MIS Distinguished Speaker Series

Temple University

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Aleksi Aaltonen

Mar 31 – Gedas Adomavicius – “Efficient and Flexible Long-Tail Recommendation Using Cosine Patterns”

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Time: Friday, 31 March 2023, 10:30–12:00
Room: LW420

Abstract

With the increasing use of recommender systems in various application domains, many algorithms have been proposed for improving the accuracy of recommendations. Among various other dimensions of recommender systems performance, long-tail (niche) recommendation performance remains an important challenge, due in large part to the popularity bias of many existing recommendation techniques. In this study, we propose CORE, a cosine-pattern-based technique, for effective long-tail recommendation. Comprehensive experimental results compare the proposed approach both to classical, widely-used recommendation algorithms and to specialized long-tail recommendation baselines, and demonstrate its practical benefits in accuracy, flexibility, and scalability, in addition to the superior long-tail recommendation performance.

Bio

Gedas Adomavicius is a professor in the Department of Information and Decision Sciences at the Carlson School of Management, University of Minnesota, where he also holds the Larson Endowed Chair for Excellence in Business Education. He received his PhD degree in computer science from New York University. His general research interests revolve around computational techniques for aiding decision-making in information-intensive environments and include personalization technologies and recommender systems, machine learning and data analytics, and electronic market mechanisms. His research has been published in a number of leading academic journals in information systems and computer science, including Information Systems Research, MIS Quarterly, Management Science, Journal of Operations Management, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems, and Data Mining and Knowledge Discovery, and has been cited more than 28,000 times to date (according to Google Scholar). He has received several research grants from major funding institutions, including the U.S. National Science Foundation CAREER award for his research on personalization technologies. He has served on the editorial boards of several leading academic journals, including as Senior Editor for Information Systems Research and MIS Quarterly. In 2017, Prof. Adomavicius received the INFORMS Information Systems Society’s Distinguished Fellow Award. At the Carlson School of Management, he has taught analytics-related courses in the undergraduate, MBA, MSBA, PhD, and Executive Education programs and has served in several administrative roles, including as the chair of the Information and Decision Sciences Department.

Mar 24 – Shaila Miranda – “Setting an IT Innovation Agenda: The Practice Repertoire of Bots in a Blockchain Discourse”

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Time: Friday, 24 March 2023, 10:30–12:00
Room: LW420

Abstract

Communities make sense of social issues through discourse. An “issue” is a matter of potential concern. Issues can involve public policy or innovations. Issues do not exist prior to a discourse, but rather are the product of sensemaking and social construction through discourse. This constitutive nature of community discourse has been noted for information technology (IT) innovation. Through discourse, actors learn vicariously about the innovation, without needing to invest in it. Through discourse, actors advance diverse frames about the innovation, advocating for competing innovations or versions of an innovation – or even subverting the innovation. Prior research has highlighted the distinctive role of mass media in drawing attention to social issues and filtering information about them to shape public opinion. Discourse now takes place on digital mass media, where social bots abound. Though researchers have noted the role played by such bots in other venues, we lack understanding of the role they play in IT innovation discourses. Our study therefore asks: How do social bots participate in an IT innovation discourse? To address this question, we studied seven years of a Twitter blockchain discourse. Because our aim was to isolate the distinctive role of bots, we limited our investigation to discourse occurring in a single geographical area – Australia – to reduce confounds by cultural factors. Using text mining in a computational theory construction approach, we observed social bots to evince three sets of practices: innovation spotlighting, innovation framing, and innovation visibilizing practices. We theorize how this practice repertoire shapes an innovation discourse, i.e., by contributing to setting the agenda for the IT innovation. As the number of social bots grows, understanding how they shape innovation discourses will be essential to key innovation stakeholders and policymakers.

Bio

Shaila M. Miranda is the W.P. Wood Professor of MIS at the Price College of Business, the University of Oklahoma. She has a doctorate in Management Information Systems from the University of Georgia and an M.A. in Sociology from Columbia University. Her research focuses primarily on public discourse and shared meaning in the arenas of digital activism and innovation. She employs a combination of qualitative and computational inductive techniques. Shaila has published a book, Social Analytics, through Prospect Press and her research has appeared in journals such as the MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Small Group Research, Information and Management, and Data Base. She serves as Senior Editor for MIS Quarterly and previously has served as Senior Editor for Information Systems Research.

