This article was downloaded by: [Istanbul Universitesi Kutuphane ve Dok]
On: 20 December 2014, At: 16:39
Publisher: Taylor & Francis
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,
37-41 Mortimer Street, London W1T 3JH, UK
International Journal of Production Research
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/tprs20
Collaboration networks and collaboration tools: a
match for SMEs?
a
b
a
a
Roula Michaelides , Susan C. Morton , Zenon Michaelides , Andy C. Lyons & Weisheng
Liu
a
a
Management School, University of Liverpool , Liverpool , UK
b
Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University ,
Loughborough , UK
Published online: 29 Aug 2012.
To cite this article: Roula Michaelides , Susan C. Morton , Zenon Michaelides , Andy C. Lyons & Weisheng Liu (2013)
Collaboration networks and collaboration tools: a match for SMEs?, International Journal of Production Research, 51:7,
2034-2048, DOI: 10.1080/00207543.2012.701778
To link to this article: http://dx.doi.org/10.1080/00207543.2012.701778
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained
in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no
representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the
Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and
are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and
should be independently verified with primary sources of information. Taylor and Francis shall not be liable for
any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever
or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of
the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic
reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any
form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://
www.tandfonline.com/page/terms-and-conditions
International Journal of Production Research, 2013
Vol. 51, No. 7, 2034–2048, http://dx.doi.org/10.1080/00207543.2012.701778
Collaboration networks and collaboration tools: a match for SMEs?
Roula Michaelidesa, Susan C. Mortonb*, Zenon Michaelidesa, Andy C. Lyonsa and Weisheng Liua
a
Management School, University of Liverpool, Liverpool, UK; bWolfson School of Mechanical and
Manufacturing Engineering, Loughborough University, Loughborough, UK
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
(Received 29 April 2012; final version received 4 June 2012)
Global patterns of industrial production have resulted in relocation of industrial operations groups in an
effort to create new markets for mass and customised mass production. The collaborative effort between these
dispersed teams increases the likelihood of combining ideas and knowledge in novel ways. Internet
technologies enable these virtual collaboration networks to seamlessly engage in discussions that demonstrate
a richness of perspectives when it comes to problem-solving and innovative idea-exchange. Indeed, knowledge
creation and harnessing collective knowledge are salient features of collaborative networks (CNs) and this is
witnessed by a new interest in these entities. However, small and medium enterprises (SMEs) display a
difficulty in partnering and collaborating in global networks, especially since their technological infrastructure
may be lacking. Given the widespread adoption of collaborative technologies in social contexts, this research
seeks to examine how such informal interactions are facilitated in SMEs through Web 2.0 tools. Specifically,
this paper seeks to contribute to existing literature by examining how Web 2.0 affects the collaborative effort
in two SME CNs; this study demonstrated that the collaboration effort is amplified when Web 2.0 tools are
available. Other parameters such as trust in other members’ ability; perception of usefulness; and
enhancement of collective knowledge are seen as supporting the CN mutuality. In addition, it brings
together the three diverse research areas of collaborative networks, internet collaborative tools and
psychological barriers and enablers.
Keywords: collaboration networks; collaborative technologies; knowledge flow; Web 2.0
1. Introduction
Collaborative networks (CNs) present a modern scientific discipline of organisations and individuals that, even
though they are geographically dispersed and have different strategic cultures and environments, come together and
interact through online tools in a network to achieve common goals (Picard and Rabelo 2010). These goals could be
problem solving, product development and innovation (Picard and Rabelo 2010).
In contemporary industry knowledge has become the force behind organisational change, with people as the
instruments accessing the wealth of available knowledge.
The objective of this research is to comparatively analyse the functioning of two diverse collaborative networks
(CNs) by examining how collaborative interaction is facilitated through Web 2.0 collaborative technologies.
Even though CNs are becoming more widely studied by researchers methods to evaluate how collaborative tools
impact on collaborators’ participation are lacking. This is due mainly to the fact that the concept of Web 2.0 tools is
usually seen in a social networking context, whilst it is still poorly defined in the organisational innovation area. So,
even though there is evidence of wide-use of these collaborative artefacts, particularly in larger firms, there are
limited discussions about knowledge flow and the use of collaborative tools and networks in SMEs. Narula (2004)
attributes this difficulty of SME partnering in collaborative networks, particularly with global collaborators, to the
inability of SMEs to access external resources and to having fewer technological assets that they can exchange than
do larger firms. This research seeks to address this gap and contribute to the discussions both from a technological
and a user participation perspective. This study contributes to the knowledge of CNs from both perspectives
by analysing the impact of collaborative Web 2.0 tools on collaborators’ participation in small and medium
enterprises (SMEs).
*Corresponding author. Email: s.c.morton@lboro.ac.uk
ß 2013 Taylor & Francis
2
International Journal of Production Research
2035
Thus, the main contribution of this paper is to provide a focus on collaboration artefacts/outcomes, knowledge
flow and collective knowledge in SMEs through comparative analysis undertaken to confirm the common factors
perceived prevalent from previous studies on electronic collaboration networks (eCNs), which due to space
constraints we refer to Michaelides et al. (2012) for proofs and more details. The current paper analyses the new
opportunities and addresses the impact of Web 2.0 technologies in terms of functioning of eCNs thus extending the
scope and dimensionality of collaborators’ participation.
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2. Literature review
2.1 Collaboration networks
Collaborative networks (CNs) are considered as an alliance of mostly autonomous geographically distributed
organisations and people that, although dissimilar in skills, culture and in how they operate, come together to
achieve a common goal and are facilitated in their collaboration by computer networks (Camarinha-Matos and
Afsarmanesh 2008). What differentiates a CN from other networks is the intentional property of collaboration to
achieve an outcome that would have not been possible otherwise, or that would have been at a much higher cost if
the collaborative network had not been used. However, collaboration technologies necessary to support the
increasingly complex nature of cross-organisational innovation have been convoluted. Distributed network
environments, networked manufacturing co-ordination and enterprise integration architectures all need highly
sophisticated skills (Cheung et al. 2008). In addition to these challenges, other issues such as the governance and coordination of the CN, the assignment of responsibilities and control and monitoring of collaborative efforts are
amplified in CNs. If unresolved, these difficulties can adversely affect costs, time management and cause detrimental
effects to network participation and organisational learning (Noori and Lee 2004).
In an effort to overcome such issues, theorists and practitioners have proposed various software infrastructures
(cf. Hill 2002, Zhang and Zhou 2004, Yujun et al. 2005). Most of those proposed, such as: video conferencing;
immersive virtual reality; and online application sharing, support the co-operation and communication effort
between collaborating companies, with the ultimate goal of making individual participation in CNs easy. This is
particularly relevant in SMEs where existing research suggests they can supplement their in-house capabilities by
seamlessly integrating with suppliers, customers, competitors and research organisations (Nieto and Santamarı́a
2007, Tsai 2009).
