MIS Distinguished Speaker Series

Temple University

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Sezgin Ayabakan

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.

Oct 22 – Ola Henfridsson to present “The Extension of Digital Ventures”

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The Extension of Digital Ventures

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Ola Henfridsson

Professor of Business Technology
Miami Herbert Business School
University of Miami

Thursday, Oct 22

9:00 – 10:00 am | Zoom

Abstact:

Digital ventures typically face significant growth expectations. A common response is to extend the current operations into new areas through core entrepreneurship processes for business extension: productive opportunity creation and opportunity actualization. We surmise that the versatility of the digital venture’s digital core (e.g., new search engine, data mining technique, platform, or voice interface) facilitates these processes by reducing cost and increasing speed. To this end, we use Penrose’s work for analyzing a two-year in-depth case study of a Chinese digital venture’s extension of their initial operations based on its credit rating technology. We trace four key processes contributing to productive opportunity creation and opportunity actualization through our grounded analysis: problematizing and concepting (creation of productive opportunity) and templating and reusing (opportunity actualization). We observe how these processes are enabled by the versatility of the case organization’s digital core. Synthesizing our findings, we contribute to the emerging digital innovation and entrepreneurship literature related to business growth by developing a process model of digital venture extension.

Oct 16 – Yulin Fang to present “Managing Collective Enterprise Information Systems Compliance – A Social and Performance Management Context Perspective”

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Managing Collective Enterprise Information Systems Compliance – A Social and Performance Management Context Perspective

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Yulin Fang

Professor
Department of Information Systems
College of Business
City University of Hong Kong

Friday, Oct 16

9:30 – 10:30 am | Zoom

Abstact:

In today’s environment characterized by business dynamism and information technology (IT) advances, firms must frequently update their enterprise information systems (EIS) and their use policies to support changing business operations. In this context, users are challenged to maintain EIS compliance behavior by continuously learning new ways of using EIS. Furthermore, it is imperative to business that employees of a functional unit maintain EIS compliance behavior collectively, due to the interdependent nature of tasks that the unit needs to accomplish through EIS. However, it is particularly challenging to achieve such a collective level of EIS compliance, due to the difficulty that these employees may encounter in quickly learning updated EIS. It is therefore vital for firms to establish effective managerial principles to ensure collective EIS compliance of a functional unit in a dynamic environment. To address this challenge, this study develops a research model to explain collective EIS compliance by integrating the IS-novel organizational literature on social context and performance management context with social capital theory. It proposes that social context, an organizational environment characterized by trust and support, positively affects collective EIS compliance by developing business-IT social capital that enhances mutual learning between business and IT personnel. Furthermore, the performance management context, an organizational environment characterized by discipline and “stretch” is seen to have a direct and beneficial effect on collective EIS compliance as well as an indirect, moderating effect on the causal chain among social contexts, business-IT social capital, and collective EIS compliance. General empirical support for this research model is provided via a multiple-sourced survey of managers and employees of 159 functional units of 53 firms that use EIS, as well as their corresponding IT unit managers. The theoretical and practical implications of these findings are discussed

Oct 2 – Ryan Wright to present “A Multi-level Contextualized View of Phishing Susceptibility”

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A Multi-level Contextualized View of Phishing Susceptibility

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Ryan Wright

C. Coleman McGehee Professor of Commerce
Director, Certificate in Cybersecurity
Associate Director, Center for the Management of Information Technology
McIntire School of Commerce
University of Virginia

Friday, Oct 2

9 – 10 am | Zoom

Abstact:

With billions of dollars in annual IT security-related damages, organizations are well aware of the critical need for protection from phishing attacks with IT security policies and best practices. However, after decades of academic research and industry interventions, phishing remains one of the top cybersecurity threats to organizations. This significant effort to combat phishing by both practitioners and academics has largely focused on three factors: 1) individual characteristics, 2) message characteristics, and 3) interventions. We advocate for moving beyond this predominant focus to encompass a context-driven understanding of phishing susceptibility. We develop a phishing susceptibility model that includes how contextual factors, including workgroup characteristics and an individual’s position in organizational social networks, can be used to predict susceptibility to phishing messages. We show the utility of this approach through a field study of the ability to detect deception email communication using a multi-wave phishing simulation in the finance division of a large university in the US. Our findings extend the understanding of phishing susceptibility through a model that incorporates variation in the workgroup and network-based factors. In addition, this research generates practical insights regarding how organizations may identify and support employees that are likely to be susceptible to phishing attacks.

Sep 11 – Anuj Kumar to present “Digitization and Divergence: Online School Ratings and Segregation in America”

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Digitization and Divergence: Online School Ratings and Segregation in America

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Anuj Kumar

Matherly Professor of Information Systems
Associate Professor
Warrington College of Business
University of Florida

Friday, Sep 11

9 – 10 am | Zoom

Abstact:

We analyze whether widespread online access to school performance information affected economic and social segregation in America. We leverage the staged rollout of GreatSchools.org school ratings from 2006–2015 to answer this question. Across a range of outcomes and specifications, we find that the mass availability of school ratings has accelerated divergence in housing values, income distributions, and education levels as well as the racial and ethnic composition across communities. Affluent and more educated families were better positioned to leverage this new information to capture educational opportunities in communities with the best schools. An unintended consequence of better information was less, rather than more, equity in access to education.

