IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa12p381.html
   My bibliography  Save this paper

Knowledge Sharing And Enrichment In The Republic Of Latvia: The Role Of Physical Vs Virtual Community Linkages

Author

Listed:
  • Guido Sechi
  • Jurgis Skilters
  • Dino Borri
  • Caterina De Lucia

Abstract

The role of ICT accessibility in enhancing regional innovation through knowledge and information exchange is a recently popular and controversial topic in regional science. Opposing views exist, related to the bigger or lesser importance of geographical proximity in knowledge exchange in an age dominated by virtual global channels. Existing studies primarily focus on regions (macro level) as units of analysis, without investigating socio-cognitive dynamics in detail, and rely on doubtful epistemological assumptions (i.e. the equation of information with knowledge). It may be hypothesized that the debate would benefit from: a) analyses focused on the micro (individual) level; b) a more complex formalization of social dynamics, by means of adequate sociological frameworks; and c) a deeper reflection on the nature of cognitive factors at stake. The present paper is aimed at investigating the effectiveness of physical (geographical) and virtual communities on information and knowledge sharing and enrichment in the republic of Latvia. Which kind of links – physical or virtual ones – are more efficient and psychologically real and important is additionally analyzed. The theoretical framework draws on social and cognitive science, combining social capital theory and cognitively oriented semantics. The theoretical model to be tested empirically relies on a complex taxonomy of social capital and a complex epistemology of shareable knowledge. The former takes into account both physical / virtual structural (network) assets and social resources which are embedded in such networks; the latter encompasses relevant dichotomies in applied epistemology history (description / experience; information / belief). Causal links between social capital dimensions (related to physical / virtual channels) and forms of knowledge are hypothesized. The empirical analysis is based on a methodological approach relying on advanced econometrics (structural equation modelling), able to encompass both measurement problems related to the intangible nature of variables under exam, and an assessment of complex cause-effect dynamics. The analysis, which is carried out at the individual level, helps to compare the effect of physical vs virtual networks in enhancing social resources and hence knowledge exchange and enrichment. The obtained results are tested against control variables accounting for social and cultural differences within the national community, in order to verify the sensitivity of results according to intra-society gaps. Such clusters are identified on the basis of considerations related to community and identity views among the citizenship. Keywords: social capital; knowledge sharing; communities; structural equation modelling JEL codes: O3; Z1; C30

Suggested Citation

  • Guido Sechi & Jurgis Skilters & Dino Borri & Caterina De Lucia, 2012. "Knowledge Sharing And Enrichment In The Republic Of Latvia: The Role Of Physical Vs Virtual Community Linkages," ERSA conference papers ersa12p381, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa12p381
    as

