About Our Authors
Martin Adam (“Agent-Based Data Curation Practices: Customer Responses to Human vs. Algorithmic Data Requesters in Established Business-to-Business Relationships”) is a professor of information systems at University of Goettingen, Germany. His interests include human-artificial intelligence collaborations and the digital transformation of work and people. His research is funded by the German Research Foundation and has been published in Information Systems Research, Journal of Management Information Systems, and other outlets. He serves in editorial roles for Information Systems Journal, Electronic Markets, and Business & Information Systems Engineering.
Amin K. Amiri (“A Theory of Strategic Information Technology Unavailability”) is a data scientist in industry. He earned his PhD in management information systems from the Sauder School of Business, University of British Columbia.
David Antons (“From Shield to Sword: How Data Privacy Can Undermine Data Security”) is professor and heads the Institute of Entrepreneurship at the University of Bonn, Germany. He held visiting positions at Judge Business School, University of Cambridge, and the Department for Computing and Information Systems, University of Melbourne. He published in Academy of Management Review, Information Systems Research, Journal of Management, Journal of Management Studies, Journal of Service Research, Journal of Product Innovation Management, and Research Policy.
V. K. Pani Baruri (“AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots”) is the managing director and chief executive officer of Algoleap, a digital and product engineering services firm. He has over 25 years of experience in banking and financial services, spanning product innovation, digital transformation, and large-scale delivery across global organizations and markets. His research interests center on artificial intelligence, particularly its governance, value creation, and organizational implications. He has completed the Executive Fellow Programme in Management (equivalent to DBA) from the Indian School of Business.
Kevin Bauer (“Knowing (Not) to Know: Explainable Artificial Intelligence and Human Metacognition”) is a professor of game-theoretic and causal artificial intelligence at Goethe University Frankfurt. He is interested in research at the intersection of technology and economics. His current research projects focus on explainable artificial intelligence and human information processing. His research has been published in journals like Management Science, Information Systems Research, Marketing Science, and Journal of the Association for Information Systems.
Izak Benbasat (“A Theory of Strategic Information Technology Unavailability”) is a professor emeritus of information systems at the Sauder School of Business, University of British Columbia. He earned his PhD in management information systems from the University of Minnesota (1974). His research focuses on human-computer interaction, intelligent decision support, and information technology adoption in organizations. He has published in premier venues, such as Information Systems Research, MIS Quarterly, and Management Science.
Alexander Benlian (“Agent-Based Data Curation Practices: Customer Responses to Human vs. Algorithmic Data Requesters in Established Business-to-Business Relationships”) is a professor of information systems at Technical University of Darmstadt. He holds a PhD from LMU Munich and previously worked at McKinsey & Company. His research explores algorithmic management, artificial intelligence (AI) literacy, and human-AI collaboration. He has published in Information Systems Research and MIS Quarterly. He serves in editorial roles for Information Systems Research and European Journal of Information Systems. His work is funded by the German Research Foundation.
Susan A. Brown (“Reference Aware Delexicalization (RAD) Framework: Theory Driven Artificial Intelligence Modeling for Domain Generalization”) is the Stevie Eller Professor at the Eller College of the University of Arizona. She completed her PhD at the University of Minnesota. Her research interests include individual motivations for and consequences of information technology use, mediated interactions, and research methods. Her work has appeared in leading journals including MIS Quarterly, Information Systems Research, and Journal of Management Information Systems. She is currently the editor-in-chief at MIS Quarterly.
Hasan Cavusoglu (“A Theory of Strategic Information Technology Unavailability”) is a professor of management information systems at the Sauder School of Business, University of British Columbia. He received his PhD in management science with a specialization in management information systems from the University of Texas at Dallas. His research centers on the economics of information systems, information security, and technology management. His work has been published in leading journals, including Information Systems, MIS Quarterly, and Management Science.
Wanliu Che (“Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction”) is a PhD student in management science and engineering at Hefei University of Technology. His research interests include theory-guided deep learning, large language model agents, and intelligent financial management. He has published in such journals as Information Processing & Management.
Jianqing Chen (“The Economics of Password Sharing”) is an Ashbel Smith Professor in Information Systems at Jindal School of Management, The University of Texas at Dallas. He received his PhD from the University of Texas at Austin. His research interests are in economic impact of artificial intelligence, platform business models, social media, and economics of information systems. His papers have been published in journals such as Management Science, Information Systems Research, MIS Quarterly, Journal of Marketing, and Journal of Marketing Research.
Xiayu Chen (“Conform or Workaround? A Multilevel Analysis of the Effect of Group Cultural Tightness on Enterprise System Use”) is an associate professor in the school of management at the Hefei University of Technology. She received her PhD in information systems from the University of Science and Technology of China and City University of HK. Her research interests include electronic commerce, social media, and system use. She has published papers in journals such as Journal of Operations Management, Information Systems Research, Information Systems Journal, Journal of Information Technology, and Decision Sciences.
Sunghun Chung (“Working Daily, Paid Monthly? Effects of On-Demand Wage Access on the Financial Engagement of Low-Wage Workers”) is an assistant professor at the George Washington University School of Business. His research investigates how digital innovations create value and how artificial intelligence (AI) can advance digital inclusion, with emphases on platform strategy and equitable, transparent AI. His work appears in Information Systems Research, MIS Quarterly, and Production and Operations Management. He employs randomized field experiments, econometrics, and machine learning. He earned his PhD from KAIST.
John D’Arcy (“Asymmetric Learning Effects of Chief Information Officer Outside Board Appointments: Cybersecurity Implications for Sender and Receiver Firms”) is a professor in the Department of Accounting and Management Information Systems at the University of Delaware’s Lerner College of Business and Economics. His research interests are in the behavioral and organizational aspects of cybersecurity. He received his PhD in management information systems from Temple University’s Fox School of Business. He currently serves as a Senior Editor at MIS Quarterly.
Alexander Everhart (“A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships”) is an instructor in the division of general medicine and geriatrics at the Washington University School of Medicine in St. Louis. As a health economist, his research uses applied econometric techniques to study the development, regulation, and adoption of safe and effective medical technologies.
