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Despite the increasing importance of multiple priors in various domains of economics and the significant theoretical advances concerning them, choice-based incentive-compatible multiple-prior elicitation largely remains an open problem. This paper develops a solution, comprising a preference-based identification of a subject’s probability interval for an event, and two procedures for eliciting it. The method does not rely on specific assumptions about subjects’ ambiguity attitudes or probabilistic sophistication. To demonstrate its feasibility, we implement it in two incentivized experiments to elicit the multiple-prior equivalent of subjects’ cumulative distribution functions over continuous-valued sources of uncertainty. We find a predominance of non-degenerate probability intervals among subjects for all explored sources, with intervals being wider for less familiar sources. Finally, we use our method to undertake the first elicitation of the mixture coefficient in the Hurwicz α-maxmin EU model that fully controls for beliefs.

We show that PE sector specialists outperform generalists at every stage of the investment life cycle. Using granular data for thousands of U.S. hotels over the last two decades, we document that specialists exert a greater positive influence on more margins of hotel operations, earn higher net cash flows over the holding period, and achieve larger capital gains upon exit than do their generalist peers and other, non-PE investors backing ex ante equivalent assets. By contrast, PE generalists’ strongest comparative advantage may be better access to attractively priced acquisition financing. Our results provide novel evidence on the heterogeneity of PE investment strategies and associated performance outcomes.

We study product differentiation in the mutual fund industry. We design a model in which funds with heterogeneous perceived quality can choose their level of product differentiation. In equilibrium, high quality funds choose broad market designs (i.e., low differentiation) appealing to many investors, while low quality funds adopt niche designs (i.e., high differentiation) that investors either love or loath. Using as a measure of fund differentiation the degree of textual uniqueness of investment strategy description in fund prospectuses, we confirm empirically that funds with lower expected performance tend to differentiate more. We use the issuance of Morningstar rating to previously unrated funds as an exogenous shock to perceived quality to identify the economic mechanism. We find that funds receiving a low rating increase their product differentiation. The effect is mainly concentrated on funds run by small management companies, a feature associated with lower performance. This increase in product differentiation makes funds more likely to survive. It also has a market-level impact on the menu of funds available to investors.

This paper compares compensation policies from the perspective of providers and policy makers in an environment with the risk of exogenous service shutdowns. Providers tend to push for vouchers as a means of compensation, whereas customers demand cash refunds or generous vouchers. Regulators, at the same time, insist that customers must be granted the right to be reimbursed in money. To address the debate, this paper develops an analytical model to explore how cash refunds and vouchers can be used for recovery from service failures. First, we show that if the regulator does not require offering cash-back as an option, the optimal voucher policy consists of a service replacement with a zero bonus, whereas a positive bonus is optimal if the cash-back option is mandatory. Second, we find that the voucher-only policy can be more profitable and efficient than the hybrid policy that offers customers a choice between cash-back and voucher. Third, we show that the voucher policy leads to the longest survival time under shutdown, followed by the selling as-is policy and then the hybrid policy, whereas the cash-back policy leads to the shortest survival time. Overall, our results show that the expected profit and survival time are two important dimensions for providers to consider when facing the risk of shutdowns, whereas policy makers want to focus on pre-shutdown efficiency, bankruptcy risk, and post-shutdown customer dissatisfaction.

Newcomers are important for the survival of online communities, but their contributions often receive negative reactions and comments from established members. Online communities realize that such negativity can take a toll on newcomers and harm the creation of user-generated content. We study a novel intervention aimed at reducing hostility toward newcomers: a “newcomer nudge” that informs community members when they are interacting with a newcomer’s post and asks them to be more lenient toward its creator. Taking advantage of granular data from a large deal-sharing community and a natural experiment, we use a difference-in-differences approach and find robust evidence that the newcomer nudge induced members to write 46% more responses per day with 10% fewer negative words during the first two days after a deal was published. Our results show that the nudge-induced change in behavior toward newcomers increased newcomer retention. However, we also observe that before the nudge, newcomers’ second posts received more net votes (upvotes minus downvotes) than their first posts. After the nudge, newcomers’ subsequent posts were less popular than their first posts, which indicates that the nudge interrupted newcomers’ learning curve by suppressing helpful feedback.

In credit markets, screening algorithms discriminate between good-type and bad-type borrowers. This is their raison d’être. However, by doing so, they also often discriminate between individuals sharing a protected attribute (e.g. gender, age, race) and the rest of the population. In this paper, we show how to test (1) whether there exists a statistical significant difference in terms of rejection rates or interest rates, called lack of fairness, between protected and unprotected groups and (2) whether this difference is only due to credit worthiness. When condition (2) is not met, the screening algorithm does not comply with the fair-lending principle and can be qualified as illegal. Our framework provides guidance on how algorithmic fairness can be monitored by lenders, controlled by their regulators, and improved for the benefit of protected groups.

Financial reporting technologies can significantly affect how firms construct and disseminate quantitative and qualitative disclosures. Leveraging the opportunity created by the eXtensible Business Reporting Language (XBRL) mandate in the United States, we use a difference-in-differences approach to examine whether and how a firm’s XBRL adoption affects the readability of its textual disclosures. We find that the initial adopters’ HTML-formatted annual reports become harder to read after the XBRL mandate. Further analysis reveals that this effect is concentrated among adopters with more quantitative disclosures, those with smaller firm size, and those with a higher level of financial complexity. Importantly, we show that managers’ reduced attention to preparing HTML-formatted annual reports, rather than increased disclosures, is likely the explanation for this decrease in textual readability. We also find that the negative effect on textual readability persists at least in the subsequent year. Taken together, our results suggest that although XBRL can standardize numerical disclosures, its initial adoption can divert managerial attention and result in reduced readability of textual disclosures.

