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Using Sustainable Competitive Advantages to Measure Technological Opportunities

Listed author(s):
  • Josu Takala

    (University of Vaasa, Finland)

  • Matti Muhos

    (University of Vaasa, Finland)

  • Sara Tilabi

    (University of Vaasa, Finland)

  • Mehmet Serif TAS

    (University of Vaasa, Finland)

  • Bingli Yan

    (University of Vaasa, Finland)

Registered author(s):

    Purpose: This paper tries to find operative competitive advantage. The results of this paper help small and medium size enterprises (SMEs) which are striving to export. In fact, this paper introduces a new technique which applies critical factor analysis, risk and opportunities analysis to measure and propose resource allocation for companies in couple of next years. Research questions: In this paper two questions are answered: 1. How to evaluate Knowledge and Technology (K/T) effect on operative Sustainable Competitive Advantages (SCA)?. 2. How the results from calculation Critical Factor Indexes (CFIs), SCA level and K/T are evaluated? Design/Methodology/approach: This research is based on 7 case studies from Oulu South region of Finland. The cases were selected from manufacturing industry including cases focusing on manufacturing of wood product, machinery and equipment, and instruments and appliances. In this research paper, the effect of technology and knowledge on SCA risk level is investigated. In other words, here this question is answered: what would be the effect of T/K calculation on (Balanced) Critical Factor Index changes. Findings: The effect of Knowledge/Technology(K/T) on (Balanced) Critical Factor Index changes depending on the proportions allocated among the different technological levels (Basic, Core or Spearhead) for each attribute separately. Therefore, the effect of K/T may be analyzed by taking the dominating technology and the resource allocation into consideration for each attribute respectively. Research limitations/implications: in this research paper, 7 case studies are investigated. For 6 of them, at least 2 respondents are interviewed. However in one case, there is only one respondent. So in this case, the calculation of CFI factor is not possible. Moreover, as the number of respondents of each case is not big, so it is not possible to eliminate the effect of standard deviation in calculation of CFIs factor. Practical implications: This research helps firms to take balance in resource allocation for each attribute in changing environments on the basis of different level of technology (Basic, Core or Spearhead).

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    This chapter was published in: Josu Takala & Matti Muhos & Sara Tilabi & Mehmet Serif TAS & Bingli Yan , , pages S2_142-163, 2013.
    This item is provided by ToKnowPress in its series Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management with number s2_142-163.
    Handle: RePEc:tkp:tiim13:s2_142-163
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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

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    1. Kraaijenbrink, Jeroen & Spender, JC & Groen, Aard, 2009. "The resource-based view: A review and assessment of its critiques," MPRA Paper 21442, University Library of Munich, Germany.
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