New Product Life Cycle Curve Modeling and Forecasting with Product Attributes and Promotion: A Bayesian Functional Approach

36 Pages Posted: 1 Mar 2022 Last revised: 19 Sep 2022

See all articles by Dazhou Lei

Dazhou Lei

Tsinghua University - Department of Industrial Engineering

Hao Hu

JD.com Smart Supply Chain Y

Dongyang Geng

JD.com Smart Supply Chain Y

Jianshen Zhang

JD.com Smart Supply Chain Y

Yongzhi Qi

JD.com Smart Supply Chain Y

Sheng Liu

Rotman School of Management

Zuo-Jun Max Shen

University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR)

Date Written: January 12, 2022

Abstract

New products are highly valued by manufacturers and retailers due to their vital role in revenue generation. Product life cycle curves often vary by their shapes and are complicated by promotional activities that induce spiky and irregular behaviors. We collaborate with JD.com to develop a flexible product life cycle curve forecasting framework based on Bayesian functional regression that accounts for useful covariate information, including product attributes and promotion. The functional model treats product life cycle curves as target variables and includes both scalar and functional predictors, capturing time-varying promotional activities. Harnessing the power of basis function transformation, the developed model can effectively characterize the local features and temporal evolution of sales curves. Our Bayesian framework can generate initial curve forecasts before the product launch and update the forecasts dynamically as new sales data is collected. We validate the superior performance of our framework through extensive numerical experiments using three real-world data sets. Compared to the forecasting method of JD.com, our framework can reduce the forecasting error by more than 17%. The improvements are consistently observed across other data sets. Furthermore, the estimated promotion effect function provides useful insights into how promotional activities interact with sales curves.

Keywords: Product life cycle, Sales forecasting, Bayesian model, Functional regression

Suggested Citation

Lei, Dazhou and Hu, Hao and Geng, Dongyang and Zhang, Jianshen and Qi, Yongzhi and Liu, Sheng and Shen, Zuo-Jun Max, New Product Life Cycle Curve Modeling and Forecasting with Product Attributes and Promotion: A Bayesian Functional Approach (January 12, 2022). Rotman School of Management Working Paper No. 4014586, Available at SSRN: https://ssrn.com/abstract=4014586 or http://dx.doi.org/10.2139/ssrn.4014586

Dazhou Lei

Tsinghua University - Department of Industrial Engineering ( email )

Beijing
China

Hao Hu

JD.com Smart Supply Chain Y ( email )

Dongyang Geng

JD.com Smart Supply Chain Y ( email )

Jianshen Zhang

JD.com Smart Supply Chain Y ( email )

Yongzhi Qi

JD.com Smart Supply Chain Y ( email )

Sheng Liu (Contact Author)

Rotman School of Management ( email )

105 St. George st
Toronto, ON M5S 3E6
Canada

Zuo-Jun Max Shen

University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR) ( email )

IEOR Department
4135 Etcheverry Hall
Berkeley, CA 94720
United States

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