Proceedings of the 3rd European Conference on Intellectual Capital

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Bongani Ngwenya late adopters respond to framing and interpreting adoption decision situations as opportunities versus threats. Thus <strong>the</strong> rationale and motivation for undertaking this research and contributing to <strong>the</strong> body <strong>of</strong> knowledge <strong>the</strong> rethinking <strong>of</strong> <strong>the</strong> classic institutional, framing and diffusion model, to suggest strategic innovation and knowledge management model or framework that emerging technologies and economies like Zimbabwe could adopt to suit <strong>the</strong>ir social, political and economic context. In <strong>the</strong> order <strong>of</strong> consideration, <strong>the</strong> author first examines some insights from <strong>the</strong> literature and conceptual framework. Following <strong>the</strong> discussion <strong>of</strong> <strong>the</strong> conceptual framework, a discussion <strong>of</strong> this empirical investigation <strong>of</strong> framing and interpreting adoption decision situations based on <strong>the</strong> interpretivist research conventions used in this paper is done. The research methodology is outlined, followed by <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> data, and discussion. Finally, <strong>the</strong> conclusions are drawn. As a result <strong>of</strong> this investigation, a strategic innovation and knowledge management framework or model that can be feasible in <strong>the</strong> emerging technologies and economies, and takes into account <strong>the</strong> social, political and economic context <strong>of</strong> <strong>the</strong>se emerging technologies and economies could be developed following fur<strong>the</strong>r research in <strong>the</strong> future. 2. Insights from <strong>the</strong> literature and conceptual framework Innovation stands out as one excellent objective <strong>of</strong> management activity in general, and knowledge management specifically (Ruggles and Little, 1997). The two experts in <strong>the</strong>ir research fur<strong>the</strong>r suggest that, or examine innovation as one end to which knowledge management can be applied. Pimentel and Campos (2008) suggest that creativity and innovation is <strong>the</strong> key to survival and pr<strong>of</strong>itability in a rapidly evolving, complex and competitive global business environment. Technology is integral to virtually every facet <strong>of</strong> business. It plays pivotal role in <strong>the</strong> development, manufacture and delivery <strong>of</strong> innovative products and services to <strong>the</strong> market. Effective management <strong>of</strong> innovation, product design and development is important for technology leadership. Thus, <strong>the</strong> alignment <strong>of</strong> intellectual property strategy with innovation and business strategy is challenging and yet critical for bottom line growth. Knowledge management comprises a range <strong>of</strong> strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption <strong>of</strong> insights and experiences. Such insights and experiences comprise knowledge, ei<strong>the</strong>r embodied in individuals or embedded in organizational processes or practices (Nonaka, 1991). Many large companies and non-pr<strong>of</strong>it organizations have resources dedicated to internal knowledge management efforts, <strong>of</strong>ten as part <strong>of</strong> <strong>the</strong>ir business strategy, information technology, or human resources management departments (Addicott, McGivern and Ferlie, 2006). Knowledge management efforts typically focus on organizational objectives such as improved performance, competitive advantage, innovation, creativity, development, <strong>the</strong> sharing <strong>of</strong> lessons learned, integration and continuous improvement <strong>of</strong> <strong>the</strong> organization. Knowledge management efforts can help individuals and groups to share valuable organizational insights, to reduce redundant work, to avoid reinventing <strong>the</strong> wheel per se, to reduce training time for new employees, and retain intellectual capital (McAdam and McCreedy, 2000; Thompson and Walsham,2004). The efficient operation <strong>of</strong> a firm requires congruence between <strong>the</strong> firm’s product and knowledge domains (Grant, 1996), a strong innovative knowledge base can increase a firm’s rent generation potential by streng<strong>the</strong>ning its ability to take advantage <strong>of</strong> opportunities in product markets (Gopalkrishnan, 2000). Also, innovation in <strong>the</strong> form <strong>of</strong> a unique and superior combination <strong>of</strong> firm resources may introduce ‘creative destruction’ to <strong>the</strong> competitive landscape and bring considerable benefits to <strong>the</strong> innovative firm (Schumpeter, 1934). Innovation can thus be a fundamental force that drives a firm’s exploitation in <strong>the</strong> marketplace, resulting in positive economic performance for <strong>the</strong> firm (Griliches, 1990; Hall, 2000). Usually, intensive investment in Research and Development can help a firm maintain an ample stock <strong>of</strong> innovative knowledge assets, which are <strong>of</strong>ten traceable, at least in part, through <strong>the</strong> firm’s patenting history (Hoetker and Agarwal, 2007). Although rival firms may imitate certain codifiable but nonpatented innovative outputs, <strong>of</strong>ten much <strong>of</strong> a firm’s innovative knowledge can be ‘isolating mechanism’ deterring rivals from appropriating economic returns through imitation (Mahoney and Pandian, 1992; Rumelt, 1984). Also, a continuous focus on accumulating innovative knowledge assets increases a firm’s absorptive capacity, putting it in a better position to transform strategic inputs into valuable products or services (Cohen and Levinthal, 1990; Kor and Mahoney, 2005). The outcome <strong>of</strong> innovative knowledge can also prove difficult for o<strong>the</strong>r firms to imitate. Apart from protective mechanisms such as copyrights and patents, <strong>the</strong> idiosyncratic features <strong>of</strong> a firm make replication difficulty if o<strong>the</strong>r firms do not have access to <strong>the</strong> asset configuration to which <strong>the</strong> innovative knowledge was applied (Helfat, 1994; Alchian and Demsetz, 1972; McGrath et al., 1996). In line with 314
