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A performance evaluation model for supply chain of shipping company in Iran: an application of the relational network DEA

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  • Hashem Omrani
  • Mehdi Keshavarz

Abstract

Shipping business is capital intensive and highly competitive. It necessitates for the shipping companies to constantly monitor their performance and measure relative efficiencies of their supply chains. Despite such importance, the studies devoted to this field have been surprisingly limited. This paper reviews the involved factors and proposes a relational network data envelopment analysis (DEA) model for measuring the efficiency of supply chain of an international shipping company in Iran with relevant sub-processes in the period 2008--2011. First, the supply chain network of the company is illustrated and then the input and output variables associated to each member are determined. The proposed model is suitable for shipping companies which usually use similar pattern in this business. Finally based on the results, recommendations are made for improvements and a new field of business is also proposed.

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  • Hashem Omrani & Mehdi Keshavarz, 2016. "A performance evaluation model for supply chain of shipping company in Iran: an application of the relational network DEA," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(1), pages 121-135, January.
    • Handle: RePEc:taf:marpmg:v:43:y:2016:i:1:p:121-135
    DOI: 10.1080/03088839.2015.1036471
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    Cited by:

    1. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    2. Shiva Moslemi & Hamidreza Izadbakhsh & Marzieh Zarinbal, 2019. "A new reliable performance evaluation model: IFB-IER–DEA," OPSEARCH, Springer;Operational Research Society of India, vol. 56(1), pages 14-31, March.
    3. Shankar, Ravi & Pathak, Devendra Kumar & Choudhary, Devendra, 2019. "Decarbonizing freight transportation: An integrated EFA-TISM approach to model enablers of dedicated freight corridors," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 85-100.
    4. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.
    5. H. Pierre Hsieh & Kuo‐Cheng Kuo & Minh‐Hieu Le & Wen‐Min Lu, 2021. "Exploring the cargo and eco‐efficiencies of international container shipping companies: A network‐based ranking approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 45-60, January.
    6. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    7. Shiva Moslemi & Abolfazl Mirzazadeh & Gerhard-Wilhelm Weber & Mohammad Ali Sobhanallahi, 2022. "Integration of neural network and AP-NDEA model for performance evaluation of sustainable pharmaceutical supply chain," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1116-1157, September.
    8. Joe Zhu, 2022. "DEA under big data: data enabled analytics and network data envelopment analysis," Annals of Operations Research, Springer, vol. 309(2), pages 761-783, February.

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