Chapter for "Handbook on the Business of Sustainability: The Organization, Implementation, and Practice of Sustainable Growth", edited by Gerry George, Martine R. Haas, Havovi Joshi, Anita McGahan and Paul Tracey; Purpose is a set of common beliefs that guide organizational members’ actions toward long-term achievements, independently of an organization’s immediate profitability. Hence, purpose reveals new motivational mechanisms for employees’ engagement that legitimacy-as-judgment research and prosociality literature address. Drawing on these approaches, this chapter investigates the sources and consequences of organizational purpose. We suggest three avenues for research by emphasizing that purpose is not another organizational goal but differs in its conceptual nature, by addressing aggregation of micro-behavior in terms of incentive structures, and by accounting for the emergence and maintenance of purpose itself.

Work-related social media networks (SMNs) like LinkedIn introduce novel networking opportunities and features that promise to help individuals establish, extend, and maintain social capital (SC). Typically, work-related SMNs offer access to advanced networking features only to premium users in order to encourage basic users to become paying members. Yet, little is known about whether access to these advanced networking features has a causal impact on the accumulation of SC. To close this research gap, we conducted a randomized field experiment and recruited 215 freelancers on a freemium, work-related SMN. Out of these recruited participants, more than 70 received a randomly assigned, free, 12-month premium membership voucher. We observe that individuals do not necessarily accumulate more SC from the ability to access advanced networking features, as the treated freelancers did not automatically change their digitized networking engagement. Those features will only unfold their full utility if the individuals are motivated to proactively engage in networking: Freelancers who have access to advanced networking features increase their SC by 4.609% for each unit increase on the strategic networking behavior scale. We confirm this finding in another study utilizing a second, individual-level panel data covering 52,392 freelancers; in tandem, we investigate the dynamics that active vs. passive features play in SC accumulation. Based on the findings, we introduce the “theory of purposeful feature utilization”: essentially, individuals must not only possess an efficacious “networking weapon"––they also need the intent to “shoot” it.

Real and private-value assets—defined here as the sum of real estate, infrastructure, collectibles, and noncorporate business equity—compose an investment class worth an estimated $84 trillion in the U.S. alone. Furthermore, private values can affect pricing in many other financial markets, such as that for sustainable investments. This paper introduces the research on real assets and private values that can be found in this special issue. It also reviews recent advances and highlights new research directions on a number of topics in the real assets space that we believe to be particularly important and exciting.

Design is increasingly adopted by organization as an innovation capability to renew and transform the firm and therefore acting as dynamic capability. However, few article address how firms build a new dynamic capability and especially in the case of the design capability. Based on a longitudinal case study of the building of design as an innovation capability within an insurance company, we suggest a capability-building framework: a capability is built by acquiring resources, deploying them in activities such as projects, capitalizing on the learning from one project to another, and thus building progressively knowledge that is then shared and diffused among the resources resulting in the renewal of their competences. This framework highlights a reinforcement dimension and distinguishes operations (Designing, spreading Design and managing Design) from building on these operations (building the Design expertise and transforming the organization through Design) in order to contribute to the firm’s resources renewal.

The avalanche of new technologies and artificial intelligence have accelerated financial innovation, compelling the law to undergo a technological update. This phenomenon extends to the likes of regtech, suptech, regulatory big data, algorithmic supervision, etc. The study aims to demonstrate how these new instruments are, in fact, part of an overarching movement observable in numerous fields; that is, the emergence of a scientific, mathematical, algorithmic law driven by risk and technologies (classified as “Smart Law”). The authors will examine the aforementioned theoretical model and highlight the practical implications for banking and finance law. They conclude on the necessity for a structural collaboration between lawyers and engineers in order to manage the inevitable hybridization of the rule of law and its technological integration.

In recent years, greater attention has been given to developing metrics that measure more than a country’s gross domestic product (GDP). Similarly, greater consideration has been given to more than just the financial performance of commercial enterprises; corporations are now expected to conduct business in ways that are responsible and sustainable, giving attention to a triple bottom line where the planet and people are prioritized along with profits. Taking French government policy and the performance of French multinational corporations as a case in point, this article explores the ways in which emerging indicators and instruments on business and human rights are relevant to the impact of business on well-being. This article examines which reporting frameworks and ranking systems best capture human rights and sustainability risks that could compromise well-being. Specifically, the article analyzes the frameworks and indicators used to measure human rights performance and the impact of rights rankings on business management. It also reviews responses by corporations to rights rankings as indicia of how measurements might be perceived as likely to result in changes in investor and consumer behavior or place brand reputation at risk.

When are the incentives of a business ecosystem’s participants aligned with its growth? How is the technology of value creation affecting this alignment? To answer these questions we formally model how value creation determines value capture in a business ecosystem. We find that alignment is typically imperfect compared to an integrated benchmark, highlighting an “ecosystem penalty” whereby participants’ returns to value creation are lower than that of the ecosystem. The occurrence of this penalty depends on whether the technology is loosely coupled (value additive in inputs), exhibits bottlenecks (value constrained by the weaker input), or is strongly supermodular (value multiplicative in inputs). Contrary to conventional wisdom, we find it can be severe for the participants who are constraining the system the most.

