Abstract : This article studies competition between different types of ad-funded platforms attracting consumers with free services. Consumers often find advertisements a nuisance on such platforms. We study how under a competitive setting platforms balance the tension between attracting consumers and rent extraction from the advertising side. We propose a flexible yet simple model that studies competition between standard platforms and social media platforms (with same-side network effects). We find that an increase in either positive same-side network effects or an increase in consumer disutility from advertisements leads to a reduction in the number of ads on that platform. When competing platforms merge, consumer side network effects do not impact prices and the number of ads is higher resulting in lower consumer surplus. In a setting where consumers present a negative (congestion) externality on each other, competition fails to protect consumer welfare and behaves erratically. Finally, we present a few extensions and discuss some policy implications.

Abstract : Paper connected to the topic: https://dox.ulg.ac.be/index.php/s/yL0SPoHITo8dd5M

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Abstract : How exactly do individuals approach financial decisions? Do they apply sophisticated formulas, back of the envelope math, do they guess or something else? We show that literally asking individuals to explain their approaches generates new insights about those questions that are reliable and have predictive power out of sample. We find, for example, that when assessing the value of an annuity 40% of individuals use some math with some using formulas similar to actuaries; the other 60% apply guessing strategies. Valuation approaches predict valuation results, valuation precision, and behavioral reaction to a priming intervention designed to match one approach discovered. Our method opens new pathways to understanding financial decision making as well as designing effective policy interventions.

Abstract : This article studies competition between platforms that attract consumers with « free » services and are funded by advertisements. Consumers often find advertisements a nuisance on such platforms. We study how under a competitive setting, platforms balances the tension between attracting consumers and rent extraction from the advertising side. We propose a flexible yet simple model that studies competition between standard platforms ( without same-side network effects) and social media platforms (with same-side network effects). We find that an increase in either same-side network effects (consumers valuing the presence of other consumers) or an increase in consumer disutility from advertisements leads to a reduction in the advertisements on a platform. We then look at a setting when competing platforms merge and find that networks effects (same side or cross side advertisement disutility) do not impact prices and advertisements are higher (unambiguously). Finally, we discuss multiple extensions such as multi-homing consumers, monopolist platforms and the case of consumer congestion (negative same side utility).

Abstract : We investigate the strategies of a data intermediary selling customized consumer information to firms for price discrimination purpose. We analyze how the mechanism through which the data intermediary sells information influences how much consumer data he will collect and sell to firms, and how it impacts consumer surplus. We consider three selling mechanisms tailored to sell customized consumer information: take it or leave it offers, sequential bargaining, and auctions. We show that the more data the intermediary collects, the lower consumer surplus. Consumer data collection is minimized, and consumer surplus maximized under the take it or leave it mechanism, which is the least profitable mechanism for the intermediary. We discuss several regulatory tools – price caps and symmetric offers – that can be used by data protection agencies and competition authorities to limit consumer information collection and increase consumer surplus.

The paper is available at : https://hal.archives-ouvertes.fr/hal-02288708/document

Abstract : De nombreux progrès ont été réalisés sur l’égalité F/H mais mais les différences de statut entre hommes et femmes subsistent dans de nombreux domaines et certains stéréotypes perdurent. La reconnaissance d’une place à part entière pour les femmes joue un rôle majeur dans celle de l’égalité de toutes les différences. Les progrès dans le domaine du droit des femmes améliorent aussi les droits des hommes. Ainsi, la prise en compte de la parentalité par l’entreprise favorise la présence des hommes dans la sphère privée. Mener une politique en faveur de la diversité, c’est d’abord favoriser la mixité, la parité dans tous les métiers et dans l’ensemble de la hiérarchie. L’entreprise a un rôle majeur à jouer dans cette évolution sociale à venir.

Biographie de l’auteur
Patrick Banon est écrivain, essayiste, spécialisé en sciences des religions et systèmes de pensée, notamment dans l’étude des monothéismes (EPHE-École Pratique des Hautes Études), chercheur affilié à la Chaire Management & Diversité de l’université de Paris-Dauphine, Patrick Banon est expert auprès de l’APM (Association Progrès du Management) et conseiller auprès d’entreprises et d’institutions en gestion de la diversité culturelle et religieuse. Il est spécialisé dans les systèmes de pensées et engagé dans la défense du droit des femmes dans le monde. Il a publié une vingtaine d’ouvrages dont notamment : Il était une fois les filles – Mythologie de la différence chez Actes Sud , Ces femmes martyrs de l’intégrisme chez Arnaud Colin , Dieu et l’entreprise chez Eyrolles

Livre Osons la mixité, Editions Prisma 2015: https://www.amazon.fr/Osons-mixit-Patrick-Banon/dp/2810413673

Abstract : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627 – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064

Abstract : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627 – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064

Abstract : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627 – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064

Abstract : Who Holds Positions in Agricultural Futures Markets
We use non-public data regarding all trader-level futures positions, reported to the U.S. grain and oilseed derivatives market regulator (the CFTC), in order to describe the nature of market participants, the maturity structure of their holdings, and the aggregate position patterns for nine different categories of traders that we separate based on their main lines of business. We provide novel evidence about the overall extent of calendar spreading and about the contribution of commercial traders to total spreading activity.