2.2 Web 2.0 contemporary collaborative technologies
Collaboration across organisational, cultural, time and geographical boundaries requires training, experience and
organisational support, necessitating the skilful use of synchronous and asynchronous Web 2.0 technologies and
communication channels (Pauleen and Yoong 2001), and the creation and maintenance of trust between all
collaborators (Ragatz et al. 1997). Even amongst competitors collaborative links have been seen as beneficial in
accessing specialised information or leveraging competitors’ network reach (Nieto and Santamaria 2007, Hackney
et al. 2008). As technology becomes more complex in the global economy and relevant knowledge becomes more
dispersed, collaboration between companies is seen as key to success. In consequence, the need to connect more
rapidly and more effectively with others through CNs, for extending in-house capabilities and problem solving, is
pivotal, particularly in SMEs. It follows, therefore, that connecting and actively participating is key in any
collaborating effort. Social interactions have been identified by Adamides and Karacapilidis (2006) as the most
essential element of the innovation and collaboration process; the objective of this work is to demonstrate that Web
2.0 technologies provide a collaborative infrastructure that encourages engagement of diverse specialist groups as
well as enhancing collective knowledge. It is the participation collaborative element that this research focuses upon
and frames the research questions below.
Not surprisingly, therefore, Internet technologies that facilitate high degrees of user interaction, as observed in
popular Web 2.0 applications such as Facebook, Twitter, Wikipedia, LinkedIn, YouTube, Flickr and Del.icio.us,
have received scholarly as well as business attention. In particular, the interactive and informal nature of Web 2.0
applications and the resulting willingness of the user to become a co-developer in new product development and
knowledge creation have marked a change in roles traditionally held by developers and users (Prahalad and
Ramaswamy 2000). In an attempt to harness the tacit knowledge and specialist skills of users in CNs many large
companies have adopted such collaborative Internet technologies making them mainstream.
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2036
R. Michaelides et al.
The Forrester Group (2008) forecast that the Web 2.0 market will continue to grow strongly: to reach $4.6
billion by 2013. The prevalence of Web 2.0 is further supported by the Time (2010) report where the highest ranked
websites in 2010 are underpinned by Web 2.0.
O’Reilly (2006) defines Web 2.0 as ‘the business revolution in the computer industry caused by the move to the
Internet as platform, used to build applications that harness network effects to get better the more people use them’.
In essence O’Reilly (2006) initiated a discussion on the next generation Internet based on an open ‘architecture of
participation’. More recently O’Reilly and Battelle (2009) refined their position by stating that one of the
fundamental ideas underlying Web 2.0 is the ability to enable applications to ‘harness collective knowledge’. In
other words, Web 2.0 can enable a large networked group of people to create collective work whose value far
exceeds that provided by any one of the individual participants (O’Reilly and Battelle 2009). Subsequently, the
boundaries between information providers and receivers have become blurred and knowledge becomes
‘decentralised, accessible and co-constructed among a broad range of users’ (Greenhow et al. 2009). Bughin et al.
(2009) propose that Web 2.0 attractiveness is due to the rising popularity of user-driven social networks and
highlight collaboration as the main benefit of these tools. Other business benefits of Web 2.0 include: lightweight
user interfaces; open source availability of code, thus lowering costs; rich information/product-sharing through
tagging; easy sharing and exchange of views that leads to better quality of social interaction; provision of a new form
of dialogue between users; help to collect information, to pick up trends, and to interact with customers and the
public; and enable the exploitation of user-generated content (Flavian and Guinaliu 2005, Abrams 2006, O’Reilly
2006, Petersen 2008, Bughin et al. 2009)
This paper looks at how such collaborative interactions in the professional environments are facilitated through
Web 2.0 technologies in SMEs.
Although previous studies have shown strong relationships between availability of Web 2.0 technologies and
user engagement (O’Reilly 2006, Bughin and Manyika 2007, Harrison and Barthel 2009, Michaelides et al. 2012),
this relationship is difficult to measure. Also, a common criticism of research on collaborative networks is the lack
of extended empirical analysis in professional environments. The literature review highlights that the tendency
towards adopting Web 2.0 technologies in business environments for collaborative innovation practices has been
mainly a result of large user adoption observed in social networks. Their flattened structures, empowered roles of
users, collaborative networks and user participation, plus access to contextualised information exhibit what is
increasingly required by modern organisations (Schneckenberg 2009). This leads to the following research questions:
Q1
Q2
Q3
What factors influence collaborators’ participation in electronic CNs (eCNs)?
Does the availability of Web 2.0 lead to increased collaborators’ participation in eCNs?
Does collaborators’ participation positively affect knowledge flow and eCN collective
knowledge?
We address these questions by analysing two cases of eCNs, focusing on collaborators’ participation, knowledge
flow and collective knowledge.
3. Research design
This research seeks to extend the work on evaluating the impact of collaborative tools in enhancing collaboration in
CNs. Towards this end a survey tool that has been developed and tested in previous work (Michaelides et al. 2012) is
seen as a valid evaluation tool for use in the current study; the survey development process is briefly introduced in
Section 6.2. This tool is now further validated in the current study, employing different empirical data sets in a new
case study with an SME focus.
The research motivation, therefore, is to extend the scope of the evaluation of impact of Web 2.0 tools into the
SME environment. The detailed evaluation tool development process can be reviewed in Michaelides et al. (2012)
and the methodological process of the survey development will not be repeated nor discussed further here. The
research design followed in this paper initially involved a systematic review of studies in the context of collaborative
networks, Web 2.0 and collaborators’ participation and key characteristics of eCNs proposed by theory emerge.
Research questions are then formulated following the theory review and hypotheses development initiated. A
connection to empirical cases is then sought to qualitatively confirm the theory findings; through interviews,
workshops and observations in real life settings. The eCN characteristics emerging from study of both Case Study 1
(CS1) and Case Study 2 (CS2) are compared to theory and the research hypotheses derived earlier from theory
International Journal of Production Research
2037
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
are re-affirmed. The impact of Web 2.0 tools in facilitating user participation, which in turn affects collaboration
success, is investigated with the use of the evaluation survey tool described earlier (Michaelides et al. 2012).
