Dynamic Modeling of Controllable Returns in E-commerce: The Impact of Seller Restrictions on Platforms

Document Type : Research Article

Authors

• Ameneh Khadivar ¹
• Maedeh Norouzi ¹
• Masoud Hadi Najafabadi ²

¹ Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

² Department of Industrial Engineering, Faculty of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran.

10.22067/jstinp.2024.88156.1105

Abstract

Effective operations management is pivotal in driving revenue and profitability for organizations in today’s business world, particularly in e-commerce and online markets. Among the critical areas of operations management, product returns have garnered increasing attention. Although product returns could benefit businesses by increasing customer loyalty, trust, and satisfaction, reducing advertising costs, and attracting new customers for sellers, they can also harm sellers by increasing transportation costs, reducing profits, and affecting product quality. As a result, e-commerce platforms need to determine an optimal level of strictness in product returns policy. This study examines the dynamic model of seller-controllable returns in e-commerce platforms and investigates how imposing restrictions on sellers with high return rates influences overall return volume. The findings demonstrate that as seller restrictions tighten, the return rate decreases, suggesting that e-commerce platforms should consider implementing policies restricting sellers with high return rates to reduce their product returns.

Keywords

• Product Returns
• Return Policies
• E-Commerce Platforms
• System Dynamics

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References

Abdulla, H., Abbey, J.D. and Ketzenberg, M., 2022. How consumers value retailer's return policy leniency levers: An empirical investigation. Production and Operations Management, 31(4), pp.1719-1733. https://doi.org/10.1111/poms.13640.

Alamerew, Y.A. and Brissaud, D., 2020. Modelling reverse supply chain through system dynamics for realizing the transition towards the circular economy: A case study on electric vehicle batteries. Journal of Cleaner Production, 254, p.120025. https://doi.org/10.1016/j.jclepro.2020.120025.

Ambilkar, P., Dohale, V., Gunasekaran, A. and Bilolikar, V., 2022. Product returns management: a comprehensive review and future research agenda. International Journal of Production Research, 60(12), pp.3920-3944. https://doi.org/10.1080/00207543.2021.1933645.

Bradley, C., Kohli, S., Kuijpers, D. and Rüdiger Smith, T., 2021. Why retail outperformers are pulling ahead. McKinsey & Company [online]. Available at: https://www.mckinsey.com/industries/retail/our-insights/why-retail-outperformers-are-pulling-ahead.

Dholakia, R.R., Zhao, M. and Dholakia, N., 2005. Multichannel retailing: A case study of early experiences. Journal of interactive marketing, 19(2), pp.63-74. https://doi.org/10.1002/dir.20035.

Forrester, J. W. and  Senge, P. M., 1980. Tests for building confidence in system dynamics models. System dynamics, TIMS studies in management sciences, 14(14), pp.209-228. URL: https://www.albany.edu/faculty/gpr/PAD724/724WebArticles.

Ghandour, A., Parackal, M. and Deans, K.R., 2023. A Framework for Relationships in eCommerce Websites. International Journal of E-Business Research (IJEBR), 19(1), pp.1-17. https://doi.org/10.4018/IJEBR.317411.

Griffis, S.E., Rao, S., Goldsby, T.J. and Niranjan, T.T., 2012. The customer consequences of returns in online retailing: An empirical analysis. Journal of operations management, 30(4), pp.282-294. https://doi.org/10.1016/j.jom.2012.02.002.

Gupta, S., Kushwaha, P.S., Badhera, U., Chatterjee, P. and Gonzalez, E.D.S., 2023. Identification of benefits, challenges, and pathways in E-commerce industries: An integrated two-phase decision-making model. Sustainable Operations and Computers, 4, pp.200-218. https://doi.org/10.1016/j.susoc.2023.08.005.

Stock, J., Speh, T. and Shear, H., 2006. Managing product returns for competitive advantage. MIT Sloan management review, 48(1), p.57. https://dialnet.unirioja.es/servlet/articulo?codigo=2124939.

Karlsson, S., Oghazi, P., Hellstrom, D., Patel, P.C., Papadopoulou, C. and Hjort, K., 2023. Retail returns management strategy: An alignment perspective. Journal of Innovation & Knowledge, 8(4), p.100420. https://doi.org/10.1016/j.jik.2023.100420.

