The grey input‐occupancy‐output analysis

The grey input‐occupancy‐output analysis Purpose – The purpose of this paper is to propose the input‐occupancy‐output analysis for grey situations and to manage the economic systems with missing information. The situation is realistic in practice. Design/methodology/approach – During the decision‐making process of an economic system, the managers often get some uncertain data for the missing information. Then, it becomes difficult to analyze the complex system by using the input‐occupancy‐output analysis. Since the uncertain data are grey numbers, the decision maker can control it by using grey system theory and the input‐occupancy‐output analysis. Findings – Get the grey direct consumption and occupancy coefficient matrices and the computational formulas of their matrix‐covered sets. The grey model of input‐occupancy‐output analysis and its covered solution are also obtained. Research limitations/implications – The chaos of the grey statistic data should satisfy a level of accuracy and it is key to get the number‐covered set that the true data belongs to. Practical implications – A feasible approach to control the economic system that the accurate data are difficult to be obtained. Originality/value – Give a new approach to study an economic system by using grey system theory. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

The grey input‐occupancy‐output analysis

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Abstract

Purpose – The purpose of this paper is to propose the input‐occupancy‐output analysis for grey situations and to manage the economic systems with missing information. The situation is realistic in practice. Design/methodology/approach – During the decision‐making process of an economic system, the managers often get some uncertain data for the missing information. Then, it becomes difficult to analyze the complex system by using the input‐occupancy‐output analysis. Since the uncertain data are grey numbers, the decision maker can control it by using grey system theory and the input‐occupancy‐output analysis. Findings – Get the grey direct consumption and occupancy coefficient matrices and the computational formulas of their matrix‐covered sets. The grey model of input‐occupancy‐output analysis and its covered solution are also obtained. Research limitations/implications – The chaos of the grey statistic data should satisfy a level of accuracy and it is key to get the number‐covered set that the true data belongs to. Practical implications – A feasible approach to control the economic system that the accurate data are difficult to be obtained. Originality/value – Give a new approach to study an economic system by using grey system theory.

Journal

KybernetesEmerald Publishing

Published: Jan 1, 2009

Keywords: Systems theory; Input‐output analysis; Consumption; Uncertainty managenent; Cybernetics

References

  • Grey model of direct solar radiation intensity on the horizontal plane for cooling loads calculation
    Hu, W.B.; Yang, C.Z.
  • Theory of grey systems: capturing uncertainties of grey information
    Lin, Y.; Chen, M.‐Y.; Liu, S.‐F.
  • Exponential prediction models based on sequence operators
    Sydow, A.; Lin, Y.; Liu, S‐F.; DeNu, R.; Mennell, W.

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