Bongani Ngwenya <strong>the</strong>se arguments, previous empirical studies (DeCarolis and Deeds, 1999; D` Este, 2005; Geroski, Machin, and Van Reenen, 1993; Roberts and Amit, 2003) have generally demonstrated that variations among firms in <strong>the</strong>ir rates <strong>of</strong> accumulating new knowledge, and in <strong>the</strong>ir stocks <strong>of</strong> innovative knowledge assets, contribute to differences in <strong>the</strong> financial performance <strong>of</strong> <strong>the</strong>se firms in <strong>the</strong>ir different industries. For example, using a sample <strong>of</strong> United States <strong>of</strong> America biotechnology firms, DeCarolis and Deeds (1999) found that both stocks and flows <strong>of</strong> organizational knowledge had a positive impact on firm performance. Research has shown similar positive effects <strong>of</strong> innovative inputs and outputs on performance in various o<strong>the</strong>r geographical and industrial settings, such as Australian retail banking (Roberts and Amit, 2003), Spanish pharmaceuticals (D` Este, 2005), and United Kingdom manufacturing (Geroski et al., 1993).This paper argues that, like Total Quality Management (TQM) practices, Openness in eGovernment, and o<strong>the</strong>r organizational practices, strategic innovation and knowledge management is an organizational practice that can also be explained and viewed from <strong>the</strong> institutional <strong>the</strong>ory’s account <strong>of</strong> diffusion, adoption and implementation. Diffusion occurs when new products and services begin flowing deeper within <strong>the</strong>ir initial markets, or to areas different from <strong>the</strong> one in which <strong>the</strong>y were originally introduced (Ruggles and Little, 1997).The conventional diffusion model mostly neglects practice implementation, yet several studies have called for viewing diffusion practices as dynamic (Rogers, 1978; Strang and Soule, 1998) and thus for studying <strong>the</strong> details <strong>of</strong> implementation (Edelman, 1992; Fiss and Zajac, 2006; Westphal and Zajac, 2001; Zbaracki, 1998). The questions <strong>of</strong> why and how organizations adopt new practices have remained a central topic in <strong>the</strong> management and organization <strong>the</strong>ory literatures (Abrahamson, 1991; Davis & Greve, 1997; Palmer, Jennings, & Zhou, 1993; Westphal, Gulati, & Shortell, 1997). Prior research has <strong>of</strong>fered a number <strong>of</strong> important insights into diffusion processes among populations <strong>of</strong> organizations, ranging from <strong>the</strong> role <strong>of</strong> organization size and market power (Geroski, 2000; Hannan & McDowell, 1984) to <strong>the</strong> importance <strong>of</strong> imitation processes (DiMaggio & Powell, 1983) and trendsetters (Abrahamson, 1996). Two distinct approaches to explaining adoption motivation have characterized much <strong>of</strong> this literature on <strong>the</strong> diffusion <strong>of</strong> practices and administrative technologies (Strang & Macy, 2001). The first approach is rooted in <strong>the</strong> economic literature, building on <strong>the</strong> rational actor model, in which organizational adoption is motivated by a desire for technical or efficiency gains and related boosts to economic performance (Katz & Shapiro, 1987; Teece, 1980). The second approach represents a more sociological perspective, emphasizing <strong>the</strong> social embeddedness <strong>of</strong> organizations and motivations that stem primarily from a desire to appear legitimate to powerful constituents, peer organizations, or outside stakeholders (Abrahamson, 1991; DiMaggio & Powell, 1983). Perhaps <strong>the</strong> most important integration <strong>of</strong> insights from both sets <strong>of</strong> explanations is Tolbert & Zucker`s (1983) two-stage model, according to which early adopters seek technical gains from adoption, but later adopters are primarily interested in <strong>the</strong> social benefits <strong>of</strong> appearing legitimate. Tolbert & Zucker consequently argued that <strong>the</strong>se later adopters implemented reforms primarily out <strong>of</strong> a desire to appear legitimate. Similarly, in <strong>the</strong>ir study <strong>of</strong> United States hospitals, Westphal, Gulati, & Shortell (1997) suggest that early adopters <strong>of</strong> Total Quality Management (TQM) practices were motivated by efficiency concerns. However as TQM practices became institutionalized and thus became expected elements <strong>of</strong> organization, <strong>the</strong> logic <strong>of</strong> evaluation shifted, and later adopters were motivated primarily by legitimacy concerns ra<strong>the</strong>r than efficiency gains. In this paper, developed technologies and economies, like US, UK, China and Japan that are strong in innovation and knowledge management are considered as early adopters <strong>of</strong> strategic innovation and knowledge management practices, while emerging technologies and economies like Zimbabwe are viewed as later adopters <strong>of</strong> <strong>the</strong> practices. According to <strong>the</strong> institutional <strong>the</strong>ory’s account <strong>of</strong> diffusion early adopters <strong>of</strong> <strong>the</strong>se practices are motivated by, and seeking technical gains from adoption, but later adopters are primarily interested in <strong>the</strong> social benefits <strong>of</strong> appearing legitimate, to realize organizational creativity and organizational development. Although this two-stage model <strong>of</strong> diffusion has been a touchstone for many studies that apply institutional <strong>the</strong>ory to practice diffusion (Baron, Dobbin, & Jennings, 1986; Meyer, Stephenson, & Webster, 1985; Pangarkar & Klein, 1998; Scott, 1995; Westphal & Zajac, 1994), it has recently drawn critical attention. For example, Lounsbury (2007) argued that segregating economic and social logics is problematic, since <strong>the</strong> distinction between technical and social benefits is itself embedded in institutions (Lounsbury, 2002; Thornton, 2004). By implication, technical and social motivations are less disjointed than previously <strong>the</strong>orized (Schneiberg & Soule, 2005; Scott, Ruef, Mendel, & Caronna, 2000). 315