4. Hypotheses development
In order to evaluate the success of CNs, Parung and Bititci (2008) propose the following metrics: input to the
collaboration seen as the contribution of each participant; mechanism of the collaboration; and output of the
collaboration. Expanding upon the previous literature discussion and in agreement with Parung and Bititci (2008),
we propose that collaborators’ contribution is the key feature of eCNs, seamlessly enabling diverse user groups to
synthesise different perspectives and cross-disciplinary ideas. This interaction between collaborators is complex and
describes not only how often a collaborator engages with the eCN, but the level at which that engagement takes
place; the nature of that engagement; and its contribution. Collaborators’ participation is key to success and
sustainability of an eCN in a similar way that user adoption is essential when a new system is implemented in large
engineering, production, manufacturing and services environments. If workers do not accept, adopt and actively use
a new system then the implementation will fail. Similarly an electronic collaboration network implementation will
fail if organisation staff do not accept, use and actively participate. The technology acceptance model (TAM)
together with IS success models are well established in the IS literature (Rogers 1983, Davis et al. 1989, DeLeon and
McLean 1992), and propose adoption constructs such as: perceived usefulness; system complexity; and network
compatibility, all of which have been extensively used and tested in literature. In this study the operationalisation of
variables adopts the theoretical constructs found in the IS literature. The dependent variable here is the
collaborators’ participation, measured by the frequency of engagement and the contribution made. The following
sections look at how these Information System (IS) theory constructs are interpreted to eCN variables and
influenced hypotheses formulation.
4.1 Perceived usefulness of CN membership
Previous studies have established that people will adopt and use a system if they find it useful (Rogers 1983, Davis
et al. 1989, DeLeon and McLean 1992). In the context of eCNs, perceived usefulness refers to the benefits
collaborators see as resulting from participation in online network activities; these can span from access to
governmental/industry/sector information and policies to furthering partnerships in professional specialist
networks. SMEs will encourage their workers to join and actively participate in specialist eCNs only if the benefits
seen, such as collective expertise and information exchanged, is relevant to their applied field of knowledge (Sharrat
and Usoro 2003, Wasko and Faraj 2005, Ma and Agarwal 2007). We therefore propose the following:
H1: Perceived usefulness of eCN membership positively impacts on collaborators’ participation
4.2 System complexity
Another established construct from the IS success models is ‘ease of use’, proposed here as ‘system complexity’. This
construct expresses difficulty of network use, barriers and enablers to use and limitations and factors affecting
collaborators participation. For the eCNs environment this construct is construed as the complexity of the
communication platform itself. As all communications between collaborators occur virtually, a convoluted eCN
deployment would impact upon collaborators’ ease of interaction and participation in network activities (cited in
Yates and Orlikowski 1992, Fulk 1993, Ma and Agarwal 2007). We therefore put forward the following proposition:
H2: Perceived complexity of the network negatively impacts on collaborators’ participation
4.3 Network compatibility
It is well documented that conflicts within eCNs can be a result of different organisational values, priorities and
different perceptions of what the collaborative outcomes are (Macedo et al. 2010). Consequently, having an eCN
that has a governance structure displaying synergies in principles, priorities, needs and practices and processes
across the collaborators is important. From an organisational perspective, this is particularly relevant to SMEs as
2038
R. Michaelides et al.
the need to connect with others, due to limited resources, is amplified in an attempt to have access to a varied
expertise base.
Therefore this study hypothesises:
H3: Perceived compatibility of the network positively impacts on collaborators’ participation
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
4.4 Collaboration outcomes/artefacts
While previous studies suggest that collaborating in a network with different partners improves product innovation
(e.g. Belderbos et al. 2004, Nieto and Santamarı́a 2007) and absorptive capability, there has been no study on the
impact of Web 2.0 technologies on eCNs in SMEs. This relates to collaboration outcomes in terms of increased
knowledge flow and efficiency gains due to access to collective knowledge. Collective knowledge is evident in online
networks as participants demonstrate a ‘diversified knowledge-base’ with a variety of professional expertise, which
means that the absorptive capacity of an online network may surpass that of the sum of the individuals involved
(Cohen and Levinthal 1990). This is of great importance to SMEs due to their size limitations and the increased need
for ‘multiple technological competences’ in product development (Narula 2004). It is of little or no surprise to see
that collaboration and networking has moved from simply being a peripheral wish in these companies to becoming
an emergent strategy in many SMEs. For SMEs, connecting and accessing external skills/expertise pools reduces
risks and enhances collective learning. Thus, it is hypothesised that:
H4: Collaborators’ participation positively impacts on collaboration outcomes, in terms of knowledge flow, and efficiency
gains due to collective knowledge
4.5 Web 2.0 tools
Enabling new, easy and informal ways for members to locate and network with other useful members in an eCN is
key to communication and collaboration success (Adebanjo and Michaelides 2010). Web 2.0 tools are modern
communication tools that offer ease of navigation, structured interfaces, website reliability (Zhang 2010) and, more
importantly, enable applications to harness collective user intelligence (O’Reilly and Battelle 2009). Amongst many
authors, in his extensive analysis Vossen (2011) argues that Web 2.0 is not simply a ‘buzzword’ but demonstrates
four core development dimensions that have resulted in a new Internet: enhanced net infrastructure, advances in
programming, rich interactive functionality, large data collections, and user participation as well as socialisation. As
Vossen (2011) argues this fourth dimension of Web 2.0, socialisation, ‘is the idea of taking software or even usergenerated content and sharing or jointly using it with others’.
Thus Web 2.0 enables users to be pro-active, to freely exchange ideas, and to collect information in a contextual
and intelligent manner. In this way collaborative innovation is driven by these new modern Internet technologies
(Baldwin and von Hippel 2009). Therefore, we propose that:
H5: Web 2.0 tools
H5.1: Availability of Web 2.0 tools positively impacts on collaborators’ participation
H5.2: Availability of Web 2.0 tools negatively impacts on complexity of the e-network
Figure 1 provides an overview showing the linkages between: the collaboration outcomes/artefacts; the
characteristics of collaboration networks; the constructs; and the hypotheses generated.
5. eCN case studies
The importance of suitable case choice was highlighted by Done et al. (2010), in terms of selecting appropriate
research settings that would provide the best opportunities to learn and extend theory. With this in mind, the two
cases selected in this study both exhibit eCNs with wide collaborative reach amongst SMEs.
5.1 CS1 – European knowledge transfer eCN
CS1 is a European wide eCN and innovation marketplace that brings together SMEs and public research
organisations (PROs) from 11 European regions, to facilitate and extend collaboration between members. CS1 is
2039
International Journal of Production Research
Collaboration nets characteristics
Collaboration
outcomes/
artefacts
H1
+
H4
+
Collaborators
participation
−
Perceived usefulness
H2
Complexity
+
+
H3
Collective
knowledge
Compatibility
−
H5.2
H5.1
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
Knowledge flow
Web 2.0 availability
Figure 1. Research hypotheses.