Our sample’s 3,854 traders account for 86 to 93 percent of the total futures open interest at the end of an average day in 2015–2018. Well over 90 percent of their positions have maturities of less than a year. Among our nine trader categories, just three (hedge funds and commercial dealers/merchants, plus commodity index traders on the long side) account for about four fifths of all reported trader positions. In fact, fewer than 200 “permanent” large traders (overwhelmingly from these three categories) make up the bulk of the daily open interest in the four largest agricultural futures markets.

In the aggregate, the positions of commercial dealers and hedge funds (including commodity pool operators, commodity trading advisors, managed money traders, and associated persons) are highly negatively correlated. This correlation is strikingly strong for short positions: as a result, the sum total of commercial dealers’ and hedge funds’ respective shares of the short open interest fluctuates relatively little over time.

We show, for the first time, that calendar spreads account for more than a third of all large trader positions; that much of the intra-year variation in the total futures open interest can be tied to changes in the extent of calendar spreading; that about half of all spread positions involve contracts expiring in 4 to 12 months (either spreading with shorter-dated contracts, or involving only maturities of 4 to 12 months); and that commercial traders who are not swap dealers (dealers and merchants, mostly) make up from a quarter to two fifths of all calendar spread positions. Again, commercial dealers’ and hedge funds’ shares of the spread open interest are negatively correlated. None of these patterns can be inferred from public data, as the CFTC’s Commitments of Traders Reports (COT) do not break out spreads for commercial traders in general and commercial dealers and merchants in particular. “https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627”

The Financialization of Food
Commodity-equity return co-movements rose dramatically during the Great Recession. This development took place following what has been dubbed the “financialization” of commodity markets. We first document changes since 1995 in the relative importance of financial institutions’ activity in agricultural futures markets. We then use a structural VAR model to ascertain the role of that activity in explaining correlations between weekly grain, livestock, and equity returns in 1995-2015. We provide robust evidence that, accounting for shocks which are idiosyncratic to agricultural markets, world business cycle shocks have a substantial and long-lasting impact on the latter’s co-movements with financial markets. In contrast, changes in the intensity of financial speculation have an impact on cross-market return linkages that is shorter-lived and not statistically significant in all model specifications.
“https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064”

Abstract : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627 – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064

Abstract : https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3438627 – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2323064

Abstract : Recent technological developments have raised concerns about threats to democracy because of their potential to distort election outcomes: (a) data-driven voter research enabling political microtargeting, and (b) growing news consumption via social media and news aggregators that obfuscate the origin of news items, leading to voters’ unawareness about a news sender’s identity. We provide a theoretical framework in which we can analyze the effects that microtargeting by political interest groups and unawareness have on election outcomes in comparison to “conventional” news reporting. We show which voter groups suffer from which technological development, (a) or (b). While both microtargeting and unawareness have negative effects on voter welfare, we show that only unawareness can flip an election. Our model framework allows the theory-based discussion of policy proposals, such as to ban microtargeting or to require news platforms to signal the political orientation of a news item’s originator.

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Abstract : There is an accepted idea that risk measurements are pro-cyclical: in times of crisis, they overestimate the future risk, while they underestimate it in quiet times. We lay down a methodology to evaluate the amount of pro-cyclicality in the way financial institutions measure risk, and identify two main factors explaining this pro-cyclical behavior: the clustering and return-to-the-mean of volatility, as it could have been anticipated but not yet quantified, and, more surprisingly, the very way risk is measured, independently of this return-to-the-mean effect. We provide CLTs and FCLT’s for functionals of quantile and dispersion estimators to support theoretically those empirical findings.

Abstract : In this paper, we consider a market where a platform has private information about which product markets are profitable. We study under which conditions the platform benefits from selling its market information exclusively to one participating seller rather than to any interested seller. We show that exclusive dealing is the preferred data monetization strategy if the relative value of operating as a monopoly seller in a profitable market is sufficiently high. In this case, we show that the platform also prefers selling exclusively its data to a seller rather than vertically integrating into the product market.

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Abstract : Change-point (CP) VAR models face a dimensionality curse due to the proliferation of parameters that arises when new breaks are detected. To handle large data sets, we introduce the Sparse CP-VAR model that determines which parameters truly vary when a break is detected. By doing so, the number of new parameters to estimate at each regime is drastically reduced and the CP dynamic becomes easier to interpret. The Sparse CP-VAR model disentangles the dynamics of the mean
parameters and the covariance matrix. The latter is driven by an infinite hidden Markov framework while the former uses CP dynamics with shrinkage prior distributions. A simulation study highlights that the framework detects correctly the number of breaks per model parameter, and that it takes advantage of common breaks in the cross-sectional dimension to more precisely estimate them. Our applications on financial and macroeconomic systems highlight that the Sparse CP-VAR model help interpreting the detected breaks. It turns out that many spillover effects have zero regimes meaning that they are zero for the entire sample period. Forecasting wise, the Sparse CP-VAR model is competitive against several recent time-varying parameter and CP-VAR models in terms of log predictive densities.

Abstract : Feature selection is receiving increasing attention in Machine Learning and Statistics. In the context of linear regression, feature selection is often formulated as a regularization problem, where the regressors are selected with the help of a term associated with the size of the regression coefficients. Such approach has led to the well-established Ridge and Lasso methods. More recently, approaches based on Mixed Integer Programming (MIP) have been introduced to directly control the size of the active set. Although computationally demanding, such approaches exhibit interesting properties and are gaining popularity due the increasing power of solvers. In this talk I will introduce the basic concepts of regularization in regression and a recent MIP-based method with reduced computational burden and improved performances in the presence of feature collinearity and signals that vary in nature and strength.

