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Manager’s decision-making in organizations empirical analysis of bureaucratic vs. learning approach

Author

Listed:
  • Eva Bolfikova

    (University of Pavol Jozef Safarik in Kosice, Faculty of Public Administration, Kosice, Slovak Republic)

  • Daniela Hrehova

    (Technical University in Kosice, Department of Social Sciences, Kosice, Slovak Republic)

  • Jana Frenova

    (The University of Presov, Faculty of Management, Presov, Slovak Republic)

Abstract

The paper is focused on the study of manager’s decision-making with respect to the basic model of learning organization, presented by P. Senge as a system model of management. On one hand, the empirical research was conducted in connection with key dimensions of organizational learning such as: 1. system thinking, 2. personal mastery, 3. mental models, 4. team learning, 5. building shared vision and 6. dynamics causes. On the other hand, the research was connected with the analysis of the bureaucratic logic of decision-making process, characterized by non-functional stability, inflexibility, individualism, power, authority and hierarchy, centralization, vagueness, fragmentariness. The objective of the research was to analyse to what extent manager’s decisionmaking is based on bureaucratic tools or organizational learning in either complex problem-solving or non-problem- solving decision-making. (MANOVA, method of the repeated measure, inter- subject factor situation: 1. non-problematic, 2. problematic). The conclusion of analysis is that there are significant differences in character of solving of problem situation and non-problem situation decision-making: the bureaucratic attributes of decision-making are more intensive in problematic situations while learning approach is more actual in non-problematic situations. The results of our analysis have shown that managers who apply the learning organization attributes in their decision-making. are more successful in problem-solving.

Suggested Citation

  • Eva Bolfikova & Daniela Hrehova & Jana Frenova, 2010. "Manager’s decision-making in organizations empirical analysis of bureaucratic vs. learning approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 28(1), pages 135-163.
  • Handle: RePEc:rfe:zbefri:v:28:y:2010:i:1:p:135-163
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    References listed on IDEAS

    as
    1. Marko Pahor & Miha Škerlavaj & Vlado Dimovski, 2007. "The Network Perspective To Organizational Learning — A Comparison Of Two Companies," World Scientific Book Chapters, in: Christian Stary & Franz Barachini & Suliman Hawamdeh (ed.), Knowledge Management Innovation, Technology and Cultures, chapter 6, pages 65-79, World Scientific Publishing Co. Pte. Ltd..
    2. repec:hal:spmain:info:hdl:2441/9832 is not listed on IDEAS
    3. Barr, Jason & Saraceno, Francesco, 2009. "Organization, learning and cooperation," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 39-53, May.
    4. Jody Hoffer Gittell, 2001. "Supervisory Span, Relational Coordination and Flight Departure Performance: A Reassessment of Postbureaucracy Theory," Organization Science, INFORMS, vol. 12(4), pages 468-483, August.
    5. Newman S. Peery, 1975. "General Systems Theory Approaches To Organizations: Some Problems In Application," Journal of Management Studies, Wiley Blackwell, vol. 12(3), pages 266-275, October.
    6. repec:hal:wpspec:info:hdl:2441/9832 is not listed on IDEAS
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    More about this item

    Keywords

    organizational learning; manager’s decision making; bureaucracy;
    All these keywords.

    JEL classification:

    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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