Designing Layouts for Sequential Experiences: Application to Cultural Institutions

A fundamental issue faced by experience providers—ranging from retail to culture—is displaying a collection of items for physical and digital interactions. The arrangement of the exhibits in different locations, which we call the layout, affects the visitors’ choices over time and space, thereby driving their engagement with the offered experience. In a collaboration with the Van Gogh Museum (Netherlands), we develop a predict-then-optimize framework to inform such operational decisions. First, we propose a sequential choice model, called pathway multinomial logit, that represents visitor activity as a sequence of conditional logit outcomes influenced by the layout. Estimation on large-scale visitor activity logs recorded on multimedia guides reveals that increase in spatial distances and search distances on the multimedia guide interface are strongly correlated with a reduction of transition propensity between artworks, while also uncovering relationships with artwork characteristics and contextual features. Counterintuitively, in response to more congestion, visitors may interact with more exhibits, including less prominent artworks. Our model predicts the next visitor transition with an out-of-sample accuracy of 63%. We test the predictive accuracy of our model against several benchmarks and modified layouts. Finally, we formulate the layout optimization problem, where the goal is to assign artworks to different locations to maximize the expected length of visitors’ paths. We establish a strong inapproximability result for this new optimization setting. Our simulations suggest that optimized layouts might lift visitor engagement by improving proximity and retention exerted by the layout

Transcending Embarrassment: On the Reputational Benefits of Laughing at Yourself

How do people judge those who commit faux pas? Across six preregistered studies (N = 3,204), we find that the answer depends on how a faux pas is presented to others and the extent to which it harms others. For faux pas that cause minimal or no harm to others, those who display amusement (by laughing at their error) are seen as warmer, more competent, and more authentic (though not significantly more or less moral) than those who display embarrassment. While both amusement and embarrassment displays serve an appeasement function (which reflects positively on actors), observers view those displaying embarrassment as being excessively self-conscious (which limits positive character judgments). In contrast, amusement displays are deemed more emotionally calibrated, since they signal that an actor recognizes the faux pas is benign and therefore not serious enough to warrant negative self-conscious emotions. In other words, observers do not believe actors ought to feel particularly embarrassed upon committing common benign faux pas. However, when a faux pas harms others, those who display amusement are seen as experiencing a deficient level of self-consciousness, since, in this case, amusement indicates a disregard for the welfare of others. As a result, as harm to others increases, the benefits of displaying amusement become either attenuated or reversed relative to displaying embarrassment. Together, these findings provide a simple framework for understanding when amusement and embarrassment displays reflect well on individuals who commit faux pas

A Contingency Model of Top Management Teams’ Task Conflict and Organizational-Level Outcomes: Evidence for a Curvilinear Relationship

The relationship between conflict and performance has been studied for decades, but little is known about how and under what conditions task conflict among top managers affects firm-level outcomes. In this study, we examine a curvilinear effect of task conflict in top management teams (TMTs) on both firm performance and TMT resilience efficacy, as moderated by behavioral integration. We argue and find that TMT task conflict can improve firm performance when behavioral integration is high, but the effect is not linear; rather it levels off. In contrast, we maintain and find that TMT task conflict can improve TMT resilience efficacy at an increasing rate when behavioral integration is low. We also find that behavioral integration itself is predicted by Chief Executive Officer relational leadership such that leaders with a more relationship-oriented style encourage more behavioral integration in their teams. Field data from 555 top managers from 111 organizations in South Korea provided support for our hypotheses. Theoretical and practical implications are discussed

Investments that Make our Homes Greener: The Role of Regulation

emissions. We study the investments triggered by a regulatory intervention requiring rented properties to satisfy minimum energy efficiency standards. The analysis shows significant investments in low capital expenditure retrofits. Using an instrumented difference-in-differences methodology, we show that the investments do not have an economically significant impact on rents, so that landlords are not compensated for them

Capacity and Pricing Management with Demand Learning

In an environment where demand is unknown to the firm, it is important to investigate how capacity adjustment and dynamic pricing can be integrated so that the firm can learn about the demand on the fly while making capacity and pricing decisions. In this paper, we design learning algorithms for the joint capacity and pricing management problem. To evaluate the performance of our algorithms, we consider a large-demand asymptotic regime where the demand and capacity are scaled up with the selling horizon T. We first establish an [Formula: see text] lower bound on the regret under any admissible policy. We propose a novel double-trisection algorithm that utilizes pricing decisions to collect demand information and tune capacity rate levels safely, attaining an [Formula: see text] regret upper bound that matches the lower bound. We then modify our algorithm to address the issue when the number of capacity adjustment opportunities K is limited and find that only a few opportunities to adjust capacity levels (i.e., [Formula: see text]) are sufficient to achieve the optimal regret rate. We also consider seasonal demands and provide a modified algorithm to incorporate the seasonality. We finally conduct numerical experiments on a test bed inspired by public operational and financial data. This paper was accepted by J. George Shanthikumar, data science. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.03749

