Risk Preferences and Demand Drivers of Extended Warranties

Jindal, Pranav

doi:10.2139/ssrn.2196033

Cited by 11 publications

(14 citation statements)

References 49 publications

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“…Similarly, both loss aversion and probability weighting can help explain the purchase of insurance against modest risks such as warranties (Rabin and Thaler, ; Cutler and Zeckhauser, 2004; Michel, ), and empirical evidence has been found in support of these approaches (Jindahl, ). Nevertheless, there is also empirical evidence calling into question whether this can be the whole story.…”

Section: Introductionmentioning

confidence: 99%

Mental Accounting, Access Motives, and Overinsurance*

Fels

2019

Scandinavian J Economics

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The access motive for insurance posits that insurance derives its value from providing access to a loss remedy that is unaffordable without insurance. I explore the potential of this alternative insurance motive to explain attitudes towards modest risks, and I argue that mental accounting makes the access motive relevant for understanding both the popularity of warranties and the avoidance of deductibles. The value of partial insurance is shown to critically depend on the way in which the insurer pays benefits. This can explain several empirical regularities that are difficult to reconcile within existing models.

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Section: Introductionmentioning

confidence: 99%

Mental Accounting, Access Motives, and Overinsurance*

Fels

2019

Scandinavian J Economics

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“…Our study complements this literature by highlighting the potential role of subjective return probability, the third behavioral piece in Prospect Theory. As a result, it is important for future behavioral studies to take a holistic view, similar to the approach in Jindal (2014), for studying how subjective probability, loss aversion, and reference dependence together affect consumer return policy preference.…”

Section: Discussionmentioning

confidence: 99%

How much do online consumers really value free product returns? Evidence from eBay

Shang

Pekgün

Ferguson

et al. 2017

J of Ops Management

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Consumer return rates have been steadily rising in recent years, resulting in growing costs for retailers who must manage the returns process and the disposition of returned products. This cost pressure is driven in part by extremely generous return policies, such as giving consumers a full refund upon return. Interestingly, this common retail practice of full refunds is inconsistent with the recommendations of many analytical models of returns, which nearly always show that a partial refund is optimal. Such inconsistencies between theory and practice might arise when the decision drivers included in the analytical models do not match the decision drivers in practice. It might also be the case that retailers are overly optimistic about the value that consumers assign to a full refund, and thus assume that the value of such a policy outweighs its costs. In this paper, we use data collected from eBay, where identical products are sold with different return policies, to investigate these open questions in the literature. We analyze both the return policy drivers from the retailer's perspective and the return policy value from the consumer's perspective. Our results suggest that the value of a full refund policy to consumers may not be as large as one might expect, and it also exhibits a large heterogeneity across buyers with different levels of online purchase experience. In addition, we provide empirical evidence for what has long been suspected by online retailers e that a non-refundable forward shipping charge quickly erodes any value that consumers assign to return policies. The generality of our results is limited by the fact that eBay differs from traditional retail contexts in many respects, including the fact that eBay buyers may not be representative of the general buyer population. However, our study of how eBay consumers value free returns provides new insights into an understudied area, and it can serve as a starting point for future studies of the value of return policies in other retail contexts.

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“…Furthermore, an innovative survey design is used to attenuate possible belief-based biases: respondents choose products and warranties under given failure probabilities. Jindal (2015) shows in simulations (based on the estimated models) that not accounting for risk aversion, loss aversion, and nonlinear probability weighting leads to roughly 16-20% lower optimal prices and, consequently, reduced profits for manufacturers.…”

Section: Product and Non-standard Preferencesmentioning

confidence: 99%

Behavioral biases in marketing

Guhl

Massner

Spann

et al. 2019

J. of the Acad. Mark. Sci.

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Psychology and economics (the mixture of which is known as behavioral economics) are two fundamental disciplines underlying marketing. Various marketing studies document the nonrational behavior of consumers, even though behavioral biases might not always be consistently termed or formally described. In this review, we identify empirical research that studies behavioral biases in marketing. We summarize the key findings according to three classes of deviations (i.e., non-standard preferences, non-standard beliefs, and non-standard decisionmaking) and the marketing mix instruments (i.e., product, price, place, and promotion). We thereby introduce marketing researchers to the theoretical foundation of and terminology used in behavioral economics. For scholars from behavioral economics, we provide ready access to the rich empirical, applied marketing literature. We conclude with important managerial implications resulting from the behavioral biases of consumers, and we present avenues for future research.

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Risk Preferences and Demand Drivers of Extended Warranties

Cited by 11 publications

References 49 publications

Mental Accounting, Access Motives, and Overinsurance*

Mental Accounting, Access Motives, and Overinsurance*

How much do online consumers really value free product returns? Evidence from eBay

Behavioral biases in marketing

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