Abstract : The question of data has been at the center of recent debates around competition policy in the digital era. Concerns in this area are wide-ranging, and encompass privacy, collusion, barriers to entry, exploitative practices, and data-driven mergers.
Data can serve several purposes: for instance it can be used to improve algorithms, to target advertising, or to offer personalized discounts to consumers. While this heterogeneity of uses for data has sparked a large literature in economics, the multiplicity of models makes it difficult to draw general conclusions about the competitive effects of data.
In this paper we introduce data into a competition-in-utility framework à la Armstrong and Vickers (2001). The three key features of data are that (i) it allows to generate more revenue for a given level of utility, (ii) it is a byproduct of firms’ economic activity, and (iii) it is a club good (non-rival and excludable).
We provide a sufficient condition for data to be pro-competitive, and apply it to several environments illustrating the variety of uses for data. This analysis sheds light on the tension between the static and the dynamic effects of data: this is precisely when data increases short-term equilibrium consumer surplus that it can be used as a barrier to entry or that it can result in market-tipping.
We then use this framework to study data-driven mergers. We consider two data-connected markets A and B: the data obtained as a byproduct of firm A’s activity can be used by firms in market B. While the concerns expressed so far by antitrust authorities revolve around the idea of input foreclosure, we show that a merger between firms in the A and B markets also affect the incentives to collect data. A critical condition for the merger to be desirable is for data-trade to be impossible absent the merger.

Abstract : This article studies incentives for a premium provider (Superstar) to offer exclusive contracts to competing platforms mediating the interactions between consumers and firms. When platform competition is intense, more consumers subscribe to the platform hosting the Superstar exclusively. This mechanism is self-reinforcing as firms follow consumer decisions and (some) join exclusively the platform with the Superstar. Exclusivity always benefits firms and may benefit consumers. Moreover, when the Superstar is integrated with a platform, non-exclusivity becomes more likely than if the Superstar was independent. This analysis provides several implications for managers and policy makers operating in digital and traditional markets.

Abstract : Shortages are highly costly in retail, but are less of a concern for store managers, as their exact amounts are usually not recorded. In order to align incentives and attain desired service levels, retailers need to design mechanisms in the absence of information on shortage quantities.
We consider the incentive design problem of a retailer that delegates stocking decisions to its store managers who are privately informed about local demand. The headquarters knows that the underlying demand process at a store is one of J possible Wiener processes, whereas the store manager knows the specific process. The store manager creates a single order before each period. The headquarters uses an incentive scheme that is based on the end-of-period leftover inventory and on a stock-out occasion at a prespecified inspection time before the end of a period. The problem for the headquarters is to determine the inspection time and the significance of a stock-out relative to leftover inventory in evaluating the performance of the store manager. We formulate the problem as a constrained nonlinear optimization problem in the single period setting and a dynamic program in the multiperiod setting. We show that the proposed “early inspection” scheme leads to perfect alignment when J=2 under mild conditions. In more general cases, we show that the scheme performs strictly better than inspecting stock-outs at the end and achieves near-perfect alignment. Our numerical experiments, using both synthetic and real data, reveal that this scheme clearly outperforms centralized ordering systems that are common practice and can lead to considerable cost reductions.

Abstract : We investigate hedge funds’ unobserved performance (UP), measured as the riskadjusted return difference between a fund firm’s reported return and the hypothetical portfolio return derived from its disclosed long equity holdings. We find that high UP is (i) positively associated with measures of managerial incentives, discretion, and skill, and (ii) driven by a fund firm’s frequent trading in equity positions, derivatives usage, short selling, and confidential holdings. Fund firms with high UP outperform fund firms with low UP by more than 6% p.a. after accounting for typical hedge fund risk factors and fund characteristics.

Abstract : Data protection legislation such as the European GDPR uses publicity, fines and a new consumer opt-in requirement to incentivise firms to protect personal data. We argue that the significance of the opt-in requirement is best understood by taking account of consumer loss aversion. Digital firms attract consumers by offering service enhancements and data security which require separate types of investment. We set out the conditions under which opt-in increases both types of investment and when security comes at the expense of service quality. We also study the welfare consequences of regulation for different types of consumer. We show that data protection legislation which includes the opt-in requirement may dilute the effect of fines but also be less harmful to investment in service enhancement.

Abstract : Introduction the research topics « Kidney exchange problem » (Marie Baratto) and « Food Waste » (Anaïs Lemaire) in the context of the advanced course « Advanced Topics in Supply Chain Management » given by Yasemin Arda.

Abstract : The Smart City discussion increased during last years. Along with changing urban challenges the discussions concentrates on different topics and – most of all – on different methodologies of implementation and shows a shift in its objectives. Generally spoken, today we can increasingly distinguish between the understanding of Smart City 1.0, SC 2.0 and recently of SC 3.0.
In this contribution, I want to look at these changes, discuss some examples with respective advantages and disadvantages. Finally, I will discuss and argue that the concept so called urban living labs are supporting the idea of ‘open Innovation’ – and therefore provide new possibilities and obstacles for the inclusion of local actors with local knowledge.

Abstract : We offer an overlapping generations equilibrium model of cryptocurrency pricing and confront it to new data on bitcoin transactional benefits and costs. The model emphasizes that the fundamental value of the cryptocurrency is the stream of net transactional benefits it will provide, which depend on its future prices. The link between future and present prices implies that returns can exhibit large volatility unrelated to fundamentals. We construct an index measuring the ease with which bitcoins can be used to purchase goods and services, and we also measure costs incurred by bitcoin owners. Consistent with the model, estimated transactional net benefits explain a statistically significant fraction of bitcoin returns.

