Prioritizing the Recognition Pattern of Affecting Factors in Deviation of Forecasts of the Senior Managers in Organizations
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Keywords

Managers forecast disclosure, Forecast biases, Managers biased forecasts, Optimistic Bias, Pessimistic bias, Iran, Fuzzy topsis.

How to Cite

Salamzadeh, Y. ., Yekta, F. A. ., & Yavarzadeh, M. R. . (2018). Prioritizing the Recognition Pattern of Affecting Factors in Deviation of Forecasts of the Senior Managers in Organizations. International Journal of Asian Social Science, 8(7), 454–475. https://doi.org/10.18488/journal.1.2018.87.454.475

Abstract

The present study has been carried out aimed to prioritize factors affecting the deviation of forecasts of senior managers in conceptual model provided by Yavarzadeh et al. (2015) in which 38 cases of factors affecting the deviation in forecasting by senior managers in organizations have been introduced. The statistical population of this study includes middle and senior managers of one of the Iranian ministries and state-owned companies. The main questions of the questionnaire are related to all aspects of the conceptual model of the basic paper and fuzzy TOPSIS technique for the rating of each dimension of the model. According to analysis of fuzzy TOPSIS, the most important factors affecting deviation of forecasts in the dimension of deviation of management forecast by the senior manager are protection against the risk of litigation, management experiences, variable operational environment, the degree of management skills, unstructured reforms, wrong information, favorable results or favorable trends and external shocks. In the dimension of optimistic bias in the management forecast, the major factors affecting the forecast deviation respectively, appearing more productive and successful for others, more manager confidence and managers' behavioral biases and In the dimension of pessimistic bias in the management forecast, the most important factor effecting on the deviation of forecast include bad news, mandatory forecast disclosure and reducing market expectations. The result of this study can help to organizations in the field of forecasting and organizational policy, for example, attracting and promoting educated and competent human resource.

https://doi.org/10.18488/journal.1.2018.87.454.475
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