Mar 17 – Sang-Pil Han – “AI Effectiveness, Task Difficulty, and Employee Income in the Gig Economy: When AI is the Default Service Provider Rather than Humans”

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Time: Friday, 17 March 2023, 10:30–12:00
Room: LW420

Abstract

Increasingly, artificial intelligence (AI) serves as a frontline operator, while humans perform backend operations. Despite growing firms in the gig economy employing a business model with AI as the default service provider, the literature is limited regarding the impact of such a model on employee income. To address such limitations, this research proposes an AI-first service framework, which asserts that AI initially attempts to solve tasks, but upon unsatisfactory service outcome, customers pay a fee for employee assistance with such tasks. To empirically investigate our proposed framework, we partner with an AI-first learning app, where AI and tutors are the default and on-request service providers, respectively. We use tutor-level observational data and find that as AI, the default service provider, becomes more effective, tutor income is mediated by changes in task volume and margin, but that the pathways differ depending on employee expertise. Findings from our granular data show that, as AI effectiveness increases, tasks that are difficult due to their broad coverage across topics are passed on to tutors such that low-expertise (vs. high-expertise) tutors accept fewer tasks. We also conduct a field experiment at the customer level to show that customers are willing to pay for extra assistance from tutors, despite receiving free service from AI, for tasks that are difficult due to in-depth knowledge required within a topic. We discuss the theoretical implications of our findings and practical ramifications to effectively manage and develop human competency in the era of an AI-driven economy.

Bio

Sang-Pil Han is an Associate Professor of Information Systems in the W. P. Carey School of Business at Arizona State University. His research focuses on artificial intelligence, digital platforms, and business analytics. His research has been published in top-tier academic journals such as Management Science, Management Information Systems Quarterly, Information Systems Research and Journal of Marketing, and featured in Harvard Business Review and BBC News. He has received grants from the Marketing Science Institute and Wharton Interactive Media Initiative, the NET Institute, the Wharton Customer Analytics Initiative, the Korea Research Foundation, the Hong Kong General Research Fund, as well as private companies. At ASU, he was a Co-Faculty Director for the Master of Science in Business Analytics program. He served as an Associate Editor at Information Systems Research. He advises a variety of organizations, including tech startups like Mathpresso, a leading AI-powered education platform, and RoundIn, an online golf learning platform, as well as non-profits like Simple Steps, a 501c3 organization that assists female immigrant talent in achieving their professional goals. In his spare time, he enjoys playing golf with his wife and two daughters.

Mar 3 – Stefan Tams – “Cognitive Aging and the Struggle of Older Workers with Post-adoptive IT Use”

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Time: Friday, 3 March 2023, 10:30–12:00
Room: LW420

Abstract

Older workers use organizational IT in qualitatively different ways than their younger counterparts. In particular, they often focus on a few core features of an IT instead of exploiting the full range of features. This behavior is indicative of the significant reduction in post-adoptive IT use that occurs as the workforce ages. However, since the causes of this reduction remain unclear, managers and systems designers have difficulty addressing the problem of the underuse of technologies by the aging workforce. By means of a serial mediation model, this research note argues that the reduction in post-adoptive IT use among older workers—and specifically the reduction in extended feature usage—is caused by the decline of fluid intelligence that occurs with aging and by the impact of this decline on the ability of users to learn about new features. To test the model, data were collected from younger and older users of Microsoft Excel. Different measures for extended feature usage were employed for triangulation purposes. To reinforce the confidence in the study results even more and to yield broader implications for the post-adoptive use of IT, intention to explore and user innovation with IT were also brought into play as outcome measures. In addition, the triangulation strategy was based on different measures for age and for the primary mediating variable. The results supported the model and indicated some important ways that managers and systems designers can help older workers use more features of workplace IT despite the decline in their fluid intelligence.

Bio

Stefan Tams holds the Professorship in Technology and Aging at HEC Montréal, Canada, where he is an associate professor of information systems. His current research interests focus on the roles of age and stress in IT use. His work has appeared in several scientific journals, including MIS Quarterly, Journal of the Association for Information Systems, European Journal of Information Systems, and Journal of Strategic Information Systems, among others. His research has been featured in The Wall Street Journal and other outlets.