April 3 – Detmar Straub to present “A Dark Future for AI: The Looming Spectre of SkyNet?”

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A Dark Future for AI: The Looming Spectre of SkyNet?

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Detmar W. Straub

Professor and IBIT Research Fellow

Temple University Fox School of Business

Regents Professor Emeritus

University System of Georgia and Georgia State University

Friday, April 3

10:30 – 12:00 pm | Zoom

Abstact:

Capabilities of AI and thinking/learning machines are clearly overtaking human abilities (a.k.a. “technological singularity” or, more plainly speaking, “singularity”), with several forecasters like Winograd (2006) predicting that machine will outthink us within the first half of the 21st century. Is it possible that humans will not be able to control the burgeoning intelligence of machines and that we will, frighteningly, be subordinated to them, especially as they become self-aware? This talk starts by sketching out some past and present forecasts of when technological singularity will be real and present, what social, economic, and political issues will emerge, what security issues will loom, and finally how futurists (including science fiction writers and the movies) have envisioned the role of human beings in the coming era of the thinking machine. While the future of humanity might be hanging in the balance, one key academic question arises. What should researchers, in particular information systems researchers, study w/r/t AI? This overall issue has been framed as IA versus AI, or intelligence (human) augmentation (IA) versus artificial (computer) intelligence (AI). Enduring research questions might include: (1) technical issues with achieving singularity and requirements such as designing a tamper-proof “kill” switch for intelligent machines; (2) behavioral questions such as the pace of change and problems with duplicating human creativity; (3) social-economic conundrums such what will people do in an era of omnipresent thinking/working machines and worldwide societal disruption; and (4) organizational matters such as will there be an IS/IT Dept. and, if so, what will it do?

April 10 – JaeHwuen Jung to present “The secret to Finding Love: A Field Experiment of Choice Structure in Online Dating Platform”

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The secret to Finding Love: A Field Experiment of Choice Structure in Online Dating Platform

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JaeHwuen Jung

Assistant Professor
Department of Management Information Systems
Fox School of Business
Temple University

Friday, April 10

10:30 – 12:00 pm | Zoom

Abstact:

Online matching platforms require new approaches to market design since firms can now control many aspects of search and interaction process through various IT-enabled features. While choice structure—the size of choice set and the number of choices a platform offers to its customers—is one of the key design features of online matching platforms, its impact on engagement and matching outcomes remains unclear. In this study, we examine the effect of different choice structures on the number of choices and matches on the platform by conducting a randomized field experiment in collaboration with an online dating platform. Specifically, we design four treatment groups with different choice structures where users can only interact with other users in the same group, select users who are in a similar age range and live in the same geographical location, and randomly assign them to each treatment group. We find that providing higher choice capacities to male and female users have a different effect on choice behaviors and matching outcomes. Moreover, while increasing the choice capacity of male users yields the highest number of choices, increasing the choice capacity of female users is the most effective way to increase matching outcomes. Structural analysis further reveals the underlying mechanisms of choice behavior and matching results, suggesting that users significantly decrease the number of choices after receiving a choice from other users and the effect of the choice capacity on matching outcomes differs by gender. We further provide a counterfactual analysis that explores optimal choice structure design depending on the gender ratio of the online dating platform.

April 24 – Xueming Luo to present “Quantifying the Impact of Human-AI Supervisor Assemblages on Employee Performance: A Field Experiment”

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Quantifying the Impact of Human-AI Supervisor Assemblages on Employee Performance: A Field Experiment

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Xueming Luo

Founder/Director of Global Center on Big Data in Mobile Analytics
Charles Gilliland Distinguish
Chair Professor of Marketing, Strategy, and MIS
Fox School of Business
Temple University

Friday, April 24

10:30 – 12:00 pm | Zoom

Abstact:

Despite the promises of artificial intelligence (AI), there are concerns from both employees and managers about adopting AI at workplaces. Examining how firms can integrate AI into performance management systems (PMS), this research focuses on the impact of various human-AI supervisor assemblages on employees’ task performances and relations with human bosses. We utilize data from a field experiment on customer service employees in a fintech company who are randomly assigned to receive job performance feedback from human managers only, an AI bot only, or human-AI supervisory assemblages. A unique feature in our experiment is that the assemblages encompass a dual human-and-AI configuration (where employees receive feedback from both human managers and an AI bot in parallel) and a shadow-AI-human-face configuration (where employees receive feedback that is generated by an AI bot but delivered by human managers). The results suggest that relative to conventional human supervision, a dual human-and-AI design negatively impacts employee task performance, whereas a shadow-AI-human-face design positively impacts employee task performance. Explorations of the mechanisms support that a dual condition with both AI and human supervision in parallel leads employees to perceive more confused leadership and feedback, less learning from the feedback, and lower employee-manager relationship quality in a vicious cycle. In contrast, the shadow-AI design significantly improves employees’ perceptions of feedback accuracy and consistency, willingness to proactively seek feedback, and organizational commitment in a virtuous cycle. These findings suggest that firms should prudently design the human-AI supervisory assemblages. As a double-edged sword, AI-based PMS should be deployed in the shadows to empower human managers, rather than to displace or compete with them, to achieve higher worker productivity and healthier employee-manager relationships.