Yangyang Fan (“Learning from Earnings Calls: Graph-Based Conversational Modeling for Financial Prediction”, “Forget Me If You Can: Auditing User Data Revocation in Recommendation Systems”) is an associate professor in the school of accounting and finance at Hong Kong Polytechnic University. She received her PhD in accounting from University of Pittsburgh in 2016. Her research interests are financial accounting and financial technology. Her work has been published in journals such as Contemporary Accounting Research, Information Systems Research, and MIS Quarterly.
Yulin Fang (“Contribute to MY IT Service: Encouraging Technology Extra-Role Behaviors in User-Artifact Interactions from a Psychological Ownership Perspective”) is a professor and director of the Institute of Digital Economy and Innovation at HKU Business School. His research interests include digital innovation, digital entrepreneurship, digital transformation, platform ecosystems, and e-commerce. He has served as a senior editor of Information Systems Research, Information Systems Journal, and Journal of Information Technology, and as an associate editor of MIS Quarterly. He is the co-editor-in-chief of Information Technology & People.
Yi Gao (“More Can Be Less: The Economics of Answer Viewing on Paid Q&A Platforms”) is an assistant professor at the Rawls College of Business, Texas Tech University. She earned her PhD from Tsinghua University in 2023. Her research examines the economics of information systems, with a focus on crowd-based platforms, the economics of artificial intelligence, and data privacy. Her work has been published in leading journals, including Information Systems Research and MIS Quarterly, and she serves as an ad hoc reviewer for several top-tier journals.
Yegin Genc (“The Differential Diffusion of Exchange and Utility Value Blockchain Tokens”) is an associate professor of information systems at Pace University. His research focuses on data-driven digital technologies and analytics, including blockchain diffusion and human–artificial intelligence decision making. He uses computational approaches, including machine learning, natural language processing, and network analysis to make sense of large-scale digital trace data. His work appears in Information Systems Research and related journals.
Debashish Ghose (“How to Tell a (News) Story? Quantifying the Impact of News Format and Storytelling on Engagement”) is assistant teaching professor of marketing at the D’Amore-McKim School of Business, Northeastern University, and technical lead at the DMSB AI Strategic Hub (DASH). His research examines AI-human collaboration, misinformation processing, advertising, and choice architecture. He holds a PhD in marketing from Temple University, an MS in economics and management of innovation and technology from Bocconi University, an MSc in management of innovation from Erasmus University, and a BTech from NIT Kurukshetra.
Alexander Gladis (“From Shield to Sword: How Data Privacy Can Undermine Data Security”) is a doctoral student at the Institute for Technology and Innovation Management at RWTH Aachen University. He holds BS and MS degrees in electrical engineering, information technology, and computer engineering. As an avid ethical hacker, his research interests are located at the intersection between the technological, managerial, and psychological sides of cybersecurity and data protection. His dissertation focuses on unforeseen ramifications of the European GDPR.
Varun Grover (“A Theory of Strategic Information Technology Unavailability”) is a distinguished professor and the George & Boyce Billingsley Endowed Chair in Information Systems at the Walton College of Business, University of Arkansas. He received his PhD in management information systems from the University of Pittsburgh. His research examines how digitalization shapes organizations and individuals. He has published in leading journals, such as Information Systems Research, MIS Quarterly, and Journal of MIS.
Zhiling Guo (“Analyzing Consumer Footprints on E-Commerce Platforms: A Multichannel Sequential Search Model with Reference Price”) is the G. Brint Ryan Professor in the department of information technology and decision sciences at the University of North Texas. She received her PhD from the University of Texas at Austin. Her work appears in Management Science, MIS Quarterly, and Information Systems Research, among others. She has served as associate editor for MIS Quarterly and currently serves as associate editor for INFORMS Journal on Computing and senior editor for Production and Operations Management.
Dominik Gutt (“NFT Disruption in Platform Competition: Evidence from Trading Card Collectibles”) is a chaired professor at the School of Business and Economics, RWTH Aachen University, and he obtained his PhD from Paderborn University in 2019. His research focuses on user-generated content, web3, and artificial intelligence. He received the AIS Early Career Award in 2024 and the Reviewer of the Year Award 2023 from MIS Quarterly. His work is published in leading journals, such as Information Systems Research and MIS Quarterly.
Nicole Hartwich (“From Shield to Sword: How Data Privacy Can Undermine Data Security”) is affiliated with RWTH Aachen University where she was assistant professor and head of the Digital Responsibility and Innovation Lab. She holds a PhD from RWTH Aachen University. Her research focuses on organizational communication, digital and technological innovation, and artificial intelligence transformation. Her work has received international awards at leading conferences.
Taha Havakhor (“Disclosure of Cybersecurity Investments and the Cost of Capital”) is an associate professor of information systems and a Desautels scholar at Desautels Faculty of Management, McGill University. His research focuses on combining advanced computational and econometrics approaches to address problems at the intersections of science, technology, and economics. His work was published or is accepted in premier outlets such as Management Science, MIS Quarterly, Information Systems Research, Production and Operations Management, and Journal of Marketing.
Jinghai He (“Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery”) is a PhD student in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. He earned his bachelor’s degrees in finance and computer science from Shanghai Jiao Tong University in 2022.
Oliver Hinz (“Knowing (Not) to Know: Explainable Artificial Intelligence and Human Metacognition”) is a professor of information systems and information management at Goethe University Frankfurt. He is interested in research at the intersection of technology and markets. His research has been published in journals like Management Science, Information Systems Research, MIS Quarterly, Journal of Marketing, Marketing Science, Journal of Management Information Systems, and Business & Information Systems Engineering as well as in a number of proceedings.
Yili Hong (“Asymmetric Learning Effects of Chief Information Officer Outside Board Appointments: Cybersecurity Implications for Sender and Receiver Firms”, “Workflow Automation in Open-Source Software Development: Accelerating Innovation Through Mechanization and Orchestration”) is a professor of business technology and Miami Herbert Centennial Endowed Chair at the Miami Herbert Business School, University of Miami. His research focuses on the future of work, digital platforms, digital media, and human– artificial intelligence interactions. He has published in Management Science, Information Systems Research, Management Information Systems Quarterly, Production and Operations Management, and the INFORMS Journal on Computing.
