Despite decades of initiatives to address healthcare inequities in the U.S., disparities across race, gender, geography, and income remain stubbornly persistent.

We propose that AI-driven wellness apps powered by large language models can foster extreme emotional attachments and dependencies akin to human relationships—posing risks like ambiguous loss and dysfunctional dependence—that challenge current regulatory frameworks and necessitate safeguards and informed interventions within these platforms.

How companies market their AI systems affects the repercussions they face when their products fail. Marketers must promote their AI products with potential failure in mind.

We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy.

The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more.

Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice.

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness.

Social movement pressures can lead organizations to concede and improve social performance to avoid disruption costs, but we theorize that such responses evoke concession costs that prompt organizations to shift resources and attention from other social domains whose performance suffers.

This research studies business alliances that seek to address climate change, offering empirical evidence to address claims advanced by alliance supporters and critics.

We investigate whether banks' adoption of data-driven technologies influences competitive dynamics in local small business lending by diminishing the information advantages traditionally held by local banks.

Following the 2008 financial crisis, the Financial Crisis Inquiry Commission (FCIC) identified major shortcomings in bank board governance, contributing to systemic risk management failures.

Using Norwegian administrative data, we identify family equity investments in startups and examine their effects on investor returns and firm behavior.

Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without explanations, and narrative AI with explanatory rationales.

Remote work has become more common, providing operational flexibility and productivity benefits, but questions remain about whether and how it affects work quality.

We examine how artificial intelligence transforms the core pillars of collaboration— performance, expertise sharing, and social engagement—through a pre-registered field experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods company.

We show that when firms compete via supply functions, transferring high-cost capacity to the largest, most efficient firm—thereby diversifying its production technologies while increasing concentration—can lower prices by prompting the leader to expand output and competitors to aggressively defend market shares.

Using a sample of 3083 firms from 62 countries over 18 years, we analyze how the structure and identity of firms' material owners influence their Environmental, Social, and Governance (ESG) performance.

Transaction cost economics theory explains when it is more efficient for a transaction between two parties to occur across the market or within an organization.

This study explores public preferences for algorithmic and human decision-makers (DMs) in high-stakes contexts, how these preferences are shaped by performance metrics, and whether public evaluations of performance differ depending on the type of DM.

For as long as there has been work, there has been a “future of work,” through humans’ ingenuity and drive to get things done easier, faster, and better.

AI companion applications—designed to serve as synthetic interaction partners—have recently become capable enough to reduce loneliness, a growing public health concern.

As consumers increasingly interact with AI applications specialized for social relationships, what is the nature and depth of these relationships among actual users, and can company actions influence these dynamics? We find that active users of the US-based AI companion, Replika, feel closer to their AI companion than even their best human friend, and anticipate mourning the loss of their AI companion more than any other technology.

Research involving multiple experiments found that consumers have biased views of their driving abilities relative to those of other drivers and automated vehicles.

From Apple to Merck to Wikipedia, more and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious.

We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators.

Celebrities have shifted from endorsing established brands to being influencers for established brands to drawing on their influence to create brands themselves.

As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse.

Can accelerators pick the most promising startup ideas no matter their provenance? Using unique data from a global accelerator where judges are randomly assigned to evaluate startups headquartered across the globe, we show that judges are less likely to recommend startups headquartered outside their home region by 4 percentage points.

Space is becoming a potential source of value for businesses across a range of sectors, including agriculture, pharmaceuticals, consumer goods, and tourism.

The authors analyzed data from multiple large-scale randomized experiments on LinkedIn’s People You May Know algorithm, which recommends new connections to LinkedIn members, to test the extent to which weak ties increased job mobility in the world’s largest professional social network.

We study how the price of remote work is determined in a globalized labor market using data from a large web-based job platform, where workers from around the world compete for remote jobs.

The shift to remote work ended the traditional 9–5 workday: employees work in bursts, at night, between caregiving tasks, and whenever they can find time between the endless distractions of messages, calls, and emails.

Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem.

As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner.