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on Marketing |
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Issue of 2017‒08‒13
three papers chosen by João Carlos Correia Leitão Universidade da Beira Interior |
| By: | Rosa Ferrer; Helena Perrone |
| Abstract: | Using an ideal setting from a major food safety crisis, we estimate a full demand model for the unsafe product and its substitutes and recover consumers’ preference parameters. Counterfactual exercises quantify the relevance of different mechanisms –changes in safety perceptions, idiosyncratic tastes, nutritional characteristics, and prices–driving consumers’ response. We find that consumers’ reaction is limited by their taste for the product and its nutritional characteristics. Due to the costs associated with switching away from the affected product, the decline in demand following a product-harm crisis tends to understate the true weight of such events in consumers’ utility. Indeed, we find that a large fraction of consumers are unresponsive to the crisis even when they significantly downgrade their product safety perception. For an accurate assessment of the crisis, managerial strategies should therefore account for how different demand drivers bind consumers’ substitution patterns. |
| Keywords: | food safety, demand estimation, scanner data, idiosyncratic utility parameters, nutritional preferences |
| JEL: | L51 L66 K13 M3 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:975&r=mkt |
| By: | Tjaden, Jasper Dag; Schwemmer, Carsten; Khadjavi, Menusch |
| Abstract: | We study ethnic discrimination in Europe's largest carpooling marketplace. Using a unique dataset with more than 17,000 rides, we estimate the effects of drivers' perceived name origins on the demand for rides. Carpooling is a novel application for studying ethnic discrimination where consumer choice entails social interaction with the service provider (i.e. driver). We find large discrimination effects for drivers with Arab, Turkish or Persian sounding names. Further analyses support assumptions consistent with statistical discrimination. Our findings broaden the perspective of ethnic discrimination by shedding light on subtle, everyday forms of discrimination in social markets and fuel ongoing discussions about anti-discrimination efforts in an era in which markets increasingly move online. |
| Keywords: | ethnic discrimination,statistical discrimination,taste-based discrimination,online markets,computational social science |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwkwp:2087&r=mkt |
| By: | Chang Wang; Dries Goossens; Martina Vandebroek |
| Abstract: | In the past decade, television broadcasters have been investing a huge amount of money for the Belgian Pro League broadcasting rights. These companies pursue an audience rating maximization, which depends heavily on the schedule of the league matches. At the same time, clubs try to maximize their home attendance and find themselves affected by the schedule as well. Our paper aims to capture the Belgian soccer fans’ preferences with respect to scheduling options, both for watching matches on TV and in the stadium. We carried out a discrete choice experiment using an online survey questionnaire distributed on a national scale. The choice sets are based on three match characteristics: month, kickoff time, and quality of the opponent. The first part of this survey concerns television broadcasting aspects. The second part includes questions about stadium attendance. The choice data is first analyzed with a conditional logit model which assumes homogenous preferences. Then a mixed logit model is fit to model the heterogeneity among the fans. The estimates are used to calculate the expected utility of watching a Belgian Pro League match for every possible setting, either on TV or in the stadium. These predictions are validated in terms of the real audience rating and home attendance data. Our results can be used to improve the scheduling process of the Belgian Pro League in order to persuade more fans to watch the matches on TV or in a stadium. |
| Keywords: | Audience ratings, Belgian soccer, Conditional logit model, Discrete choice experiment, Mixed logit model, Schedule, Stadium attendance |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:ete:kbiper:588528&r=mkt |