Public Research Organisations (PROs)
Software technologies, enterprise software,
content management systems, home
networking, data mining, data centres
Hardware technologies, nanotech and
microelectronics, sensors, storage, imagery,
instrumentation, new materials
SME
sectors
Healthcare and medical technologies,
nanotech, services, diagnostics, therapies
etc.
Green and white biotech, agro-food,
environmental and energy technologies,
industrial applications, …
Agrofoods
Healthcare
Converging
techniques
Tourism/
media/comms
Energy
European technology transfer collaborative network−engineering competitive innovation
Figure 2. CS1
European technology transfer collaborative network.
funded by the EU and, as such, integrates with innovation relay centres (IRCs); European networks providing
transnational technology services to SMEs. An overview of the collaborative network is shown in Figure 2.
One of the differentiating features of CS1 is the provision of dense collaborative linkages not only between PROs
and industry, but also incorporating linkages to venture capitalists as well. It has been well established that
collaboration with research organisations enables a company to access scientific knowledge previously unexplored
(Tsai 2009).
This is a topical case study. In Europe, industry faces the challenge not only of remaining competitive in
traditional sectors but of becoming leaders in new market environments. With the new European Growth agenda,
coined EU2020, particular emphasis is placed on the way research findings and innovation are transferred to
relevant European industrial sectors to encourage growth (EU Commission 2010). Europe as a whole is lagging
behind Japan and the USA in innovation and in research and development (R&D). With a specific focus on
business, R&D in the EU is 66% lower than the US and 122% lower than Japan, as a share of GDP; venture capital
investments are 64% lower than the US; and the share of population completing tertiary education is 69% lower
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2040
R. Michaelides et al.
than the US and 76% lower than Japan (EU Commission 2010). This gap can be largely explained by the superior
US performance in early-stage venture capital availability, high levels of connectedness between companies, share of
population with tertiary education and number of US patents (ProInno Europe 2006). Research activities within
Europe are mainly centred on Universities and large non-European firms. What this means for SMEs is that the
cutting edge research and support universities offer industrial firms, in the guises of offering advice, research
contacts or even ideas that can help firms to identify and incorporate valuable external knowledge into their
innovation processes, tends only to be accessed by large companies (Mowery et al. 2001). On average, only 13% of
small firms collaborate with European R&D and innovation infrastructures (Innovation/SMEs 2001). Europe’s
competitive advantage is decreasing which indicates that knowledge and technology transfer is currently not
working in an optimum fashion.
The Advisory Unit of the European Investment Fund (EIF 2007) cites lack of critical mass and fragmentation as
key reasons for the breakdown of knowledge transfer from PROs to SMEs in Europe. Adding to the problem is the
widespread limited financial capacity and lack of resources of SMEs constraining their innovation and collaboration
activities. This is evident from a study conducted for the European Association of Biotechnology (EuropaBio/
Critical I 2006) which concluded that, even though Europe and the US have the same number of biotechnology
companies, ‘the US industry employs twice as many people, spends almost 3 times as much on R&D, raises 3 or 4
times as much venture capital and has access to 4 times as much debt finance’.
SMEs perceive the current technology and knowledge transfer procedures as too cumbersome, too bureaucratic
or driven by academia. Even when SMEs find possible partners, they tend to have a poor understanding of practical
issues involved with collaborative partnerships from other countries and regions. This is in line with the research
findings on ‘absorptive capacity’ introduced by Cohen and Levinthal (1989, 1990), where a firm’s ability to apply
university research for its own commercial gain is a function of its investment in R&D. Lim (2000) takes this
argument further by stating that a firm’s absorptive capacity is primarily a function of its connectedness which is a
critical element required in order to create a successful collaborative project.
CS1 is thus an eCN set up to develop European SME partnerships and increase access to venture capital via
online collaboration and company matching. Another aim of this eCN is to enable access to continuously updated
market intelligence, research and analysis, business and technical information. Sustained competitiveness in the
global economy depends on technological innovations such as a firm’s ability to apply new technologies, develop
new products, access new markets effectively and incorporate best practice in enterprise management (Jones-Evans
et al. 1999).
Existing European initiatives focus on partnering via traditional matchmaking processes in a passive way (i.e.
face-to-face meetings at events). Interested parties make contacts through these events but there is essentially no
efficient and simple way of finding partners that are tailored to the interested parties’ needs. With the introduction
of the online platform virtual linkages as well as physical face-to-face connections are enabled. Thus viewing
attendee companies’ profiles before these events enables targeted connections to occur.
5.2 CS2 – UK engineering knowledge transfer eCN
CS2 is one of a number of specialist-related networks in the UK and aims to benefit a large section of UK industry
by harnessing the academic strengths of leading universities and industrial and technology transfer expertise, and to
address the needs of companies active in the design and manufacture of complex products in its specific field. It has
a strong manufacturing focus, which is of interest here; Barnett et al. (2009) have stated that this specific sector faces
several challenges in terms of knowledge, experience and ‘skills’ management. These challenges include an ageing
workforce, highly mobile and dispersed workers and compressed development times across all engineering
industries. Registration to CS2 is free, albeit in exchange for basic information such as professional affiliation,
county and country, personal/professional interests and personal profile visibility preference. Membership resides at
around 2500 people, with the majority using it to gain access to information published by the CN host.
6. Methodology and research development
6.1 Case studies
As the objective of this current research was to understand the complex impact that Web 2.0 tools have on
collaborators’ participation, a qualitative research method was utilised. The research methodology employed is case
International Journal of Production Research
2041
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
study based utilising two case studies; in line with Yin (2009), observations having more than one case study
amplifies the analytic benefits of empirical research. Hartley (2004) also highlights the advantage of multi-case study
research in identifying contrasts and similarities between different cases. The suitability of case study research in
areas of online networks has been extensively used and well noted (Gongla and Rizzuto 2001, Adebanjo and
Michaelides 2010, Michaelides et al. 2012). The case study approach enables the researcher to work within real-life
case settings thus facilitating in-depth understanding of user behaviour and identification of factors affecting online
participation within actual organisational settings. Consequently, relevant theory building occurs following these
detailed observations (Benbasat et al. 1987). Case study research is also particularly suitable for developing new
theory and ideas and can be used for theory testing and refinement (Voss et al. 2002).
For Done et al. (2010) it is particularly important that case selection provides the best opportunities to learn and
extend theory. To address this, both cases chosen demonstrated similar collaborative challenges:
.
.
.
.
.
geographic disparity;
poor communication structures;
information mismatch from disparate databases and legacy systems;
poor visibility of information hindering work co-ordination;
and complex user relationships.
The cases were selected as they presented ready access to data but, more importantly, due to their nature and
scope. CS1 is a leading EU wide eCN with European outreach to SMEs, PROs and venture capitalists. CS2 is one of
the largest engineering networks of SMEs in the UK.
