SPEAKER

Prof. Zoe Cullen
Associate Professor of Business Administration
Harvard University

ABSTRACT

Workplace surveillance generates data that can train AI systems to replicate worker expertise. Using a large online survey experiment of U.S. full-time workers, we show that workers adjust their knowledge contributions when made aware of this dynamic: they rationally withhold expertise due to career concerns. We formalize this behavior in a model of knowledge supply under surveillance-enabled AI and use it to evaluate alternative policies. Individual data ownership— workers’ preferred policy—eliminates knowledge withholding but creates negative externalities: one worker’s data strengthens the firm’s bargaining position against others, potentially making all workers worse off. In contrast, collective data ownership achieves the first-best outcome, promoting knowledge sharing while allowing workers to benefit from AI-driven productivity gains. These findings highlight the importance of labor agreements in shaping AI adoption in labor markets.

SPEAKER

Prof. Eduard Talamàs
Assistant Professor
IESE Business School
University of Navarra

ABSTRACT

Do improvements in Artificial Intelligence (AI) benefit workers? We study how AI capabilities influence labor income in a competitive economy where production requires multidimensional knowledge, and firms organize production by matching humans and AI-powered machines in hierarchies designed to use knowledge efficiently. We show that advancements in AI in dimensions where machines underperform humans decrease total labor income, while advancements in dimensions where machines outperform humans increase it. Hence, if AI initially underperforms humans in all dimensions and improves gradually, total labor income initially declines before rising. We also characterize the AI that maximizes labor income. When humans are sufficiently weak in all knowledge dimensions, labor income is maximized when AI is as good as possible in all dimensions. Otherwise, labor income is maximized when AI simultaneously performs as poorly as possible in the dimensions where humans are relatively strong and as well as possible in the dimensions where humans are relatively weak. Our results suggest that choosing the direction of AI development can create significant divisions between the interests of labor and capital.

SPEAKER

Prof. Maria Guadalupe
Professor of Economics
INSEAD

ABSTRACT

Workplaces across many industries are characterized by what is stereotypically called  “masculine” norms: i.e. highly competitive and aggressive norms, often portrayed as necessary to increase performance. Using rich survey and archival data from faculty and staff in business schools, we develop a novel way to measure these hyper-competitive norms norms and show that they are negatively correlated with employee well-being, both increasing turnover intentions and reducing workplace well-being. We then examine why these norms persist despite their negative consequences and find that the associated lower well-being is not offset by higher performance – neither in terms of research quantity nor impact. Finally, we show that no organizational subgroup thrives in hyper-competitive environments. While neither men nor women benefit from such norms, even “superstar” performers in the top performance deciles experience negative implications.

SPEAKER

ABSTRACT

Income-Driven Repayment (IDR) plans tie student loan repayment to income and forgive unpaid debt after certain years of repayment. We investigate how these features affect one’s career choices through a survey where the same student is asked to select job profiles under various repayment plans. Consistent with our Ben-Porath style model, the survey results reveal that IDR is a double-edged sword. On the one hand, 36% of students underinvest in their human capital under the standard repayment plan relative to their would-be choices in a debt-free scenario; an IDR resembling the Saving on a Valuable Education (SAVE) plan reduces this fraction to 20%. On the other hand, IDRs induce moral hazards: Under a SAVE-like plan, 22% of students choose job profiles with lower initial wages and higher wage growth than their choices in a debt-free scenario, leaving part of their debt forgiven. A simple calculation indicates that this type of moral hazard alone would render SAVE-like plans inviable were they carried out by private lenders; however, government-run IDRs are sustainable due to the government’s capacity to collect individuals’ lifetime income taxes.

SPEAKER

ABSTRACT

Extant research has overlooked why companies receive varying levels of criticism for not engaging with polarized social issues. Further, little is known about the consequences of engaging with these issues in the face of criticism. To understand which firms are at the highest risk of missteps, we integrate insight from expectations management and identity theory. We argue that external criticism stems from general audiences’ expectations – which vary significantly between firms – being left unmet. These expectations have two dimensions: predictive, reflecting audiences’ perceptions of the likelihood a firm will engage based on past actions and related cues; and prescriptive, based on their beliefs as to whether a firm has a moral obligation to respond. We further posit that responding to a polarized issue in the face of criticism can backfire, eliciting greater and increasingly bipartisan critique. An empirical analysis of criticism for silence and subsequent corporate responses to a controversial voting law in Georgia supports these arguments. In this context, prescriptive and predictive expectations interacted to lead to mostly Democratic-leaning critique. Firms that subsequently broke their silence received both Democratic- and Republican-leaning criticism afterwards. Post-hoc analyses revealed that early (prior to a buildup of critique) and substantive (vs. symbolic) engagement was associated with less criticism.