    Download full text from publisher

    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa12/e120821aFinal00383.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ikujiro Nonaka, 1994. "A Dynamic Theory of Organizational Knowledge Creation," Organization Science, INFORMS, vol. 5(1), pages 14-37, February.
    2. Roberto Camagni & Roberta Capello, 2005. "ICTs and territorial competitiveness in the era of internet," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 39(3), pages 421-438, September.
    3. Peter J. Lane & Michael Lubatkin, 1998. "Relative absorptive capacity and interorganizational learning," Post-Print hal-02311860, HAL.
    4. Ron Boschma & Anne L. J. ter Wal, 2007. "Knowledge Networks and Innovative Performance in an Industrial District: The Case of a Footwear District in the South of Italy," Industry and Innovation, Taylor & Francis Journals, vol. 14(2), pages 177-199.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido Sechi & Jurgis Skilters & Marta Selecka & Krista Berzina & Liva Brice, 2013. "The Impact Of Hybrid Infrastructure On Trust, Motivation And Knowledge Sharing In An Intentional Community: A Latvian Case Study," ERSA conference papers ersa13p521, European Regional Science Association.
    2. María José Ruiz-Ortega & Gloria Parra-Requena & Pedro Manuel García-Villaverde, 2016. "Do Territorial Agglomerations Still Provide Competitive Advantages? A Study of Social Capital, Innovation, and Knowledge," International Regional Science Review, , vol. 39(3), pages 259-290, July.
    3. Scaringella, Laurent & Burtschell, François, 2017. "The challenges of radical innovation in Iran: Knowledge transfer and absorptive capacity highlights — Evidence from a joint venture in the construction sector," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 151-169.
    4. Nay Chi Khin Khin Oo & Sirisuhk Rakthin, 2022. "Integrative Review of Absorptive Capacity’s Role in Fostering Organizational Resilience and Research Agenda," Sustainability, MDPI, vol. 14(19), pages 1-27, October.
    5. Song Wei & Gao Liang & Pan Gang, 2014. "Effects of R&D Cooperation to Innovation Performance in Open Innovation Environment," International Journal of Business and Social Research, LAR Center Press, vol. 4(5), pages 151-160, May.
    6. Daniel RUSU, 2022. "Association of Knowledge Management with Strategic Management: Directions and Trends at International Level," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 7(1), pages 49-66, February.
    7. Bouncken, Ricarda B. & Fredrich, Viktor & Kraus, Sascha & Ritala, Paavo, 2020. "Innovation alliances: Balancing value creation dynamics, competitive intensity and market overlap," Journal of Business Research, Elsevier, vol. 112(C), pages 240-247.
    8. Sofka, Wolfgang, 2007. "What Makes Foreign Knowledge Attractive to Domestic Innovation Managers?," ZEW Discussion Papers 07-055, ZEW - Leibniz Centre for European Economic Research.
    9. Marco-Lajara, Bartolomé & Zaragoza-Sáez, Patrocinio del Carmen & Claver-Cortés, Enrique & Úbeda-García, Mercedes, 2016. "Knowledge sources, agglomeration, and hotel performance," Journal of Business Research, Elsevier, vol. 69(11), pages 4856-4861.
    10. Namgyoo Park & John Mezias & Jinju Lee & Jae-Hoon Han, 2014. "Reverse knowledge diffusion: Competitive dynamics and the knowledge seeking behavior of Korean high-tech firms," Asia Pacific Journal of Management, Springer, vol. 31(2), pages 355-375, June.
    11. Byung Park, 2010. "What matters to managerial knowledge acquisition in international joint ventures? High knowledge acquirers versus low knowledge acquirers," Asia Pacific Journal of Management, Springer, vol. 27(1), pages 55-79, March.
    12. Kenneth Zahringer & Christos Kolympiris & Nicholas Kalaitzandonakes, 2017. "Academic knowledge quality differentials and the quality of firm innovation," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(5), pages 821-844.
    13. Vesna Vlaisavljevic & Carmen Cabello Medina & Ana Pérez-Luño, 2014. "Does The Diversity Of Partners In Alliances Guarantees Innovation Performance? The Influence Of Social Capital And Knowledge Codifiability On Such Relationship," Working Papers 14.01, Universidad Pablo de Olavide, Department of Business Organization and Marketing (former Department of Business Administration).
    14. Marshall S. Jiang & Preet S. Aulakh & Yigang Pan, 2007. "The nature and determinants of exclusivity rights in international technology licensing," Management International Review, Springer, vol. 47(6), pages 869-893, December.
    15. Li, Xiaoqing & Roberts, Joanne & Yan, Yanni & Tan, Hui, 2014. "Knowledge sharing in China–UK higher education alliances," International Business Review, Elsevier, vol. 23(2), pages 343-355.
    16. Stefan Wagner & Karin Hoisl & Grid Thoma, 2014. "Overcoming localization of knowledge — the role of professional service firms," Strategic Management Journal, Wiley Blackwell, vol. 35(11), pages 1671-1688, November.
    17. Vanhaverbeke, W.P.M. & Beerkens, B.E. & Duysters, G.M., 2003. "Explorative and exploitative learning strategies in technology-based alliance networks," Working Papers 03.22, Eindhoven Center for Innovation Studies.
    18. Torugsa, Nuttaneeya (Ann) & O’Donohue, Wayne, 2016. "Progress in innovation and knowledge management research: From incremental to transformative innovation," Journal of Business Research, Elsevier, vol. 69(5), pages 1610-1614.
    19. Leone, Maria Isabella & Messeni Petruzzelli, Antonio & Natalicchio, Angelo, 2022. "Boundary spanning through external technology acquisition: The moderating role of star scientists and upstream alliances," Technovation, Elsevier, vol. 116(C).
    20. Adenfelt, Maria & Lagerström, Katarina, 2006. "Knowledge development and sharing in multinational corporations: The case of a centre of excellence and a transnational team," International Business Review, Elsevier, vol. 15(4), pages 381-400, August.

    More about this item

    Keywords

    social capital; knowledge sharing; communities; structural equation modelling jel codes: o3; z1; c30;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • Z1 - Other Special Topics - - Cultural Economics
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa12p381. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.