Specific case evidence was sought on the characteristics of each eCN to validate the theory findings used in the
hypotheses development; evidence such as user behaviour (frequency and extent of engagement), eCN usefulness,
ease of access and use, compatibility and availability of Web 2.0 tools were specifically targeted. Interviews were
conducted with the network managers (NMs) and members during European networking events held in the UK,
Belgium and Greece. Visit observations of both networks activities were used to supplement the data collection
effort. Finally, follow-up validation workshops were run with the NMs, involving a small number of users.
The resultant information from the empirical case work undertaken here was used to validate our assumption
that the theoretical IS emergent constructs collaborators’ participation; perceived usefulness; complexity;
compatibility; Web 2.0 availability and collaboration outcomes are indeed aligned with eCN characteristics. The
specific inter-relationships between these constructs and collaborators’ participation were investigated with the use
of a survey, which is detailed in the next section.
6.2 Survey development
As identified in Section 3, the motivation for this research is to further advance the previously developed survey
evaluation tool by testing it in a new empirical setting with an SME focus (Michaelides et al. 2012). The qualitative
process followed to develop the survey instrument, detailed in the study of Michaelides et al. (2012), consists of two
stages: survey content validity confirmation and testing for construct validity. Interviews with differing user groups
of the two eCNs were used to confirm survey validity. As the views and issues relating to collaborators’ participation
in both case studies converged, the survey content was deemed valid. Moreover, these issues aligned well with the
constructs adopted from IS theory. Construct validity was sought to ensure that the survey parameters used in the
evaluation tool were well defined, clear and comprehensive. To ascertain this, the advanced user group members of
the NMs were asked to give their own understanding of the constructs by defining them in their own words. These
results closely aligned with the intended definitions of the proposed constructs, thus supporting their validation.
Once the validity of the survey was qualitatively established the survey was implemented across all members of CS1,
which was selected as the research setting for use of the survey instrument due to its large SME member base and its
European reach. The research hypotheses described in Section 3 were tested by analysing data collected from the
CS1 members through (i) the web-based survey and (ii) survey data collection during a face-to-face event. Online
surveys demonstrate strong advantages over paper-based questionnaires such as lower costs, faster responses, and
reaching a sample that is not geographically restricted (Tan and Teo 2000). However, several scholars have
highlighted the low response rates of online surveys (Cook et al. 2000, Sheehan 2001). To avoid low response rates,
the online survey data were complemented by a paper-based survey that was distributed and collected during one of
the largest networking events that took place in the North of England.
2042
R. Michaelides et al.
7. Findings
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
7.1 Interviews
Based on the interviews with the NMs, issues were identified that formed the basis of the survey. Further
information gathered from attendees of networking events, user interviews, on-field investigation of network
facilities and informal validation workshops resulted in a comparative summary of the two CNs, shown in Table 1.
Both eCNs required initial user registration and membership was audited by the relevant NM, ensuring that
member information was valid and content reliable. This, in turn, enhanced trust within the network as well as the
security and confidentiality of information shared. However, the membership approval process between the two
case studies varied in rigour. CS1 registration required detailed company financial information, which was due to
the opportunity it generated for finance matching with venture capitalists. CS2 adopted a more open model where
basic information was required for registration. Even though this simple registration process encouraged a large
number of users to register, the lack of detailed profiling information meant that participation and trust was
reduced.
Real-time conversations and synchronous idea generation were enabled in both cases through web-conferencing
software such as AccessGrid and Interwise. Access to information, such as the technology reports published by the
UK Technology Strategy Board (TSB), was facilitated in CS2, providing organisational connectivity, information
aggregation and access to updated sector specific news. Varying Web 2.0 functionalities were included in both eCNs,
primarily facilitating: content contribution; discussion structuring; specialist expert groupings through expertise,
skills and experience profiles; sharing of documents; whiteboards for brainstorming; shared calendar of events;
embedded email; and chat tools. More advanced Web 2.0, such as dynamic web linking, content syndication,
managing communications message-centre across members’ unique communities and inviting colleagues to
knowledge communities and team rooms were also included in both networks. An interesting functionality,
incorporated in CS1 to facilitate increased company connectivity, is a smart social network facility, known as
‘radar’, enabling connections by automatically sifting through large data sets to instantly and visually match
companies and people with shared interests. CS1 encourages users to indicate their subjects of interest, expertise and
the type of collaboration sought thus creating a large dataset of companies and the potential for information
matching. Furthermore, the state of a product developed was captured in the company profile as being in ‘concept
stage’, ‘prototype developed’, ‘tested product’, and ‘ready to go to market’, thus providing an easy indication of
product ‘readiness’ for investment by venture capitalists. Another unique feature of the eCN was to offer
Table 1. Comparative analysis of the two case studies.
Case
Lead organisation
Primary Focus
CN Sectors
Network reach
Membership
Web 2.0 functionality
Membership approval process
Collaboration events
Collaboration activities and
information direction
CS1
EU funding
Matching SMEs with public research
organisations to solve specific
technology/scientific issues and
match funding with venture
capitalists
SMEs: engineering/IT/biotech
PRO/Universities
Venture capitalists
Patent and KT professionals
EU
1600
Extensive
Yes – members had to provide
extensive company data to be able
to join
Virtual as well as face-to-face
Mostly inside-out; user centred
content
CS2
UK public funding
Access to knowledge repositories
relating to manufacturing and
engineering
Engineering
Specialist engineering network –
technology transfer initiative
2500
Large but not extensive
No – open network to all who wanted
to register
Virtual
Mostly outside-in; most content disseminated from network managers
and organisers
2043
International Journal of Production Research
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
networking face-to-face events to complement virtual matching and connectedness. This resulted in strengthened
collaborative bonds in line with the findings of Stuckey and Smith (2004) and Koh et al. (2007).
7.2 Survey analysis
This paper reports on a comprehensive survey of practitioners in CS1, aimed at obtaining information as to how
they engage and interact with the eCN. The surveyed sample covers people with a wide range of positions,
experiences and expertise who have substantial participation in and, importantly, interaction with the collaborative
network. The survey was live online for a period of one month and conducted through a well-known free web survey
engine. An introductory email including the online survey web-link was sent to all members from the network
manager. The email explained the purpose and identified the timeframe of the research. Raw data were collected
with demographic data at strategic points. A total of 67 responses were collected, among which 14 responses had
multiple missing values. These responses were excluded from further analysis; hence 53 responses were regarded
valid. All valid respondents have membership of the CS1 network. The majority of respondents have experience in
using online social networks (79%). The demographic profile of respondents is displayed in Table 2.
Considering the developed hypotheses in this research require an explicit description of relationships among
variables, the multiple linear regression was utilised to achieve this requirement, on the basis of preliminary analyses
which aimed to check the conformability to Pearson Correlation’s assumption of normality linearity and homoscedasticity, as shown in Table 3.