Cheng Hua (“Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery”) is an associate professor in the Department of Management Science at Antai College, Shanghai Jiao Tong University. He joined Antai College as an assistant professor in 2020 and has served as an associate professor since 2023. He earned his PhD in operations research from Yale School of Management in 2020 after receiving bachelor’s degrees from Shanghai Jiao Tong University and the University of Michigan–Ann Arbor.
Ao Huang (“Workflow Automation in Open-Source Software Development: Accelerating Innovation Through Mechanization and Orchestration”) is a PhD candidate at the Business Technology Department, Miami Herbert Business School, University of Miami. His research focuses on artificial intelligence, workflow automation, open-source software development, and live streaming. He has published in Management Science and Information Systems Research.
Ni Huang (“Workflow Automation in Open-Source Software Development: Accelerating Innovation Through Mechanization and Orchestration”) is the Dennis and Smith Family Endowed Chair Professor of Business Technology at the Miami Herbert Business School, University of Miami. Her research focuses on understanding how digital technology can enhance user experiences and improve business outcomes. She has published in Management Science, Information Systems Research, MIS Quarterly, and Production and Operations Management.
Jeffrey L. Jenkins (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) is a scholar, entrepreneur, and tech innovator. He has consistently published in the top information systems journals and has been ranked in the top 50 for research productivity in these journals over the last decade. Selected honors received include the AIS Impact Award, the AIS Distinguished Member: Cum Laude Distinction, and the AIS Early Career Award.
Ashish Kumar Jha (“Where the Ball Starts Rolling? An Empirical Investigation into Initial Opinion Formation on Social Media Platforms”) is a professor of business analytics at Trinity Business School, Trinity College Dublin. He is the director of Trinity Centre for Digital Business and Analytics. He earned his doctorate in management of information systems from the Indian Institute of Management Calcutta. He researches how firms and users interact and exchange information on digital platforms using experiments and secondary data analysis.
Baojun Jiang (“Content Exclusivity on Advertising Revenue–Sharing Platforms”) is a professor of marketing at Washington University in St. Louis. His research interests include the sharing economy, competitive strategy, behavioral economics, platforms, and the marketing–operations interface. His work has been published in leading journals such as Management Science, Marketing Science, Journal of Marketing Research, Information Systems Research, Manufacturing and Service Operations Management, Operations Research, and Production and Operations Management.
Cuiqing Jiang (“Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction”) is a professor at the School of Management, Hefei University of Technology. He received his PhD in management science and engineering from that university. His research interests include artificial intelligence and predictive analytics, intelligent credit risk evaluation, and intelligent financial management. He has published in such journals as MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of the Association for Information Systems, and many others.
Ekaterina Jussupow (“Knowing (Not) to Know: Explainable Artificial Intelligence and Human Metacognition”) is an associate professor of information systems at Technical University of Darmstadt. Her research is at the intersection of technology and psychology, focusing on human decision making in collaboration with artificial intelligence, especially in medical decision making. Her research has been published in journals such as Information Systems Research, MIS Quarterly, and Business & Information Systems Engineering as well as in a number of proceedings.
Ioannis Filippos Kanellopoulos (“NFT Disruption in Platform Competition: Evidence from Trading Card Collectibles”) is an assistant professor at the Tilburg School of Economics and Management, Tilburg University. He obtained his PhD from the Rotterdam School of Management, Erasmus University, in 2024. His research focuses on digital platforms, blockchain economics, and online creator communities. His work has been nominated for the Best Student Paper Award at the Workshop on Information Systems and Economics (WISE) 2022 and the Best Paper Award at the International Conference on Information Systems (ICIS) 2023.
Pinar Karaca-Mandic (“A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships”) is a Distinguished McKnight University Professor and the C. Arthur Williams Jr. Professor in Healthcare Risk Management at the University of Minnesota’s Carlson School of Management. She founded the Business Advancement Center for Health and is a research associate at the National Bureau of Economic Research. Her work examines healthcare markets, technology diffusion, and health equity. She cofounded XanthosHealth and earned her PhD in economics from the University of California, Berkeley.
Prasanna P. Karhade (“AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots”) (PhD, University of Illinois Urbana-Champaign) teaches at the CUHK Business School. His research focusses on artificial intelligence governance and entrepreneurship. Prasanna pioneered using the induction of decision trees for theory building in MIS research with his 2015 MIS Quarterly paper from his dissertation. His 2020 Journal of Management Information Systems paper further integrated induction of trees with abduction for theory building. This Information Systems Research paper integrates induction of trees with the hermeneutic approach for theory building.
Abhishek Kathuria (“AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots”) (PhD, Emory University) is a professor of information systems and analytics at Deakin Business School, Australia. He previously served as faculty at the Indian School of Business and The University of Hong Kong Business School. His research explores the antecedents and business value of digital & information technology. His work has appeared in journals including MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of the AIS, and Production and Operations Management.
David Kim (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) is an assistant professor of information systems & supply chain management at Texas Christian University’s Neeley School of Business. His research focuses on cybersecurity, predictive modeling, and decision science, leveraging human–computer interaction trace data to understand cognitive processes during decision making. He earned his PhD in management information systems from the University of Arizona.
Jihye Kim (“Working Daily, Paid Monthly? Effects of On-Demand Wage Access on the Financial Engagement of Low-Wage Workers”) earned a PhD in management engineering (information systems (IS)) from Korea Advanced Institute of Science and Technology (KAIST). Her research interests include the economics of information systems, IS and operational efficiency, societal impacts of IS, and algorithmic bias. She employs causal inference (e.g., quasi-experimental methods, causal machine learning), applied machine learning, and natural language processing.
Benjamin Knight (“Human-Algorithm Collaboration in Gig Work: The Role of Experience, Skill Level, and Task Complexity”) is a staff data scientist at Instacart.
Benn R. Konsynski (“AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots”) is the George S. Craft Distinguished University Professor of Information Systems and Operations Management at Goizueta Business School, Emory University. He held faculty positions at University of Arizona and Harvard Business School and served as adviser and board member on public and private corporations. He was named Baxter Research Fellow at Harvard and Hewlett Fellow at The Carter Center. He has numerous publications and holds a PhD in computer science from Purdue University.
