Speaker:

Prof. Raffaella Sadun
Professor of Business Management, Strategy Unit, Harvard Business School

The Demand for Executive Skills (with Joe Fuller, Stephen Hansen and Tejas Ramdas)

Abstract:

We use a large and unique corpus of job specifications for C-suite positions to document and explain heterogeneity across firms in the skills demanded for high-level executives.  A novel classification algorithm maps the text for each executive search into six separate skill clusters, all of which show considerable variation.  Patterns in the \textit{social skills} cluster are particularly striking: it features large growth in the sample, is the relatively most common cluster in CEO searches, and has a large sample variance.  We propose a mechanism whereby social skills faciliate the exchange of problems within firms; construct proxies for the need for such coordination; and show these correlate with the presence of social skills language.  These correlations do not appear for the other skill clusters.  The results suggest that the varied structure of firms induces demand for different executive skills.

Speaker:

Dr. Danielle Li
Associate Professor, Technological Innovation, Entrepreneurship, and Strategic Management
MIT Sloan

Abstract:

This paper views hiring as a contextual bandit problem: to find the best workers over time, firms must balance “exploitation” (selecting from groups with proven track records) with “exploration” (selecting from under-represented groups to learn about quality). Yet modern hiring algorithms, based on “supervised learning” approaches, are designed solely for exploitation. Instead, we build a resume screening algorithm that values exploration by evaluating candidates according to their statistical upside potential. Using data from professional services recruiting within a Fortune 500 firm, we show that this approach improves the quality (as measured by eventual hiring rates) of candidates selected for an interview, while also increasing demographic diversity, relative to the firm’s existing practices. The same is not true for traditional supervised learning based algorithms, which improve hiring rates but select far fewer Black and Hispanic applicants. In an extension, we show that exploration-based algorithms are also able to learn more effectively about simulated changes in applicant hiring potential over time. Together, our results highlight the importance of incorporating exploration in developing decision-making algorithms that are potentially both more efficient and equitable.

Speaker:

Dr. Claudine Gartenberg
Assistant Professor of Management
Wharton School of the University of Pennsylvania

Abstract:

Analyzing data from approximately 1.5 million employees across 1,108 established public and private US companies, we find that employee beliefs about their firm’s purpose is weaker in public companies. Among public companies, purpose is higher for firms with long-term investors and lower for firms with high hedge fund ownership. These patterns are most pronounced within the salaried middle and hourly ranks, rather than senior executives. These differences in purpose across firms can be attributed, in part, to differences in the background of the CEOs and reward structures within the companies. Our findings are consistent with higher owner commitment, and the corresponding policies that arise with this higher commitment, are associated with a stronger sense of purpose inside organizations.

Speaker:

Dr. Allison S. Gabriel
Associate Professor and Robbins Fellow
Eller College of Management
The University of Arizona

Abstract:

According to self-regulation theories, affect plays a crucial role in driving goal-directed behaviors. Yet, past work presents inconsistent results regarding the effects of positive and negative affect, with theory heavily relying on understanding the separate, unique effects of each affective experience. In the current investigation, we integrate tenets of emotional ambivalence with self-regulation theories to examine how the conjoint experience of positive and negative affect yields benefits for behavioral regulation. We test these ideas within a self-regulatory context that has frequently studied the possible benefits of affect—the job search. Specifically, across two within-person investigations, we explore how emotional ambivalence relates to job search success (i.e., interview invitations, job offers) via job search self-regulatory processes (i.e., metacognitive strategies, effort). To capture emotional ambivalence during job search, we utilize a person-centered analytic technique known as multilevel latent profile analysis (MLPA). Results illustrate that the subsequent week (i.e., at time t + 1; Study 1) and month (Study 2) after job seekers experience emotional ambivalence (i.e., higher levels of positive and negative affect at time t), they receive more job offers via increased search efforts and interview invitations. Theoretical and practical implications for studying emotional ambivalence in organizational scholarship are discussed.

Speaker:

Dr. Ivy Dang

Assistant Professor of Marketing
HKU Business School , The University of Hong Kong

Abstract:

Using data on user search and matching histories from an online dating site, we study the role of information in matching markets, emphasizing how partial or full information about the other side influences the final matching outcomes. We find that more information about the other side may make matching outcomes worse. This effect is mainly driven by the misaligned preferences (i.e., preference mismatch) between the two sides. Our findings suggest there exists an optimal amount of information that the platform should provide to each side before a match is proposed. A consumer theory model is developed to rationalize the behavior and shed light on optimal information provision strategies.

Speaker:

Dr. Alan P. Kwan

Assistant Professor of Finance
HKU Business School , The University of Hong Kong

Abstract:

This paper introduces a measure of work-from-home activity using a novel dataset of firm-mapped internet content consumption covering tens of thousands of business and consumer interest websites. I build a classifier of incoming traffic into residential, business, VPN and mobile networks. Validating this classification, I find remote IPs spike in traffic in the middle of March, the share of remote IP traffic in a county exhibit a high, 0.765 covariance with mobile phone data on workplace visits, and is higher in firms who ex-ante had better remote IT and in knowledge-intensive industries. Studying organizational factors affecting WFH, I find a strong role of social interactions. I document a lower shift toward remote work in response to local social distancing or Covid-cases in organizations with stronger social connections and less generalist workers, in firms with stronger culture (especially teamwork culture), and in areas with more social capital. If local cases or social distancing comprise exogenous variation in WFH, I find firms spend more time on business relevant reading, but less on researching new topics. These findings provide suggestive evidence for the ostensible tradeoff WFH poses between productivity and creativity.