The European response to COVID-19 has revealed an inconvenient truth. Despite having integrated public health concerns across all its policies – be it agriculture, consumer protection, or security –, the Union cannot directly act to save people’s lives. Only member states can do so. Yet when they adopted unilateral measures to counter the spread of the virus, those proved not only ineffective but also disruptive on vital supply chains, by ultimately preventing the flow of essential goods and people across the Union. These fragmented efforts in tackling cross-border health threats have almost immediately prompted political calls for the urgent creation of a European Health Union. Yet this call raises more questions than answers. With the aim to offer a rigorous and timely blueprint to decision-makers and the public at large, this Special Issue of the European Journal of Risk Regulation contextualizes such a new political project within the broader constitutional and institutional framework of EU public health law and policy. By introducing the Special, this paper argues that unless the envisaged Health Union will tackle the root causes of what prevented the Union from effectively responding to COVID-19 – the divergent health capacity across the Union –, it might fall short of its declared objective of strengthening the EU’resilience for cross-border health threats.

Do personalized offerings enabled by big data only bring economic benefits to firms but not to consumers? In this paper, we seek to address this question by examining a particular category of personalized offerings provided by algorithmic product recommendation systems. While the economic value of algorithmic product recommendations to firms is mostly understood, their benefits to consumers are not well quantified in the literature. We conduct a randomized field experiment on an apparel retailer’s website in the US to estimate the benefits of recommendations to consumers. We find that recommendations helped consumers discover lower-priced products on the website, which results in a higher probability of product purchase (lower likelihood of failed search efforts) and a lower price of purchased products. Specifically, an additional recommended product page view due to recommendations leads to a 15 percent increase in purchase probability and a $1.59 decrease in the purchase price. The product recommendations are particularly beneficial to consumers for product categories with a higher relative price dispersion and a higher proportion of niche products. Due to these benefits, consumers substitute 0.14 keyword search page views and 0.63 product category page views for each recommended product page view under recommendations. The recommendations generated a surplus of $56,631 (3.8 percent of the total sales), two-thirds of which the retailer captured as additional revenue, and the remaining one-third the consumers as price savings.

We examine whether impact investing is more effective in fostering business venture success and social impact when directed toward ventures located in vs. outside disadvantaged urban areas (i.e., areas with high crime, unemployment, and poverty). We explore this question in the context of loans made to business ventures located in French “banlieues” vs. “non-banlieues”. We find that loans issued to banlieue ventures, compared to non-banlieue ventures, yield greater improvements in financial performance, as well as greater social impact in terms of the creation of local employment opportunities, quality jobs, and jobs for minorities — all of which contribute to the social inclusion of marginalized communities and the development of sustainable cities.

We study how data abundance affects the informativeness of financial analysts' forecasts at various horizons. Analysts produce forecasts of short-term and long-term earnings and choose how much information to collect about each horizon to minimize their expected forecasting error, net of information acquisition costs. When the cost of obtaining short-term information drops (i.e., more data becomes available), analysts change their information collection strategy in a way that renders their short-term forecasts more informative but that possibly reduces the informativeness of their long-term forecasts. Using a large sample of analysts' forecasts at various horizons and novel measures of their exposure to abundant data (e.g., social media data), we provide empirical support for this prediction, which implies that data abundance can impair the quality of long-term forecasts.

Under International Financial Reporting Standards, managers can use two approaches to increase the estimated fair value of goodwill in order to justify not recognizing impairment: (1) make overly optimistic valuation assumptions, and (2) increase future cash flow forecasts by inflating current cash flows. Because enforcement constrains the use of optimistic valuation assumptions, we hypothesize that enforcement influences the relative use of these two choices. We test this hypothesis by comparing a sample of 1,958 firms from 36 countries that are likely to delay recognizing goodwill impairment (suspect firms) to a sample of control firms. First, we find that firms in high‐enforcement countries use a higher discount rate to test goodwill for impairment than firms in low‐enforcement countries. We also find a more positive association between discount rate and upward cash flow management for suspect firms than for control firms. This result is consistent with suspect firms substituting optimistic valuation assumptions with inflated current cash flows. Second, we find that, relative to control firms, suspect firms exhibit higher upward cash flow management in high‐enforcement countries than in low‐enforcement countries. Third, we show that suspect firms in high‐enforcement countries are more likely to eventually impair goodwill.

Previous research have opposed secrecy and openness as mutually exclusive processes. In this paper, we suggest a more nuanced approach to secrecy in open innovation, drawing from Philosophy and Sociology. We have conducted a two-year research program in the defense industry, collecting data on the practices of concealment in open innovation activities. We found that focal actors utilize distinct cognitive techniques to decontextualize knowledge in the course of open innovation projects in order to safeguard secrecy while preserving mutual learning. Further, focal actors design contrasted relational approaches to secrecy with their open innovation partners. Such approaches are based on the positions of secrecy boundaries, which are internal or external to the relationship. In fact, actors intentionally make use of the reversible nature of secrecy, balancing inclusion and exclusion of knowledge in partnerships, to meet objectives that sometimes go beyond knowledge protection. Finally, we build on our findings to introduce a capability-based framework of secrecy management in openness processes. This framework, which we call Knowledge Discretion, suggests that actors overcome tensions stemming from secrecy and openness playing on the contextual depth and relational breadth of external knowledge sharing.

