A multi-criteria decision making approach to evaluating the performance of Indian railway zones

Esther Jose, Puneet Agarwal, Jun Zhuang and Jose Swaminathan ()
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Esther Jose: University at Buffalo
Puneet Agarwal: California Polytechnic State University
Jun Zhuang: University at Buffalo
Jose Swaminathan: Vellore Institute of Technology

Annals of Operations Research, 2023, vol. 325, issue 2, No 16, 1133-1168

Abstract: Abstract The Indian Railways is India’s biggest employer and undeniably influences the country’s transportation network, economy, and social and cultural systems. The network is split into zones for operational reasons. It is vital to evaluate these railway networks to identify their strengths and shortcomings and to improve their performance. Past works often use Data Envelopment Analysis to evaluate railway services. Our contribution lies in the inclusion of several aspects not previously considered, such as (i) both tangible and intangible criteria, (ii) the hierarchical nature of the problem, and (iii) additional useful criteria and data to analyze the performance of the zones, including physical assets, operating ratio, accidents, comfort, travel experience, flexibility, transparency, etc. We use the novel Hierarchical Fuzzy Axiomatic Design method to evaluate the performance of sixteen zones in the Indian Railways since it suits our problem well. We find that the Southern Railway zone performs best, while the Northeast Frontier zone is ranked last. We also identify the strengths and weaknesses of all railway zones.

Keywords: Multi-criteria decision making; Performance evaluation; Fuzzy axiomatic design; Railways; Ranking (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-022-04866-2

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