-662.

Becker, J., Knackstedt, R. and Pöppelbuß, J. (2009). Developing maturity models for IT management.

Business & Information Systems Engineering, 1 (3), 213-222.

Becker, J., Knackstedt, R. and Pöppelbuß, J. (2010a). Vergleich von Reifegradmodellen für die

hybride Wertschöpfung und Entwicklungsperspektiven. In Proceedings of the Multikonferenz

Wirtschaftsinformatik, 415, Göttingen, Germany.

Becker, J., Niehaves, B., Poeppelbuss, J. and Simons, A. (2010b). Maturity models in IS research. In

Proceedings of the 18th European Conference on Information Systems, Pretoria, South Africa.

Becker, J., Beverungen, D., Knackstedt, R., Matzner, M. and Müller, O. (2011). Information Needs in

Service Systems - A Framework for Integrating Service and Manufacturing Business Processes. In

Proceedings of the 44th Hawaii International Conference on System Sciences (HICSS), 1–10,

Kauai, Hawaii.

Berkovich, M., Leimeister, J.M. and Krcmar, H. (2011). Requirements Engineering for Product

Service Systems. Business & Information Systems Engineering, 3 (6), 369–380.

Beverungen, D. (2011). Mapping the Emerging Field of Service Science: Insights from a Citation

Network and Cocitation Network Analysis. In Proceedings of the 32nd International Conference

on Information Systems (ICIS), Shanghai, China.

Chesbrough, H. and Spohrer, J. (2006). A research manifesto for services science. Communications of

the ACM, 49 (7), 35-40.

Clarke, R.J. and Nilsson, A. (2008). Business services as communication patterns: A work practice

approach for analyzing service encounters. IBM Systems Journal, 47 (1), 129-141.

Davies, A., Brady, T. and Hobday, M. (2006). Charting a path toward integrated solutions. MIT Sloan

Management Review, 47 (3), 39.

De Bruin, T., Freeze, R., Kaulkarni, U. and Rosemann, M. (2005). Understanding the main phases of

developing a maturity assessment model. In Proceedings of the Australasian Conference on

Information Systems (ACIS), Sydney, Australia.

Dietrich, B. (2006). Resource planning for business services. Communications of the ACM, 49 (7), 62–

64.

Dietrich, B., Paleologo, G.A. and Wynter, L. (2008). Revenue management in business services.

Production and Operations Management, 17 (4), 475–480.

Eisenhardt, K.M. (1989). Building Theories from Case Study Research. The Academy of Management

Review, 14 (4), 532-550.

Eisenhardt, K.M. and Graebner, M.E. (2007). Theory building from cases: Opportunities and

challenges. The Academy of Management Journal 50 (1), 25-32.

Frank, U. (2006) Evaluation of Reference Models. In Reference modeling for business systems

analysis, Fettke, P. and Loos, P.E., Eds. Idea Group Inc., Hershey, PA, pp. 118-139.

Fraser, P., Moultrie, J. and Gregory, M. (2002). The use of maturity models/grids as a tool in assessing

product development capability. In Proceedings of the IEEE International Engineering

Management Conference, Cambridge, UK, pp. 244-249.

German Standards Institute (DIN), Publicly Available Specification 1082: Standardized process for

the development of industrial services in networks. Beuth Verlag, Berlin, 2008.

German Standards Institute (DIN), Publicly Available Specification 1090: Information systems

requirements on collecting and providing relevant service information in the technical customer

processes. Beuth Verlag, Berlin, 2009a.

German Standards Institute (DIN), Publicly Available Specification 1094: Product-service systems –

Value creation by integrating goods and services. Beuth Verlag, Berlin, 2009b.

German Standards Institute (DIN), Publicly Available Specification 1091: Interface specifications for

the integration of manufacturing and service. Beuth Verlag, Berlin, 2010.

Glushko, R.J. and Tabas, L. (2009). Designing service systems by bridging the front stage and back

stage. Information Systems and e-Business Management, 7 (4), 407-427.