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Proceedings <stron
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. Hier
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Preface These proceedings represent
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educating through ‘hands on’ co
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Ibrahim Elbeltagi is a Senior lectu
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Theodora Ngosi has a PhD in Compute
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José Vale is an invited assistant
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Social Knowledge: Are you Ready? 1
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John Girard don’t know.” (Benne
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John Girard The real question becom
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John Girard our belief that many le
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John Girard organizations to gain k
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Intellectual Capital Accounting - H
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Academic Research Papers 15
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Khodayar Abili and Mahyar Abili The
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Khodayar Abili and Mahyar Abili Nah
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Khodayar Abili and Mahyar Abili Tim
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Knowledge Transfer in Romanian Univ
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Simona Agoston et al. Table 1: Know
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Simona Agoston et al. homoscedastic
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Simona Agoston et al. included in <
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A Modeling Approach to Intellectual
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Eckhard Ammann (referring to <stron
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Eckhard Ammann Figure 2: The IC spa
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Eckhard Ammann section 2. They are
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Eckhard Ammann From an overall pers
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Sorin Anagnoste and Gabriela Dumitr
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Gabriela Atanasiu and Florin Leon T
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Gabriela Atanasiu and Florin Leon
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Gabriela Atanasiu and Florin Leon B
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Gabriela Atanasiu and Florin Leon a
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Developing and Implementing Strateg
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2. Technology, faculty, and staff B
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Learning programs Individual poten
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Bob Barrett facts with the<
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Intellectual Capital Dynamics withi
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Ruxandra Bejinaru and Stefan Iordac
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Education and Training Practice Str
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Andrea Bencsik et al. We wanted to
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Andrea Bencsik et al. In this sampl
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Table 4: Types of
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References Andrea Bencsik et al. An
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Ayşen Berberoğlu and Emine Ünar
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Ayşen Berberoğlu and Emine Ünar
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Table 7: Descriptive statistics Ay
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Knowledge Dynamics Modeling Using A
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Constantin Bratianu et al. will hav
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Constantin Bratianu et al. 5. a) Gi
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Constantin Bratianu et al. 5. Data
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Constantin Bratianu et al. Nissen,
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2. Technology and infrastructure Sh
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Sheryl Buckley and Apostolos Gianna
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Donley Carrington and Mike Tayles t
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Donley Carrington and Mike Tayles f
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Donley Carrington and Mike Tayles l
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Donley Carrington and Mike Tayles i
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Donley Carrington and Mike Tayles G
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John Dumay and Jim Rooney on a more
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John Dumay and Jim Rooney Taking <s
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John Dumay and Jim Rooney “For ex
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John Dumay and Jim Rooney Mouritsen
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Marziye Ehrami et al. 1. Creation
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Marziye Ehrami et al. Note: In 2005
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Earnings Quality and Othe</
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Magdi El-Bannany resource-based per
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Magdi El-Bannany Based on this argu
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Magdi El-Bannany Table 2: Descripti
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Magdi El-Bannany variable equal to
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Magdi El-Bannany Edvinsson, L. & Ma
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Ahmed Elsetouhi and Ibrahim Elbelta
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Albrecht Fritzsche and Rebecca Geig