Abstract : En Belgique, la représentation des acteurs socio-économiques et leur participation à la prise de décision politique sont organisées par l’entremise de la concertation sociale. Historiquement, les organisations représentatives des travailleurs et les organisations représentatives des employeurs se rassemblent au sein d’instances spécifiques, afin de dégager des accords consensuels qui porteront potentiellement effet dans le processus de décision politique. Il s’agit dès lors d’explorer les possibilités pour les acteurs portant les intérêts de l’économie sociale d’être représentés et de prendre part à ce système. La recherche doctorale menée à ce sujet met au jour les intentions des acteurs de l’économie sociale face à la concertation sociale et éclaire les positions marginales qu’ils occupent actuellement dans les instances belges, bruxelloises, flamandes et wallonnes, qui y sont relatives.

Abstract : E-commerce is a thriving market around the world and suits very well the busy lifestyle of today’s customers. In 2016 consumers in US were purchasing more things online than in stores. Meantime. This growing e-commerce poses a huge challenge for transportation companies, especially in the last mile delivery that hefty share in total parcel delivery cost often reaches or even exceeds 50%, making it a top concern for many companies. In order to gain a competitive advantage, companies are exploring creative and innovative solutions to improve the efficiency of the last mile delivery. Nowadays, the most common delivery service is home delivery. Customers wait at home to get their orders. Besides home delivery, companies like Amazon, Fedex, etc., develop locker delivery. When customers shop online, they can choose a nearby locker as a pickup location. In the recent two years, there is a new concept called trunk delivery that allows to deliver goods to the trunk of a car. Volvo launched its in-car delivery service in Sweden in 2016 which allows the owners of Volvo to choose their cars as delivery locations. What interests us is to combine all these delivery services and study an efficient last mile delivery system. The problem that arises in this context is a vehicle routing problem with synchronization characteristics since when the order is delivered to a customer’s car, it requires the simultaneous presence of the shipper and the car at the same location. In this seminar we will formally introduce the problem and the mathematical formulation. We then present the algorithms that we developed to tackle the problem and the results that we obtain on benchmark instances.

Abstract : We propose a generic framework for Bayesian inference in distributional regression models in which each parameter of a potentially complex response distribution and not only the mean is related to a structured additive predictor. The latter is composed additively of a variety of different functional effect types such as nonlinear effects, spatial effects, random coefficients, interaction surfaces or other (possibly nonstandard) basis function representations. To enforce specific properties of the functional effects such as smoothness, informative multivariate Gaussian priors are assigned to the basis function coefficients. Inference can then be based on computationally efficient Markov chain Monte Carlo simulation techniques where a generic procedure makes use of distribution-specific iteratively weighted least squares approximations to the full conditionals. We will discuss practical aspects of distributional regression along different applications concerning for example the analysis of income inequality in Germany.

Abstract : This study investigates the export behavior of SMEs in an emerging country, Russia. Instead of isolating individual conditions that lead companies to export, we focus on the conjunctural causation of exporting and the presence of equifinality and asymmetry in the decision to export. This last causal pattern is explored by contrasting the sufficient and necessary conditions for non-exporting SMEs with those that export. For performing our analysis, we selected frequently used independent variables in the export literature and study the export behavior of private manufacturing Russian SMEs in 2013. The outcome of our empirical analysis shows the importance of considering causal complexity when assessing exporting behavior. In particular, we were able to identify sufficient and necessary conditions for nonexporting behavior, but only necessary conditions related with exporting.

Abstract : We introduce a new statistical methodology to form portfolios of private market funds with similar risk-return profiles, which we interpret as private factors. We find that two private factors are priced. The first priced factor, dominated by European Buyout funds, is well spanned by commonly used public equity factors. The second priced factor is dominated by valueadd real estate and mezzanine funds, is unspanned by public equity factors. A non-priced factor, dominated by natural resources funds, provides significant diversification benefits and an inflation hedge despite being well spanned by public equity factors.

Abstract : Un nombre croissant de théoriciens et d’acteurs soutiennent le développement d’une conception participative et délibérative de la démocratie pour pallier le malaise contemporain du gouvernement représentatif. Cette tendance est marquée par le développement de dispositifs où des citoyens, recrutés suite à un processus de tirage au sort, prennent part à une expérience de délibération publique. Les exemples les plus standardisés sont les panels citoyens, les conférences de consensus et les sondages délibératifs, mais également les jurys d’assises qui ont une histoire plus ancienne. Le séminaire propose d’explorer ces pratiques en traitant deux questions: (1) Les citoyens sont-ils intéressés par un tel mode de participation (2) quelles sont les conséquences externes de ces dispositifs?
Inscriptions auprès d’Elodie Dessy: edessy@uliege.be

