Scholarly Works, Department of Marketing
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Browsing Scholarly Works, Department of Marketing by Author "Jiang, Juncai"
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- Price-Matching Guarantees with Endogenous Consumer SearchJiang, Juncai; Kumar, Nanda; Ratchford, Brian T. (Informa, 2017-10-01)Price-matching guarantees (PMGs) are offered in a wide array of product categories in retail markets. PMGs offer consumers the assurance that, should they find a lower price elsewhere within a specified period after purchase the retailer will match that price and refund the price difference. The goal of this study is to explain the following stylized facts: (1) many retailers that operate both online and offline implement PMG offline but not online; (2) the practices of PMG vary considerably across retail categories; and (3) some retailers launch specialized websites that automatically check competitors’ prices for consumers after purchase. To this end, we build a sequential search model that endogenizes consumers’ pre- and postpurchase search decisions. We find that PMG expands retail demand but intensifies price competition on two dimensions. PMG drives retailers to offer deeper promotions because it increases the overall extent of consumer search, which we call the primary competition-intensifying effect. We also find a new secondary competition-intensifying effect, which results from endogenous consumer search. As deeper promotions incentivize consumers to continue price search, retailers are forced to lower the “regular” price to deter consumers from searching. The strength of the secondary competition-intensifying effect increases with the ratio of product valuation to search cost, which explains the variation in PMG practices online versus offline and across retail categories. We show that an asymmetric equilibrium exists such that one retailer offers PMG while the other does not. In this equilibrium, the PMG retailer may benefit from launching a price check website to facilitate consumers’ postpurchase search.
- A Theoretical and Empirical Investigation of Feedback in Ideation ContestsJiang, Juncai; Wang, Yu (Wiley, 2019-11-11)Ideation contests are commonly used across public and private sectors to generate new ideas for solving problems, creating designs, and improving products or processes. In such a contest, a firm or an organization (the seeker) outsources an ideation task online to a distributed population of independent agents (solvers) in the form of an open call. Solvers compete to exert efforts and the one with the best solution wins a bounty. In evaluating solutions, the seeker typically has subjective taste that is unobservable to solvers. In practice, the seeker often provides solvers with feedback, which discloses useful information about her private taste. In this study, we develop a game-theoretic model of feedback in unblind ideation contests, where solvers’ solutions and the seeker's feedback are publicly visible by all. We show that feedback plays an informative role in mitigating the information asymmetry between the seeker and solvers, thereby inducing solvers to exert more efforts in the contest. We also show that some key contest and solver characteristics (CSC, including contest reward, contest duration, solver expertise, and solver population) have a direct effect on solver effort. Interestingly, by endogenizing the seeker's feedback decision, we find that the optimal feedback volume increases with contest reward, contest duration, solver expertise, but decreases with solver population. Thus, CSC elements also have an indirect effect on solvers’ effort level, with feedback volume mediating this effect. Employing a dataset from Zhubajie.com, a leading online ideation platform in China, we find empirical evidence that is consistent with these theoretical predictions.