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Table 4: Applicability of</
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S&P 500 Market Cap ($ billions) 14,
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Tatiana Garanina and Yana Pavlova T
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Tatiana Garanina and Yana Pavlova I
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Impact of Investme
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Lidia García-Zambrano et al. 2003;
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Lidia García-Zambrano et al. 4.2 P
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Table 7: Goodness of</stron
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Lidia García-Zambrano et al. reaso
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Lidia García-Zambrano et al. Rodri
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Víctor Raúl López Ruiz et al. co
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Víctor Raúl López Ruiz et al. NI
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EI c k i 1 w PC i ic Víctor Raúl
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Víctor Raúl López Ruiz et al. Ta
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Víctor Raúl López Ruiz et al. Co
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Víctor Raúl López Ruiz et al. At
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Maria de Lourdes Machado and Odíli
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Intellectual Capital and Corporate
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Agnes Maciocha when objects in a da
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Agnes Maciocha 4. Presentation <str
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Agnes Maciocha while in the
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Agnes Maciocha Choong K., “Intell
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The Influence of H
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Anca Mândruleanu From the<
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Anca Mândruleanu In Table 2, <stro
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Eliciting Tacit Knowledge From a Do
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Peter Marshall and Damian Gordon MM
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Peter Marshall and Damian Gordon re
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Peter Marshall and Damian Gordon ar
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Peter Marshall and Damian Gordon Th
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Maurizio Massaro et al. crucial fac
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Maurizio Massaro et al. exclusive (
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Maurizio Massaro et al. autonomy <s
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Maurizio Massaro et al. Chennal (20
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Intellectual Capital Management: Ca
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Florinda Matos et al. These models
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Complaints System dos clients New
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Florinda Matos et al. Finally, <str
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Florinda Matos et al. The training
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Florinda Matos et al. 47. Opinion
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Florinda Matos et al. In th
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Florinda Matos et al. The Quadrant
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Florinda Matos et al. Integrated te
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Florinda Matos et al. The networks
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Knowledge Management for Knowledge
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3. Our research Ludmila Mládková
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Page 284 and 285: Applying the VAIC
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Page 298 and 299: Maria Cristina Morariu Tobin’s q
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Page 304 and 305: Fattah Nazem Ackerley (2006) reveal
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Page 312 and 313: Andrei Stefan Nestian organization.
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Page 318 and 319: Increasing Knowledge Management Mat
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Page 326 and 327: 5. Discussion and summary Theodora
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Page 332 and 333: Bongani Ngwenya This paper extends
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Page 338 and 339: The Quality of Kno
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Page 360 and 361: Nicolae Al. Pop et al. satisfaction
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Anna Romiti and Daria Sarti Governa
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Anna Romiti and Daria Sarti Therefo
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Anna Romiti and Daria Sarti Valkoka
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Kent Rondeau and Terry Wagar planne
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2.1 Study measures Kent Rondeau and
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Kent Rondeau and Terry Wagar contri
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Kent Rondeau and Terry Wagar Our re
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Intellectual Capital and a Firm’s
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Figure 1: Hypothes
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Helena Santos-Rodrigues et al. Norm
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Helena Santos-Rodrigues et al. To s
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Helena Santos-Rodrigues et al. Our
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Factors Influencing the</st
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Thanaletchumi Sathasivam et al. 2.3
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Thanaletchumi Sathasivam et al. The
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Thanaletchumi Sathasivam et al. gro
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Thanaletchumi Sathasivam et al. The
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Thanaletchumi Sathasivam et al. 11.