Goh, Y.M. and McMahon, C. (2009). Improving reuse of in-service information capture and feedback.

Journal of Manufacturing Technology Management, 20 (5), 626–639.

Günther, O., Ivantysynova, L., Rode, J. and Ziekow, H. (2009). IT Infrastructures in Manufacturing:

Insights from Seven Case Studies. In Proceedings of the 15th Americas Conference on Information

Systems (AMCIS), San Francisco, CA.

Herbsleb, J., Zubrow, D., Goldenson, D., Hayes, W. and Paulk, M. (1997). Software quality and the

capability maturity model. Communications of the ACM, 40 (6), 30-40.

Hevner, A., March, S., Park, J. and Ram, S. (2004). Design science in information systems research.

MIS Quarterly, 28 (1), 75–105.

Hildenbrand, K., Gebauer, H. and Fleisch, E. (2006). Strategische Ausrichtung des Servicegeschäfts in

produzierenden unternehmen. In Erfolgreich mit After Sales Services - Geschäftsstrategien für

Servicemanagement und Ersatzteillogistik, 1, Barkawi, K. et al., Eds. Springer, Heidelberg, pp. 73-

94.

Järvinen, P. (2007). On reviewing of results in design research. In Proceedings of the 15th European

Conference on Information Systems (ECIS), pp. 1388-1397, St. Gallen, Switzerland.

Kankanhalli, A., Tan, B. C. Y., and Wei, K. K. (2005). Contributing knowledge to electronic

knowledge repositories: An empirical investigation. MIS Quarterly, 29 (1), 113–143.

Maglio, P.P. and Spohrer, J. (2008). Fundamentals of service science. Journal of the Academy of

Marketing Science, 36 (1), 18–20.

Maglio, P.P., Vargo, S.L., Caswell, N. and Spohrer, J. (2009). The service system is the basic

abstraction of service science. Information Systems and e-Business Management, 7 (4), 395-406.

Metters, R. (2010). The Neglect of Service Science in the Operations Management Field. Handbook of

Service Science, 309–319.

Mettler, T., Rohner, P. and Winter, R. (2010) Towards a Classification of Maturity Models in

Information Systems. In Management of the Interconnected World, D'Atri, A., De Marco, M.,

Braccini, A.M. and Cabiddu, F., Eds. Physica-Verlag, Heidelberg, pp. 333-340.

Nägele, R. and Vossen, I. (2006) Erfolgsfaktor kundenorientiertes Service Engineering—

Fallstudienergebnisse zum Tertiarisierungsprozess und zur Integration des Kunden in die

Dienstleistungsentwicklung. In Service Engineering, vol. 2, Bullinger, H.J. and Scheer, A.-W., Eds.

Springer, Heidelberg, pp. 521-543.

Neely, A. (2008). Exploring the financial consequences of the servitization of manufacturing.

Operations Management Research, 1 (2), 103–118.

Neff, A.A., Herz, T.P., Uebernickel, F. and Brenner, W. (2012). The Influence of Information

Technology on Industrial Services in the Manufacturing Industry–A Literature Review and Future

Research Directions. In Proceedings of the 16th Pacific Asia Conference on Information Systems

(PACIS), Ho Chi Minh City, Vietnam.

OECD (2011). Services related occupations in manufacturing sectors 2000 and 2008. Science,

technology and industry scoreboard.

Oliva, R. and Kallenberg, R. (2003). Managing the transition from products to services. International

Journal of Service Industry Management, 14 (2), 160–172.

Österle, H. (2010). Business in the Information Age: Heading for New Processes. Springer, Berlin.

Paulk, M.C., Curtis, B., Chrissis, M.B. and Weber, C.V. (1993). Capability maturity model, version

1.1. Software, IEEE, 10 (4), 18-27.

Peffers, K., Tuunanen, T., Rothenberger, M.A. and Chatterjee, S. (2007). A design science research

methodology for information systems research. Journal of Management Information Systems, 24

(3), 45-77.