Abstract : En Europe, une entreprise sociale se livre à une activité économique tout en poursuivant une finalité sociale et en mettant en œuvre une gouvernance inclusive. À suivre le discours des instances internationales, dans une optique favorable à leur développement et à leur pérennité, les entreprises sociales ne devraient pas être taxées comme les entreprises commerciales, dans la mesure où une telle charge fiscale pourrait, à long terme, menacer leur viabilité (nécessité d’un « cadre fiscal approprié et cohérent »). Par le biais d’une étude rétrospective, descriptive et prospective, nous pouvons conclure que, en matière d’impôts sur les revenus, ce cadre fiscal approprié et cohérent n’existe pas en Belgique (première partie) et que la mise en place d’un tel cadre nécessiterait un changement de paradigme : ce n’est plus la réalisation de profits qui devrait déterminer le régime de fiscalisation mais l’affectation réservée à ces profits (deuxième partie). Ce séminaire permettra notamment d’évoquer des évolutions quasi-croisées entre droit des personnes morales et droit fiscal : alors qu’au fil du temps le régime de fiscalisation des revenus des entreprises sociales s’est orienté vers une sanctuarisation du critère de l’activité (pour une même activité réalisée, un même impôt doit en principe être appliqué), sous l’effet du Code des sociétés et des associations, le droit des personnes morales connaitra une sanctuarisation du critère de la finalité (association, fondation et société se distingueront uniquement selon leur finalité).

Abstract : Over its history, organization studies has too rarely interrogated a fundamental, yet deceptively simple, question: What is an organization? Although the lion’s share of scholarship in management and organization studies conceives of organizations as entities within which communication occurs, “Communication Constitutes Organization” (CCO) scholarship has attracted interest because it makes a productive reversal, that is, by asking how organization happens in communication. CCO scholarship holds that organizations, as well as organizational phenomena, come into existence, persist, and are transformed in and through interconnected communication practices. The presentation aims to resituate CCO theorizing within the linguistic turn and to position CCO with respect to other lines of scholarship underwritten by a rich conception of language and discourse. We contribute to CCO scholarship with reflections on three theoretical orientations and provide a set of possibilities for its further development.

Abstract : This paper examines the relation between the information contained in the two first Greeks of ATM options – Delta and Gamma – and the pricing of stocks. Specifically, I sort the cross-section of US stocks on a Probability Adjusted Implied Volatility Spread (PAVS), defined as the difference in the normalized Delta/Gamma ratio of a zero-delta straddle strategy. I show that a zero-cost trading strategy on this measure provides statistically significant average monthly returns. In particular, the new metric improves the spread from the put-call parity deviations of Cremers and Weinbaum (2010), as it implicitly recovers the probability distribution of stock returns contained in the option pricing model, to obtain market participants’ views about future stock prices.

Abstract : We investigate the characteristics of infrastructure as an asset class from an investment perspective of a limited partner. While non U.S. institutional investors gain exposure to infrastructure assets through a mix of direct investmentsand private fund vehicles, U.S. investors predominantly invest in infrastructure through private funds. We find that the stream of cash flows delivered by private infrastructure funds to institutional investors is very similar to that delivered by other typesof private equity, as reflected by the frequency and amounts of net cash flows. U.S. public pension funds perform worse than other institutional investors in their infrastructure fund investments, although they are exposed to underlying deals with very similarproject stage, concession terms, ownership structure, industry, and geographical location. By selecting funds that invest in projects with poor financial performance, U.S. public pension funds have created an implicit subsidy to infrastructure as an assetclass, which we estimate within the range of $730 million to $3.16 billion per year depending on the benchmark.

Abstract : Team as a Service (TaaS) is a new outsourcing service that enables on-demand creation and management of distributed teams for fast growing companies. The companies that use the TaaS model form a team according to the needs of a given project and provide managerial service throughout. Motivated by this new application, we study the Team Formation Problem (TFP) in which the quality and cost of communication is taken into account using the proximity of the potential members in a social network. Given a set of required skills, TFP aims to construct a capable team that can communicate and collaborate effectively. We study TFP with two measures for communication e ffectiveness: sum of distances and diameter. We compare the quality of solutions using various performance measures. Our experiments indicate the following: First, considering only the sum of distances or the diameter as the communication cost may yield solutions that perform poorly in other performance measures. Second, the heuristics in the literature fi nd solutions that are signifi cantly far from optimal whereas a general purpose solver is capable of solving small and medium size instances to optimality. To fi nd solutions that perform well on several performance measures, we propose the diameter constrained TFP with sum of distances objective. To solve larger sizes, we propose a novel branch and bound approach: we formulate the problem as a quadratic set covering problem, use the reformulation-linearization technique and relaxation to be able to decompose it into a series of linear set covering problems and impose the relaxed constraints through branching. Our computational experiments show that the algorithm is capable of solving large sizes that are intractable for the solver. Finally, we study a two stage stochastic variant of the problem with uncertain communication costs and report the results of preliminary experiments.

Abstract : Deep Learning methods have revolutionized the field of AI, and have shown much promise in applications such as computer vision and natural language processing. In this talk, we will focus on the legal domain. Specifically, we will present our current research (algorithms and results) on deep learning methods applied for analyzing legal texts. These latter texts are particularly problematic to classical NLP algorithms as they are syntactically complex and long, which makes it hard to create computational models of the underlying language. We will describe how deep learning helps in overcoming some of these challenges.

Abstract : Conventional finance models indicate that the magnitude of stock prices should not influence portfolio choices or future returns. This view is contradicted, however, by empirical evidence. In this paper, we report the results of an experiment showing that trading prices, in experimental markets, are processed differently by participants, depending on their magnitude. Our experiment has two consecutive treatments. One where the fundamental value is a small number (the small price market) and a second one where the fundamental value is a large number (the large price market). Small price markets exhibit greater mispricing than large price markets. We obtain this result both between-participants and within-participants. Our findings show that price magnitude influences the way people perceive the distribution of future returns. This result is at odds with standard finance theory but is consistent with: (1) a number of observations in the empirical finance and accounting literature; and (2) evidence in neuropsychology on the use of different mental scales for small and large numbers.

