39th Edition of the HEC-ESSEC-INSEAD
Fri March 9, 2018, from 9:00 AM to 5:00 PM
The HEC-ESSEC- INSEAD research seminar has been a tradition among the three schools to
exchange research ideas in the past forty years. The three schools rotate to host the research seminar each year and this year HEC will host the event. The seminar aims to stimulate fruitful research exchange and discussion.

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Event details

Program

 

9.00-9.30Welcome coffee



9.30-10.30Keynote speaker: ”Prediction, Judgment, and Complexity”, Avi Goldfarb, Rotman School of Management 

Abstract: We interpret recent developments in the field of artificial intelligence (AI) as improvements in prediction technology. In this paper, we explore the consequences of improved prediction in decision-making. To do so, we adapt existing models of decision-making under uncertainty to account for the process of determining payoffs. We label this process of determining the payoffs ‘judgment.’ There is a risky action, whose payoff depends on the state, and a safe action with the same payoff in every state. Judgment is costly; for each potential state, it requires thought on what the payoff might be. Prediction and judgment are complements as long as judgment is not too difficult. We show that in complex environments with a large number of potential states, the effect of improvements in prediction on the importance of judgment depend a great deal on whether the improvements in prediction enable automated decision-making. We discuss the implications of improved prediction in the face of complexity for automation, contracts, and firm boundaries.



10.30-11.15 – ”Brand as Performance: How Firms Shape Brand Dynasties to Manage Human Brands,” Delphine Dion, ESSEC Business School, with Eric Arnould, Aalto U., Helsinki, Finland and EM Lyon

Abstract: How should one manage a human brand over time? In particular, how should one manage it beyond the founder’s lifetime? Drawing from extensive ethnographic work in luxury, services, and mass-market goods, we provide new insights into understanding human brands and move the discussion about branding into new territory. Our conceptualization of human brands goes beyond the more typical marketing interest in celebrities. We redefine human brands based on the distinctive characteristics of their brand identity. Theorizing human brand management as a temporal challenge constitutes another extension of the existing literature on branding. We show how firms configure brand dynasties to manage human brands beyond the founder’s lifetime. We embrace the complexity of branding by recognizing the citational, material, and routinized aspects of branding. We contribute to the literature on branding by investigating the concept of brand performativity, showing that it can help researchers develop a richer understanding of how brands are produced and performed in context. This research codifies new ways to manage brands, especially luxury brands. 

 

11.15-11.45Coffee break



11.45-12.30 –  ”The adoption of a multisided platform by different types of users: a spatiotemporal analysis,Ludovic Stourm, HEC Paris 

 

Abstract

The recent years have seen the explosion of the sharing economy with platforms such as AirBnB, Uber and BlaBlaCar, which essentially act as matchmakers between individuals willing to rent a resource (apartment, labor, space) and individuals willing to monetize the resources they own. In this research, we construct a spatiotemporal model of diffusion to empirically analyze how such a multisided platform is adopted by different types of users over time and space. In particular, our model can be used to measure the distinct influence of existing users in one side of the platform on the adoption decision by new users in another side. We apply our model on a unique dataset from a European car-sharing platform with about 400,000 users split in two groups: car owners and car renters. We present the results of this analysis and investigate how the initial distribution of users affects the speed of diffusion of the platform.



12.30-14.00Buffet lunch at Oberkampf



14.00-14.45 – “Consumer Objectification and the Market for Heels in the Women’s Footwear Industry”, Clément Bellet, INSEAD

Abstract: Objectification – the tendency to perceive and treat an individual as an object – permeates female consumers’ everyday life, with dire psychological and socio-economic consequences. Building on past work linking objectification with greater appearance motives, the current research investigates how attitudes toward objectification influences the offer and demand for an iconic conspicuous product: heels. Namely, we expect that (1) reminders of the negative consequences of objectification on women will lower the demand for heels and (2) designers from socio-cultural background in which objectification is higher will promote greater prevalence of heel in brands’ collections. A first study examines longitudinal product-level data from a leading online retailer in three countries before and after an event that made the negative consequences of objectification salient – the #MeToo movement – which was followed by a significant drop in actual heel purchases, mostly driven by red heeled shoes. A second study examines exhaustive shoe assortment data from a global online fashion portal. Brands whose designers are (a) men, (b) from high gender inequality countries, and (c) born before the sexual revolution (1970s) have a greater proportion of heels in their collection.



14.45–15.30 – "Predicting Trial and Repeat Purchase of Consumer Packaged Goods From Aggregated(Grouped) Data: A Model,” Albert C. Bemmaor, ESSEC Business School

Abstract: The author develops a model that separates trial from repeat purchases of new products. Themodel relies on the following assumptions: (i) Times to trial are distributed as Pareto across consumers, (ii) repeat purchases are consistent with a NBD, and (iii) adoption rates and repeat purchasing frequencies are independent. Despite their apparent simplicity, it can be shown that these assumptions are consistent with previous empirical findings. The result is the Pareto/NBD of the second kind. The model is tested on grouped (purchasing frequency) data and aggregated (sales) data for a total of 22 products. The results show that, when compared to a model which is estimated on such granular data as individual-level transactions with marketing variables, the Pareto/NBD of the second kind provides forecasts of trial and repeat purchases with a comparable accuracy from purchasing frequency data alone. When the model is estimated with sales data and marketing variables are included, trial and repeat can be recovered with an error which is similar to that obtained from granular data. The level oferror is also assessed with a simulation and shown to be quite low.



15.30-16.00 – Coffee break



16.00–16.45 – ”Effects of a Single Negative Review on Online Search and Purchase:” Marton Varga, INSEAD

Abstract: We estimate the impact of a single negative review on consumers' online shopping activity at a multi-category retailer. Since the retailer shows recently submitted reviews first, upon the arrival of a new review some older ones will be displayed on higher order review-pages. Therefore, we can compare consumers who searched for a product when on its first review-page there was a negative review with consumers who searched for the same product when that negative review was available on the second review-page only - thereby requiring an additional click to view. Our identification strategy tackles the problem of spurious correlation between newest reviews and unobserved demand fluctuations and provides an approximation for the effect of submitting a negative review. We find that among consumers who see a bad review the probability of purchasing the product drops by 17.2%, while the probability of continued search for other items increases by 5.2%. We derive own-review and cross-review elasticities (i.e. changes in sales of the focal product and of its competitors due to a bad review) for hundreds of items in Tech and Home-&-Garden categories, and illustrate the managerial usefulness of our method.

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