Massive Online Open Courses (MOOCs) are a booming phenomenon in the digital era, having attracted millions of users around the world to date. At the same time, educational delivery via MOOCs comes with its own distinct difficulties for students and instructors, as the online nature of MOOCs creates every opportunity for digital distraction and procrastination. In this work, we consider that the digital nature of MOOCs and online learning management systems (LMSs) may also offer unique opportunities to counteract procrastination. Building on the temporal motivation theory, this study examines a number of calls-to-action (CTAs) pertaining to the completion and submission of course assignments, with an eye toward combatting student procrastination on MOOCs. We report on the results of a randomized field experiment on a leading MOOC platform in China. By randomly treating MOOC users with different CTAs related to active course assignments, we seek to examine the impacts of alternative informational interventions on students’ duration to and probability of on-time assignment submission. We consider multiple types of CTAs: a simple call-to-action, a deadline reminder, descriptive norm interventions (communicating peer assignment completion rates), and a simple CTA combined with a financial incentive. We find that descriptive norms lead to higher probabilities of assignment completion and a shorter time to completion. In contrast, we find that the deadline reminder has a surprisingly counter-productive effect. Subsequently, exploring heterogeneity in the response to our different interventions – considering factors such as course load, education level, and user tenure on the MOOC platform – we find evidence that the deadline reminder, in particular, can backfire if students’ active course load is low. This result suggests that students with low course loads may perceive the deadline to be distant, which reduces their sense of urgency and leads to complacency. We discuss the implications of our findings for both research and practice.

In this paper, we develop and test a behavioral theory of lost leadership. Using insights from the literature on goals as reference points and prospect theory, we predict that former leaders exert more effort compared to otherwise identical competitors. We test this prediction using two contexts. The first, quasi-laboratory, data comes from an educational business game. The second setting draws on field data from a two-month banking sales contest. We find that provision of effort increases following the loss of leadership. We also explore whether past leaders exert more effort in general or simply shift effort from other, potentially less-salient goals. We find evidence of both mechanisms. Finally, we investigate the temporal effects and find that having been a leader has an attenuating effect on subsequent behavior.

Media dissemination plays an important role in facilitating price discovery. Political pressure that restricts media dissemination can hinder this function and affect investors’ perceptions. This paper studies the magnitude of newspaper censorship in China and its economic consequences using a setting of “tunneling” scandals. We find significant evidence of censorship of tunneling-related negative news at the national and local level. We further show that news that survives censorship reduces information asymmetry and improves pricing efficiency. We find that censorship blocks informative tunneling news and delays incorporation of tunneling reporting into prices.

How do banks remunerate risk managers and what are the implications for risk-taking? Studying 127 German banks during the years 2003 to 2007, we show that risk managers' remuneration is positively aligned with performance-linked pay in front offices (FOs). When bonuses in FOs increase by one Euro, the bonus of a risk manager increases by 13.6 to 33.5 Cents, depending on the risk manager’s seniority. Risk-sharing among employees or labor market competition do not explain this finding. Banks with more aligned incentive pay between risk management and FOs during the years before the crisis of 2008-2009 performed better in the crisis.

We consider a firm that faces the following pricing and leadtime disclosure decision. Either, (1) offer the same price to all arriving customers and disclose no leadtime information, in which case customers know only an expected leadtime, or, (2) vary the price dynamically based on the current inventory status, and disclose leadtime information dynamically. The second option allows the firm to offer a price discount for a long leadtime, and to offer a short leadtime when it has a large inventory. In order to determine which pricing and leadtime disclosure policy attains higher maximum profit, we formulate and solve a Markov decision problem for each policy and compare the two solutions. The comparison suggests that, typically, there is a critical inventory level, above which static pricing and no leadtime disclosure yields higher profit, and, below that level, dynamic pricing and leadtime disclosure yields a higher profit. We also identify certain situations where the static policy leads to profits at least as large as those under the dynamic policy, for any state, and we examine the price differences between the two policies. Finally, the structure of the solution is similar to the situation where the system manager can pause the production process, except that now this extra lever partly mitigates the superiority of the static policy.

This paper examines a development process in which a firm explores alternative approaches for the development of a single product. To do this, the firm employs competing internal teams, but it also needs to involve key suppliers who are responsible for the development of a key component (or subsystem) via a collaboration with one or several internal teams. We explore how internal competition affects the suppliers' collaborative efforts and the firm's profits, and also how the firm should allocate the internal teams to potential suppliers. Our analysis suggests that this setting is significantly different from standard tournament settings, implying that existing research results should not be simply extrapolated to supply chain settings. For example, unlike in traditional tournaments, we find that increasing supplier competition by increasing the number of teams per supplier can actually increase supplier efforts. We develop a tournament model with two suppliers who differ both in their expertise for the specific type of development project and in their development costs (i.e., their cost-effectiveness). We also identify a critical influential factor: the cost savings resulting from the similarity between different development efforts by the same supplier (with different internally competing teams). If the cost savings are not very high, i.e., if the different development efforts are not very similar, the firm should optimally allocate more teams to the supplier with less relevant expertise or lower cost-effectiveness. Similarly, involving a third supplier is beneficial only if the cost savings are low. While companies make significant efforts to identify the supplier with the best expertise, our results show that allocating more teams to the stronger supplier generally undermines the suppliers' incentives to exert high levels of effort. Hence, allocating the most teams to that supplier might not always improve firm profits.

Consumers often anthropomorphize non-human entities. In this research, we investigate a novel antecedent of anthropomorphism: language. Some languages (e.g., English) make a grammatical distinction between humans (he, she) and non-humans (it), whereas other languages (e.g., French) do not (all objects are gender-marked). We propose that such grammatical structures of languages influence the way individuals mentally represent non-human entities, and as a result, their generalized tendencies to anthropomorphize such entities. Across 10 studies, we provide evidence that speakers of languages that do not grammatically distinguish between humans and non-humans (it-less languages) anthropomorphize more than do speakers of languages that do make this distinction (non-it-less languages). We demonstrate the effects across natural languages (French, Turkish, English) and by manipulating grammatical gender. We show that the effects are observable in naturally occurring consumer contexts (e.g., secondary sales data), and that gender-marking in it-less languages influences consumers’ interactions with brands, even though the gender-markings are semantically arbitrary, and that these effects occur nonconsciously. Our findings have implications for the broader debate on the extent to which language influences thought, and also suggest ways in which managers can leverage nonconscious grammatical anthropomorphism to influence consumer perceptions, attitudes, and behavior.