Abstract : In Wallonia (Belgium), the public support for residential solar photovoltaic panels has two interesting features. First, the subsidies for solar production, in the form of tradable green certificates, were particularly generous which encouraged households to have large installations. Second, the region used a net metering system to record power exchanges with the grid. With net metering, the meter runs backwards when power is supplied to the grid. But, if production exceeds consumption on a yearly basis, the production surpluses are freely available for consumption. In this context, we test for a possible rebound effect. Based on a large sample of residential PV installation in Wallonia, we observe in our data and estimations, that a large proportion of households oversize their installation to benefit from the subsidies and, later consume most of their excess production. The effect is highly significant and production surpluses are almost entirely consumed. There are thus evidence of a strong increase in energy consumption by residential PV owners.

Abstract : TBA

Abstract : The promotion of “energy democracy” in low carbon transitions has become a significant topic for energy social science research. Furthermore, research on community energy has tended to assume that grassroots energy initiatives lead to citizen involvement and shared local benefit, despite limited empirical evidence. Here we report the results of cross-national research examining civic participation amongst the members of two renewable energy cooperatives, one based in the UK and the other in Belgium. Results show that levels of participation beyond financial investment varies markedly, with higher levels for relatively low cost, less active activities (e.g. reading newsletters) and lower levels for more active, timeconsuming activities (e.g. attending the Annual General Meeting, volunteering). Social identification is the most important factor explaining multiple forms of participation, with environmental and economic factors less important. The concept of “stealth democracy” is used to discuss the findings and draw out the benefits and risks associated with the importance of social factors for engaging communities in energy transitions.

Biography : Thomas Bauwens is an economist specialized in environmental and energy issues with a pronounced interest in multi-disciplinarity. He is currently a post-doctoral researcher at the Utrecht University’s Copernicus Institute of Sustainable Development. He is conducting research on the roles of circular start-up hubs in the transition towards a circular economy within the framework of a research project funded by the Netherlands Organisation for Scientific Research. He holds a PhD in economics from the Centre for Social Economy within HEC-Management School of the University of Liège (Belgium) and a master in economics from the Economic School of Louvain. During his PhD, he conducted a long-term stay as a visiting researcher at the Environmental Change Institute, University of Oxford. After that he completed a post-doctoral research stay at the Swiss Federal Institute of Technology in Lausanne (EPFL) within the Human-Environment Relations in Urban Systems (HERUS) Laboratory.

Abstract : Following the development of decentralized generation and smart appliances, energy communities have become a phenomenon of increased interest. While the benefits of such communities have been discussed, there is increasing concern that inadequate grid tariffs may lead to excess adoption of such business models. Furthermore, snowball effects may be observed following the effects these communities have on grid tariffs. We show that restraining the study to a simple cost-benefit analysis is far from satisfactory. Therefore, we use the framework of cooperative game theory to take account of the ability of communities to share gains between members. The interaction between energy communities and the DSO then results in a non-cooperative equilibrium. We provide mathematical formulations and intuitions of such effects and carry out realistic numerical applications where communities can invest jointly in solar panels and batteries. We show that such a snowball effect may be observed, but its magnitude and its welfare effects will depend on the grid tariff structure that is implemented, leading to possible PV over-investments.

Abstract : Nous vivons dans un monde digital où la technologie permet de transformer en profondeur de nombreux processus de gestion. Machine et deep learning, blockchain, machines intelligentes et véhicules autonomes, digital twins, IoT, e-textiles, immersion via réalité virtuelle, augmentée et mixte sont quelques-unes des technologies les plus prometteuses pour les entreprises. Dans cet exposé, nous nous concentrerons essentiellement sur les technologies immersives et les présenterons brièvement. Avec la réalité virtuelle, (presque) tout est possible ! En coiffant un casque de réalité virtuelle, l’utilisateur se déconnecte momentanément du monde réel pour être immergé dans un environnement graphique et sonore qui devient sa nouvelle réalité. Dans ce nouvel univers entièrement contrôlable, il peut expérimenter différentes tâches, parfois délicates, en toute sécurité et à moindre coût. Grâce à sa cousine, la réalité augmentée, une personne peut enrichir son environnement (réel) avec des couches d’information et ainsi être aidée dans ses prises de décision et dans le pilotage de processus.
Au HEC Digital Lab, dans le cadre de nos missions d’enseignement, de recherche et de service à la communauté, régulièrement pour répondre à des demandes d’entreprises partenaires, nous concevons de tels environnements et testons comment les rendre les plus immersifs et efficaces. Nous sommes également un membre fondateur du groupe Teaching With VR qui, au niveau de l’Université, prépare de nouvelles formes d’enseignement basée sur ces technologies.
Lors de cette séance, nous utiliserons des casques Oculus, Vive et Hololens pour présenter quelques-uns de nos environnements: apprentissage d’une langue étrangère, validation d’un projet de construction (HEC), gestion d’un entrepôt logistique, sensibilisation à la sécurité sur chantier et aux procédures d’urgence, formation au pilotage d’un Boeing 737, guidage pour la conception de palettes, tourisme et marketing, visite de sites…

