MIS Distinguished Speaker Series

Temple University

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Oct 1 – Manju Ahuja to present “Maladaptive Mobile Use and Family-work Conflict: A Resource Drain Theory Approach to Examine Their Effects on Productivity and Well-being”

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Maladaptive Mobile Use and Family-work Conflict: A Resource Drain Theory Approach to Examine Their Effects on Productivity and Well-being

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Manju Ahuja

Frazier Family Professor of Computer Information Systems
College of Business
University of Louisville

Friday, Oct 1

10:30am – 12 pm | Alter 603

Abstact:

While acknowledging the many benefits of anytime-anywhere connectivity, recent research has called for further investigation into the maladaptive side of mobile technology use in the work-family interface realm. We rely on Resource Drain Theory to investigate how family-work conflict (FWC) leads to excessive use of mobile devices for work purposes during non-work hours, which, in turn, affects individual productivity and well-being. Further, we examine the role of competitive climate as a boundary condition. We conducted a field study across two measurement periods involving 324 individuals and their partners. Our results suggest that FWC affects productivity and well-being through excessive mobile use, and that competitive climate amplifies these effects. The study contributes by providing a better understanding of excessive mobile use phenomenon in terms of its determinants and consequences. We discuss the theoretical and practical implications of our findings, and outline directions for future research.

Oct 30 – Gordon Gao to present “How Artificial Intelligence Affects Human Performance in Medical Chart Coding”

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How Artificial Intelligence Affects Human Performance in Medical Chart Coding

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Guodong (Gordon) Gao

Professor
Director, Inovalon Artificial Intelligence Lab for Advanced Insights
Co-Director, Center for Health Information and Decision Systems
Robert H. Smith School of Business
University of Maryland

Friday, Oct 30

9:00 – 10:00 am | Zoom

Abstact:

While the impact of artificial intelligence (AI) on jobs has generated considerable discussion and debate, little is known about how AI affects knowledge worker productivity. We developed an AI solution for medical chart coding in a publicly traded company and then evaluated its impact on productivity regarding coders’ job experience. We find evidence that AI improves worker productivity overall. However, different from existing studies on skill biased technological change, we find that seniority goes the opposite way: the productivity of senior workers has a much less productivity boost from the use of AI than that of junior workers. To uncover the mechanism behind this surprising finding, we look at the task specific experience. Our results confirm the existence of complementarity between human experience and AI. Further analysis reveals that the performance discrepancy of job experience is attributable to senior user resistance. This paper provides new empirical insights into how AI affects knowledge worker productivity, with important implications for wider adoption and use of AI among knowledge workers.

Jan 24: Lynn Wu to speak on Social Network Effects on Performance and Layoffs: Evidence from the Adoption of a Social Networking Tool

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Lynn Wu

PhD Candidate
Sloan School of Management,
MIT

January 24, 2011

Speakman Hall 200, 1000am – 1130am

Abstract

By studying the changes in employees’ networks and performance before and after the introduction of a social networking tool, I find that a structurally diverse network (low in cohesion and rich in structural holes) has a positive effect on work performance. The size of the effect is smaller than traditional estimates, suggesting that omitted individual characteristics may bias the estimated network effect. I consider two intermediate mechanisms by which a structurally diverse network is theorized to improve work performance: information diversity (instrumental) and friendship (expressive). I quantify their effects on two types of work outcomes: billable revenue and layoffs. Analysis shows that the information diversity derived from a structurally diverse network is more correlated with generating billable revenue than is friendship. However, the opposite is true for layoffs. Friendship in a diverse network of colleagues is more correlated with reduced layoff risks than is information diversity. Field interviews suggest that friends can serve as advocates in critical situations, ensuring that favorable information is distributed to decision makers. This, in turn, suggests that having a structurally diverse network can drive both work performance and job security, but that there is a tradeoff between either mobilizing friendship or gathering diverse information. Furthermore, it is important to examine the mechanisms by which friendship reduces the risks of being laid off. If friendship promotes team effectiveness, delegating decisions rights to managers is optimal. However, if managers choose to optimize their own power at the expense of the firm, the positive impact of friendships on layoffs is evidence that delegating layoff decisions to managers can incur important costs.

For a copy of the paper, click here..