Kaveh Pishghadam, H. and Esmaeeli, H., 2021. A system dynamics model for evaluating the firms' capabilities in maintenance outsourcing and analyzing the profitability of outsourcing. Scientia Iranica, 30(2), pp.712-726. https://doi.org/10.24200/sci.2021.55108.4080.

Khadivar, A., Rostami, M. R., Keshmiri, A. and Rahimian, S., 2024. Modeling the Cost of Banking Services Using the Activity-Based Costing Method and System Dynamics. Journal of Industrial Management Perspective, 14(2), pp.206-229. doi: 10.48308/jimp.14.2.206.

Li, D., Chen, J., Chen, B. and Liao, Y., 2022. Manufacturer’s contract choice and retailer’s returns management strategy. Transportation Research Part E: Logistics and Transportation Review, 165, p.102862. https://doi.org/10.1016/j.tre.2022.102862.

Liu, P., Hendalianpour, A., Hafshejani, M.F., Yaghoobi, F. and Feylizadeh, M., 2023. System dynamics model: developing model for supplier selection with a focus on CSR criteria. Complex & Intelligent Systems, 9(1), pp.99-114. https://doi.org/10.1007/s40747-022-00788-5.

Mostaghel R., Oghazi, P., Parida, V. and Sohrabpour, V., 2022. Digitalization driven retail business model innovation: Evaluation of past and avenues for future research trends. Journal of Business Research, 146, pp.134-145. https://doi.org/10.1016/j.jbusres.2022.03.072.

Patro, C.S., 2023. Consumers' Digital Shopping Experience: A Study of the Factors Influencing Purchase Decision. International Journal of E-Business Research (IJEBR), 19(1), pp.1-17. https://doi.org/10.4018/ijebr.318475.

Peck, J. and Childers, T.L., 2003. To have and to hold: The influence of haptic information on product judgments. Journal of marketing, 67(2), pp.35-48. https://doi.org/10.1509/jmkg.67.2.35.18612.

Petersen, J.A. and Kumar, V., 2010. Can product returns make you money?. MIT Sloan Management Review. Available at: https://sloanreview.mit.edu/article/can-product-returns-make-you-money/.

Prashar, S., Vijay, T.S. and Parsad, C., 2015. Antecedents to online shopping: Factors influencing the selection of web portal. International Journal of E-Business Research (IJEBR), 11(1), pp.35-55. https://doi.org/10.4018/ijebr.2015010103.

Ramcharran, H., 2013. E-commerce growth and the changing structure of the retail sales industry. International Journal of E-Business Research (IJEBR), 9(2), pp.46-60. https://doi.org/10.4018/jebr.2013040104.

Rogers, D.S., Lambert, D.M., Croxton, K.L. and García-Dastugue, S.J., 2002. The returns management process. The international journal of logistics management, 13(2), pp.1-18. https://doi.org/10.1108/09574090210806397.

Rokonuzzaman, M., Iyer, P. and Harun, A., 2021. Return policy, No joke: An investigation into the impact of a retailer's return policy on consumers' decision making. Journal of Retailing and Consumer Services, 59, p.102346. https://doi.org/10.1016/j.jretconser.2020.102346.

Russo I., Confente, I. and Borghesi, A., 2018. Consumer satisfaction and loyalty in digital markets: Exploring the impact of their antecedents. In Digital Technology and Organizational Change: Reshaping Technology, People, and Organizations Towards a Global Society (pp. 141-148). Springer International Publishing. https://doi.org/10.1007/978-3-319-62051-0_12.

Saghaei, A., Khadivar, A. and Khani, M., 2022. Modeling new product diffusion in a competitive market using agent-based simulation. Journal of Systems Thinking in Practice, 1(1). https://doi.org/10.1234/jstp.2022.0123.

Son, Son, J., Kang, J.H. and Jang, S., 2019. The effects of out-of-stock, return, and cancellation amounts on the order amounts of an online retailer. Journal of Retailing and Consumer Services, 51, pp.421-427. https://doi.org/10.1016/j.jretconser.2019.02.008.

Ventana Systems Inc. (2023). Vensim. Available at: https://vensim.com/software.

Yan, Q, Zhou S, Zhang X, Li Y. A system dynamics model of online stores’ sales: Positive and negative E-WOM and promotion perspective. Sustainability. 2019 Oct 31;11(21):6045. https://doi.org/10.3390/su11216045.