Speaker:

Dr. Jiyin Cao

Assistant Professor, Management
Stony Brook University

Abstract:

Having friends in high places is often considered necessary to achieve success. Indeed, connections with upper-class individuals have been identified as a key component of social capital. Despite the tangible benefits upper-class network contacts can offer, we find that these networks have a dark side: the increased potential for unethical behavior, over and above one’s own social class. We propose that because upper-class individuals are less constrained by social norms, individuals with many upper-class contacts will perceive their network as having looser social norms. As a result, individuals with upper-class network ties will view morality as more relative and will be more likely to engage in unethical behavior. To test our core hypothesis that having upper-class contacts increases unethical behavior, we conducted five multi-method (archival, field, quasi-experimental, and experimental) studies involving a range of samples (CEOs, nationally representative adults, student roommates) in multiple cultures. Overall, the current research takes a property of networks (its class composition), links it to perceptions of that network (the perceived norm looseness of one’s network contacts) and connects it to a psychological mindset (moral relativism) that ultimately affects unethical behavior. These findings demonstrate that the benefits of social capital also carry a moral cost.

Speaker:

Dr. Rembrand Koning

Assistant Professor of Business Administration
Harvard Business School
Harvard University

Abstract:

Recent field experiments demonstrate that advice, mentorship, and feedback from randomly assigned peers improve entrepreneurial performance. These results raise a natural question: what is preventing entrepreneurs and managers from forming these peer connections themselves? We argue that entrepreneurs may be under-networked because they lack the necessary social skills—the ability to communicate effectively and interact collaboratively with new acquaintances—that allow them to match efficiently with knowledgeable peers. We use a field experiment in the context of a business training program to test if a short social skills training module improves the number and complementarity of peers that participants choose to learn from. We find that entrepreneurs who were exposed to the social skills training formed 50% more relationships with peers. These relationships exhibited more matching based on managerial skill and were more ethnically diverse. Finally, the training also increased entrepreneurs’ monthly profits by approximately 20%. Our findings suggest that social skills help entrepreneurs build relationships that create value for both themselves and their peers.

Speaker:

Dr. Hengchen Dai
Assistant Professor of Management and Organizations and Behavioral Decision Making
UCLA

Abstract:

As digitization enables service platforms to access users’ information, important questions arise about how digital service platforms should disseminate information to improve service capacity and enjoyment. We examine a strategy that involves providing customer-related information to individual service providers at the beginning of a service encounter. We causally evaluate this strategy via a field experiment on a large live-streaming platform that connects viewers and individual broadcasters. When viewers entered shows, we provided viewer-related information to broadcasters who were randomly assigned to the treatment condition (but not to control broadcasters). Our analysis, involving a subsample of 49,998 broadcasters, demonstrates that relative to control broadcasters, treatment broadcasters expanded service capacity by 12.62% by increasing both show frequency (3.31%) and show length (7.10%), thus earning 10.44% more based on our conservative estimate. Moreover, our intervention increased service enjoyment (measured by viewer watch time) by 4.51%. Two surveys and additional analyses provide evidence for two mechanisms and rule out several alternative explanations. Our low-cost, information-based intervention has important implications for digital service platforms that have little control over service providers’ work schedules and service quality.

Speaker:

Professor Tarun Khanna
Jorge Paulo Lemann Professor
Harvard Business School
Harvard University

Abstract:

Given the widespread adoption of remote work during the COVID-19 pandemic, it is likely that workers and organizations continue to adopt hybrid-remote work practices in the longer term. In a hybrid-remote work arrangement, work is partly done in a physical office and partly done remotely. Yet we lack causal evidence on how hybrid-remote work affects worker performance and intra-firm communication patterns. We report evidence from a field experiment, conducted within an organization in Bangladesh in the summer of 2020. Following a government mandated four-month lockdown due to COVID-19, the experiment entailed randomizing the list of workers who were allowed back in office on any given day. More specifically, for a period of five weeks following the lockdown, we exploit an exogenous cap of the maximum number of workers allowed back in office and conduct daily lotteries to determine which workers were allowed to work in the office versus work at home. We exploit this allocation protocol and use data on emails exchanged among employees in the pre-lockdown, lockdown and post-lockdown (i.e. treatment) periods to study intra-firm communication patterns. Our preliminary results indicate that employees who spent more time in the office sent 0.3% fewer emails per day. Moreover, employees who spent more time in the office together also sent 0.3% fewer emails to each other. We furthermore find that employees who followed a hybrid work protocol that involved intermediate levels of number of days in the physical office received 34-44% higher performance ratings from their managers, compared to employees who mostly worked from home or mostly worked from the office.