Manasvi Kumar (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) is a visiting assistant professor of supply chain and information management at Northeastern University. His research primarily focuses on identifying and mitigating the effects of respondent-induced measurement errors in online surveys through fine-grained human-computer interaction data. Prior to joining Northeastern, Manasvi received his PhD in management information systems from the University of Arizona.
Subodha Kumar (“How to Tell a (News) Story? Quantifying the Impact of News Format and Storytelling on Engagement”, “To Collect or to Purchase? Collaboration Between Manufacturer and E-Commerce Platform on Customization”) is the Paul R. Anderson Distinguished Chair Professor of Statistics, Operations, andData Science and the founding director of the Center for Business Analytics and Disruptive Technologies at Temple University’s Fox School of Business. He is the deputy editor of Production and Operations Management and the founding executive editor of Management and Business Review. He has published more than 280 papers in reputed journals and refereed conferences. He holds a robotics patent and is routinely cited in the media.
Harris Kyriakou (“The Differential Diffusion of Exchange and Utility Value Blockchain Tokens”) is an associate professor at ESSEC Business School. His research provides insights into how organizations can create value beyond their typical boundaries and strategic endeavors. He currently focuses on how artificial and collective intelligence enhances product development processes. He is a recipient of the AIS Early Career Award, was named among the Best 40 Under 40 MBA professors from Poets & Quants, and received awards from the Case Centre for his teaching content.
Jong Youl Lee (“To Claim or Not To Claim? Hidden Costs of Business Page Claiming”) is an assistant professor of information systems and business analytics at the College of Business, Florida International University. He earned his PhD in computers and information systems from the Simon Business School at the University of Rochester. His research examines the economic and behavioral implications of information technology, with a particular focus on platform strategy and healthcare.
Stephanie Lee (“The Effects of the FTC Policy and Affiliation Disclosures on Product Review Video Engagement: Evidence from YouTube”) is an assistant professor of information systems at the Foster School of Business, University of Washington. She received her PhD in economics from Stanford University. Her research examines the economic and social consequences of information technologies. Her work has been published in journals including Management Science, Information Systems Research, Journal of Marketing, Journal of Marketing Research, and Production and Operations Management.
Yan Leng (“SUVA: A Probabilistic Framework for Auditing LLMs with an Application to Social Preferences”) is an assistant professor at the McCombs School of Business, The University of Texas at Austin, and courtesy faculty in computer science and the School of Information. She studies behavior in networks and large language models using behavioral economics, and develops interpretable machine learning methods for social and digital systems. She holds a PhD from the Massachusetts Institute of Technology.
Ting Li (“NFT Disruption in Platform Competition: Evidence from Trading Card Collectibles”) is a professor of digital business at Rotterdam School of Management and a founding member of the Erasmus Centre for Data Analytics. Her research focuses on the strategic use of information and its economic impacts on consumer behavior and firm strategy. Her work has been published in leading journals such as Management Science, MIS Quarterly, and Information Systems Research. She was recognized by Poets & Quants as a Top Under 40 Professor.
Defu Lian (“Forget Me If You Can: Auditing User Data Revocation in Recommendation Systems”) is a professor at the School of Computer Science and Technology, University of Science and Technology of China, Hefei, China. His research interest includes spatial data mining and recommender systems. He has published in referred journals and conference proceedings, such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transaction on Knowledge and Data Engineering and ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Lena Liebich (“Knowing (Not) to Know: Explainable Artificial Intelligence and Human Metacognition”) is a junior researcher at the Leibniz Institute for Financial Research SAFE and a PhD candidate in economics at Goethe University Frankfurt. Her research investigates how information technologies, particularly artificial intelligence, reshape the way that humans make decisions, collaborate, and organize work.
Kai H. Lim (“Contribute to MY IT Service: Encouraging Technology Extra-Role Behaviors in User-Artifact Interactions from a Psychological Ownership Perspective”) is the Yeung Kin Man Chair Professor of Information Technology Innovation and Management at Hong Kong Polytechnic University. He served as a senior editor of MIS Quarterly (two terms) and was on editorial boards of ISR, MIS Quarterly, and JAIS. His research has widely appeared in MIS Quarterly, ISR, JMIS, and JAIS. He has won numerous teaching and research awards. He is also an honorary professor of Fudan University and an AIS Fellow.
Dengpan Liu (“More Can Be Less: The Economics of Answer Viewing on Paid Q&A Platforms”) is a professor in the Department of Management Science and Engineering, School of Economics and Management, Tsinghua University. His research focuses on the economics of information systems, particularly digital platforms and e-commerce. His work has been published in leading journals, including Management Science, Information Systems Research, and MIS Quarterly, and he currently serves as a senior editor for Production and Operations Management.
Junming Liu (“Analyzing Consumer Footprints on E-Commerce Platforms: A Multichannel Sequential Search Model with Reference Price”) is an associate professor in the department of information systems at the City University of Hong Kong. He received his PhD from the Rutgers Business School at Rutgers University. His general areas of research are data mining, supply chain analytics, and large-scale optimization. He has published prolifically in top venues of data mining and information systems, including MIS Quarterly, Information Systems Research, Production and Operations Management, and INFORMS Journal on Computing.
Yezheng Liu (“Conform or Workaround? A Multilevel Analysis of the Effect of Group Cultural Tightness on Enterprise System Use”) is a professor in the School of Management at the Hefei University of Technology. His research focuses on the electronic commerce and business intelligence. He has published papers in journals such as Marketing Science, IEEE Transactions on Knowledge and Data Engineering, Decision Support Systems, European Journal of Operational Research, International Journal of Production Research, and International Journal of Production Economics.
Tian Lu (“A User Purchase Motivation-Aware Product Recommender System”) is an assistant professor in the Department of Information Systems, W. P. Carey School of Business, Arizona State University. His research examines dynamic interactions between humans, algorithms, and information technology, with a focus on adaptive decision making and human–artificial intelligence collaboration. His work has been published in leading journals such as Information Systems Research, MIS Quarterly, and Management Science. He has received multiple best paper awards at premier information systems conferences.
