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Strategies to Predict E-Commerce Inventory and Order Planning

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  • Mohammad Anwar Rahman

    (Central Connecticut State University, New Britain, CN, USA)

  • Laura Casanovas

    (Central Connecticut State University, New Britain, CN, USA)

Abstract

This study examines the characteristics of a prediction model for businesses in the online marketplace by considering the market trend, prior sales and decision maker's preference on potential demand estimate. With the rapid growth of the electronic market, the main challenge for online sellers is the ability to analyze customer expectation, market data, and sales information to make the accurate procurement decision. The proposed model integrates a mathematical structure for a target season sale comprising upcoming demand projection by seller's internal team, data from past sales and the overall trend of seller's e-brand to determine the online customer demand. The study proposed a newsvendor model as a tool for sellers to make the instantaneous decision of ordering merchandise from the supplier when the quick response to the customer order is a priority for electronic market. Results of the study provide insights into the procurement dynamics and implications of the e-commerce inventory plan.

Suggested Citation

  • Mohammad Anwar Rahman & Laura Casanovas, 2017. "Strategies to Predict E-Commerce Inventory and Order Planning," International Journal of Technology Diffusion (IJTD), IGI Global, vol. 8(4), pages 17-30, October.
    • Handle: RePEc:igg:jtd000:v:8:y:2017:i:4:p:17-30
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