Skip to main content

Intertemporal Content Variation with Customer Learning

Publication ,  Journal Article
Bernstein, F; Chakraborty, S; Swinney, R
Published in: Manufacturing and Service Operations Management
May 1, 2022

Problem definition: We analyze a firm that sells repeatedly to a customer population over multiple periods. Although this setting has been studied extensively in the context of dynamic pricing—selling the same product in each period at a varying price—we consider intertemporal content variation, wherein the price is the same in every period, but the firm varies the content available over time. Customers learn their utility on purchasing and decide whether to purchase again in subsequent periods. The firm faces a budget for the total amount of content available during a finite planning horizon, and allocates content to maximize revenue. Academic/practical relevance: A number of new business models, including video streaming services and curated subscription boxes, face the situation we model. Our results show how such firms can use content variation to increase their revenues. Methodology: We employ an analytical model in which customers decide to purchase in multiple successive periods and a firm determines a content allocation policy to maximize revenue. Results: Using a lower bound approximation to the problem for a horizon of general length T, we show that, although the optimal allocation policy is not, in general, constant over time, it is monotone: content value increases over time if customer heterogeneity is low and decreases otherwise. We demonstrate that the optimal policy for this lower bound problem is either optimal or very close to optimal for the general T period problem. Furthermore, for the case of T = 2 periods, we show how two critical factors—the fraction of “new” versus “repeat” customers in the population and the size of the content budget—affect the optimal allocation policy and the importance of varying content value over time. Managerial implications: We show how firms that sell at a fixed price over multiple periods can vary content value over time to increase revenues.

Duke Scholars

Published In

Manufacturing and Service Operations Management

DOI

EISSN

1526-5498

ISSN

1523-4614

Publication Date

May 1, 2022

Volume

24

Issue

3

Start / End Page

1664 / 1680

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 3509 Transportation, logistics and supply chains
  • 1505 Marketing
  • 1503 Business and Management
  • 0102 Applied Mathematics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bernstein, F., Chakraborty, S., & Swinney, R. (2022). Intertemporal Content Variation with Customer Learning. Manufacturing and Service Operations Management, 24(3), 1664–1680. https://doi.org/10.1287/msom.2021.1025
Bernstein, F., S. Chakraborty, and R. Swinney. “Intertemporal Content Variation with Customer Learning.” Manufacturing and Service Operations Management 24, no. 3 (May 1, 2022): 1664–80. https://doi.org/10.1287/msom.2021.1025.
Bernstein F, Chakraborty S, Swinney R. Intertemporal Content Variation with Customer Learning. Manufacturing and Service Operations Management. 2022 May 1;24(3):1664–80.
Bernstein, F., et al. “Intertemporal Content Variation with Customer Learning.” Manufacturing and Service Operations Management, vol. 24, no. 3, May 2022, pp. 1664–80. Scopus, doi:10.1287/msom.2021.1025.
Bernstein F, Chakraborty S, Swinney R. Intertemporal Content Variation with Customer Learning. Manufacturing and Service Operations Management. 2022 May 1;24(3):1664–1680.

Published In

Manufacturing and Service Operations Management

DOI

EISSN

1526-5498

ISSN

1523-4614

Publication Date

May 1, 2022

Volume

24

Issue

3

Start / End Page

1664 / 1680

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 3509 Transportation, logistics and supply chains
  • 1505 Marketing
  • 1503 Business and Management
  • 0102 Applied Mathematics