Incorporating AHP and Evidential Reasoning for Quantitative Evaluation of Inland Port Performance

Chengpeng Wan, Di Zhang () and Hang Fang
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Chengpeng Wan: Wuhan University of Technology
Di Zhang: Wuhan University of Technology
Hang Fang: Wuhan University of Technology

Chapter Chapter 7 in Multi-Criteria Decision Making in Maritime Studies and Logistics, 2018, pp 151-173 from Springer

Abstract: Abstract Inland ports are core strategic resources promoting the development of regional economy. They are not only connections between production and consumption, domestic and foreign freight transport, but also critical infrastructure supporting the national and regional economic development, whose performance will inevitably influence the economy of the port city and even the relevant hinterlands. Thus, the measurement of inland port performance is of great significance in order to improve its performance and facilitate its development. Based on the literature review of port performance evaluation and brainstorms with domain experts, an assessment model for quantitatively measuring inland port performance is established in a three-level hierarchical structure composing of a goal level, a criteria level, and an index level. The relative importance of each criterion is obtained through the Analytic Hierarchy Process (AHP) method and evaluation results in the index level are then aggregated and calculated using the Evidential Reasoning approach. Based on a utility function, the performance of inland port is represented in the form of a crisp value for comparison in different years. The application of the assessment model is demonstrated using a case of the Port of Wuhan. The results of case study indicate that the assessment model developed in this chapter is able to provide insights for the evaluation of the performance of inland ports in different countries.

Keywords: Inland port performance; Inland waterway transportation; Evidential reasoning; Hierarchical model; Analytic hierarchy process (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/978-3-319-62338-2_7

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