A Novel Group Decision Making Model to Compare Online Shopping Platforms

Sanjib Biswas; Biplab Biswas; Kaushik Mitra

doi:10.31181/sdmap2120259

Authors

Sanjib Biswas Amity Business School, Amity University Kolkata, Major Arterial Road, AA II, Newtown, West Bengal 700135, India Author https://orcid.org/0000-0002-9243-2403
Biplab Biswas Amity Business School, Amity University Kolkata, Major Arterial Road, AA II, Newtown, West Bengal 700135, India Author https://orcid.org/0000-0001-5869-4998
Kaushik Mitra Amity Business School, Amity University Kolkata, Major Arterial Road, AA II, Newtown, West Bengal 700135, India Author https://orcid.org/0000-0002-3507-5999

DOI:

https://doi.org/10.31181/sdmap2120259

Keywords:

E-commerce, CIMAS, Borda count, RAM, Modified preference selection index, Double normalization

Abstract

Over the years, E-commerce industry has been witnessing a phenomenal growth, thanks to rapid technological advancement in Industry 4.0. There has been a standout surge in the use of various online shopping platforms (OSP) for daily use. The recent pandemic has accelerated the growth trajectory and made a transformational change in the digital commerce landscape. As a result, there has been a proliferation of OSPs in the competitive domain. It is therefore pertinent to address the questions: How do the customers select their favorite OSP? To what extent the OSPs differ based on consumers’ preferences? The present work addresses these questions by proposing a novel group decision making framework. The ongoing study provides several innovative extensions of multi criteria decision making models like Borda count, criteria importance assessment (CIMAS), modified preference selection index (MPSI), and root assessment method (RAM). In this paper, the researchers provide a novel use of the Borda count method, integrated with CIMAS for determining criteria weights utilizing ranking of the criteria. Further, a novel extension of MPSI and RAM has been made with multiple normalizations. In this paper, the authors demonstrate a rare combination of vector and non-linear normalization using the Heron mean. The present paper derives the final criteria weights by combining Borda count, CIMAS and multi-normalization based MPSI (MNMPSI) using Bayesian logic. The criteria are selected based on Uses and Gratification theory (UGT). The findings reveal that interactive app interface and features (C16), user-friendly interface and search (C13), convenience in shopping (C14), product availability and variety (C12) and discounts and offers (C8) exert significant influence in selecting the OSP. Further, it is observed that Flipkart (A2) and Amazon (A1) are the top performers in the eyes of the users. The stability and reliability of the proposed methodology are examined by conducting a sensitivity analysis and comparing with several other models. The robustness of the proposed methodology and practical relevance of the findings of the present work shall provide notable impetus to the analysts and strategic decision-makers.

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Biswas, S., & Pamučar, D. S. (2021). Combinative distance-based assessment (CODAS) framework using logarithmic normalization for multi-criteria decision making. Serbian Journal of Management, 16(2), 321-340. https://doi.org/10.5937/sjm16-27758

Deveci, M., Gokasar, I., Pamucar, D., Biswas, S., & Simic, V. (2022). An integrated proximity indexed value and q-rung orthopair fuzzy decision-making model for prioritization of green campus transportation. In q-Rung orthopair fuzzy sets: theory and applications (pp. 303-332). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-1449-2_12

Biswas, S., Pamučar, D., Božanić, D., & Halder, B. (2022). A New Spherical Fuzzy LBWA‐MULTIMOOSRAL Framework: Application in Evaluation of Leanness of MSMEs in India. Mathematical Problems in Engineering, 2022(1), 5480848. https://doi.org/10.1155/2022/5480848

Pamucar, D., & Biswas, S. (2023). A novel hybrid decision making framework for comparing market performance of metaverse crypto assets. Decision Making Advances, 1(1), 49-62. https://doi.org/10.31181/dma1120238

Puška, A., Štilić, A., Nedeljković, M., Božanić, D., & Biswas, S. (2023). Integrating fuzzy rough sets with LMAW and MABAC for green supplier selection in agribusiness. Axioms, 12(8), 746. https://doi.org/10.3390/axioms12080746

Sanyal, A., Biswas, S., & Sur, S. (2024). An Integrated Full Consistent LOPCOW-EDAS Framework for Modelling Consumer Decision Making for Organic Food Selection. Yugoslav Journal of Operations Research. http://dx.doi.org/10.2298/YJOR240315022S

Biswas, S., Pamucar, D., Dawn, S., & Simic, V. (2024). Evaluation based on relative utility and nonlinear standardization (ERUNS) method for comparing firm performance in energy sector. Decision Making Advances, 2(1), 1-21. https://doi.org/10.31181/dma21202419

Biswas, S., Pamucar, D., & Kar, S. (2022b). A preference-based comparison of select over-the-top video streaming platforms with picture fuzzy information. International Journal of Communication Networks and Distributed Systems, 28(4), 414-458. https://doi.org/10.1504/IJCNDS.2022.123872

Božanić, D., Epler, I., Puška, A., Biswas, S., Marinković, D., & Koprivica, S. (2024). Application of the DIBR II–rough MABAC decision-making model for ranking methods and techniques of lean organization systems management in the process of technical maintenance. Facta Universitatis, Series: Mechanical Engineering, 22(1), 101-123. https://doi.org/10.22190/FUME230614026B

Görçün, Ö. F., Pamucar, D., & Biswas, S. (2023). The blockchain technology selection in the logistics industry using a novel MCDM framework based on Fermatean fuzzy sets and Dombi aggregation. Information Sciences, 635, 345-374. https://doi.org/10.1016/j.ins.2023.03.113

Pamucar, D., Torkayesh, A. E., & Biswas, S. (2023). Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 328(1), 977-1019. https://doi.org/10.1007/s10479-022-04529-2