Publications

Abstract http://www.tei-c.org/ns/1.0">Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation for early diagnosis tests for NDDs. We conducted a discrete choice experiment with a representative sample of the French adult population (N = 1017). Participants were asked to choose between early diagnosis tests that differed in terms of: (1) type of test (saliva vs. AI-based tests analysing electronic health records); (2) identity of the person communicating the test results; (3) sensitivity; (4) specificity; and (5) price. We calculated the weights in the decision for each attribute and examined how socio-demographic characteristics influenced them. Respondents revealed a reduced utility value when AI-based testing was involved (valuated at an average of €36.08, CI [€22.13; €50.89]) and when results were communicated by a private company (€95.15, CI [€82.01; €109.82]). We interpret these figures as the shadow price that the public attaches to medical data privacy. Beyond monetization, our representative sample of the French population appears reluctant to adopt AI-powered screening, particularly when performed on large sets of personal data. However, they would be more supportive when medical expertise is associated with the tests.
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Abstract Honest and dishonest behaviors may both diffuse among the members of an organization. Knowing which of the two spreads faster is important because it impacts the extent to which managers will need to resort to other, potentially more costly solutions to curb dishonest behavior. Assessing empirically which of honest behavior or dishonest behavior spreads faster is challenging because this requires field measurements of social relationships and dishonest behavior of individual members, which poses both measurement and inference problems. We examine an original fine-grained data set from a large company that allows for identifying agents likely to be dishonest and interactions among employees while offering a natural experiment that circumvents the inference problems associated with identifying peer-to-peer diffusion. We find (1) that dishonest behavior diffuses, whereas honest behavior does not; (2) that diffusion likely operates through spreading information about opportunities for collusion; and (3) that policies that screen on dishonesty at hiring may be efficient to curb dishonest behavior in environments with high turnover. This paper was accepted by Lamar Pierce, organizations. Funding: R. Ferrali acknowledges support from the Mamdouha S. Bobst Center for Peace and Justice [Grant 2016-12-Bobst], the French National Research Agency [Grant ANR-17-EURE-0020], and Aix-Marseille University—A*MIDEX [Excellence Initiative]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01981 .
Keywords Natural experiment, Dishonesty, Organization Behavior, Network analysis
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Abstract In this article, we propose a theory that explains how Free/Libre Open Software (FLOSS) projects work and how companies rely on these FLOSS projects to develop their commercial offers, what we refer to as their "opensource" business model(s). This article builds on and refines the studies of the FLOSS organization by connecting two interrelated aspects: 1) how this organization evolves over time, in order to 2) better understand the value that users create and capture at each moment of a FLOSS project, with a particular focus on open-source companies, which are specific users who do business based on the software created by the FLOSS project. We describe these models and show that the open-source business models of companies are based on contributing to FLOSS projects in order to be able to provide "3A" services (assurance, adaptation, and assistance or support for use) that are complementary to the access to the software. Providing these services requires participation in the FLOSS project, which provides the project with the resources to operate. This work can help the software engineering community by showing how FLOSS evaluation tools can be improved by taking into account the maturity of the solution, the strategic need of the target user, and the complementary open-source offers that exist.
Keywords FLOSS, Open-source, Business models, Value network, Software-flow, Strategy, FLOSS Open-source Business models Value network Software-flow Strategy, FLOSS
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Abstract 101 real couples participated in a controlled experimental risk-taking task involving variations in household and individual income risks, while controlling for ex-ante income inequality. Our design disentangles the effects of household risk, intra-household risk inequality, and ex-post payoff inequality. We find that most couples (about 79%) pooled their risk at the household level when risks were borne symmetrically, but a significant proportion of couples (about 36%) failed to do so when individual risks were borne asymmetrically. Additionally, within the scope of the control variables we have utilized, we find that intra-household risk inequality has a larger impact on non-married couples compared to married ones. These results remain robust when the analysis is limited to couples in which both spouses are risk-averse. Lastly, we find that preferences for household efficiency are significantly correlated across both certain and risky situations. However, couples consisting of two income-maximizing spouses do not show greater aversion to risk inequality compared to couples with other compositions.