The results of multiple linear regression are shown in Table 4, using two elements associated with collaborators
participation as dependent variables and five key elements defined before as explanatory variables. Collaborators’
participation is seen as a complex parameter consisting of two elements quantifying both the frequency of
Table 2. Demographic profile of respondents.
Organisation type
Years of using internet
Career
Frequency
Percent
10
20
8
15
6
23
21
3
17
18
8
10
18.87
37.74
15.09
28.30
11.32
43.40
39.62
5.66
32.08
33.96
15.09
18.87
Academic
Industry – SMEs
Industry – Large companies
Other
Less than 1 year
1 to 5 years
6 to 10 years
11 to 15 years
Engineer
Researcher
Consultant
General management
Table 3. Correlation matrix of the variables included.
P.Use
Cmplx
Comp
Web 2.0
Coll Knwldg
Cp-t
Cp-f
P.Use
Cmplx
Comp
Web 2.0
Coll Knwldg
1.000
0.117
0.319
0.277
0.234
0.183
0.201
1.000
0.159
0.248
0.178
0.236
0.029
1.000
0.312
0.116
0.214
0.238
1.000
0.112
0.458
0.138
1.000
0.201
0.346
Cp-t
Cp-f
1.000
0.216
1.000
Notes: P.Use, perceived usefulness; Cmplx, complexity; Comp, compatibility; Web 2.0, availability of Web 2.0; Coll Knwldg,
collective knowledge; Cp-t, collaborators participation – active contribution; Cp-f, collaborators participation – frequency
correlation coefficients significant at the 0.05 level: displayed in bold.
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2044
R. Michaelides et al.
collaborators’ participation (Cp-f) as well as active participation and contribution (Cp-t). This means that time
spent on each value activity is also evaluated as collaborators’ participation. The results indicate that the hypotheses
are supported. That is to say, collaborators’ participation is positively associated with the perceived usefulness
parameter, compatibility, availability of Web 2.0 and increasing efficiency. In contrast, the complexity parameter
indicates a negative relationship with collaborators’ participation.
Unsurprisingly, from Table 4 it can be seen from the findings that there is a positive association between
collaborators’ participation and perceived value (0.465 and 0.521), which means that Hypothesis 1 is supported
through our research.
As expected, the frequency that users engage with the innovation network is negatively associated with
complexity of network system ( 0.239). The time users spent on active engagement and contribution to the virtual
network is also negatively associated with system complexity ( 0.613). This result revealed that complexity of
network systems may ‘force’ users to spend less time actively contributing ideas (Table 4). Thus, Hypothesis 2 is also
supported.
Another anticipated outcome was that users will actively engage with a collaboration network if this
demonstrates compatibility with existing organisational practices and current technological platforms. There is a
positive association between compatibility and frequency of collaborators’ participation (0.238) and active
engagement with contribution to the virtual network (0.569). These results (detailed in Table 4) show that
Hypothesis 3 is supported.
Another interesting finding is that innovation through knowledge flow and collective knowledge is strongly
linked with collaborators’ participation. In line with conclusions from Tickle et al. (2011), our findings indicate that
content generated by collaborators in eCNs are more relevant and increases users interaction and sustainability of
the eCN through high returns. Member-generated content resulted in a more active, open, trusting interactive eCN
and users would engage more. Table 4 also demonstrates that collaborators’ participation has positive association,
0.036 and 0.098 respectively, with the increased efficiency by using collective knowledge. Thus Hypothesis 4 is also
supported.
In terms of the Web 2.0 collaboration technologies and their impact on collaborators’ participation, the findings
here support the positive correlation in the hypotheses. As shown in Table 4, the availability of Web 2.0 tools
positively impacts the frequency of collaborators’ participation (value of 0.413), as well as the time a user spends on
active engagement and content contribution (value of 0.218). In addition, the availability of Web 2.0 tools makes an
e-collaboration network less complex and difficult to navigate. As there is a negative association with system
complexity, Hypothesis 5 is also supported.
In terms of individual Web 2.0 functionalities and their usefulness, the highest ranked was the social matching
radar tool. Also, tagging was seen as particularly useful to actively organise and create own knowledge, illustrating
the importance of metadata. The interactions and relationships between collaborators’ participation and its
determinant eCN characteristics, together with the relation between knowledge flow, collective knowledge and
collaborators’ participation are also illustrated in Table 4.
Table 4. Analysis of relationship between collaborators’ participation and key elements:MLS.
Collaborators
participation:
time and active
contribution
Constant
Perceived value
Complexity
Compatibility
Availability of Web 2.0
Increases efficiency by using collective knowledge
R2
Adjusted R2
Notes: **P 5 0.5; ***P 5 0.01.
3.412***
0.465**
0.613***
0.569**
0.218**
0.098**
0.420
0.014
Collaborators
participation:
frequency
2.447***
0.521***
0.239**
0.238***
0.413***
0.036**
0.564
0.021
International Journal of Production Research
2045
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
8. Discussion
This paper investigates the use of Web 2.0 in electronic collaborative networks. The research has synthesised IS
theories to develop a set of virtual collaborators network variables that impact on collaborators’ participation. The
case studies provided validity to the proposed research hypotheses. One of the key findings is that having an
advanced technology platform with modern communication and collaboration tools is not, in itself, sufficient to
enhance collaborators’ participation.
Going beyond the technological aspect, Web 2.0 tools provide a new shift in collaborative networks in that the
control, creation and development of knowledge is seen as flowing inside-out (user-generated content). This is in line
with the findings of Bughin and Chui (2011) who concluded that successful networked companies show high levels
of Web 2.0 adoption and usage combined with new ways in how they operate and in their structure. These
companies build interaction and collaboration into workers daily activities rather than making participation an
additional duty. Thus ‘employees are much more likely to share information, while its flow throughout the company
is far less likely to be hierarchical; decisions are made at lower levels’ (Bughin and Chui 2011).
Trust is also vital in encouraging participation within any virtual collaboration network. This confirms findings
that trust in other members’ ability, expertise and integrity amplifies the level of participation within the network,
thus supporting a strong sense of mutuality and encouraging future contribution (Wasko and Faraj 2005, Tickle
et al. 2011).