The Effects of Artificial Intelligence on Management Education

The emergence of generative AI tools capable of matching human performance in business school assignments challenges fundamental assumptions about management education. This paper explores how AI could fundamentally reshape business schools, suggesting we may be entering a "third epoch" of management education following the practice-oriented era of the early 1900s and the research-focused transformation of the 1960s. As AI begins to rival core analytical capabilities taught in business programs, schools must reconsider their unique value proposition and educational approach. Through the primary lens of a value-based strategy framework, we analyze how AI could reshape demand patterns, teaching methods, and operational models. The paper identifies key uncertainties and strategic priorities, exploring how business schools could leverage their research strengths to guide this transformation. The potential decline of traditional business education could weaken the foundation of informed and ethical business practices, making adaptation imperative. While AI presents significant challenges to current educational models, it also offers compelling opportunities for schools to reinvent management education for an AI-augmented future

Trade fragmentation, inflationary pressures and monetary policy

How does trade fragmentation affect inflationary pressures? What is the response of monetary policy needed to sustain inflation at target? To address these questions, we develop a two-sector, small open-economy model featuring imperfect international risk-sharing and household heterogeneity, capturing both the supply-side and demand-side effects of fragmentation. In the model, fragmentation takes the form of import-price increases or a decline in tradable-sector productivity. The sign and magnitude of its impact on inflationary pressures, and the appropriate policy response, depend not only on the direct effect of higher import prices or lower productivity on supply but also, crucially, on how aggregate demand adjusts to lower real incomes. In turn, this depends on the pace of fragmentation (gradual versus front-loaded) and other key structural factors highlighted by the model. We compare outcomes under Taylor-type monetary policy rules to a constrained-efficient allocation

Behind the Curtain of Workforce Diversity: Evidence from EEO-1 Reports

We leverage the 2023 court-ordered FOIA release of standardized Equal Employment Opportunity (EEO-1) reports to examine the workforce diversity of federal contractors. Using the released data for a sample of over 19,000 publicly traded and private firms, we provide descriptive evidence on the variation in gender and racial diversity of these companies’ workforce. We also document the existence of a racial gap between managers and lower-level employees. A substantial portion of that gap cannot be explained by industry or geographic factors, reflecting the influence of firm-level characteristics. Then, focusing on a sample of over 800 publicly traded federal contractors, we find robust evidence that the racial managerial gap is associated with firms’ decision to withhold the voluntary disclosure of their EEO-1 forms. While our findings are subject to several caveats, we provide important evidence on workforce diversity and highlight the importance of using granular, firm-level data to study diversity topics

Achieving Holism: Narrating Multiple Identities in the Moment and Over Time

People’s multiple identities often wax, wane, and are transformed over their lifetimes, both as sources of personal meaning and as realities communicated to others. Yet, despite a research turn toward studying identities as multiple and dynamic, largely still missing is a cohesive view of people’s efforts to narratively integrate the sum of their many evolving parts. In this paper, we take a narrative perspective on the notion of identity holism to theorize how people build a meaningful whole by making narrative claims involving “4Cs”—credibility, coherence, continuity, and causality. Cutting across these claims are more abstract themes, or leitmotifs, of identity coalescence and coevolution, which are internally experienced as static and dynamic holism, respectively. We discuss how holism, and particularly dynamic holism, fosters personal authenticity, wisdom, adaptiveness, and resilience; the broader contributions of our theorizing to the literatures on identity and narrative; and implications for management and future research

Perceptions of Knowledge Transferability and Entrepreneurial Entry: The Role of Firm-Initiated Turnover

I examine the understudied effects of perceived non-transferable knowledge on labor market choices after firm-initiated turnover. Using a large, nationally representative dataset, I assess how workers’ perceptions of knowledge transferability, expectations to remain at a firm, and type of turnover experienced correlate with the decision to engage in entrepreneurship. I find that the release of workers with perceived non-transferable knowledge into the external environment through firm-initiated turnover reliably foreshadows entrepreneurship, especially as workers’ prior expectations to continue wage employment at a source firm increases. This finding indicates that beyond necessity, opportunity and financial resources, workers’ self-perceptions of their human capital and unfulfilled career expectations matter to the choice of entrepreneurship. It also suggests that firm-initiated turnover may be a form of knowledge divestiture with important ex-post implications when workers’ perceptions of transferability align with reality