Abstract : « Les cas de dommage causés par une multiplicité d’auteurs en droit de la responsabilité civile laissent souvent la jurisprudence comme la doctrine dans une position délicate. De nombreux paradoxes – comme la surdétermination causale par exemple – ont fait douter de la pertinence des notions de causalité juridique appliquées à ces cas. L’article se propose de montrer qu’une modélisation en termes de jeux coopératifs permet de lever un certain nombre de ces paradoxes en fournissant des clefs de répartition entre co-auteurs tout en maintenant une approche cohérente de la causalité juridique. »

Abstract : Invoking the scale invariance property used by most option pricing models, Bates (2005) presents a model-free method to compute the delta and the gamma from the shape of the volatility smile. That promising approach yields hedging strategies which solely rely on market information and whose performance had, to the best of our knowledge, yet to be tested on a large-scale sample. That is what this paper does using roughly 6 million daily hedges of S&P500 calls and puts from January 1996 to April 2016.
Our first major finding is that smile-implied delta-neutral and delta-gamma-neutral hedging strategies cannot outperform their Black-Scholes counterparts neither in a mean-variance framework, nor with a tail risk metric.
In light of these disappointing results, we turn our attention to managing volatility-related Greeks. We extend the relation that holds in the stochastic implied volatility model to build smile-implied vegas, vannas and volgas from smile-implied gammas. We find that the smile-implied delta-gamma-vega neutral hedging strategy strongly outperforms its Black-Scholes counterpart, especially for put options. Adding the vanna or the volga into the hedging strategy does not improve the quality of replication. All in all, our findings suggest that option market information is particularly worthwhile for managing volatility risk, not underlying price risk.

Abstract : While digitalization is not new as such, its rapid and extensive impacts transform deeply many aspects of life, including work and employment. Both very pessimistic and optimistic scenarios about the future of work predict the end of working as we know it. In the context of digitalization, shifts are apparent in how work and employment are carried out, such as the emergence of new types of work organization and labour (for instance, through new means of allocating work such as crowd employment and the sharing economy); occupation shifts and new identities (including de-professionalization and user-generated content) and new work relationships arising from geographical dispersion of labour (which involve strategic use of location, potential pressure on regulation regimes). This presents new challenges for policy actors and stakeholders and complicates the potential and arenas for regulation. The objectives of the presentation are to critically discuss the theoretical debates in sociology related to the digitalization of work and employment and to address policy challenges related to digitalization of work and employment. The presentation is based on the recently published book: Meil, P., Kirov, V. (eds.), (2017), “Policy Implications of Virtual Work”, Basingstoke: Palgrave.

Abstract : There is ample evidence that Governmental Venture Capital (GVC) funds exert a negligible role on the performance of target ventures, except when they syndicate with private Venture Capital (PVC) investors. Yet, the origination of PVC-GVC syndicates still received no academic attention. Interestingly, very often lead PVC investors decide to invite GVC in their syndicate. In this paper we study the reasons why PVC would chose to do so. While most of the motivations for syndication highlighted by existing literature do not seem to explain the choice of PVC to syndicate with a GVC, we identify three motivations that instead could be relevant. PVC investors could decide to partner up with GVC to i) build a track record, if they do not have one, 2) to diversify their portoflio and invest outside of their industry “comfort zone”, and 3) to invest in risky opportunities, exploiting GVC as a way to lower the exposure to the venture’s risk. We provide evidence on these three causes for syndication with GVC based on a unique international sample of syndicates in which PVC is the lead investor. We show that less experienced PVC investing in industries where they are less comfortable are more likely to invite a GVC partner. In first rounds, also the industry riskiness seems to motivate such choice. We also show that PVC that in the first years of their life partner up with GVC more often, later are able to build a track record faster, and syndicate more with other PVC. Interesting differences emerge across geographical locations: the track record argument is more strongly supported in Europe, while the comfort zone argument effect is driven by US-based syndicates. This result suggests that GVC has a role in the development of VC markets, but such role is different in different economies.

Abstract : We consider a single-machine scheduling problem with release dates and inventory constraints. Each job has a deterministic processing time and has an impact (either positive or negative) on the central inventory level. We aim to find a sequence of jobs such that the makespan is minimized while all release dates and inventory constraints are met. We show that the problem is strongly NP-hard even when the capacity of the inventory is infinite. To solve the problem, we introduce two mixed integer programming (MIP) formulations, a dynamic programming (DP) approach and also a branch-and-bound (B&B) algorithm.
This problem has some interesting applications in scheduling load/unload operations of warehouses. In a loading/unloading terminal, trucks arrive in a loading/unloading dock either to deliver (unload) or to pick up (load) a certain number of final products. The terminal include a storage space that is used to store these final products in inventory.

Abstract : Data brokers collect customer information from several sources and sell them to other firms. We propose a simple model of the sector, in which two data brokers can sell customer level information to a downstream firm. The information enables the downstream firm to price discriminate. The optimal strategy of the data brokers depends on the nature of the information available. In particular, we show that when data are « additive » or « supra-additive », both brokers find it optimal to compete and the downstream firm acquires information from both. However, when data are « sub-additive », with the combined value being lower than the sum of the value of the two datasets, data brokers prefer to share data and sell it jointly.

Abstract : User Stories (US) are the most commonly used requirements artifacts within agile methods such as eXtreme Programming (XP) and Scrum. They are written in natural language using prose or following a specific template. In practice, many templates have been proposed with no semantic for each syntax used in these templates. Within this research, we first propose the unified model for US templates and provide semantic of each syntax. Then, we adapt the goal-oriented modeling language for analyzing US sets; it is called Rationale Tree (RT). It allows identifying dependencies between US and provides a global view of the systems which allows improving the planning activities, and therefore the development life cycle of agile methods.