Feb 10 – Rajiv Garg – “The Price of Losing Trust: An Empirical Analysis of Social Misconduct by YouTube Creators”

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Time: Friday, 10 February 2023, 10:30–12:00
Room: LW420

Abstract

We study the consequences of reported social misconduct for YouTube creators. Using a staggered difference-in-differences approach, we find that YouTube channels of creators who are found to have misconducted themselves experience significant drops in both subscription and viewership. Such drops translate to economically significant financial losses ranging from $4,734 to $8,233 per month per channel. We find that the effects are similar for channels that feature products and those that do not, and that the effects are more pronounced for channels whose creators can be visually identified. These consequences of social misconduct can be attributed to loss of customer trust, which we show can be partially mitigated by means of credible online apologies.

Bio

Professor Garg’s research uses economic and statistical techniques to analyze information flow in digital platforms and networked structures. More specifically, Professor Garg’s research spans following four broad areas: 1) diffusion of digital content across networks, 2) digital marketing strategies for social and mobile commerce, 3) role of digital technologies in labor markets and entrepreneurship, and 4) identification of business value of data streams generated by digital technologies (blockchain, NFT, IoT, AR/VR, etc.). Professor Garg’s research has appeared in academic journals like Management Science, MIS Quarterly (MISQ), Information Systems Research (ISR), Production and Operations Management (POM), Journal of Management Information Systems (JMIS), and various other journals and peer reviewed conference proceedings. His work has received media coverage in Forbes, Fortune, Austin Statesman, Dallas Morning News, Pittsburgh Post-Gazette, Medium, and more. For his contributions to the field of technology and engineering, Professor Garg was nominated and named a senior member of IEEE.

Jan 27 – David Lanter – Enabling Data Protection by Design with Data Provenance Metadata”

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Time: Friday, 27 January 2023, 10:30–12:00
Room: LW420

Abstract

Privacy by design is part of the larger “data protection by design” achieved by security architecture and focuses on leveraging privacy protection principles, controls along with privacy enhancing technologies into the design of information management technologies and systems. The European Union’s General Data Protection Regulation (GDPR) makes protecting privacy and personal data a default requirement for system and service behavior of systems and services that must be thought through and designed in. Although the concept of privacy and data protection by design found its way into GDPR, the authors of the legislation acknowledged that “its concrete implementation remains un-clear”. Data provenance information, however, offers a way to meet these requirements. This presentation provides an overview of pioneering research the author conducted to combine information systems and related processing workflows with digital provenance metadata capture and processing to augment scientific reproducibility, comparison, trust or to otherwise improve information system assisted decision support.

Bio

David Lanter is an Assistant Professor of Practice and Director of the Information Technology Auditing and Cyber Security (ITACS) programs at Temple University’s Fox School since 2016. Prior to coming to Temple University, he was Vice President of Information Management Systems at CDM Smith, Research Director at Rand McNally, Software Design Engineer at Microsoft, Assistant Professor of Geography and Research Fellow at University of California – Santa Barbara, Systems Analyst at Grumman Data Systems, Software Engineer at Navigation Sciences, and President of Geographic Designs Inc. Dave earned his Bachelor of Arts degree with honors in Science, Technology and Society from Clark University, Master of Arts degree in Geographic Information System design from SUNY-Buffalo, Master of Science degree in Information Technology Auditing and Cyber Security from Temple University, and his Ph.D. in Geographic Information Processing from the University of South Carolina. He is a certified Geographic Information Systems Professional (GISP), Certified Information Systems Auditor (CISA), and Certified Information Systems Security Professional (CISSP). Dr. Lanter is a member of ISACA and ISACA’s Philadelphia Chapter where he authors and presents continuing professional education webinars and workshops. He is also a member of Urban and Regional Information Systems Association (URISA) where he serves on the faculty of URISA’s GIS Leadership Academy, instructs workshops on GIS data quality assurance and cybersecurity, and served as past chair of URISA’s Workshop Development Committee.