Keywords Experiment, Household risk taking, Inequality
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Abstract We study candidates' position adjustments in response to information about voters' preferences. Repositioning allows candidates to move closer to the median voter, but it incurs financial and electoral costs. In a subgame-perfect equilibrium, candidates diverge from the center ex ante if the costs of adjustment are sufficiently large. This allows them to increase the chances of a costless victory when the information is strongly in their favor. Our theory highlights a dynamic of moderation during the campaign stage in competitive elections, as well as a prominent role for minor adjustments made preemptively by the favored candidate. JEL Classification: C72, D72, D82 Model. We enrich the Downs-Hotelling framework by introducing an information shock, creating a two-stage game. The shock reveals the location of the median voter. This captures the idea that voters' aggregate preferences fluctuate over time and that their current leanings are disclosed during the electoral cam-This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Keywords Re-positioning, Spatial voting, Imperfect information, Flip-flop
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Abstract Recent data from US states reveal a negative correlation between environmental degradation and environmental concerns, which in turn seem inversely linked to fertility rates. We introduce a dynamic model to examine explicitly this interplay and explain the observed positive correlation between the carbon intensity of the economy and fertility in data from US states. The key ingredient of our model is that preferences for the number of children and environmental concerns may be complementary or substitutable. Interesting results occur when environmental concerns and the number of children are substitutable. At a stable steady state, a stronger effect of environmental concerns on household preferences reduces the number of children, as stressed by recent literature. The dynamics show that lower fertility rates are associated with lower environmental impacts from economic production, such as reduced carbon intensity.
Keywords Environmental concerns, Environmental degradation, Transitional dynamics, Fertility, Carbon intensity
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Abstract Recent data from US States reveal a negative correlation between environmental degradation and environmental concerns, which in turn seem inversely linked to fertility rates. We introduce a dynamic model to examine explicitly this interplay and explain the observed positive correlation between the carbon intensity of the economy and fertility in data from US States. The key ingredient of our model is that preferences for the number of children and environmental concerns may be complementary or substitutable. Interesting results occur when environmental concerns and the number of children are substitutable. At a stable steady state, a stronger effect of environmental concerns on household preferences reduces the number of children, as stressed by recent literature. The dynamics show that lower fertility rates are associated with lower environmental impacts from economic production, such as reduced carbon intensity.
Keywords Carbon intensity Fertility Environmental concerns Environmental degradation Transitional dynamics
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Abstract Présentation éditoriale du numéro spécial consacré à Bertrand Lemennicier
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Abstract Who makes it to the top? We use the leading socio-economic survey in Germany, supplemented by extensive data on the rich, to answer this question. We identify the key predictors for belonging to the top 1 percent of income, wealth, and both distributions jointly. Although we consider many, only a few traits matter: Entrepreneurship and self-employment in conjunction with a sizable inheritance of company assets is the most important covariate combination across all rich groups. Our data suggest that all top 1 percent groups, but especially the joint top 1 percent, are predominantly populated by intergenerational entrepreneurs.
Keywords Top wealth, Top income, Rich-group classification modeling, Predictions, Intergenerational transfers
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Abstract How to allocate limited resources among children is a crucial household decision, especially in developing countries where it can have strong implications for children and family survival. We provide the first large scale study linking variations in parental income in the early life of children to subsequent child health and parental investments across siblings in developing countries, using data from multiple waves of the Demographic and Health Surveys spanning 54 countries. Variations in the world prices of locally suitable crops are used as measures of local income. We find that children born in periods of higher income receive better health investments and display persistently higher levels of health than their siblings. Children whose siblings were born during favourable income periods receive less investment and exhibit worse health. These findings are consistent with a model of sibling rivalry where parents invest in the child with the highest returns and complementarities in investment across periods. We also provide evidence that other investments (education, parental time use and child labour) react to sibling rivalry. Our results suggest that income shocks can enlarge disparities within households.
Keywords Intra-household allocations, Parental investments, Income, Health
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