SPEAKER

ABSTRACT

Generative artificial intelligence (GenAI) has fundamentally reshaped the landscape of creativity and innovation, revolutionizing the very processes through which ideas are conceived and brought to fruition. However, little is known about how the deployment of GenAI affects the nature of creative ideas as well as subsequent implementation efforts due to machine-colored psychological ownership. We study how to optimize the human-AI co-creation workflow for better creative outcomes. Integrating the literature on human-AI collaboration with research on the collaborative process of creativity, we propose complement and dependency AI augmentation as two distinct process structures of co-creation, which lead to different creative outcomes and implementation efforts. In two preregistered studies—an online experiment with entrepreneurs coupled with a field experiment with graphic designers—we found that both process structures surpassed human-only work by enhancing the novelty and usefulness of ideas generated, yet complement AI outperformed dependency AI in preserving the heterogeneity of ideas at the level identical to that of human-only work. Complement AI fostered a stronger sense of psychological ownership than dependency AI, which translated into a more positive indirect effect on implementation efforts. However, it was still surpassed by human-only work. The negative indirect effect of dependency AI on implementation efforts was especially salient for women (vs. men). By casting light on the process structures of human-AI co-creation and emerging subtle gender disparities, our work provides deep insights into optimizing gender-sensitive creative workflow and reconfiguring organizational innovation ecosystems in an intelligent-machine-driven economy.

SPEAKER

ABSTRACT

During the transition between technological regimes, incumbents often face a strategic choice: to enter the new market with products designed from scratch based entirely on the new technology or to transition into the new market by keeping links with the old technology via hybrid products. Hybrid products have not been extensively studied and the scant literature to date has focused on their relationship with innovation and technical performance metrics. This existing work does not provide a clear indication of what is the relationship between investments in hybrid products and performance in the market based on the new technology. To address this gap, we adopt a question-based abductive approach to explore this relationship and further identify which other factors can affect the results. Our context is the US automobile industry between 2009 and 2024, a period when the auto industry began its transition from internal combustion engines to electric vehicles. We find that incumbents that invest in hybrid vehicles during the transition are associated with inferior market performance in the market for electric vehicles. We also find that the degree of hybridization and the type of target market moderates the magnitude of this hybrid penalty. Our findings suggest that following a hybrid product strategy entails important limitations that firms need to carefully consider during technological transitions.

SPEAKER

ABSTRACT

My research addresses the question of why women are less likely than men to occupy brokerage positions in informal social networks. In my prior work, I introduced a novel theoretical perspective—the construal approach—to understanding gender differences in returns to brokerage. Using this theoretical perspective, my previous research has shown that women benefit less than men from brokerage due to gender stereotypes, which affect how they perceive themselves and how they are perceived by others in this role. In this talk, I will share research that further advances the construal perspective by illuminating the role of construal in women’s networking behaviour and, accordingly, the circumstances under which they are likely to attain brokerage roles. I highlight the critical role of women’s sense of belonging in contexts where they are underrepresented and negatively stereotyped, and how this shapes women’s social networks. In Study 1, I examine the friendship networks of MBA students, showing that the more women feel a sense of belonging at the beginning of their tenure, the more likely they are to occupy brokerage positions in the friendship network six months later. In contrast, men’s sense of belonging is unrelated to their subsequent friendship networks. I replicate this in an online experiment, showing that women (but not men) who are assigned to think about a time when they belonged (vs. did not belong) indicate more comfort with occupying a brokerage position. In Study 3, examining a second cohort of MBA students, I demonstrate that engaging in networking behaviours mediates the link between women’s (but not men’s) early sense of belonging and their subsequent friendship network brokerage. I conclude the talk by offering insights into future directions arising from this research, highlighting opportunities, limitations, and open questions.

SPEAKER

ABSTRACT

We show that government deleveraging causes liquidity squeeze among government contractors, an unintended consequence of containing sub-national debts. Our empirical analysis exploits China’s top-down deleveraging policy in 2017 and a purposefully-built dataset of listed firms matched with government procurement contracts. We find that private contractors experience larger accounts receivable increases, larger cash holding reductions, more share-pledging activities, worse operating performance, and higher probabilities of ownership change than noncontractors. Effects are muted among state-owned enterprises, implying that local governments selectively delay payments. Our findings reveal a novel trade credit channel for a reverse crowding-in effect whereby government deleveraging amplifies financial distortions against private firms.

SPEAKER

ABSTRACT

Inspired by research on the temporal nature of opportunities, we extend the idea that financially motivated shareholder activists target firms based on opportunities. We argue that certain organizational conditions create “windows of opportunity” for these activists to intervene in companies, which, when exploited, increase their odds of success. Drawing on event-based theories of organizational change and disruption, we hypothesize that firms become more likely targets of shareholder activists after experiencing organizational events that cause internal disruption to their business. We test this in the context of litigation and leadership transitions, and find that shareholder activists are more likely to target firms shortly after they experience either event. We further show that activists are more successful in achieving their objectives when they target firms based on these opportunities. Viewing opportunities through a temporal lens, this study extends research on the drivers of shareholder activism.