Feb 21 – Omar El-Sawy to present “Humanistic Orchestration of Artificial Intelligence Applications in Real-Time Business Platform Contexts: A Rhythmic Fabric Theory”

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Humanistic Orchestration of Artificial Intelligence Applications in Real-Time Business Platform Contexts: A Rhythmic Fabric Theory

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Omar El-Sawy

Kenneth King Stonier Professor of Business Administration
Professor of Data Sciences and Operations Department
Marshall School of Business
University of Southern California

Friday, February 21

10:30 – 12:00 pm | Speakman 200

Abstact:

AI applications are increasingly being deployed in real-time business platform contexts in which tempo is very fast and digital connectivity is very high. This creates a number of new challenges that go beyond the typical challenges and perspective of the deployment of digital technologies, as AI applications come with a different level of engagement and learning that require more complex orchestration. This presentation develops and exposits the elements of a theory for the humanistic orchestration of AI applications in real-time management business platform contexts that is based on rhythms.

We use an abductive theory building approach that moves from empirical observation to inductive insights to empirical diagnosis to theory development. Our recent real-time management study (Rydén & El Sawy, “How Managers Perceive Real-Time Management: Thinking Fast & Flow”, California Management Review, Feb 2019) has uncovered a phenomenon that is key to humanistic engagement in real-time contexts that we have called Fast & Flow. In this presentation, we draw on a case study of a renter’s insurance AI-enabled application (Lemonade) to couple AI engagement with Fast & Flow behavior. We argue that a rhythmic perspective using Fast & Flow is more appropriate in real-time business platform settings, and we develop a rhythmic fabric ontology for AI engagement. Using this rhythmic perspective, we build elemental propositions of a rhythmic theory for humanistic AI orchestration in real-time business platform settings. We use another case study context (Microsoft Outlook) to illustrate the rhythmic theory in action and make recommendations for the way forward for AI orchestration in organizations. Implications for information systems researchers and management researchers are provided.

(work with Pernille Rydén, Danish Technical University)

Feb 7 – Zhiqiang (Eric) Zheng to present “How Much is Financial Advice Worth? The Transparency-Revenue Tension in Social Trading”

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How Much is Financial Advice Worth? The Transparency-Revenue Tension in Social Trading

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Zhiqiang Zheng

Zhiqiang (Eric) Zheng

Ashbel Smith Professor
Department of Information Systems and Operations Management
Naveen Jindal School of Management
University of Texas at Dallas

Friday, February 7

10:30 – 12:00 pm | Speakman 200

Abstact:

Social trading — an emerging paradigm in the spirit of the sharing economy — enables a trader to share her trading wisdom with other investors. A special type of social trading is copy trading, where less experienced investors (followers) are allowed to copy the trades of experts (traders) in real-time after paying a fee. Such a copy trading mechanism often runs into a transparency-revenue tension. On the one hand, social trading platforms need to release traders’ trades as transparently as possible to allow followers to evaluate traders. On the other hand, complete transparency may undercut the platform’s revenue since followers could free ride. That is, followers could manually copy the trades of a trader to avoid paying following fees.

This study addresses the tension by optimizing the level of transparency by delaying the release of the information pertaining to the trades executed by traders on the platform. We capture the economic impact of the delay using the notions of profit-gap and delayed-profit. Profit-gap is calculated as the difference between the profit of the real-time trade and the delayed-profit of the trade (i.e., the profit of the same trade executed after adding some time delay). First, we propose stochastic differential models that capture the impact of delay on profit-gap and delayed-profit. Next, we propose a mechanism that elucidates the economic effects of profit-gap and delayed-profit on followers, and consequently, the amount following a trader: (1) Protection Effect and (2) Evaluation Effect. The protection effect becomes stronger as the profit-gap increases. The evaluation effect becomes stronger when the delayed-profit increases or when a trader attracts more evaluation activities (views) on her profile page. Empirical investigations find support for the above mentioned effects of profit-gap and delayed-profit on the amount of money following a trader.

We then develop a stochastic control formulation that optimizes platform revenue. The control is the optimal delay that is calculated as a function of the current amount of money following a trader and the number of views on the trader’s profile page. The optimized revenue can be incorporated into an algorithm to provide a systematic way to infuse the platform’s goals into the ranking of the traders. A counterfactual study is conducted to demonstrate the performance of the optimal delay policy (versus a constant delay policy) using data from a leading social trading platform operating in the Foreign Exchange market.