Sustaining user interaction in a way that ensures they continue to contribute creatively and engage with the
network members is key to the longevity of the eCN (Koh et al. 2007, Harrison and Zappen 2005). In an SME this is
more of a challenge as members may fear that their expertise is not of an appropriate level to make a relevant
contribution. The results clearly indicate that members’ perceptions of usefulness and of having their expectations
and needs met are important dimensions of collaborative networks. Moreover, the results further substantiate that
the availability of Web 2.0 technologies enables users to easily engage in a rather informal manner for idea creation
or problem solving, thus furthering social bonds that are critical in collaborative efforts. The members of CS1
viewed the eCN’s specialist groups and expert blogs as a joint space suitable to explore a common vision to a
problem affecting the sector within an informal environment. The social interactions captured by this work have
demonstrated that Web 2.0 technologies provide a collaborative infrastructure in SMEs that encourages
engagement of diverse specialist groups, as well as enhancing collaborative outcomes such as knowledge flow
and collective knowledge. Dynamic time efficiencies in CS1 were seen in work activities such as searching,
processing, problem solving, company-matching with funding, decision-making and project activities. This
substantiates the findings of Inkpen and Tsang (2005) that well-constructed and managed collaborative networks
offer clear benefits to SMEs, by helping decode and harness flows of information such as technological change,
sources of technical assistance, market requirements and strategic choices by other firms, thus strengthening their
competitive advantage (Bougrain and Haudeville 2002).
A useful finding from this research study is that collaborators’ participation is a composite construct. This
further substantiates the multi-dimensionality of the collaborator’s participation construct proposed by Michaelides
et al. (2012), which includes level of engagement and contribution.
Other expected benefits of collaborative networks are validated here, such as sharing of resources; openness of
information; engaging with experts of different knowledge sets and capabilities; enhancement of collective
knowledge and furthering of reputation (Bititci et al. 2007, Macedo et al. 2010). The thinking behind this is that
interaction knowledge is not only exchanged but collectively further developed and the network knowledge base
increased (Todtling et al. 2009).
9. Conclusions and future research
This paper synthesises a framework of constructs that relates collaboration network strategy, collaborators’
participation, perceived usefulness and competitive priorities, network complexity, competencies and competitive
capabilities. The findings support the fact that it is not sufficient for companies to simply take into account the
straightforward, tangible benefits of networks, such as increased number of users, when judging the effective
deployment of networks. Organisations that enable the employment of collaborative technologies by their
employees will also need to ensure compatibility between the different systems and competitive priorities. If
technologies are perceived to be too complex users will not participate, neither will they engage meaningfully nor
contribute to the knowledge flow required for collaborative engineering networks to be perceived as valuable assets
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2046
R. Michaelides et al.
in contemporary industry. The dynamics of contemporary industrial environments have changed as companies are
discovering the importance of exploiting emerging employee, customer, and supplier networks. The strength of our
findings here relate to the transformational impact of Web 2.0 tools in generating new insights and knowledge areas
within online collaborative networks.
It should be noted that this study has several limitations that would require further research. First, for both cases
the interviews were conducted using a small selection of participants. Future research would benefit from
investigation of much larger groups of collaborative networkers. Also, in CS1 the paper survey was conducted
during a specific networking face-to-face live event, chosen due to availability and geographical access. In addition,
the results of this study were generated by active participants of the collaboration network. It would be of particular
interest to investigate the network users that do not contribute content, or who become members and then do not
log in to the network. Second, is the fact that only one aspect of collaboration technologies was examined and this
relates to Web 2.0 tools. Another limitation comes from restricting focus to publicly funded eCNs. Both cases of
eCNs studied here were funded by public grants, through EU or national initiatives, and they have been unable to
sustain presence after completion of the funding period. Further profiling of eCNs with a funding sustainability
aspect is planned for the future. Finally, it is the intention that further studies would examine more widely the online
networks in other industries and use the proposed framework to evaluate the network dynamics and value of using
collaboration tools in the private sector and the service industries.
Acknowledgements
The support of the Engineering and Physical Sciences Research Council under grant EP/C534239/1 and the Economic and Social
Research Council under grant RES331270005 for this work is gratefully acknowledged.
References
Adebanjo, D. and Michaelides, R., 2010. Analysis of Web 2.0 enabled e-clusters – a case study. Technovation, 30 (4), 238–248.
Adamides, E.D. and Karacapilidis, N., 2006. A knowledge centred framework for collaborative business process modelling.
Business Process Management Journal, 12 (5), 557–575.
Abrams, C., 2006. Seven core benefits of Web 2.0 for traditional industries [online]. Available from: http://www.contentmanager.net/magazine/article_1252_web2_0_benefits.html [Accessed 10 July 2009].
Baldwin, C. and von Hippel, E., 2009. Modeling a paradigm shift: From producer innovation to user and open collaborative
innovation [online]. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1502864 [Accessed 23 December
2009].
Barnett, J., Harding, J.A., and Nurse, A., 2009. Design and development of a classification system for knowledge management
tools and methods. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture,
224 (B6), 981–993.
Bougrain, F. and Haudeville, B., 2002. Innovation, collaboration and SMEs internal research capacities. Research Policy, 31 (5),
735–747.
Belderbos, R., et al., 2004. Heterogeneity in R&D cooperation strategies. International Journal of Industrial Organization,
22 (8–9), 1237–1264.
Benbasat, I., Goldstein, D.K., and Mead, M., 1987. The case research strategy in studies of information systems. MIS Quarterly,
11 (3), 369–386.
Bughin, J. and Chu, I.M., 2011. How Web 2.0 pays off: the growth dividend enjoyed by networked enterprises. McKinsey
Quarterly, Issue 2, 17–21, 4 pp, 2 graphs.
Camarinha-Matos, L.M. and Afsarmanesh, H., eds. 2008. Classes of collaborative networks. New York: Hershey.
Cheung, W.M., et al., 2008. Advanced product development integration architecture: an out-of-box solution to support
distributed production networks. International Journal of Production Research, 46 (12), 3185–3206.
Cohen, W.M. and Levinthal, D.A., 1990. Absorptive-capacity – a new perspective on learning and innovation. Administrative
Science Quarterly, 35, 128–152.
Davis, F.D., Bagozzi, R.P., and Warshaw, P.R., 1989. User acceptance of computer technology: a comparison of theoretical
models. Management Science, 35 (8), 982–1003.
Deleon, W.H. and McLean, E.R., 1992. Information systems success: the quest for the dependent variable. Information Systems
Research, 3 (1), 60–95.
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
International Journal of Production Research
2047
EIF 2007. Improving knowledge transfer between research institutions and industry across Europe: embracing open innovation,
European Commission, EUR22836, Luxembourg: Office for Official Publication of the European Communities, 2007,
36pp.
EU Commission, 2010. Europe 2020 flagship initiative: Innovation union [online]. Communication from the Commission to the
European
Parliament,
Brussels.
Available
from:
http://eur-x.europa.eu/LexUriServ/LexUriServ.do?uri=
COM:2010:0546:FIN:EN:PDF [Accessed 16 November 2010].
Europabio/Criticali 2006. Biotechnology in Europe: 2006 comparative study. The European Association for Bioindustries,
Belgium, 42pp.
