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Artemis time: A mathematical model to calculate maximum acceptable waiting time in B2C e-commerce

Author

Listed:
  • Ehsan Mousavi Khaneghah
  • Nosratollah Shadnoush
  • Amin Salem

Abstract

One of the main challenges in e-commerce is how to calculate the maximum acceptable time for response to the customer from the business firms. This case has a direct impact on many business concepts such as customer loyalty, satisfaction, and trust. In this paper, a mathematical model is presented to calculate the maximum acceptable time. In this regard, based on a set of functions, while investigating factors affecting the business from customer’s perspective, this mathematical model has the ability to use in any kind of B2C-based e-commerce system due to the consideration of the partial elongation set between elements that affect time transparency. The business using this function and managing the elements that affect this function is able to manage its operations in a way that conducts business activities in accordance with client time estimates. This will increase satisfaction and customer’ trust in the business.

Suggested Citation

  • Ehsan Mousavi Khaneghah & Nosratollah Shadnoush & Amin Salem, 2017. "Artemis time: A mathematical model to calculate maximum acceptable waiting time in B2C e-commerce," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1405509-140, January.
  • Handle: RePEc:taf:oabmxx:v:4:y:2017:i:1:p:1405509
    DOI: 10.1080/23311975.2017.1405509
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    References listed on IDEAS

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    1. Giampaolo Viglia, 2014. "Pricing, Online Marketing Behavior, and Analytics," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-41326-0, December.
    2. Hackl, Franz & Kummer, Michael E. & Winter-Ebmer, Rudolf & Zulehner, Christine, 2014. "Market structure and market performance in E-commerce," European Economic Review, Elsevier, vol. 68(C), pages 199-218.
    3. Nicolas Poggi & David Carrera & Ricard Gavaldà & Eduard Ayguadé & Jordi Torres, 2014. "A methodology for the evaluation of high response time on E-commerce users and sales," Information Systems Frontiers, Springer, vol. 16(5), pages 867-885, November.
    4. Dickinger, Astrid & Stangl, Brigitte, 2013. "Website performance and behavioral consequences: A formative measurement approach," Journal of Business Research, Elsevier, vol. 66(6), pages 771-777.
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