Would You Like Some Risk with That? Willingness to Pay for the Extended Service Contract Warranty
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James M. Loveland
,
Katherine E. Loveland
Abstract
The purpose of this paper was two-fold. First, we sought to examine and identify factors (from the consumer side) that drove willingness to pay (WTP) for extended service contract (ESC) warranties. Second, we identified levers from the manufacturers’ perspective, that managers could control, which might also affect WTP for these ESC warranties. To test our hypotheses, a series of experiments involving 927 participants was employed. First, a set of paired experiments focused on TVs and laptops were conducted. These experiments used the double-bound contingent valuation method to assess the influence of different aspects of the product and the sales pitch on WTP. Based on these findings, an additional experiment was conducted in which the hedonic/utilitarian nature of the same product was manipulated to further refine and verify the proposed mechanisms driving WTP. Overall, we found that while loss aversion drives the decision process, factors such as: whether the product is hedonic or utilitarian, the perceived brand equity, the price, and the regulatory focus of the warranty sales pitch, all influence how consumers decide to mitigate or avoid thinking about risk. Our findings suggest that consumers try to avoid risk and seek positive support for hedonic goods, while for utilitarian goods they actively assess risk, even when the product might be viewed as hedonic or utilitarian. This manuscript and its findings provide a solid conceptual framework from which to develop a more cohesive theoretical approach to understanding ESC warranties, and it also provides important insights to managers on how to enhance the profitability and attractiveness of their ESC offerings.
Contingent Valuation and WTP Model (Sinha et al. 2010)
The model is designed to estimate product demand when a certain group of consumers are expected to be in the “never purchaser” category. The model is developed according to the following two-step procedure:
Step A: Estimating WTP. First, we asked all respondents in the (No-No) group whether they would be willing to “pay anything at all”. This gave us the “No-No-No” group of respondents (i.e. those respondents who said “No” to the initial bid presented to them, “No” to the subsequent lower follow-up bid and finally also “No” to the follow-up question asking them whether they would pay anything at all for the warranty. Hence, for individual j,
=F(B Lj , θ), where F(B Lj , θ) is the cumulative distribution function (cdf) of a chosen parametric distribution for WTP with parameter vector θ. Similarly,
Equations (1)–(4) represent the probabilities of observing the different responses to each of the individual bids and yield the likelihood function for estimating the mean WTP for the sample.
Step B: Jointly Estimating WTP and Propensity for being a “Never buyer”. In order to jointly estimate WTP and Probability (WTP = 0), we define two groups of consumers as follows:
Group A consists of individuals whose WTP is “always zero”. This is the never buyer category and is observed with probability p j . This probability may be modeled as a function of individual covariates X ij in a logit model.
Group à consists of individuals whose WTP is “not always zero”. These individuals may or may not purchase the warranty and are observed with probability (1 − p j ).
We do not know which group a randomly drawn individual belongs to, but we do know that Pr(WTP = 0| A , X ij ) = 1 and that Pr(WTP = k| A , X ij ) = 0, k > 0. Hence,
Letting nnn, nn, ny, yn and yy represent dummy indicators for the (No-No-No), (No-No), (No-Yes), (Yes-No) and (Yes-Yes) group respectively, Equations (1)–(6) yield a sample log-likelihood of:
Our estimates are based on maximizing this likelihood function.
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