Mikhail Lysyakov (“To Claim or Not To Claim? Hidden Costs of Business Page Claiming”) is an assistant professor of information systems and technology at Simon Business School, University of Rochester. He earned his PhD in information systems from the University of Maryland. His research explores user behavior and platform strategy in digital environments, with a focus on integrating deep learning and econometric methods. His work examines social media and crowdsourcing platforms and investigates how artificial intelligence technologies shape user interactions.
Ojaswi Malik (“AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots”) is a doctoral student in strategic management at the Foster School of Business, University of Washington. She has a background in international business and information systems. She uses multiple methodologies in her research, including econometric techniques, machine learning, and configurational methods. Her current research interests focus on how entrepreneurs mobilize external resources to scale their businesses.
Likoebe Mohau Maruping (“The Differential Diffusion of Exchange and Utility Value Blockchain Tokens”) is a professor of computer information systems and a member of the Center for Digital Innovation at the J. Mack Robinson College of Business at Georgia State University. His research is primarily focused on innovation in start-ups and small- and large-scale collectives such as teams, communities, and crowds. He focuses on how digital technology, governance, and collaboration are implicated in innovation at different levels of analysis.
Amit Mehra (“More Can Be Less: The Economics of Answer Viewing on Paid Q&A Platforms”) is a professor at the University of Texas at Dallas. He serves as an associate editor at Management Science and a senior editor at Production and Operations Management. His research explores how technology shapes consumer and firm behavior on digital platforms, retailing, future of work, and economics of artificial intelligence. His work has appeared in leading journals including Management Science, Information Systems Research, MIS Quarterly, and Production and Operations Management.
Syam Menon (“Bargaining over Data and Analytics: Sellers, Buyers and Consultants”) is a professor of information systems at the University of Texas at Dallas. He received his PhD from the University of Chicago. His current interests include crowdsourcing, data sharing, privacy, and recommendation system design. His contributions have appeared in Management Science, Information Systems Research, MIS Quarterly, Operations Research, the INFORMS Journal on Computing, Production and Operations Management, and many other outlets.
Abhay Nath Mishra (“Agent-Based Data Curation Practices: Customer Responses to Human vs. Algorithmic Data Requesters in Established Business-to-Business Relationships”) is a professor and Kingland Systems Faculty Fellow at the Ivy College of Business at Iowa State University. His research has been published in Information Systems Research, Management Science, MIS Quarterly, Production and Operations Management, Journal of Operations Management, Journal of the American Medical Informatics Association, and others. He is an associate editor at Information Systems Research and has served as an associate editor at MIS Quarterly.
Dmitry Mitrofanov (“Human-Algorithm Collaboration in Gig Work: The Role of Experience, Skill Level, and Task Complexity”) is an assistant professor of business analytics at Carroll School of Management, Boston College.
Vijay Mookerjee (“Bargaining over Data and Analytics: Sellers, Buyers and Consultants”) is a professor of information systems at the School of Management, University of Texas at Dallas. He holds a PhD in management, with a major in management information systems, from Purdue University. His current research interests include optimal software development methodologies, storage and cache management, and the economic design of expert systems and machine learning systems. He has published in and has articles forthcoming in several Information Systems and Operations Research journals.
Susan Mudambi (“How to Tell a (News) Story? Quantifying the Impact of News Format and Storytelling on Engagement”) is professor emeritus of marketing at Temple University’s Fox School of Business, where she also held a secondary appointment in management information systems. Her research focuses on marketing strategy, technology in marketing, international business, and customer-supplier relationships. She holds a PhD in marketing from the University of Warwick, an MS from Cornell University, and a BA from Miami University.
Serguei Netessine (“Human-Algorithm Collaboration in Gig Work: The Role of Experience, Skill Level, and Task Complexity”) is senior vice dean for Innovation and Global Initiatives and Dhirubhai Ambani Professor of Innovation and Entrepreneurship at the Wharton School, University of Pennsylvania.
Wonseok Oh (“Working Daily, Paid Monthly? Effects of On-Demand Wage Access on the Financial Engagement of Low-Wage Workers”) is the K.C.B. Chair Professor of Information Systems at KAIST College of Business. He earned his PhD from NYU Stern. His research focuses on economics of information systems, artificial intelligence strategy, digital platforms, and marketing, with publications in premier journals such as Information Systems Research, MIS Quarterly, Management Science, and Journal of Marketing Research. He currently serves as senior editor of Information Systems Research and associate editor of Management Science.
Jun Pei (“To Collect or to Purchase? Collaboration Between Manufacturer and E-Commerce Platform on Customization”) serves as a professor with the School of Management, Hefei University of Technology, Hefei. He has published in Management Science, Production and Operations Management, INFORMS Journal on Computing, and Decision Sciences. He serves as editor-in-chief for Energy Systems, review board member for Production and Operations Management, associate editor for Decision Sciences, Journal of Global Optimization, and Optimization Letters, and lead guest editor for Annals of Operations Research.
Saša Pekeč (“Beyond Truthful Reporting: Robust Strategies for Worst-Case Payoff Maximization in Large Markets”) is the Peterjohn-Richards distinguished professor at the Fuqua School of Business, Duke University. His research focuses on market design, combining microeconomics, data analytics, and algorithmic methods to improve competition, coordination, and market-clearing in large platforms and complex market systems.
Venu Puthineedi (“Where the Ball Starts Rolling? An Empirical Investigation into Initial Opinion Formation on Social Media Platforms”) is an assistant professor of information systems at NEOMA Business School and earned his PhD from Trinity College Dublin. His research sits at the intersection of technology, people, and behavior, with a focus on how social media and generative artificial intelligence (AI) shape online judgment, engagement, and trust. He uses experiments and data-driven methods to generate insights for responsible platform and AI design. He teaches statistics, business analytics, and AI.
Liangfei Qiu (“Balancing Acts: Unveiling the Dynamics of Post Removal on Social Media User-Generated Content”) is the PricewaterhouseCoopers Professor and University Research Foundation Professor at Warrington College of Business, University of Florida. He received his PhD from the University of Texas at Austin. His current research focuses on social technology (social networks, social media, and prediction markets), platform technology (sharing/gig economy, e-commerce platforms, and healthcare analytics), and telecommunications technology.