Dec 2 – Robert Gregory – “Skin in the Game: The Transformational Potential of Decentralized Autonomous Organizations”

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Time: Friday, 2 December 2022, 10:30–12:00
Room: LW420

Abstract

Decentralized autonomous organizations (DAOs) are a new form of organizing that are worth theorizing because of their potential to address collective action problems. As community-facilitated human-machine systems deployed on a blockchain, they rely on self-governance through smart contracts and voluntary member contributions. Yet, the promise of decentralization is difficult to sustain. To this end, this paper engages in phenomenon-based theorizing of DAOs by drawing on the lens of polycentric commons and examining the case of Decentralized Finance (DeFi) DAOs with a specific focus on MakerDAO. We contribute to the burgeoning literature on DAOs and new forms of technology-enabled organizing with a model explaining the transformational potential of DAOs through a set of three mechanisms (sustained participation, collective direction, and scaled organizing). This model explains how polycentric governance as implemented in DAOs helps address the inherent challenges of sustaining collective action in the commons.
Bio
Robert W. Gregory is Associate Professor of Business Technology at University of Miami Herbert Business School. He is also Research Fellow with MIT’s Center for Information Systems Research (CISR). He holds a diploma (combined bachelor’s and master’s degree) in Management Information Systems from the University of Cologne, Germany, a master’s degree in International Management from the Community of European Management Schools (CEMS), and a Ph.D. equivalent, Dr. rer. pol., in Business Administration from Goethe University Frankfurt, Germany. He co-founded and serves as the outgoing president of the AIS special interest group on Digital Innovation, Transformation, and Entrepreneurship (SIGDITE). He serves as Associate Editor for Information Systems Research and Senior Editor for Journal of the Association for Information Systems, where he handles the ‘theory’ paper submissions. He received the Early Career Award from the global Association for Information Systems (2016) and the Best Reviewer Award from Information Systems Research (ISR) and Management Information Systems Quarterly (MISQ). Robert’s research program focuses on novel management and information systems phenomena related to the diffusion and innovation with digital technologies and the associated transformation of individuals, organizations, and markets. His research has appeared in premier journals, including MIS Quarterly, Information Systems Research, and Academy of Management Review. His teaching covers digital innovation and disruption, digital transformation, and product and project management across undergraduate, master’s, MBA, and executive levels and spans multiple countries and cultures. He has worked and collaborated with leading blue chip companies across Europe and USA.

Nov 4 – Ramesh Sharda – “Network-based Health Analytics”

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Time: Friday, 4 November 2022, 10:30–12:00
Room: LW420

Ramesh Sharda
Chuck and Kim Watson Chair
Vice Dean for Grad Programs and Research
Regents Professor of Management Science and Information Systems
ConocoPhillips Chair of Technology Management
Spears School of Business
Oklahoma State University
https://business.okstate.edu/directory/16728.html

Abstract

Networks have been around a long time, but analytics/data science projects seldom use network level properties directly in analyzing a problem. We illustrate how network measures can be used to help inform medical decision-making. Examples include network applications in descriptive, predictive, and prescriptive analytics: Applications of network metrics in health analytics – comorbidities; descriptive analytics in health demographics based upon comorbidities; incorporating comorbidities to predict hospital lengths of stay; clique modeling to determine identify diseases combinations that impact mortality, etc.

Bio

Ramesh Sharda is the Vice Dean for Research and the Watson Graduate School of Management, Watson/ConocoPhillips Chair and a Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University. He has coauthored two textbooks (Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support, 11th edition, Pearson and Business Intelligence, Analytics, and Data Science: A Managerial Perspective , 4th Edition, Pearson). His research has been published in major journals in management science and information systems including Management Science, Operations Research, Information Systems Research, JMIS, EJIS, Decision Support Systems, Interfaces, INFORMS Journal on Computing, and many others. He is a member of the editorial boards of journals such as the Decision Support Systems, Decision Sciences, ACM Database, and Information Systems Frontiers. He served as the Executive Director of Teradata University Network through 2020 and was inducted into the Oklahoma Higher Education Hall of Fame in 2016. Ramesh is a Fellow of INFORMS and AIS. He was the winner of 2020 OSU Eminent Faculty Award. Ramesh also won the Fulbright Distinguished Chair Award at Aalto University in Finland for 2022-2023.

