An analysis of price strategies with price matching in the presence of showrooming

Zeng, Yuwen; Hou, Wenhua

doi:10.1111/itor.13187

Cited by 6 publications

(4 citation statements)

References 50 publications

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“…This cost

s

can be treated as the same across all consumers, or it can be assumed to be heterogeneous among consumers. The former can be understood as the average cost for consumers to visit offline stores, which is adopted in our paper for analytical tractability similar to mainstream studies (Balakrishnan et al., 2014; Gao and Su, 2017; Dan et al., 2021; Xu et al., 2021; Zeng and Hou, 2022; Chen et al., 2023). In addition, even if extended to consider heterogeneity, some key results still have similarity and robustness (Jing, 2018; Jiao and Hu, 2022).…”

Section: Problem Descriptionmentioning

confidence: 99%

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Personalized pricing versus showrooming: competition between online and offline retailers

Ren,

Tian,

Kang

et al. 2024

Int Trans Operational Res

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This study examines how personalized pricing affects customers’ showrooming behavior in the duopoly competition with horizontal product differentiation between traditional and online retailers. For the available personalized pricing strategies, we obtained the optimal decisions for both retailers in the scenarios with and without showrooming. Our results indicate that adopting personalized pricing under particular conditions enables each retailer to be more profitable, even in the presence of showrooming purchases. This finding explains why an increasing number of online and offline retailers have implemented personalized pricing based on technical means and consumer purchase records. It is also demonstrated that personalized pricing can counter showrooming behavior of consumers amidst the competition between both retailers, which provides a novel theoretical basis for dealing with cross‐channel shopping in multichannel retail competition. We further clarify how retailers can avoid being trapped in a prisoner's dilemma when both sides have access to personalized pricing. Also, the adoption of personalized pricing can improve consumer surplus and social welfare.

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“…This cost

s

Section: Problem Descriptionmentioning

confidence: 99%

“…Target requires suppliers to provide exclusive products not available to other sellers. Best Buy matches its prices with those of its online competitors (Zeng and Hou, 2022).…”

Section: Introductionmentioning

confidence: 99%

Personalized pricing versus showrooming: competition between online and offline retailers

Ren,

Tian,

Kang

et al. 2024

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…Q. Examine, via the lens of game theory, how offline service costs influence price matching decisions of online and offline platforms and how they affect the offline service levels given by merchants (Chen and Chen, 2019; Zeng and Hou, 2022). Q.…”

Section: Future Research Directionsmentioning

confidence: 99%

Showrooming: a retrospective and prospective review using the SPAR-4-SLR methodological framework

Sharma

Dutta

Priya³

2023

IJRDM

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PurposeThis article undertakes a literature review on showrooming, offering an exhaustive overview of research publications and future research objectives that will contribute to extending the understanding of the phenomenon.Design/methodology/approachThe showrooming literature has been collected from journals indexed by SCOPUS and ranked by ABDC. This was later analysed with the SPAR-4-SLR framework and the TCCM methodology (theories, contexts, characteristics, and methodologies) proposed by Paul et al. (2021) and Paul and Rosado-Serrano (2019).FindingsThe insights of this review include bibliometrics of showrooming research and the number of explored showrooming theories, methodologies, and contexts from which the phenomenon has been studied. It also highlights the various aspects that might be considered while building an optimal approach.Research limitations/implicationsArticles published in SCOPUS-indexed and ABDC-ranked journals between 2012 and August 2022 were considered. Some articles published in conference proceedings and journals, not fulfilling the aforementioned criteria, might have been missed.Practical implicationsSPAR-4-SLR and TCCM methodologies would aid the researchers in further exploration of this phenomenon and suggest options for enhancing customer experience (CX) eventually leading to customer retention. Retail channel managers will find this knowledge handy in “encouraging loyal showrooming” and ensuring business sustainability.Originality/valueThis study uses the novel SPAR-4-SLR framework to structure the review, while TCCM methodology sheds light on the showrooming from the perspective of various theories, contexts, characteristics, and methodologies. The scope for further research identified through the above-mentioned framework and methodology would be of high value to the researchers and practitioners alike.

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“…In most research studies, the model assumes a stationary, known distribution from which the buyers' offers are generated and which cannot be influenced by the seller. In a competitive market, a seller integrates realistic knowledge into the decision-making process in order to improve performance [10], [11], when a listing price is one of the decision parameters of the seller's policy that can influence the offer distribution.…”

Section: Introductionmentioning

confidence: 99%

Optimal Real Estate Pricing and Offer Acceptance Strategy

Khmelnitsky

Singer

2023

IEEE Access

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We consider the problem of choosing the best of a set of sequential offers proposed by the market in a house-selling process. During each decision epoch, the seller sets a listing price, observes the offers and decides whether to accept the maximum one or to reject all of them. We model a fixed holding cost, which is the constant marketing cost of searching for buyers, and a variable cost that is proportional to the number of offers received during each epoch. The objective is to maximize the expected revenue. Most previous studies assume a stationary known distribution from which the buyers' offers are generated and which reflects the market valuation of the house. In contrast, we assume that the number of incoming offers, and the distribution from which each individual offer is generated, are affected by the seller's listing price (i.e., price-based demand response). Thus, we propose a new approach for the selling policy, which consists of the listing price and the offer acceptance threshold in each period. We derive the seller's optimal selling policy and apply it to a scenario involving the sale of individual residential properties in Ames (Iowa), which yields results consistent with empirical observations. INDEX TERMS Housing market policy, dynamic pricing, sequential decision making, optimal stopping.

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An analysis of price strategies with price matching in the presence of showrooming

Cited by 6 publications

References 50 publications

Personalized pricing versus showrooming: competition between online and offline retailers

Personalized pricing versus showrooming: competition between online and offline retailers

Showrooming: a retrospective and prospective review using the SPAR-4-SLR methodological framework

Optimal Real Estate Pricing and Offer Acceptance Strategy

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