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Competition can help predict sales

Author

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  • Sima M. Fortsch
  • Jeong Hoon Choi
  • Elena A. Khapalova
Abstract
This paper develops linear and nonlinear forecasting models to propose a sophisticated and accurate forecasting method in a fiercely competitive environment, such as the U.S. auto industry. Our results indicate that companies could operate successfully in a highly competitive market by using the competitors' sales to accurately predict their sales and plan for raw material, production, and finished goods inventories. Our suggested methodology is beneficial when the competitors are within similar strategic groups. The data for this study are obtained from the “U.S. Automotive News” data services, which contain time series records for inventory and sales for multiple automakers. To keep the analysis straightforward, we have chosen data for four major automotive companies known for their high‐level competition: the General Motors Company, the Ford Company, the Toyota Corporation, and the Honda Company because of intense rivalry due to competing within the same strategic business units. The results show a benefit is achieved by including the total sales for at least one competitor in the linear or the nonlinear forecasting models to predict domestic sales for the desired company.

Suggested Citation

  • Sima M. Fortsch & Jeong Hoon Choi & Elena A. Khapalova, 2022. "Competition can help predict sales," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 331-344, March.
    • Handle: RePEc:wly:jforec:v:41:y:2022:i:2:p:331-344
    DOI: 10.1002/for.2818
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    References listed on IDEAS

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    1. Vinay Singh & Bhasker Choubey & Stephan Sauer, 2024. "Liquidity forecasting at corporate and subsidiary levels using machine learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(3), September.

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