Brands and advertisers often tap into the crowd to generate ideas for new products and ad creatives by hosting ideation contests. Content evaluators then winnow thousands of submitted ideas before a separate stakeholder, such as a manager or client, decides on a small subset to pursue. We demonstrate the information value of data generated by content evaluators in past contests and propose a proof-of-concept machine learning approach to efficiently surface the best submissions in new contests with less human effort. The approach combines ratings by different evaluators based on their correlation with the past stakeholder choices, controlling for submission characteristics and textual content features. Using field data from a crowdsourcing platform, we demonstrate that the approach improves performance by identifying nonlinear transformations and efficiently reweighting evaluator ratings. Implementing the proposed approach can affect the optimal assignment of internal experts to ideation contests. Two evaluators whose votes were a priori equally correlated with sponsor choices may provide substantially different incremental information to improve the model-based idea ranking. We provide additional support for our findings using simulations based on a product design survey.

This paper develops a method to flexibly adapt interpolation grids of value function approximations in the estimation of dynamic models using either NFXP (Rust, Econometrica: Journal of the Econom etric Society, 55, 999– 1 033, 1987) or MPEC (Su & Judd, Econometrica: Journal of the Econometric Society, 80, 2213–2230, 2012). Since MPEC requires the grid structure for the value function approximation to be hard-coded into the constraints, one cannot apply iterative node insertion for grid refinement; for NFXP, grid adaption by (iteratively) inserting new grid nodes will generally lead to discontinuous likelihood functions. Therefore, we show how to continuously adapt the grid by moving the nodes, a technique referred to as r-adaption. We demonstrate how to obtain optimal grids based on the balanced error principle, and implement this approach by including additional constraints to the likelihood maximization problem. The method is applied to two models: (i) the bus engine replacement model (Rust, 1987), modified to feature a continuous mileage state, and (ii) to a dynamic model of content consumption using original data from one of the world’s leading user-generated content networks in the domain of music.

Problem definition: We study customer-centric privacy management in service systems. Academic/practical relevance: We explore the consequences of extended control over personal information by customers in such systems. Methodology: We adopt a stylized queueing model to capture a service environment that features a service provider and customers who are strategic in deciding whether to disclose personal information to the service provider—that is, customers’ privacy or information disclosure strategy. A customer’s service request can be one of two types, which affects service time but is unknown when customers commit to a privacy strategy. The service provider can discriminate among customers based on their disclosed information by offering different priorities. Results: Our analysis reveals that, when given control over their personal data, strategic customers do not always choose to withhold them. We find that control over information gives customers a tool they can use to hedge against the service provider’s will, which might not be aligned with the interests of customers. More importantly, we find that under certain conditions, giving customers full control over information (e.g., by introducing a privacy regulation) may not only distort already efficiently operating service system but might also backfire by leading to inferior system performance (i.e., longer average wait time), and it can hurt customers themselves. We demonstrate how a regulator can correct information disclosure inefficiencies through monetary incentives to customers and show that providing such incentives makes economic sense in some scenarios. Finally, the service provider itself can benefit from customers being in control of their personal information by enticing more customers joining the service. Managerial implications: Our findings yield insights into how customers’ individually rational actions concerning information disclosure (e.g., granted by a privacy regulation) can lead to market inefficiencies in the form of longer wait times for services. We provide actionable prescriptions, for both service providers and regulators, that can guide their choices of a privacy and information management approach based on giving customers the option of controlling their personal information.

We analyze firm-level analyst forecasts during the COVID crisis. First, we describe expectations dynamics about future corporate earnings. Downward revisions have been sharp, mostly focused on 2020, 2021 and 2022, but much less drastic than the lower bound estimated by Gormsen and Koijen (2020). Analyst forecasts do not exhibit evidence of over-reaction: As of mid-May, forecasts over 2020 earnings have progressively been reduced by 16%. Longer-run forecasts, as well as expected “Long-Term Growth” have reacted much less than short-run forecasts, and feature less disagreement. Second, we ask how much discount rate changes explain market dynamics, in an exercise similar to Shiller (1981). Given forecast revisions and price movements, we estimate an implicit discount rate going from 10% in mid-February, to 13% at the end of March, back down to their initial level in mid-May. We then decompose discount rate changes into three factors: changes in unlevered asset risk premium (0%), increased leverage (+1%) and interest rate reduction (-1%). Overall, analyst forecast revisions explain most of the decrease in equity values between January 2020 and mid May 2020, but they do not explain shorter term stock market movements.

Ten years after the introduction of participatory democracy as one of the democratic foundations of the European Union, this introductory chapter to "Citizen Participation in Democratic Europe" provides some theoretical background on the role citizens play, and should play, within the EU democratic system. As such, it offers a contribution about the place of citizen participation in the wider, ongoing debate about how to develop the EU’s democratic system in a post-pandemic Europe. It sets the scene for the subsequent chapters written, again, not only by academic scholars but also civil society advocates and practitioners from across Europe who experience on a daily basis the realities of EU citizen participation. Ultimately, this edited volume argues how Europe’s long-standing democracy challenge can be addressed through the emergence of a new model of EU citizen participation, and a set of democratic innovations emerging bottom-up across the continent. To do so, it offers a re-evaluation and systematisation of EU level citizen participation and its future development, which remains largely underexplored.

