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A computing theory for collaborative and transparent decision making under time constraint

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  • Hideyasu Sasaki

    (Ritsumeikan University)

Abstract

In this paper, we present a computing theory on the accelerated critical point of selection of proper strategies between collaboration and competition and its mathematical analysis for collaborative and transparent decision making under “time constraint”, i.e., cost of time pressure, which decision makers face in negotiation. Web 2.0 provides a useful digital environment to support various time-stressed human behaviors for collaborative decision making. However, little research has examined the collaborative behavior under time constraint on the Internet in its designs and implementations on electronically supported decision making. Those systems are implemented in black boxes so that we need transparent designs of decision support systems to promote collaboration by time-stressed decision makers. The essential problem on collaborative decision making under time constraint is the discovery and evaluation on the critical point of selection of proper strategies between collaboration and competition. Most of the current decision support systems accept the half of maximum acceptable time for negotiation as a critical point, a priori, though that conventional point is often late for proper decision making. The proposed theory shows that a critical point is to be accelerated at the one-third of maximum acceptable time for negotiation. We have formulated the proposed computing theory based on mathematical formulation, and checked its feasibility in its applications to a case study. The proposed theory promotes collaborative and transparent decision making in consideration of the properties of stakes under time pressure by selecting the strategy of collaboration or competition at the much earlier stage.

Suggested Citation

  • Hideyasu Sasaki, 2011. "A computing theory for collaborative and transparent decision making under time constraint," Information Systems Frontiers, Springer, vol. 13(2), pages 207-220, April.
  • Handle: RePEc:spr:infosf:v:13:y:2011:i:2:d:10.1007_s10796-009-9189-5
    DOI: 10.1007/s10796-009-9189-5
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    References listed on IDEAS

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    Cited by:

    1. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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