Mohammad S. Rahman (“Disclosure of Cybersecurity Investments and the Cost of Capital”) is the Daniels School Chaired Professor in Management at Purdue University. He was named one of the World’s Top 40 Business School Professors Under 40 by Poets and Quants in 2017 and has been recognized with different prestigious awards, including the INFORMS ISS Practical Impacts Award and the Sandy Slaughter Early Career Award. He has served, and continues to serve, on the editorial boards of leading journals, including Management Science and Information Systems Research.
Jyotishka Ray (“Bargaining over Data and Analytics: Sellers, Buyers and Consultants”) is an assistant professor at the Department of Management Information Systems, Operations and Supply Chain, and Business Analytics at the University of Dayton. Previously, he was a faculty at Miami University and the California State University. He earned his doctorate from the University of Texas at Dallas. He has published research articles in Information Systems Research and Production and Operations Management.
Ronald E. Rice (“Conform or Workaround? A Multilevel Analysis of the Effect of Group Cultural Tightness on Enterprise System Use”) is the Arthur N. Rupe Chair in the Social Effects of Mass Communication in the Department of Communication at the University of California, Santa Barbara, and a former president of the International Communication Association. His research interests include environmental communication, public communication campaigns, information science and bibliometrics, and social networks. He has published 14 books and over 150 refereed journal articles.
Huaxia Rui (“To Claim or Not To Claim? Hidden Costs of Business Page Claiming”) is the Xerox Chair Professor and an affiliated faculty member at the Goergen Institute for Data Science and Artificial Intelligence at the University of Rochester. He is interested in artificial intelligence, economics, and social media and has published in information systems, economics, and management academic journals. His research has been covered in media, including Financial Times and The Wall Street Journal. Rui received his PhD from the University of Texas at Austin.
Torsten-Oliver Salge (“From Shield to Sword: How Data Privacy Can Undermine Data Security”) is professor and director at the Institute for Technology and Innovation Management at RWTH Aachen University. He holds a PhD from the University of Cambridge. His research interests in the field of information systems (IS) include data privacy,data sharing, IS investment, and IS payoff. He published in Academy of Management Review, Information Systems Research, Journal of Applied Psychology, Journal of Management, Journal of Marketing, Organization Science, and MIS Quarterly.
Soumya Sen (“A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships”) is an associate professor and 3M Fellow at the University of Minnesota’s Carlson School of Management, where he directs the Management Information Systems Research Center. His interdisciplinary research spans internet economics and artificial intelligence for societal impact, with publications in engineering, information systems, and healthcare journals. He earned his PhD in systems engineering from the University of Pennsylvania and completed postdoctoral research at Princeton University.
Guohou Shan (“Balancing Acts: Unveiling the Dynamics of Post Removal on Social Media User-Generated Content”) is an assistant professor at D’Amore-McKim School of Business, Northeastern University. He received his PhD from Temple University. His current research focuses on content moderation, the impact of AI on human behavior and organizational outcomes, and feedback.
Jianchao Sheng (“The Economics of Password Sharing”) is an assistant professor in the Faculty of Business for Science & Technology, School of Management, University of Science and Technology of China. He received his PhD from the University of Science and Technology of China. His research interests include digital content platforms and the economics of artificial intelligence. His work has appeared in IEEE Transactions on Engineering Management, Transportation Research Part E, and Electronic Commerce Research and Applications.
Justin Short (“Asymmetric Learning Effects of Chief Information Officer Outside Board Appointments: Cybersecurity Implications for Sender and Receiver Firms”) is an assistant professor in the Department of Accounting and Information Management and a Neel Corporate Governance Center Research Fellow at the University of Tennessee’s Haslam College of Business. His research interests are in corporate governance and financial reporting. He received his PhD in accounting from the University of Tennessee’s Haslam College of Business.
Joydeep Srivastava (“How to Tell a (News) Story? Quantifying the Impact of News Format and Storytelling on Engagement”) is the Robert L. Johnson Professor of Marketing and Chair of the Department of Marketing at the Fox School of Business, Temple University. His research examines managerial and consumer decision making, with interests in bargaining, auctions, warranties, pricing, branding, and the psychology of money. He holds a PhD in business administration from the University of Arizona and a BSc in geosciences from Presidency College, University of Calcutta.
Heshan Sun (“Contribute to MY IT Service: Encouraging Technology Extra-Role Behaviors in User-Artifact Interactions from a Psychological Ownership Perspective”) is the Richard Van Horn Professor of IT and Analytics at University of Oklahoma. His research interests include human technology/artificial intelligence interaction, business analytics, and online crowd behavior. He has published in MIS Quarterly, Information Systems Research, and Journal of the Association for Information Systems, among many others. He is a senior editor at MIS Quarterly, the Journal of the Association for Information Systems, and the AIS Transactions on HCI.
Sandeep Suntwal (“Reference Aware Delexicalization (RAD) Framework: Theory Driven Artificial Intelligence Modeling for Domain Generalization”) is an assistant professor in the College of Business at the University of Colorado. His interdisciplinary research examines information security, online misinformation, model generalizability, and theory-driven design science, bridging information systems and computational linguistics. His work appears in journals including Information and Computer Security and Sport Marketing Quarterly, as well as key natural language processing conference venues such as Empirical Methods in Natural Language Processing (EMNLP) and Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL).
Chee-Wee Tan (“Conform or Workaround? A Multilevel Analysis of the Effect of Group Cultural Tightness on Enterprise System Use”) is a professor at the Department of Management and Marketing in the Hong Kong Polytechnic University. He received his PhD in management information systems from the University of British Columbia. His research interests focus on design and innovation issues related to digital platforms. His work has been published in journals such as MIS Quarterly, Journal of Operations Management, and Information Systems Research, among others.