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Enhancing IC Formation by Evoking H
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Klaus Bruno Schebesch to portray <s
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Klaus Bruno Schebesch 4. Leaning an
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Klaus Bruno Schebesch We argue in f
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Klaus Bruno Schebesch come
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In Search of key F
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Karen Smits et al. contribution, wi
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Karen Smits et al. Table 1: Correla
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Karen Smits et al. staff feel that
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Marta-Christina Suciu et al. This p
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Marta-Christina Suciu et al. <stron
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Marta-Christina Suciu et al. The qu
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Marta-Christina Suciu et al. This t
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Information and Communication Techn
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Jukka Surakka et al. The participan
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Jukka Surakka et al. people. Commun
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Personal Knowledge Management (PKM)
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Marzena Świgoń provide th
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Marzena Świgoń (number and type <
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Marzena Świgoń measure self-perce
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Eduardo Tomé what we consider to b
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Eduardo Tomé IC. The intervention
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Eduardo Tomé In the</stro
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Eduardo Tomé to stress that <stron
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Eleni Magdalini Vasileiadou et al.
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José María Viedma Marti products
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Sustainable competitive advantage T
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José María Viedma Marti knowledge
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José María Viedma Marti pr<strong
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José María Viedma Marti All <stro
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ICBS I CBS José María Viedma Mart
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José María Viedma Marti Sullivan,
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2. Balanced scorecard framework Ang
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Angelos Vouldis and Angelica Kokkin
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Unclear benefits of</strong
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Angelos Vouldis and Angelica Kokkin
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9. Discussion and conclusions Angel
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The Global Position of</str
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Piotr Wisniewski safeguarding IC vi
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Piotr Wisniewski Figure 2: Ten larg
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Piotr Wisniewski suspected
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Piotr Wisniewski 2) Slow growth in
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Piotr Wisniewski US 3.8 3.8 3.9 4.3
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498
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500
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2. Hypothesis deve
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3.2 Control variables Deborah Brans
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Deborah Branswijck and Patricia Eve
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Deborah Branswijck and Patricia Eve
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Korosh Gholami et al. Durkheim beli
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Korosh Gholami et al. The effect <s
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Measure the Unmeas
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Knowledge Capital 5. Efforts for de
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Exclusive use of L
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Emmanouil Gkinoglou from th
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Project Assets Need for synergies Q
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Table 5: Sustainability checklist E
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Emmanouil Gkinoglou The next challe
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Kai Mertins and Ronald Orth generat
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Kai Mertins and Ronald Orth Never<s
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Kai Mertins and Ronald Orth <strong
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Ad 2 Structure of
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Kai Mertins and Ronald Orth Hauff,
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Maria Simonova “Concept o
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Maria Simonova The concept regardin
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Maria Simonova Becker, G. S. (1983)
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2. The aim of appl
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Nellija Titova W+I+DP+D+T+M+R (equa
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Nellija Titova performing better. I
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5. Conclusions and furthe</
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Nellija Titova Annex 2: Summary on
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Meaning in the tab
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Krishanthi Ganga Vithana et al. for
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Krishanthi Ganga Vithana et al. sti
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5. Conclusion Krishanthi Ganga Vith
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The Tobing Knowledge Management Arc
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Paul Lumbantobing et al. user, know
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Paul Lumbantobing et al. people con
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Paul Lumbantobing et al. influence
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Develop KM Strategy Description Dev
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Paul Lumbantobing et al. In <strong
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Yuli Purwanti et al. Figure 1: Imag
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Yuli Purwanti et al. Table below is
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Nargiza Abdullaeva and Campbell War
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Andreea Feraru and Nicoleta Ciucesc
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Roxana Mironescu This could be <str
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Roxana Mironescu Daft, R.L. (2002)
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Paloma Sánchez and Oihana Basilio
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Evaluating Intellectual Capital Usi
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Proceedings of the 3rd European Conference on Intellectual Capital

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