Abstract : 
A streaming platform obtains contents from content providers and offers paying commercial spaces to advertisers. Users value contents’ variety and are heterogeneously bothered by ads. When the size of the market is large, the platform offers only a paying subscription, whereas a small market results in the offer of a menu of subscriptions, with ad-intolerant users paying a positive price and moderately-averse users opting for a free-of-charge solution.

Abstract : 
Within psychological contract framework, this research examines employment relationships of contingent workers. To do so, it introduces contingency-related psychological contracts, which focuses on unique needs and motivators of contingent workers. The central aim is to investigate the relationship between contingent employees’ perceptions of breach/fulfillment of contingency-related psychological contracts and their work outcomes (i.e., job satisfaction, turnover intention, organizational identification, and organizational citizenship behavior). This research gives special attention to one particular group of contingent workers, who are involved in any form of triangular employment relationships (e.g., agency workers, platform workers, and etc.).

Abstract :  In this paper, we take a new look at the relationship between interest rate differentials and exchange rates.
To do so, we introduce a forecasting approach that accounts for high-order dependencies in daily exchange rates.
Our model relies on a GARCH-in-mean specification where the innovations are assumed to follow a sinh-arcsinh (SH) ditribution with a time-varying asymmetry parameter, depending on interest rates. This model is used to predict the direction of change of three major currency pairs (USD/EUR, USD/GBP and USD/CHF) over the period 1999-2016. We find a dynamic asymmetry specification to be significant and driven by the interest rates. Economically speaking, we show that, notwithstanding a better in-sample performance compared to benchmark models for all pairs, weare able to obtain a positive out-of-sample performance for the USD/CHF pair.

Abstract : not available

Abstract :In particular, this paper explores different two-stage semi-parametric methods to determine technical efficiency in long-term care provision in Ireland.  Technical efficiency (TE) scores in the health sector literature are often estimated using either a non-parametric conventional Data Envelopment Analysis (DEA) or the fully parametric Stochastic Frontier Analysis (SFA) approach.  While the SFA technique accounts for noise in the data and also allows for an unbiased estimation of the factors affecting efficiency, this method requires specification of the functional form of a production or cost function.  On the other hand, DEA does not impose these restrictions.  However, the estimation of the efficiency determinants using the conventional DEA scores in the second stage may lead to biased estimates of both the TE scores and the efficiency determining variables.  This paper tries to fill the gap between the conventional DEA and SFA approaches and applies alternative semi-parametric methods.  The methods considered do not impose any functional form restrictions on the data, and they also account for random sampling variability and reduce the bias in both the estimated TE scores and the estimated efficiency determinants.  In this paper, we model TE in terms of an input distance function which allows us to estimate input-oriented technical efficiencies by investigating how much the input vector can be proportionally reduced while holding the output vector fixed.  Output is measured as total patient days, while inputs are measured as medical staff, non-medical staff and the number of beds in long-term care units. Furthermore, we use several efficiency determining variables which are divided into objective quality characteristics and conventional determinants such as size, ownership, location, chain, case mix and the age of the nursing home facilities.  Additionally, we split the sample into different groups: private and public nursing homes; chain and non-chain private units; and nursing homes located in rural and urban areas.  We find notable differences in the results between the conventional DEA and the semi-parametric methods.  We also derive some conclusive findings with respect to the estimated TE scores and the efficiency determining variables for the long-term care sector in Ireland.

Abstract :We estimate international factor models with time-varying factor exposures and risk premia at the individual stock level using a large unbalanced panel of 58,674 stocks in 46 countries over the 1985-2017 period. We consider market, size, value, momentum, profitability, and investment factors aggregated at the country, regional, and world level. The country market in excess of the world or regional market is required in addition to world or regional factors to capture the factor structure for both developed and emerging markets. We do not reject mixed CAPM models with regional and excess country market factors for 76% of the countries. We do not reject mixed multi-factor models in 80% to 94% of countries. Value and momentum premia show more variability over time and across countries than profitability and investment premia. The excess country market premium is statistically significant in many developed and emerging markets but economically larger in emerging markets.

Abstract :The U.S. is experiencing unprecedented economic, social and ideological stratification linked in part to rapid technological change, economic restructuring, and the growth of « narrowcast » media. All of these contributes to a fragmentation of the very knowledge base of society. We can learn how to address growing inequality and insecurity from certain metropolitan regions that have overcome fragmentation by building diverse knowledge communities and embracing a common regional destiny. Recognizing the importance of collectively produced information and knowledge serves as a basis for rethinking the future of work and employment. This can help us develop a range of new income strategies  and policies—including perhaps a universal technology dividend—to address the high levels of inequality and insecurity we currently face.  

Abstract :Moving beyond initial notions of ‘disability’, ‘ageing’ and ‘physical accessibility’, inclusive design needs to embrace wider contemporary contexts and explore the full spectrum of ‘human diversity’. Thus, moving from ‘physicality’ to overall ‘quality’ of live and exploring non-physical and ‘psycho-social’ elements of inclusivity. This talk explores this concept and its dimensions, exploringthe way forward.

Abstract :This presentation examines the use of transformational technologies and innovative services to enhance mobility and accessibility in Smart Cities. It explores current examples and possible future opportunities to provide improved services to all segments of society and addressing environmental concerns.