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Identification and ranking of key factors impacting efficiency of Indian shipping logistics sector

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Abstract

Shipping logistics is one of the very important criteria which can directly and indirectly affect the economy and GDP of any country. Shipping logistics depends on various factors which have been addressed by several authors in their previous studies. Studies in this literature are focused on selecting the most impactful factors among all the criteria. Methods used in this literature are fuzzy Analytical hierarchy process (AHP) and fuzzy Technique for order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria decision analysis. These methods also helped in this literature to develop a new hybrid method “fuzzy TOPSIS AHP”. There have been no studies involving maritime logistics with comparative analysis of multi-criteria decision making i.e., fuzzy AHP and fuzzy TOPSIS AHP. The literature involved large number of expert opinions on the factor prioritization of maritime logistics. Factors selected for prioritization are Environmental Sustainability, Supply and Demand, Operations and Port Selection. However, the research showed that the comparative analysis of the results was quite opposite to one another and proposed a new way for researchers to use the hybrid method of fuzzy TOPSIS AHP method in future research. The study aimed to improve the existing maritime model which can help professionals to get connected with the maritime logistics firms. The study also aims to contribute this model for researchers in their study related to maritime logistics.

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  1. Source: Ministry of Shipping-GOI, Care Ratings, Indian Ports Association, https://www.ibef.org/download/ports-mar-2019.pdf.

References

  1. Acciaro, M., Vanelslander, T., Sys, C., Ferrari, C., Roumboutsos, A., Giuliano, G., Lam, J.S.L., Kapros, S.: Environmental sustainability in seaports: a framework for successful innovation. Marit. Policy Manag. 41(5), 480–500 (2014). https://doi.org/10.1080/03088839.2014.932926

    Article  Google Scholar 

  2. Chen, C.T.: Extensions of the TOPSIS for group decision-making under fuzzy environment—(Vertex method—full formulars—do exel file). Fuzzy Sets Syst. 114(1), 1–9 (2000). https://doi.org/10.1016/S0165-0114(97)00377-1

    Article  Google Scholar 

  3. Corbett, J.J., Winebrake, J.: The Impacts of Globalisation on International Maritime Transport Activity. Springer, Berlin (2008)

    Google Scholar 

  4. D’este, G.M., Meyrick, S.: Carrier selection in a RO/RO ferry trade part. Decision factors and attitudes. Marit. Policy Manag. 19(2), 115–126 (1992). https://doi.org/10.1080/03088839200000019

    Article  Google Scholar 

  5. Daganzo, C.F.: The crane scheduling problem. Transp. Res. Part B 23(3), 159–175 (1989). https://doi.org/10.1016/0191-2615(89)90001-5

    Article  Google Scholar 

  6. Daultani, Y., Goswami, M., Vaidya, O.S., Kumar, S.: Inclusive risk modeling for manufacturing firms: a Bayesian network approach. J. Intell. Manuf. 30(8), 2789–2803 (2019)

    Article  Google Scholar 

  7. De, A., Mogale, D.G., Zhang, M., Pratap, S., Kumar, S.K., Huang, G.Q.: Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies. Int. J. Prod. Econ. 225, 107566 (2019)

    Article  Google Scholar 

  8. Ducruet, C., Lugo, I.: Cities and transport networks in shipping and logistics research. Asian J. Shipp. Logist. 29(2), 145–166 (2013). https://doi.org/10.1016/j.ajsl.2013.08.002

    Article  Google Scholar 

  9. Gupta, E.V., Mogale, D.G., Tiwari, M.K.: Optimal control of production and maintenance operations in smart custom manufacturing systems with multiple machines. IFAC-PapersOnLine 52(13), 241–246 (2019)

    Article  Google Scholar 

  10. Kumar, S., Hoffmann, J.: Globalization: the Maritime nexus. In: Grammenos, C. (ed.) Handbook of Maritime Economics and Business, pp. 35–62. Loyds List Press, London, United Kingdom (2002)

    Google Scholar 

  11. Hsieh, T.Y., Lu, S.T., Tzeng, G.H.: Fuzzy MCDM approach for planning and design tenders selection in public office buildings. Int. J. Project Manag. 22(7), 573–584 (2004). https://doi.org/10.1016/j.ijproman.2004.01.002

    Article  Google Scholar 

  12. Jugović, A., Komadina, N., Hadžić, A.P.: Factors influencing the formation of freight rates on maritime shipping markets. Sci. J. Marit. Res. 29, 23–29 (2015)

    Google Scholar 

  13. Kim, K.H., Moon, K.C.: Berth scheduling by simulated annealing. Transp. Res. Part B Methodol. 37(6), 541–560 (2003). https://doi.org/10.1016/S0191-2615(02)00027-9

    Article  Google Scholar 

  14. Le, T.V., Stathopoulos, A., Van Woensel, T., Ukkusuri, S.V.: Supply, demand, operations, and management of crowd-shipping services: a review and empirical evidence. Transp. Res. Part C Emerg. Technol. 103(March), 83–103 (2019). https://doi.org/10.1016/j.trc.2019.03.023

    Article  Google Scholar 

  15. McGinnis, L.M.: Maternal separation vs removal prom group companions in rhesus monkeys. J. Child Psychol. Psychiatry 20(1), 15–27 (1979). https://doi.org/10.1111/j.1469-7610.1979.tb01703.x

    Article  Google Scholar 

  16. Meena, S.R., Meena, S.D., Pratap, S., Patidar, R., Daultani, Y.: Strategic analysis of the Indian agri-food supply chain. Opsearch 56(3), 965–982 (2019). https://doi.org/10.1007/s12597-019-00380-5