Yong Tan (“The Effects of the FTC Policy and Affiliation Disclosures on Product Review Video Engagement: Evidence from YouTube”) is the Michael G. Foster Endowed Professor of Information Systems at the Michael G. Foster School of Business, University of Washington, and a distinguished fellow of the INFORMS Information Systems Society. His research interests include social media and networks, sharing economy, fintech, mobile and electronic commerce, and big data analytics. He has published in Information Systems Research, Management Science, and Management Information Systems Quarterly, among others.
Yixuan Tang (“Learning from Earnings Calls: Graph-Based Conversational Modeling for Financial Prediction”) is a PhD student in the Department of Information Systems, Business Statistics and Operations Management at Hong Kong University of Science and Technology. Her research interests are natural language processing, large language models, and their application in business and finance.
Lin Tian (“Content Exclusivity on Advertising Revenue–Sharing Platforms”) is a professor of operations management at the School of Management, Fudan University. He has published more than 40 articles in peer-reviewed academic journals, including Information Systems Research, Journal of Marketing Research, Marketing Science, Management Science, Manufacturing and Service Operations Management, and Operations Research. His research interests encompass the sharing economy, platform supply chains, and the interface between operations management and marketing.
Joseph S. Valacich (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) the Muzzy Endowed Chair, stands as a prolific scholar, tech entrepreneur, and educational trailblazer. His portfolio boasts over 115 journal publications, including 37 in nine distinguished Financial Times top 50 outlets. Recognized as an AIS Fellow in 2009, he received the AIS Impact Award in 2021 and the prestigious AIS Leo Award in 2022, the field’s highest honor for lifetime achievements.
Moritz von Zahn (“Knowing (Not) to Know: Explainable Artificial Intelligence and Human Metacognition”) is a postdoctoral researcher at the Institute of Information Systems and Information Management at Goethe University Frankfurt. His research studies the application, development, and impact of artificial intelligence. He has published in journals such as Information Systems Research, Business & Information Systems Engineering, and Marketing Science.
Jiaan Wang (“A User Purchase Motivation-Aware Product Recommender System”) is a research assistant in the Department of Information Management and Business Intelligence at the School of Management, Fudan University. He received his MS degree from Soochow University. His main research interests include information systems, natural language processing, and large language models. He has published more than 30 research papers in leading journals such as INFORMS Journal on Computing, as well as in top international artificial intelligence conferences.
Mingzheng Wang (“Analyzing Consumer Footprints on E-Commerce Platforms: A Multichannel Sequential Search Model with Reference Price”) is a professor in the school of management at Zhejiang University. His research directions include data-driven decision making, information systems, and operations management. He has published over 60 papers in top journals, including Operations Research, Manufacturing & Service Operations Management, Information Systems Research, INFORMS Journal on Computing, and Production and Operations Management. He received the best student paper award at ICIS 2022 and the best paper award on POMS International Conference in China 2023.
Yingfei Wang (“Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery”) is an assistant professor of information systems at the Foster School of Business at the University of Washington. She holds a PhD in computer science from Princeton University (2017) and a bachelor’s degree in computer science with a dual degree in economics from Peking University (2012).
Zhao Wang (“Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction”) is an associate professor at the School of Management, Hefei University of Technology. He received his PhD in management science and engineering from that university. His research interests include data mining, predictive analytics, and FinTech. He has published in such journals as MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Decision Support Systems, European Journal of Operational Research, and many others.
Hang Wei (“Content Exclusivity on Advertising Revenue–Sharing Platforms”) is currently a professor of operations management at Shanghai University of Finance and Economics. He has published more than 50 articles in peer-reviewed journals, including Information Systems Research, Production and Operations Management, and Naval Research Logistics. His research interests span internet and operations management, the interface between operations management and finance, and service operations management.
Shaobo Wei (“Conform or Workaround? A Multilevel Analysis of the Effect of Group Cultural Tightness on Enterprise System Use”) is a professor in the school of management at the Hefei University of Technology. He obtained his PhD in information systems from the University of Science and Technology of China and City University of Hong Kong. His research focuses on human–artificial intelligence integration, enterprise systems use, and online communities. He has published papers in journals such as Information Systems Research, Journal of Operations Management, Journal of Business Ethics, Decision Sciences, and Journal of Information Technology.
Yuansheng Wei (“Content Exclusivity on Advertising Revenue–Sharing Platforms”) received his PhD in marketing from Fudan University, Shanghai, China, in 2020. He is currently an assistant professor of operations management at Shanghai University of Finance and Economics. His research focuses on developing analytical models to assess firms’ operational strategies within the platform economy. His work has been published in leading journals such as Information Systems Research, International Journal of Research in Marketing, and Marketing Letters.
Paul Weisgarber (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) is a PhD student in management information systems at the University of Arizona’s Eller College of Management. His research interests include human-computer interaction, digital behavioral biometrics, and deception detection. Paul’s current research focuses on identifying response distortion behaviors in self-report questionnaires. He holds a BS degree from the U.S. Air Force Academy and an MBA from the University of Notre Dame’s Mendoza College of Business.
David W. Wilson (“Are You, You? Seamlessly Fighting Identity Fraud with Keystroke Dynamics”) is an assistant professor of information systems at Brigham Young University. Previously, he was Director of Data Science at Neuro-ID, a behavioral analytics firm focused on fraud and customer experience. His research examines digital behavior, cybersecurity, and human–computer interaction, and has appeared in MIS Quarterly, Information Systems Research, and the European Journal of Information Systems.
Chenxi Xu (“Beyond Truthful Reporting: Robust Strategies for Worst-Case Payoff Maximization in Large Markets”) is a PhD candidate at the Fuqua School of Business, Duke University. His research interests include using optimization methods to address mechanism design problems.
Jiarong Xu (“A User Purchase Motivation-Aware Product Recommender System”) is an assistant professor at the school of management, Fudan University. Her main research interests include data mining and applied machine learning, with a focus on modeling emerging problems and developing novel algorithms for real-world applications. She has published over 40 research papers in leading journals such as INFORMS Journal on Computing, and in international artificial intelligence conferences. She received the AAAI Distinguished Paper Award.
