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Organization of Knowledge Transfer in Clusters: A Knowledge-Based View

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New Developments in the Theory of Networks

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

In this paper, we develop a knowledge-based view on the organization of knowledge transfer in clusters. Starting from the information richness theory, we argue that tacitness of the partners’ knowledge determines the information richness of the knowledge transfer mechanisms in clusters. We examine the following hypotheses: (a) If the cluster partners’ knowledge is characterized by a low degree of tacitness, knowledge transfer mechanisms with a lower degree of information richness (e.g. email, intranet, documents, newsgroups) are used; (b) if the cluster partners’ knowledge is characterized by a high degree of tacitness, knowledge transfer mechanisms with a higher degree of information richness (e.g. seminars, workshops, formal meetings) are used. We test these hypotheses by using data from the Green Building Cluster of Lower Austria. Using complexity, teachability and codifiability as measures for tacitness of the cluster partners’ knowledge, the empirical results from Green Building Cluster in Austria partly support these hypotheses. Our results indicate that an increase in teachable knowledge results in the use of more knowledge transfer mechanisms with a lower degree of information richness, and an increase in complex, but articulable knowledge results in the use of more knowledge transfer mechanisms with a higher degree of information richness. In addition, we show that trust positively influences the use of all modes of knowledge transfer.

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Authors and Affiliations

  1. Chair of Real Estate Development, Vienna University of Technology, Gusshausstr. 30, A-1040, Vienna, Austria

    Marijana Srećković

Authors
  1. Marijana Srećković
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  2. Josef Windsperger
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Correspondence to Marijana Srećković .

Editor information

Editors and Affiliations

  1. , School of Business and Economics, University of Jyväskylä, MaE, Jyväskylä, 40014, Finland

    Mika Tuunanen

  2. Fak. Sozial-u.Wirtschaftswiss., Inst. BWL / LS Organisation, Universität Wien, Brünner Str. 72, Wien, 1210, Austria

    Josef Windsperger

  3. Centre Recherche en Economic et, Management (CREM), Universite de Rennes 1, rue Jean Macé 11, Rennes CX, 35708, France

    Gérard Cliquet

  4. School of Management, Erasmus University Rotterdam, Burg. Oudlaan 50, Rotterdam, 3000 DR, Netherlands

    George Hendrikse

Appendix

Appendix

1.1 Measures of Variables

Lower-IR-knowledge transfer mechanisms (LIR)

To what extent does the cluster company use knowledge transfer mechanisms with a lower degree of IR: (Intranet, chat discussions, online forum, newsgroups, email, fax, formal letters, existing documents) (1, no extent;…7, to a very large extent)

Higher-IR-knowledge transfer mechanisms (HIR)

To what extent does the cluster company use knowledge transfer mechanisms with a higher degree of IR: (Seminars, workshops, video conferences, committees, informal meetings, formal meetings) (1, no extent;…7, to a very large extent)

Complexity (COMPLEX) Coefficient alpha: 0.88

The general manager has to evaluate complexity on a 7 point scale (1,strongly disagree; …7, strongly agree):

Complex 1: Cluster partners must master many diverse activities and tasks, in order to be able to apply the partner knowledge successfully

Complex 2: The tasks and activities for the application of partner know-how are very difficult

Complex 3: The tasks and activities for the application of the partner know-how are very heterogeneous

Complex 4: The tasks and activities for the application of the partner know-how are very interdependent

Complex 5: The partner know-how can be easily divided in separate tasks (reverse coded)

Teachability (TEACH) Coefficient alpha: 0.92

The general manager has to evaluate teachability on a 7 point scale (1, strongly disagree; …7, strongly agree):

Teach 1: The cluster partners can easily learn the most important activities of the relationship through personal communication with employees of the partner firm

Teach 2: The partners can easily learn the most important activities of the relationship through personal support provided by employees of the partner firm

Teach 3: The employees of the cluster firms can master the new knowledge of the cluster partner through training

Teach 4: Training to apply the new knowledge is a quick and easy job

Teach 5: The cluster partners can easily learn the most important activities and tasks through job rotation between the cluster firms

Codifiability (COD) Coefficient alpha: 0.80

The general manager has to evaluate codifiability on a 7 point scale (1,strongly disagree; …7, strongly agree):

Cod 1: Large parts of the business processes between the partner firms can be carried out by using information technology

Cod 2: Critical parts of the business processes between the partners can be extensively documented in written form

Trust (TRUST) Coefficient alpha: 0.93

The general manager has to evaluate trust on a 7 point scale (1,strongly disagree; …7, strongly agree):

Trust 1: There is great trust between us and partners

Trust 2: There is an atmosphere of openness and sincerity

Trust 3: The mutual cooperation is on a partnership basis

Trust 4: Information sharing between the partners exceeds the level stipulated in the contract

Firm size (SIZE)

Number of employees

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Srećković, M., Windsperger, J. (2011). Organization of Knowledge Transfer in Clusters: A Knowledge-Based View. In: Tuunanen, M., Windsperger, J., Cliquet, G., Hendrikse, G. (eds) New Developments in the Theory of Networks. Contributions to Management Science. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2615-9_17

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