I study the effect of improved access to health insurance on the rate new business formation and the quality of those newly created businesses. I develop theoretical models which provide predictions on how improved access to health insurance would heterogeneously affect firms by non-profit status and capital requirements. Using the 2006 reform of the Massachusetts health insurance market, I test those predications and find non-profit entrepreneurship was significantly affected although overall entrepreneurship seems constrained by factors other than access to health care such as access to capital. I also provide evidence that the quality of non-profits created by the shock where poor. These results suggest that even when policy changes are able to induce more entrepreneurship, the marginal quality of those entrepreneurs may be poor.

Firms often partially fund new projects for preliminary development rather than fully fund them to fruition. This staged development yields early feedback which can improve an individual project through learning and a portfolio of projects by the termination of weaker ideas. Although prior empirical studies have found a positive relationship between staged development and outcomes, these studies were limited to settings that only allowed for learning, i.e. projects were never terminated. To capture the full effect, this paper exploits a form staged development in the television show industry where a new show’s first episode is filmed and evaluated before commissioning the full show. Using Netflix’s entry into television show production as a source of randomization, a negative treatment effect of piloting on show ratings is measured for shows that are more likely to survive piloting. Mechanism evidence suggests piloting worsens shows by impeding their ability to attract actors and lowering planning of the full season. Hence, staged development can have a downside: the lack of commitment to projects can prevent them from getting the resources and effort necessary for success.

Recent decades have witnessed a growing focus on two distinct income patterns: persistent pay inequity, particularly a gender pay gap, and growing pay inequality. Pay transparency is widely advanced as a remedy for both. Yet we know little about the systemic influence of this policy on the evolution of pay practices within organizations. To address this void, we assemble a novel data set combining detailed performance, demographic and salary data for approximately 100,000 US academics between 1997 and 2017. We then exploit staggered shocks to wage transparency to explore how this change reshapes pay practices. We find evidence that pay transparency causes significant increases in both the equity and equality of pay, and significant and sizeable reductions in the link between pay and individually-measured performance.

Europe has largely been absent from the US-dominated debate surrounding the introduction of nudge-type interventions in policy-making. Yet the European Union and some of its Member States are exploring the possibility of informing their policy action with behavioural insights. While a great deal of academic attention is currently been paid to the philosophical, ethical and other abstract implications of behavioural-informed regulation, such as those concerning autonomy, dignity and moral development, this chapter charts and systematizes the incipient European Nudge discourse. Besides a few isolated initiatives displaying some behavioural considerations (e.g. consumer rights, revised tobacco products directive, sporadic behavioural remedies in competition law), the EU – similarly to its own Member States – has not yet shown a general commitment to systematically integrate behavioural insights into policy-making. Given the potential of this innovative regulatory approach to attain effective, low-cost and choice-preserving policies, such a stance seems surprising, especially when measured against growing citizen mistrust towards EU policy action. At a time in which some EU countries are calling for a repatriation of powers and the European Commission promises to redefine - in the framework of its Better Regulation agenda - the relationships between the Union and its citizens, nudging might provide a promising way forward. In the aftermath of the Brexit vote, this promise has not only been shared by the 27 remaining Member State but also represents one of their major priorities . Yet with promises come challenges too. The chapter proceeds as follows. Section 2 sets the scene by discussing the growing appeal of nudging among policymakers within and across Europe. Section 3 introduces the notion of behavioural policymaking and contrasts it with that of nudging. Section 4 describes the early and rather timid attempts at integrating behavioural insights into EU policymaking and identifies some domestic experiences. Section 5 discusses the institutional and methodological efforts undertaken by the EU and some of its member states to embrace behavioural policymaking. In turn, section 6 discusses the major difficulties of integrating behavioural insights into EU policymaking and offers some concluding remarks.

A firm’s resources are well understood to be a source of competitive advantage. However, how a firm comes to acquire resources with the traits that provide competitive advantage is less clear. To explore this question, this paper studies a setting where heterogenous incumbent firms were affected by a common environmental shock and investigates the characteristics of firms that successfully adapted to the new environment. Netflix’s entry into the television show production forced the United States incumbent networks to alter how some television shows are made. The paper finds that incumbent networks with prior experience in the new practice did not fare better than their peers. However, those with existing deep supplier relationships were better able to manage this transition. This result suggests the resources providing competitive advantage may come primarily through serendipity rather than active planning by firms.

We build a social structural model of fame, which departs from the atomistic view of prior literature where creativity is the sole driver of fame in creative markets. We test the model in a significant empirical context: 90 pioneers of the early 20th century (1910–25) abstract art movement. We find that an artist in a brokerage rather than a closure position was likely to become more famous. This effect was not, however, associated with the artist’s creativity, which we measured using both objective computational methods and subjective expert evaluations, and which was not itself related to fame. Rather than creativity, brokerage networks were associated with cosmopolitan identities—broker’s alters were likely to differ more from each other’s nationalities--and this was the key social-structural driver of fame.

We estimate the causal effect of state-mandated business closures on economic and health outcomes in the context of the COVID-19 crisis in the US. We first show that business closures lead to a substantial drop in sales, earnings, and market values for affected firms. We then exploit sectoral variations in exposure to these restrictions across areas within the same state, and show that locking down 10% of the labor force is associated with a significant contraction in employment, but allows to reduce COVID-19 weekly infection and death rates by respectively 0.023 and 0.0015 percentage points. The findings translate into 24,000 saved lives for a cost of $115 billion. Finally, our empirical analysis suggests that the cost per life saved associated to business closures could have been significantly reduced if restrictions had targeted areas with intense workplace interactions

