Séminaires de recherche

Reducing Peak-Hour Subway Crowding: Investigating the Effectiveness of Disincentives


Intervenant : Leonard Lee
Professeur Associé , National University of Singapore

2 mai 2016 - Salle T015 - De 09h30 à 11h00

Reducing Peak-Hour Subway Crowding: Investigating the Effectiveness of Disincentives

Leonard Lee
National University of Singapore

The public transportation system in Singapore is facing peak-hour overloads. At times, subway trains are over-crowded to the extent that commuters cannot board the trains. One approach to managing the crowd is to impose a peak-hour surcharge to discourage travel during peak hours. Given that people are generally more motivated to avoid losses than to acquire gains, disincentives may be more effective than off-peak discounts in shifting demands from peak to off-peak periods. Nonetheless, commuters may display strong reactions against a surcharge policy, making it challenging to implement such a policy. The present research examines the effectiveness of a surcharge policy at shifting travel from peak to off-peak periods while developing and testing different potential solutions to increase commuters’ receptivity toward peak-hour surcharge. In particular, using a longitudinal randomized controlled trial (RCT) involving more than 900 commuters across the nation, we investigated the behavioral and psychological impact of donating the collected surcharge to charity, and the degree of autonomy commuters have in deciding the benefactor of the donation.

Does Advertising Serve as a Signal? Evidence from Field Experiments in Mobile Search


Intervenant : Harikesh Nair
Professeur Marketing , Graduate School of Business, Stanford University

4 mars 2016 - Bâtiment T, Salle T027 - De 14h00 à 15h30

In a large-scale field experiment, we demonstrate that advertising can serve as a signal that enhances consumers' evaluations of advertised goods. We implement the experiment on a mobile search platform that provides listings and reviews for an archetypal experience good, restaurants. In collaboration with the platform, we randomize more than 200,000 consumers into exposure or no exposure of ads for about 600+ local restaurants. In conditions in which consumers are exposed to advertising, we also randomly vary the disclosure to the consumer of whether a restaurant's listing is an ad. This enables us to isolate the eect on outcomes of a consumer knowing that a listing is sponsored - a pure signaling effect. We find that this disclosure alone increases calls to the restaurant by 77%, holding fixed all other attributes of the ad. This effect is higher when the consumer uses the platform away from his typical city of search, when the uncertainly about restaurant quality is larger, and for restaurants that have received fewer ratings in the past. Further, on the supply side, newer, higher rated and more popular restaurants advertise more on the platform. Taken together, we interpret these results as consistent with a signaling equilibrium in which ads serve as implicit signals that enhance the appeal of the advertised restaurants. Our results also imply that advertisers and search-platforms would gain by making the ads discernible, and thus holds implications for platform design.

Robust Dynamic Estimation


Intervenant : Olivier Rubel
Professor Assistant Marketing , UC Davis Graduate School of Management

21 janvier 2016 - Bâtiment T, Salle T201 - De 13h30 à 15h00

Managing marketing resources over time requires dynamic model estimation, which necessitates specifying some parametric or nonparametric probability distribution. When the data generating process differs from the assumed distribution, the resulting model is misspecified. To hedge against such a misspecification risk, the extant theory recommends using White’s (1980) sandwich estimator. This approach, however, only corrects the variance of estimated parameters, but not their values. Consequently, the sandwich estimator does not affect any managerial outcomes such as marketing budgeting and allocation decisions. To overcome this drawback, we present the minimax framework that does not necessitate any distributional assumptions to estimate dynamic models. Applying minimax control theory, we derive an optimal robust filter, illustrate its application to a unique advertising data set from the Canadian Blood Services, and contribute several novel findings. We discover the compensatory effect: advertising effectiveness increases and the carryover effect decreases as robustness increases. We also find that the robust filter uniformly outperforms the Kalman filter on the out-of-sample predictions. Furthermore, we uncover the existence of a profit-volatility tradeoff, similar to the returns-risk tradeoff in finance, whereby the volatility of profit stream decreases at the expense of reduced total profit as robustness increases. Finally we prove that, unlike for-profit companies, managers of non-profit organizations should optimally allocate budgets opposite of the advertising-to-sales ratio heuristic; that is, advertise more (less) when sales are low (high).

The End of History Illusion


Intervenant : Jordi Quoidbach
Professeur Assistant , University Pompeu Fraba, Barcelona

20 janvier 2016 - Bâtiment T, Salle T201 - De 13h30 à 15h00

We measured the personalities, values, and preferences of more than 19,000 people who ranged in age from 18 to 68 and asked them to report how much they had changed in the past decade and/or to predict how much they would change in the next decade. Young people, middle-aged people, and older people all believed they had changed a lot in the past but would change relatively little in the future. People, it seems, regard the present as a watershed moment at which they have finally become the person they will be for the rest of their lives. This “end of history illusion” had practical consequences, leading people to overpay for future opportunities to indulge their current preferences.

Homophily and Influence: Pricing to Harness Word-of-Mouth on Social Networks


Intervenant : Peter Zubcsek
Professeur Assistant de Marketing , University of Florida

27 novembre 2015 - Bâtiment T, Salle T201 - De 13h30 à 15h00

Large-scale social platforms have enabled marketers to obtain rich data on the structure of word-of-mouth (WOM) networks and the correlation of friends’ preferences (network assortativity). We study how the similarity or difference of friends’ reservation prices for a product should affect the optimal price and advertising levels for that product. To this end, we build an analytical model of informative advertising and pricing over a social network. Connections between consumers are added in a way that allows neighbors’ preferences to be positively or negatively correlated, thereby introducing homophily or heterophily in the model. Consumers may learn about products either directly via advertising, or via WOM spread by their peers who have adopted a product. We find that in the typical scenario when blanket advertising is not affordable, firms set a price lower than the naïve optimum in order to leverage the social value of more price-sensitive customers. We also characterize the relationship between assortativity and the marketing instruments (price and advertising) of the firm, to find that either instrument may be substitutes or complements with assortativity depending on the cost of advertising relative to the market’s valuation for the product, the overall connectivity, and the assortativity of the network.