Pöppelbuß, J., Knackstedt, R. and Becker, J. (2009). Towards a Consolidated Concept of Maturity in

Providing Customer Solutions. In Proceedings of the International Symposium on Service Science

(ISSS), pp. 535-545, Leipzig, Germany.

Rai, A. and Sambamurthy, V. (2006). Editorial notes—the growth of interest in services management:

opportunities for information systems scholars. Information Systems Research, 17 (4), 327–331.

Rosemann, M. and De Bruin, T. (2005). Towards a Business Process Management Maturity Model. In

Proceedings of the 13th European Conference on Information Systems (ECIS), Regensburg,

Germany.

Sampson, S.E. and Froehle, C.M. (2006). Foundations and implications of a proposed unified services

theory. Production and Operations Management, 15 (2), 329–343.

Simpson, J.A. and Weiner, E.S.C. (1989). The Oxford English Dictionary 12. Oxford University Press,

Oxford, UK.

Spath, D. and Demuß, L. (2006) Entwicklung hybrider Produkte—Gestaltung materieller und

immaterieller Leistungsbündel, in Service Engineering, vol. 2, Bullinger, H. J. and Scheer, A.-W.,

Eds. Springer, Heidelberg, pp. 463-502.

Spohrer, J., Maglio, P. P., Bailey, J., and Gruhl, D. (2007). Steps toward a science of service systems.

Computer, 40 (1), 71–77.

Spohrer, J. and Kwan, S.K. (2009). Service Science, Management, Engineering, and Design

(SSMED): An Emerging Discipline - Outline & References. International Journal of Information

Systems in the Service Sector, 1 (3), 1–3.

Stille, F. (2003). Product-related Services–Still Growing in Importance. DIW Economic Bulletin, 40

(6), 195–200.

Strähle, O., Füllemann, M., and Bendig, O. (2012). Service now! Time to wake up the sleeping giant,

(Ed, Bain & Company).

Teboul, J. (2006). Service is front stage: positioning services for value advantage. Palgrave

Macmillan.

Thomas, O., Walter, P., Loos, P., Nüttgens, M. and Schlicker, M. (2007). Mobile technologies for

efficient service processes: a case study in the German machine and plant construction industry. In

Proceedings of the 13th Americas Conference on Information Systems (AMCIS), 09–12, Keystone,

CO.

Thomas, O., Walter, P. and Loos, P. (2008). Product-Service Systems: Konstruktion und Anwendung

einer Entwicklungsmethodik. Wirtschaftsinformatik, 50 (3), 208–219.

Tremblay, M.C., Hevner, A.R. and Berndt, D.J. (2010). Focus groups for artifact refinement and

evaluation in design research. Communications of the Association for Information Systems, 26 (27),

599-618.

Tuli, K.R., Kohli, A.K. and Bharadwaj, S.G. (2007). Rethinking customer solutions: From product

bundles to relational processes. Journal of Marketing, 71 (3), 1–17.

Urwiler, R. and Frolick, M.N. (2008). The IT value hierarchy: Using Maslow's hierarchy of needs as a

metaphor for gauging the maturity level of information technology use within competitive

organizations. Information Systems Management, 25 (1), 83-88.

Vargo, S.L. and Lusch, R.F. (2004). Evolving to a new dominant logic for marketing. Journal of

Marketing, 1–17.

vom Brocke, J. (2007). Design Principles for Reference Modeling-Reusing Information Models by

Means of Aggregation, Specialization, Instantiation, and Analogy. In Reference modeling for

business systems analysis, Fettke, P. and Loos, P.E., Eds. Idea Group Inc., Hershey, PA, pp. 47-75.

vom Brocke, J., Simons, A., Niehaves, B., Riemer, K., Plattfaut, R. and Cleven, A. (2009).

Reconstructing the giant: on the importance of rigour in documenting the literature search process.

In Proceedings of the 17th European Conference on Information Systems (ECIS), 1–13, Verona,

Italy.

Wölfl, A. (2005). The service economy in OECD countries. In OECD Science, Technology and

Industry Working Papers, 1–81.

Yin, R. (2009). Case study research: Design and methods. Sage Publications.