    Article  Google Scholar 

  17. Mogale, D.G., Lahoti, G., Jha, S.B., Shukla, M., Kamath, N., Tiwari, M.K.: Dual market facility network design under bounded rationality. Algorithms 11(4), 54 (2018)

    Article  Google Scholar 

  18. Mogale, D.G., Ghadge, A., Kumar, S.K., Tiwari, M.K.: Modelling supply chain network for procurement of food grains in India. Int. J. Prod. Res. (2019a). https://doi.org/10.1080/00207543.2019.1682707

    Article  Google Scholar 

  19. Mogale, D.G., Cheikhrouhou, N., Tiwari, M.K.: Modelling of sustainable food grain supply chain distribution system: a bi-objective approach. Int. J. Prod. Res. (2019b). https://doi.org/10.1080/00207543.2019.1669840

    Article  Google Scholar 

  20. Pham, H.C., Nguyen, T.T., Mcdonald, S., Tran-Kieu, N.Q.: Information sharing in logistics firms: an exploratory study of the Vietnamese logistics sector. Asian J. Shipp. Logist. 35(2), 87–95 (2019). https://doi.org/10.1016/j.ajsl.2019.06.001

    Article  Google Scholar 

  21. Pratap, S., Daultani, Y., Tiwari, M.K., Mahanty, B.: Rule based optimization for a bulk handling port operations. J. Intell. Manuf. 29(2), 287–311 (2018)

    Article  Google Scholar 

  22. Psaraftis, H.N.: Green maritime logistics: the quest for win-win solutions. Transp. Res. Procedia 14, 133–142 (2016). https://doi.org/10.1016/j.trpro.2016.05.049

    Article  Google Scholar 

  23. Rødseth, K.L., Wangsness, P.B., Schøyen, H.: How do economies of density in container handling operations affect ships’ time and emissions in port? Evidence from Norwegian container terminals. Transp. Res. Part D Transp. Environ. 59, 385–399 (2018). https://doi.org/10.1016/j.trd.2017.12.015

    Article  Google Scholar 

  24. Saaty, T.L.: How to make a decision: advice for scientists. Eur. J. Oper. Res. 48, 9–26 (1990)

    Article  Google Scholar 

  25. Sayareh, J., Alizmini, H.R.: A hybrid decision-making model for selecting container seaport in the persian gulf. Asian J. Shipp. Logist. 30(1), 75–95 (2014). https://doi.org/10.1016/j.ajsl.2014.04.004

    Article  Google Scholar 

  26. Seo, Y.J., Ha, M.H., Yang, Z., Bhattacharya, S.: The ship management firm selection: the case of South Korea. Asian J. Shipp. Logist. 34(3), 258–268 (2018). https://doi.org/10.1016/j.ajsl.2018.09.008

    Article  Google Scholar 

  27. Singh, S.H., Maiyar, L.M., Bhowmick, B.: Assessing the appropriate grassroots technological innovation for sustainable development. Technol. Anal. Strateg. Manag. 32(2), 175–194 (2020)

    Article  Google Scholar 

  28. Sirisawat, P., Kiatcharoenpol, T.: Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers. Comput. Ind. Eng. 117, 303–318 (2018). https://doi.org/10.1016/j.cie.2018.01.015

    Article  Google Scholar 

  29. Tong, J., Nachtmann, H.: Cargo prioritization and terminal allocation problem for inland waterway disruptions oa. Marit. Econ. Logist. 19(3), 403–427 (2017). https://doi.org/10.1057/mel.2015.34

    Article  Google Scholar 

  30. Trishala, S.: Insights into the Indian Maritime Industry and ports in India, pp. 1–26 (2016). http://www.aivp.org/wp-content/uploads/2016/06/suresh_trishala_indian_maritime_industry.pdf

  31. Ugboma, C., Ugboma, O., Ogwude, I.C.: An analytic hierarchy process (AHP) approach to port selection decisions—empirical evidence from Nigerian ports. Marit. Econ. Logist. 8(3), 251–266 (2006). https://doi.org/10.1057/palgrave.mel.9100160

    Article  Google Scholar 

  32. Ursavas, E.: Crane allocation with stability considerations OA. Marit. Econ. Logist. 19(2), 379–401 (2017). https://doi.org/10.1057/mel.2015.35

    Article  Google Scholar 

  33. Venkita Subramanian, K., Thill, J.C.: Effect of privatization and inland infrastructural development on India’s container port selection dynamics. Asian J. Shipp. Logist. 35(4), 220–229 (2019). https://doi.org/10.1016/j.ajsl.2019.12.009

    Article  Google Scholar 

  34. Zeng, Q., Feng, Y., Chen, Z.: Optimizing berth allocation and storage space in direct transshipment operations at container terminals oa. Marit. Econ. Logist. 19(3), 474–503 (2017). https://doi.org/10.1057/mel.2016.2

    Article  Google Scholar 

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Acknowledgements

Authors thank anonymous reviewers for their constructive comments.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, India

    Dhirendra Prajapati & Saurabh Pratap

  2. Operations Management Group, Indian Institute of Management, Lucknow, India

    Yash Daultani

  3. Geneva School of Business Administration, HES-SO, University of Applied Sciences Western Switzerland, Geneva, Switzerland

    Naoufel Cheikhrouhou

Authors
  1. Dhirendra Prajapati
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  2. Yash Daultani
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  3. Naoufel Cheikhrouhou
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  4. Saurabh Pratap
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Correspondence to Saurabh Pratap.

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Prajapati, D., Daultani, Y., Cheikhrouhou, N. et al. Identification and ranking of key factors impacting efficiency of Indian shipping logistics sector. OPSEARCH 57, 765–786 (2020). https://doi.org/10.1007/s12597-020-00442-z

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