Oct 28 – Lynn Wu – “Innovation Strategy after IPO: How AI Analytics Spurs Innovation after IPO”

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Time: Friday, 28 October 2022, 10:30–12:00
Room: LW420

Lynn Wu
Associate Professor of Operations, Information and Decisions
The Wharton School, The University of Pennsylvania
https://oid.wharton.upenn.edu/profile/wulynn/

Abstract

We examine the role of AI analytics in facilitating innovation in firms that have gone through IPO. Using patent data on over 1,000 publicly traded firms, we find that firms acquiring AI analytics capability post-IPO experience less of a decline in innovation quality compared to similar firms that have not acquired that capability. This effect is greater when only machine learning capabilities are considered. Moreover, we find this sustained rate of innovation is driven principally by the continued development of innovations that combine existing technologies into new ones—a form of innovation that is especially well supported by analytics. By examining three main mechanisms that hampered post-IPO innovation, we find that AI analytics can ameliorate the pressure to meet short-term financial goals and disclosure requirements. However, it has limited effect in addressing managerial incentives. For firms with long product cycles, the disclosure effect is reduced to a greater extent than it is for those with short cycles. Overall, our results show the importance of examining technology as a critical input factor in innovation. We show that the increased deployment of analytics may reduce some of the innovative penalties suffered by IPOs, and that investors and managers can potentially mitigate post-IPO reductions in innovative output by directing capital acquired in the IPO process to the acquisition of AI analytics capabilities.

Bio

Her research examines how emerging information technologies, such as artificial intelligence and analytics, affect innovation, business strategy, and productivity. Specifically, her work follows three streams. In the first stream, she examines how data analytics and artificial intelligence affect firm innovation, business strategy, labor demand, and productivity for both large firms and startups. In her second stream, she studies how enterprise social media and online platforms affect work performance, career trajectories, entrepreneurship success, and the formation of new type of biases that arise from using technologies. In her third stream of research, Lynn leverages fine-grained nanodata available through online digital traces to predict economic indicators such as real estate trends, labor trends and product adoption. Lynn has published articles in economics, management and computer science. Her work has been widely covered by media outlets, including, NPR, the Wall Street Journal, Businessweek, New York Times, Forbes, and The Economist. She has won numerous awards such as Early Career awards from INFORMS and AIS, best paper awards from Information System Research, AIS, ICIS, HICSS, CHITA, and Kauffman. She has also won the Dean’s teaching award.

Oct 21 – Michelle Carter – “The Interplay of Content, Platform, and Identity: An Empirical Examination of Social Media Allyship”

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Time: Friday, 21 October 2022, 10:30–12:00
Room: Speakman 200

Michelle Carter
Associate Professor
Washington State University
https://directory.business.wsu.edu/Directory/Profile/michelle.carter/

Abstract
In recent years, organizations of every shape and size have embraced the “whole self” movement, which encourages employees to show up authentically in the workplace. The movement dovetails with diversity, equity, and inclusion (DEI) programs and organizations’ use of social media to signal allyship with historically disadvantaged groups. Such signaling encourages job candidates to follow suit, as a means of demonstrating their trustworthiness and confidence to prospective employers. However, while social media allyship can lead to positive outcomes for organizations, it may not benefit individuals. Cybervetting research cautions against taking a public stand on potentially sensitive social issues in case it negatively affects perceptions of job suitability. Thus, the “whole self” movement creates an interesting conundrum: on one hand, organizations may view social media allyship positively; on the other, it could prove detrimental to individuals if the stance taken is not aligned with the values of hiring agents who use online content to evaluate job candidates. In this presentation, Michelle Carter will discuss research that takes an identity perspective to explore hiring agents’ views on the effectiveness of social media allyship in general, and for individuals’ job prospects.

Bio
Dr. Michelle Carter is an associate professor in the Carson College of Business at Washington State University and an affiliate associate professor in the Information School at the University of Washington. Michelle’s research focuses on information technologies’ involvement in identity and social change, factors that shape IT usage behaviors, and information systems management. Her work has appeared in MIS Quarterly, the European Journal of Information Systems, the Journal of the Association for Information Systems, the Journal of Information Technology, as well as other journals, books, and conference proceedings. Michelle is an associate editor for the Journal of the Association for Information Systems (JAIS) and a senior editor of the upcoming JAIS special issue on technology and social inclusion. She is a past-president of the Association for Information Systems (AIS) Special Interest Group on Social Inclusion and previously chaired the AIS committee on diversity and inclusion. Michelle is a Distinguished Member – Cum Laude of the AIS and was recognized for her research and service contributions to the IS field as a 2016 recipient of the AIS Early Career Award. In 2021, Michelle was elected to serve on the AIS Council as Vice President for Special Interest Groups and Colleges.