In manufacturing, the accumulation of experience that occurs with production is likely to impact an organization's ability to innovate. However, how different types of experience may relate to the characteristics of an organization's innovation output is an open question. In this study we investigate how a firm's accumulated related and unrelated manufacturing experiences are associated with this firm's ability to innovate its production methods. We choose as our context the manufacturing of active pharmaceutical ingredients (APIs) for anti-cancer drugs that have lost product-patent protection. This allows us to examine our research question in a multi-product and multi-firm longitudinal setting. To characterize firms' innovation output we observe their portfolios of patented manufacturing inventions, which we qualitatively evaluate over time (through a unique collaboration with expert patent attorneys) along two critical dimensions: novelty and scope. We find that experience with manufacturing related products is associated with a decrease in the novelty and an increase in the scope of the manufacturing methods that a firm develops and patents for a focal product. Conversely, experience with manufacturing unrelated products is associated with an increase in a focal product's patents' novelty and a decrease in its patents' scope. This simultaneous consideration of both novelty and scope allows us to demonstrate how different types of experience may enhance one dimension of innovation while hurting another, and helps to reconcile conflicting conceptual arguments that have been presented in the literature. Our findings provide practical guidance regarding how managers might want to structure their firms' product portfolios and the longitudinal effect of their choices on their firm's intellectual property.

Despite a heated debate on the perceived increasing complexity of financial regulation, there is no available measure of regulatory complexity other than the mere length of regulatory documents. To fill this gap, we propose to apply simple measures from the computer science literature by treating regulation like an algorithm - a fixed set of rules that determine how an input (e.g., a bank balance sheet) leads to an output (a regulatory decision). We apply our measures to the regulation of a bank in a theoretical model, to an algorithm computing capital requirements based on Basel I, and to actual regulatory texts. Our measures capture dimensions of complexity beyond the mere length of a regulation. In particular, shorter regulations are not necessarily less complex, as they can also use more "high-level" language and concepts. Finally, we propose an experimental protocol to validate measures of regulatory complexity.

We examine how the U.S. Food and Drug Administration Amendments Act (FDAAA) of 2007, which requires additional disclosures regarding clinical trial results, impacts information asymmetry between the disclosing pharmaceutical firm and capital market participants, the general public, academics, and practitioners. We document a reduction in information asymmetry in capital markets. We also document an increase in adverse event and product problem complaint reports filed against the pharmaceutical firms to the FDA and a higher number of drug and medical device recalls for affected firms after the FDAAA enactment. Finally, cross-sectional analyses suggest that the increase in FDA complaint reports and recalls after the FDAAA enactment was more prominent in firms with a higher bid-ask spread decrease. Taken together, our results suggest that the FDAAA has some benefits for both investors and consumers.

Data is increasingly regarded as an essential infrastructural resource for economic growth, innovation and the overall wellbeing of society. Thanks to our enhanced capability to collect, process and use data, we are able to know where the epicentre of an earthquake is, how to limit a pandemic such as Zika from spreading or even how to reduce pollution in cities.This data ‘revolution’ must be contextualised within a broader, 3-centurylong attempt to neutralise irrationality in human decisionmaking by gaining increased access to information. Yet, while virtually every organisation today, including small companies or grassroots movements, is a data entity, only a few of them (generally in the private sector) have collected vast amounts of data (be it personal or non-personal) and acquired a unique capability to make sense of such information.As a result, most of this much-prized data is in the hands of businesses, not of public authorities, with the latter lagging behind in embracing the power of data to inform their daily policies and service-delivery actions. Hence the challenge — entrusted by the European Commission to our expert group — to explore the creation of an enabling environment for privately held data to be shared with (or at least be accessible to) public authorities in complying with their public-interest missions. For the time being, most of the efforts focus on getting the supply-side ready (e.g. by developing data-sharing models, de-risking data sharing or re-skilling personnel) for B2G data sharing, but omit the need to sensitise and prepare the demand side (the public authorities). More critically, at a time in which reputation-based mechanisms transcend the mere financial rating and venture into state-driven ‘social credit’ scoring, the role that citizens play in the data-sharing equation remains limited and ancillary to most of the solutions at stake.This report, which has benefited from the experience and dedication of 23 experts coming from different walks of life, strives to address both of these systemic shortcomings. By carving out a role to play for both the public sector and citizens, it offers an initial set of ethically-aware paths the EU might chart to break new ground in advancing and accompanying B2G data sharing. The hope is that by following some of this expert advice the EU might become a global leader in fostering not only a market for B2G data access, but also a sensible, inclusive and participatory data culture through a set of viable, practicable and scalable welfare-enhancing solutions. Only a more cautious, humble and humanised approach to the unprecedented amount of data we produce and collect every day may pave the way for a future in which it is the human factor that defines our daily life experiences

This article offers an original case study of the failed sale of Victoria’s Secret’s business to examine the deep consequences of the COVID-19 pandemic in the context of M&A transactions. After presenting the case, it draws two lessons from it by: (1) proposing a multi-layered analysis of the effects of covid-19 depending on the type of event considered and on the contract language, and (2) exploring the possible reshaping of the termination right in connection with the dramatic variations of the target’s value during the interim period caused by COVID-19.

