Managing Customer Search via Bundling
Chenguang (Allen) Wu (),
Chen Jin () and
Ying-Ju Chen ()
Additional contact information
Chenguang (Allen) Wu: Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Chen Jin: Department of Information Systems and Analytics, School of Computing, National University of Singapore, 117417 Singapore
Ying-Ju Chen: School of Business and Management, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Manufacturing & Service Operations Management, 2022, vol. 24, issue 4, 1906-1925
Abstract:
Problem definition : Product bundling has been a pervasive marketing strategy, and its success has been largely attributed to its strength in reducing customers’ valuation dispersion. Less is known about the efficacy of bundling in settings where customers are less sure about their valuations for a product, especially when that product is newly launched or has an experience nature, and can conduct costly search to learn the product content and discover their true valuations. In this paper, we investigate the interplay between product bundling and customer search and its implications for a monopolist’s optimal pricing strategy. Academic/practical relevance : The existing search theory has focused on decision making that selects the best among multiple alternatives, with costly search being mandatory for the acquisition of each alternative. In this paper, we introduce a framework of multiproduct demands and nonobligatory search , where customers demanding multiple products strategically decide whether to conduct costly search to resolve valuation uncertainty, while reserving the right to purchase these products without having to search them first. Methodology : We apply a nonobligatory search framework to study two different markets: (1) a market of one mature and one new product, in which valuation uncertainty exists for the new product only; and (2) a market of two new products, in which valuation uncertainty exists for both products. The firm fully anticipates the customers’ search behaviors, determines whether to bundle these products or unbundle them, and optimally sets prices. Results : We show that bundling cultivates search in a market of one mature and one new product, but inhibits search in a market of two new products. This contrast emerges as a result of market structures: Bundling reduces the appeal of search by making the search decisions sequential and path-dependent in the latter market, but is less effective in doing so due to the existing heterogeneity in the former market. Our results thus point to an intricate interplay between customer search, market heterogeneity, and prices and their joint impact on the monopolist’s optimal bundling strategy. We also study mixed bundling and show that its economic benefits only carry through when customers’ search cost is not too large. In this case, mixed bundling can lead to considerable revenue improvement in a market of one mature and one new product, but only tiny revenue improvement in a market of two new products. We also study the joint management of product return and product bundling and show that a positive refund should generally be offered for returned products to stimulate customers’ no-search purchase. Managerial implications : Our paper provides guidance for firms selling multiple experience or new products. We propose product bundling to manage customer search, identifying regimes for its economic benefits and clarifying its implication for customer welfare.
Keywords: multiproduct search; nonobligatory search; bundling; pricing (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://dx.doi.org/10.1287/msom.2022.1082 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:24:y:2022:i:4:p:1906-1925
Access Statistics for this article
More articles in Manufacturing & Service Operations Management from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().