Flavian, C. and Guinaliu, M., 2005. The influence of virtual communities on distribution strategies in the internet. International
Journal of Retail and Distribution Management, 33 (6), 405–425.
Freyne, J., et al., (2009). Increasing engagement through early recommender intervention. 3rd ACM conference on recommender
systems, 22–25 October, New York: ACM, 85–92.
Gartner Incorporated 2006. Hype cycle report: Gartner highlights key emerging technologies in 2006 hype cycle [online]. Source.
Available from: http://www.gartner.com/it/page.jsp?id=495475 [Accessed 30 March 2008].
Gongla, P. and Rizzuto, C.R., 2001. Evolving communities of practice: IBM global services experience. IBM System Journal,
40 (4), 842–862.
Harrison, T.M. and Barthel, B., 2009. Wielding new media in Web 2.0: Exploring the history of engagement with the
collaborative construction of media products. New Media Society, 11 (1–2), 155–178.
Harrison, T. and Zappen, J.P., 2005. Building sustainable community information systems: lessons from a digital government
project. In:Proceedings of the dg.0 2005 national conference on Digital government research, ACM International 2005, 15–18
May, Atlanta, Georgia, USA. Digital Government Society of North America, 145–150.
Hill Jr, S., 2002. Working in-concert. Information Week, 20, 53–54.
Jones-Evans, D., et al., 1999. Creating a bridge between university and industry in small European countries: the role of the
Industrial Liaison Office. R&D Management, 29 (1), 47–56.
Kaufmann, A. and Todtling, F., 2002. How effective is innovation support for SMEs? An analysis of the region of Upper
Austria. Technovation, 22 (3), 147–159.
Koh, J., et al., 2007. Encouraging participation in virtual communities. Communications of the ACM, 50 (2), 69–73.
Lim, K., 2000. The many faces of absorptive capacity: spillovers of copper interconnect technology for semiconductor chips.
Industrial and Corporate Change, 18, 1249–1284.
Michaelides, R., Morton, S.C. and Liu, W., (2012). A framework for evaluating the benefits of collaborative technologies in
engineering innovation networks. Production Planning & Control. The Management of Operations. Forthcoming.
Mowery, D.C., et al., 2001. The growth of patenting and licensing by U.S. universities: An assessment of the effects of the BayhDole act of 1980. Research Policy, 30 (1), 99–119.
Narula, R., 2004. R&D collaboration by SMEs: new opportunities and limitations in the face of globalisation. Technovation,
24 (2), 153–161.
Nieto, M.J. and Santamarı́a, L., 2007. The importance of diverse collaborative networks for the novelty of product innovation.
Technovation, 27 (6–7), 367–377.
Noori, H. and Lee, W.B., 2004. Collaborative design in a networked enterprise: the case of the telecommunications industry.
International Journal of Production Research, 42 (15), 3041–3054.
O’Reilly, T., 2006. Web 2.0 compact definition: Trying again [online]. Available from: http://radar.oreilly.com/2006/12/web-20compact-definition-tryi.html [Accessed 1 January 2012].
O’Reilly, T. and Battelle, J., 2009. Web squared: Web 2.0 five years on [online]. Web 2.0 summit. 20–22 October, San Francisco.
Available from: http://www.web2summit.com/web2009/public/schedule/detail/10194 [1 January 2012].
Parung, J. and Bititci, U., 2008. A metric for collaborative networks. Business Process Management Journal, 14 (5), 654–674.
Pauleen, D.J. and Yoong, P., 2001. Relationship building and the use of ICT in boundary-crossing virtual teams: A facilitator’s
perspective. Journal of Information Technology, 16 (4), 205–220.
Petersen, S.K., (2008). Loser generated content: From participation to exploitation. First Monday, Mar. 2008, 13, (3). Available
from: http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2141/1948 [Accessed 10 December 2010].
Picard, W. and Rabelo, R.J., 2010. Engagement in collaborative networks. Production Planning & Control, 21 (2), 101–102.
PROINNOEUROPE. 2006. European Innovation Scoreboard 2006: Comparative Analysis of Innovation Performance.
Luxembourg. Available from: www.proinno-europe.eu/doc/EIS2006_final.pdf [Accessed 12 December 2010].
Ragatz, G., Handfield, R., and Scannell, T., 1997. Success factors for integrating suppliers into new product development.
Journal of Product Innovation Management, 14 (3), 190–202.
Rogers, E.M., 1983. Diffusion of innovations. New York: Free Press.
Rubin, H., Bukofzer, A., and Helms, S., 2003. From ivory tower to Wall Street – University technology transfer in the US,
Britain, China, Japan, Germany and Israel. International Journal of Law and Information Technology, 11 (1), 59–86.
Schneckenberg, D., 2009. Web 2.0 and the empowerment of the knowledge worker. Journal of Knowledge Management, 13 (6),
509–520.
Downloaded by [Istanbul Universitesi Kutuphane ve Dok] at 16:39 20 December 2014
2048
R. Michaelides et al.
Sheehan, K.B., 2001. E-mail survey response rates: A review. Journal of Computer-Mediated Communication, 6 (2).
Stuckey, B. and Smith, J.D., 2004. Building sustainable communities of practice. In: P. Hidreth and C. Kimble, eds. Knowledge
networks: Innovation through communities of practice. Hershey, PA: Idea Group.
Tan, M. and Teo, T.S.H., 2000. Factors influencing the adoption of internet banking. Journal of the Association for Information
Systems, 1, 1–44. Available from: jais.isworld.org/articles/1-5/article.pdf [Accessed 12 December 2010].
Voss, C., Tsikriktsis, N., and Frohlich, M., 2002. Case research in operations management. International Journal of Operations
and Production Management, 22 (2), 195–219.
Vossen, G., 2011. Web 2.0: From a buzzword to mainstream web reality. In: M.S. Obaidat and J. Filipe, eds. ICETE 2009 CCIS
130. Berlin/Heidelberg: Springer-Verlag, 53–67.
Yates, J. and Orlikowski, W.J., 1992. Genres of organizational communication – a structurational approach to studying
communication and media. Academy of Management Review, 17 (2), 299–326.
Yin, R.K., 2009. Case study research: Design and methods. Thousand Oaks, London: Sage.
Yujun, Y., et al., 2005. Internet-based collaborative product development chain for networked product development.
The International Journal of Advanced Manufacturing Technology, 28 (7–8), 845–853.
Zhang, Z., 2010. Feeling the sense of community in social networking usage. Transactions on Engineering Management, 57 (2),
225–239.
Zhang, K. and Zhou, J., 2004. Design and development of a platform for internet-based collaborative product development.
Journal of Computer Science and Technology, 4 (2), 115–120.