Ling Xue (“The Differential Diffusion of Exchange and Utility Value Blockchain Tokens”) is a professor of management information systems (IS) at the University of Georgia. His research delves into the governance and other sociotechnical aspects within various digital contexts, such as digital platforms, open-source communities, blockchain ecosystems, artificial intelligence, green information technology (IT), and corporate IT environments. He has published in Information Systems Research and other major journals in IS and other business disciplines.
Ping Yan (“To Collect or to Purchase? Collaboration Between Manufacturer and E-Commerce Platform on Customization”) serves as a lector with the School of Management, Hefei University of Technology, Hefei. He received a PhD degree in management science and engineering from Hefei University of Technology, Hefei, China, in 2024. He has published papers on Management Science, Production and Operations Management, and Annals of Operations Research. His research interests include business analytics, platform operations, and supply chain management.
Yi Yang (“Learning from Earnings Calls: Graph-Based Conversational Modeling for Financial Prediction”, “Forget Me If You Can: Auditing User Data Revocation in Recommendation Systems”) is an associate professor in the Department of Information Systems, Business Statistics and Operations Management at Hong Kong University of Science and Technology. He received his PhD in computer science from Northwestern University in 2015. His research designs machine learning methods to solve challenging business and fintech problems. His work has been published in journals such as Information Systems Research, MIS Quarterly, Journal of Marketing, and INFORMS Journal on Computing.
Seokchae Yoon (“Working Daily, Paid Monthly? Effects of On-Demand Wage Access on the Financial Engagement of Low-Wage Workers”) is a PhD student in management engineering (information systems (IS)) at KAIST. His research examines how information systems across diverse modalities impact people’s lives, with a focus on healthcare applications. He employs probabilistic models, predictive models, and econometrics.
Yuan Yuan (“SUVA: A Probabilistic Framework for Auditing LLMs with an Application to Social Preferences”) is an assistant professor of business analytics at the UC Davis Graduate School of Management. His research uses big data, machine learning, and causal inference to study social and organizational networks and to develop methods for online field experiments (A/B testing). He received his PhD degree from the Massachusetts Institute of Technology.
Hao Zhang (“Analyzing Consumer Footprints on E-Commerce Platforms: A Multichannel Sequential Search Model with Reference Price”) is an associate professor in the college of management and economics at Tianjin University. He received his PhD from Zhejiang University and Singapore Management University. His research focuses on applying the econometric method to analyze consumer behaviors and adopting the design science paradigm to optimize platform decision making. His work has been accepted by Information Systems Research and he received the best student paper award at the International Conference on Information Systems (ICIS) 2022.
Hongzhe Zhang (“A User Purchase Motivation-Aware Product Recommender System”) is an assistant professor in information systems at the Chinese University of Hong Kong, Shenzhen. He received a PhD in financial services analytics from the Lerner College of Business and Economics, University of Delaware. His research focuses on solving important problems in financial technology, privacy-preserving artificial intelligence, and recommender systems by designing novel machine learning methods. His work has been published in leading journals such as Information Systems Research and MIS Quarterly.
Jingwen Zhang (“The Effects of the FTC Policy and Affiliation Disclosures on Product Review Video Engagement: Evidence from YouTube”) is an assistant professor of business administration at the Gies College of Business, University of Illinois at Urbana-Champaign. She received her PhD in business administration from the University of Washington. Her research interests lie at the intersection of causal inference, machine learning, and digital platforms. Her research methodologies encompass machine learning, econometrics, structural modeling, and controlled experiments.
Kunpeng Zhang (“Learning from Earnings Calls: Graph-Based Conversational Modeling for Financial Prediction”) is an associate professor in the Department of Information Systems at the University of Maryland, College Park. He received his PhD in computer science from Northwestern University in 2013. His research focuses on developing machine learning methods to analyze unstructured data for informed business decisions. His work has been published in journals such as Information Systems Research, MIS Quarterly, Journal of Marketing, INFORMS Journal on Computing, and IEEE TKDE.
Tianjian Zhang (“Disclosure of Cybersecurity Investments and the Cost of Capital”) is an assistant professor of information systems at California State University, Dominguez Hills. He is interested in the economics of cybersecurity, financial technologies, and technology diffusion.
Huimin Zhao (“Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction”) is a professor of information technology management at the Lubar College of Business, University of Wisconsin-Milwaukee. He received his PhD in management information systems from The University of Arizona. He has served as a senior editor for Decision Support Systems and an associate editor for Information Systems Research, MIS Quarterly, and Journal of Business Analytics.
Zeyu Zheng (“Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery”) has been an associate professor at the University of California, Berkeley, in the Department of Industrial Engineering and Operations Research since 2024. His research mainly focuses on stochastic models. He joined Berkeley as an assistant professor in 2018. He received a PhD in management science and engineering (2018), PhD minor in statistics (2018), and MA in economics (2016) from Stanford University and a BS in mathematics (2012) from Peking University.
Yi Zhu (“A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships”) is a tenure-track assistant professor in the Department of Information Systems and Business Analytics at Ambassador Crawford College of Business and Entrepreneurship, Kent State University. He earned his PhD in information and decision sciences from the Carlson School of Management, University of Minnesota. His research interests lie in health information technology, artificial intelligence, design science, network science and economics, and influencer economy.
Zhihao Zhu (“Forget Me If You Can: Auditing User Data Revocation in Recommendation Systems”) is a postdoctoral fellow in the Department of Information Systems, Business Statistics and Operations Management at Hong Kong University of Science and Technology. He received his PhD in computer science from the University of Science and Technology of China in June 2025. His research focuses on machine learning privacy, with publications in top-tier computer science venues including International Conference on Learning Representations, ACM Web Conference, and Conference on Empirical Methods in Natural Language Processing.
Haiyun (Melody) Zou (“Contribute to MY IT Service: Encouraging Technology Extra-Role Behaviors in User-Artifact Interactions from a Psychological Ownership Perspective”) is an associate professor at Warwick Business School. Her research interests include adoption and use of information technology, human behavior and information systems, and human-computer interaction. Her research has appeared in Information Systems Research, Journal of the Association for Information Systems, and Information Systems Journal. She is a recipient of the AIS Early Career Award. She has been a track cochair for ECIS 2025 and 2026 and a minitrack cochair for AMCIS 2026.
