Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market

Reimers, Imke; Xie, Claire

doi:10.2139/ssrn.2730922

Cited by 10 publications

(13 citation statements)

References 23 publications

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“…Clearly stochastic policies such as π H can explain a coupon redemption ratio below 1 when we have p x ≥ v. However, coupon redemption ratios from such policies are sensitive to the coupon value v, at least in the cases with only one coupon. We can illustrate the intuition of this claim by looking at equation (32): given the same λj , Pj and T , one can show by induction on T that the gap between v and V (v, T ) increases monotonically as v increases. Therefore, the redemption ratio under the condition p x /v ≥ 1 should also increase monotonically with v. However, this is not fully consistent with our observations in Figure 5: the redemption ratio under v = 30 is not significantly greater than the one under v = 20.…”

Section: Observations On the Coupon Redemption Behaviormentioning

confidence: 99%

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An Inattention Model for Traveler Behavior with e-Coupons

Qiu¹

2018

SSRN Journal

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In this study, we consider traveler coupon redemption behavior from the perspective of an urban mobility service. Assuming traveler behavior is in accordance with the principle of utility maximization, we first formulate a baseline dynamical model for traveler's expected future trip sequence under the framework of Markov decision processes and from which we derive approximations of the optimal coupon redemption policy. However, we find that this baseline model cannot explain perfectly observed coupon redemption behavior of traveler for a car-sharing service.To resolve this deviation from utility-maximizing behavior, we suggest a hypothesis that travelers may not be aware of all coupons available to them. Based on this hypothesis, we formulate an inattention model on unawareness, which is complementary to the existing models of inattention, and incorporate it into the baseline model. Estimation results show that the proposed model better explains the coupon redemption dataset than the baseline model. We also conduct a simulation experiment to quantify the negative impact of unawareness on coupons' promotional effects. These results can be used by mobility service operators to design effective coupon distribution schemes in practice.

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Section: Observations On the Coupon Redemption Behaviormentioning

confidence: 99%

“…Therefore, recent research mostly focused on reduced-form models or even data-driven approaches. For example, Reimers and Xie [32] proposed reduced-form models for coupons' market expansion and revenue cannibalization effects. The authors estimated their models using restaurant coupon data from Groupon.…”

Section: Customer Behavior With Couponsmentioning

confidence: 99%

An Inattention Model for Traveler Behavior with e-Coupons

Qiu¹

2018

SSRN Journal

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“…This is best illustrated by considering an example. In general, users benefit from digital coupons through reduced prices (Reimers and Xie 2019). However, groups of users who systematically produce a lower rate of mouse clicks receive more coupons and, hence, are disproportionately favored.…”

Section: Ai Fairness For E-commercementioning

confidence: 99%

The Cost of Fairness in AI: Evidence from E-Commerce

2021

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Contemporary information systems make widespread use of artificial intelligence (AI). While AI offers various benefits, it can also be subject to systematic errors, whereby people from certain groups (defined by gender, age, or other sensitive attributes) experience disparate outcomes. In many AI applications, disparate outcomes confront businesses and organizations with legal and reputational risks. To address these, technologies for so-called “AI fairness” have been developed, by which AI is adapted such that mathematical constraints for fairness are fulfilled. However, the financial costs of AI fairness are unclear. Therefore, the authors develop AI fairness for a real-world use case from e-commerce, where coupons are allocated according to clickstream sessions. In their setting, the authors find that AI fairness successfully manages to adhere to fairness requirements, while reducing the overall prediction performance only slightly. However, they find that AI fairness also results in an increase in financial cost. Thus, in this way the paper’s findings contribute to designing information systems on the basis of AI fairness.

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“…Ali explores the coordination and incentive issues that may arise from the different types of collaborations between telecommunication firms and banks [7]. Reimers and Xie develop a model of consumer demand to empirically study whether (i) firms can use coupons as a means of price discrimination to attract new consumers without cannibalizing revenue from existing ones and (ii) these new consumers return to the firm after price promotion [8]. Edelman et al analyse the conditions under which a business can benefit from issuing e-coupons [9], and Dholakia provides survey-based evidence that some businesses benefit from using e-coupons by finding new consumers [10].…”

Section: Informationmentioning

confidence: 99%

Incentive and Coordination in the Two-Sided Market: Evidence from the P2P Lending Market

Zhao

Shi

2021

Discrete Dynamics in Nature and Society

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Two-sided markets serve as information intermediaries by connecting participants on both sides. In this study, we focus on the coordination of participants in the P2P lending market using a coupon strategy as an incentive to attract investment. Using a two-sided market model, we find that when a platform adopts the coupon strategy, (i) the platform utility and participants’ utility are both greater and (ii) the number of participants is greater. In addition, as most research on two-sided markets and coupon strategy focuses on theoretical models, our study provides empirical support using data from Renrendai.com over 2018 to 2019.

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Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market

Cited by 10 publications

References 23 publications

An Inattention Model for Traveler Behavior with e-Coupons

An Inattention Model for Traveler Behavior with e-Coupons

The Cost of Fairness in AI: Evidence from E-Commerce

Incentive and Coordination in the Two-Sided Market: Evidence from the P2P Lending Market

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