Designing a hybrid approach based on Analytic Network Process and Fuzzy DEMATEL for performance evaluation of province in road transportation area

Document Type : Scientific - Research

Authors

Tehran University

Abstract

The continuous improvement in organizations performance depends on their continuous goal oriented evaluation. One of the most critical and important areas of world is the transportation area, that is categorized into three groups of railway, air and road transportation. Iran by transporting 600 million tons of goods, 900 million persons, 10 million tons of transit per year, performs the transportation of 90 percent of this on its own. In the road transportation section 423000 truck are utilized to transport goods, which these trucks are derived by 464000 drivers. Also so far (1394) number of 4299 companies/ institutes activate in road good transportation. The performance improvement of these companies/ institutes is closely depend on performance evaluation and identifying the strengths and weaknesses, that they can improve their performance by reinforcement of these strengths and stabilization of weaknesses. In order to present an efficient performance evaluation approach, the appropriate criteria and effective and efficient model must be selected. Therefore, the current paper for the purpose of measuring the efficiency of Iranian provincial road transportation, presents a combined novel approach based on analytical network process and fuzzy Decision Making Trial And Evaluation (DEAMATEL). The analytical network process is applied to weight the criteria and fuzzy Decision Making Trial And Evaluation (DEAMATEL) was utilized to calculate the inter dependencies between criteria. Then by utilizing the information of each province, the effectiveness of the model will be determined. The obtained results represents the effectiveness and efficiency of proposed approach and was confirmed by experts organization

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References

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History

  • Receive Date: 24 January 2017
  • Revise Date: 14 July 2017
  • Accept Date: 24 July 2017

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