A dozen of green and sustainable labels have emerged on the financial markets of the Member States of the European Union since the creation of a first label in 1997 in France, allocated to nearly 1,360 financial products, demonstrating a quantitative success, especially in France. This article analyzes the development of such green and socially responsible labels in Europe over the past decades , their construction dynamics, and questions the real benefits of a proliferation of labels in this industry. Does the multiplicity of factors contributing to the development of labels achieve the desired end or does it encumber the market with loud but uncertain signals? While household savings are at their highest and there is a demand for financing the ecological transition, does the proliferation of labels not complicate the readability of the market ? We show that, instead of simplifying the choice of agents, the multiplication of labels tends to increase the noise provided by each of the quality signals and deteriorate confidence. Economic agents have less interest in benefiting from a generic label but are looking for less demanding labeling at a lower cost. The whole system can therefore play in a counterproductive way, each actor minimizing the intrinsic effort provided. As the number of labels grows, the information asymmetry grows and end investors may therefore turn away from labeled products. Only regulator can counter this trend.; Une dizaine de labels verts et durables ont vu le jour sur les marchés financiers des États membres de l'Union européenne depuis la création d'un premier label en 1997 en France, attribués à près de 1360 produits financiers, démontrant un succès quantitatif, notamment en France. Cet article analyse l'évolution de ces labels verts et durables en Europe au cours des dernières décennies, leur dynamique de construction, et s'interroge sur les réels bénéfices d'une prolifération de labels dans ce secteur. La multiplicité des facteurs contribuant au développement des labels atteint-elle le but recherché ou encombre-t-elle le marché de signaux forts mais incertains? Alors que l'épargne des ménages est au plus haut et qu'il existe une demande de financement de la transition écologique, la multiplication des labels ne complique-t-elle pas la lisibilité du marché? Nous montrons que, au lieu de simplifier le choix des agents, la mutliplication des labels tend à accroître le bruit fourni par chacun des signaux de qualité et détériorer la confiance. Les agents économiques ont moins intérêt à bénéficier d’un label générique mais recherchent à moindre coût une labelisation moins exigeante. L’ensemble du système peut donc jouer de façon contreproductive, chaque acteur minimisant l’effort intrinsèque fourni. L’asymmétrie d’information s’accroît à mesure que le nombre de labels grandit et les investisseurs finaux risquent donc de se détourner in fine des produits labelisés. Seul le regulateur peut contrer cet effet.

We investigate how Activist Short Sellers (AShSs) expose publicly listed firms in an increasingly popular form of “research reports” openly denouncing alleged frauds, flawed business models, accounting irregularities, and wrongdoings. We focus on six AShSs that issued research reports that often led to a strong negative market reaction. Our empirical analysis exploits both qualitative and quantitative methods for a comprehensive dataset of 383 research reports targeting 171 unique firms, and three first-hand interviews with AShSs. Drawing on Aristotle’s rhetoric, we first examine how AShSs use narratives in striving to convince other investors that the target firms are overvalued. Specifically, we search the documents produced by AShSs for stylized narratives related to credibility-based (ethos), emotions-based (pathos), and logic-based (logos) rhetorical strategies. To assess the impact of these strategies, we examine the extent to which the AShSs’ rhetorical strategies resonate in 3,665 press articles. As expected, the press often refers to logos-based arguments. Interestingly, the press also brings up frequently pathos-based and ethos-based statements. Considering the importance of the press in shaping investors’ opinions, our study points to AShSs’ narratives playing a major role in policing financial markets. Theoretically, we show that AShSs, as dissenting market participants, produce narratives that go beyond the language of formal rationality – as they strive to reveal new information and frame it persuasively, in order to destabilize the extent of trustworthiness surrounding target firms.

We propose a new methodology to implement unconditionally optimal dynamic mean-variance portfolios. We model portfolio allocations using an auto-regressive process in which the shock to the portfolio allocation is the gradient of the investor's realized certainty equivalent with respect to the allocation. Our methodology can accommodate transaction costs, short-selling and leverage constraints, and a large number of assets. In out-of-sample tests using equity portfolios, long-short factors, government bonds, and commodities, we find that its risk-adjusted performance, net of transaction costs, is on average more than double that of other benchmark allocations.

This paper contains the on on-line appendix to the paper with the same title forthcoming in ILRR.; Is the Bayh-Dole intellectual property regime associated with more and better academic entrepreneurship than the Professor Privilege regime? The authors examine data on US PhDs in the natural sciences, engineering, and medical fields who became entrepreneurs in 1993–2006 and compare this to similar data from Sweden. They find that, in both countries, those with an academic background have lower rates of entry into entrepreneurship than do those with a non-academic background. The relative rate of academics starting entrepreneurial firms is slightly lower in the United States than in Sweden. Moreover, the mean economic gains from becoming an entrepreneur are negative, both for PhDs originating in academia and non-academic settings in both countries. Analysis indicates that selection into entrepreneurship occurs from the lower part of the ability distribution among academics. The results suggest that policies aimed at supporting entrepreneurial decisions by younger, tenure-track academics may be more effective than general incentives at increasing academic entrepreneurship in general.

Problem Definition: Project managers are responsible for setting and then revising projects' goals. As uncertainty related to project performance is resolved, a project manager is tasked with comparing ongoing costs, and potentially achieved scope, to a baseline plan. We question whether project managers can rationally anticipate and track this revision process. Academic/Practical Relevance: In practice, projects often fail to meet their goals and are subject to changes in scope, cost, and scheduled time. We consider the implications of behavioral tendencies and the revision strategy on decisions made and on overall project performance. Methodology: Our stylized model compares a rational project manager to a behavioral one. Specifically, we offer a framework for modeling mental accounting—which includes loss aversion and reference point updating—and narrow framing. We use the model to explore how project-level decisions are made. Results: We show that mental accounting results in insufficient adjustments of project scope and cost during revisions, and prevents abandoning projects even when doing so is optimal. Ultimately, mental accounting and narrow framing decrease projects' actual profits. Managerial Implications: We offer practical prescriptions for mitigating harmful effects of loss aversion, reference-point updating, and narrow framing. Beyond training, hiring less loss averse project managers, and practicing scenario planning, we show that reviewing a project using a cost milestone instead of a scope milestone helps maintain the reference cost equal to the budgeted cost, thereby inducing overall better decisions.