About Our Authors
Martin Adam (“Team-Enacted Use vs. Developer-Needed Use of Agile Practices: How Perceptual (In-)Congruence and Team Feedback-Seeking Shape Developer Well-Being”) is a chaired professor of information systems at the University of Goettingen. His research interests include human-artificial intelligence collaboration as well as the digital transformation of work and people. He has published in Information Systems Research, Journal of the AIS, Information Systems Journal, and European Journal of Information Systems. He serves as an associate editor at Information Systems Journal, Business & Information Systems Engineering, and Electronic Markets.
Abayomi Baiyere (“Beyond Digital vs. IT: The Untold Story of Their Relationship from an Organizing Logic Perspective”) is an associate professor at the Smith Business School, Queen’s University. He serves as an associate editor and guest senior editor and has led several special interest groups. His research sits at the intersection of digital transformation, digital disruption, and the societal impact of digitalization. Some of his research has been accepted by leading journals and conferences, and some have been recognized with best paper awards/nominations.
Alexander Benlian (“Team-Enacted Use vs. Developer-Needed Use of Agile Practices: How Perceptual (In-)Congruence and Team Feedback-Seeking Shape Developer Well-Being”) is a chaired professor of information systems at Technical University of Darmstadt. He earned his PhD from Ludwig Maximilian University Munich before working at McKinsey & Company. His research explores digital transformation, algorithmic management, and human-artificial intelligence 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.
Brian Birkhead (“Algorithms to the Rescue: Market Mechanisms for Consensual Trading of Unbiased Individual Data”) is the managing director of Coniak Limited, an award-winning UK data science and strategic marketing consultancy. He is a former academic in mathematics and statistics at Warwick University and University College London, where he was deputy director of the Clinical Operational Research Unit. He has more than 20 years of experience as a strategic marketing and analytics consultant specializing in the retail and financial services sectors, majoring in loyalty and customer relationship marketing.
Erik Brynjolfsson (“Gains from Product Variety: Evidence from a Large Digital Platform”) is a professor at Stanford University, the director of the Stanford Digital Economy Lab, a senior fellow at the Stanford Institute for Human-Centered AI and the Stanford Institute for Economic Policy Research, and a research associate at the National Bureau of Economic Research. His research examines the impact of digital technologies on the economy.
Gang Chen (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) is an assistant professor of information management and business intelligence at the School of Management, Fudan University. His research interests include structured reasoning of large language models, theory-driven deep learning, and multimodal business intelligence. His work has been published in MIS Quarterly, Information Systems Research, Decision Support Systems, Pattern Recognition, Information Processing & Management, and Electronic Commerce Research and Applications, among others.
Guoqing Chen (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is a Distinguished Professor of Arts, Humanities and Social Sciences at Tsinghua University School of Economics and Management. He currently serves as vice chairman of the Tsinghua University Research Council. His research interests include business intelligence and big data analytics, e-business and decision support, information technology strategy and management, fuzzy logic, etc. His work appears in top journals such as Information Systems Research, INFORMS Journal on Computing, and Production and Operations Management.
Long Chen (“Gains from Product Variety: Evidence from a Large Digital Platform”) currently serves as the president of Luohan Academy. Previously, he was the chief strategy officer of Ant Financial Group. He earned a PhD in finance from the University of Toronto and was a tenured professor at the Olin Business School, Washington University in St. Louis. Upon returning to China in 2010, he became the associate dean of the Cheung Kong Graduate School of Business and a professor of finance.
Angela Aerry Choi (“To Split or to Merge? How Partitioning Affects Consumption and Engagement with Digital Content”) is an assistant professor of information systems in the Business School at Korea University. She received her PhD in information systems from the College of Business at the KAIST. Her research focuses on the economics of information systems, artificial intelligence-driven business, digital content, and mobile platform marketing. Her work has been published in premier journals, including Information Systems Research, MIS Quarterly, and the Journal of Operations Management.
Maxime C. Cohen (“Strategic Best-Response Fairness Framework for Fair Machine Learning”) is the Scale AI Chair Professor and the academic director of the Bensadoun School of Retail Management at McGill University. He has worked on several applications, including retail, ridesharing, sustainability, online advertising, peer-to-peer lending, real estate, and healthcare. He received his PhD in operations research from the Massachusetts Institute of Technology in 2015. His research has appeared in numerous journals, including Management Science, Information Systems Research, and Operations Research.
Ashkan Eshghi (“Algorithms to the Rescue: Market Mechanisms for Consensual Trading of Unbiased Individual Data”) is a Houlden Fellow at the Information Systems Management and Analytics Group at Warwick Business School, University of Warwick. Before joining Warwick Business School, he received his PhD in business technology management from Haskayne School of Business, University of Calgary. His primary research interests include the economics of digital privacy and information security, online market design, value of information, and the economics of artificial intelligence.
Haiyang Feng (“A Study of Ride-Hailing Platforms’ Business Models in the Presence of Surge Demand”) is a professor of information management and management science at the College of Management and Economics, Tianjin University. He received his PhD in management science from Tianjin University (2014). His current research interests include economics of information systems, platform strategy, and business analytics. His work is published in leading academic journals including MIS Quarterly, Journal of the Association for Information Systems, Decision Support Systems, among others.
Nan Feng (“A Study of Ride-Hailing Platforms’ Business Models in the Presence of Surge Demand”) is a professor of information management and management science at the College of Management and Economics, Tianjin University. He received his PhD in management science from Tianjin University (2007). His current research interests include digital platform management, industrial internet platforms, and information security. His work is published in academic journals including Information Systems Research, MIS Quarterly, Journal of the Association for Information Systems, among others.
Natasha Zhang Foutz (“Ephemeral State-Dependent Recommendation for Digital Content”) is Ramon W. Breeden, Sr. Research Associate Professor of Commerce at the University of Virginia. She studies media entertainment and marketing analytics. Her research has been published in leading marketing and information systems journals. She has received Best Paper awards at global conferences, Mallen Award for lifetime published scholarly contributions to motion picture industry studies, Best Reviewer and Best AE awards, and All-University Teaching Award.
Xijie Gao (“Gains from Product Variety: Evidence from a Large Digital Platform”) is an assistant professor of economics and data science at Nanyang Technological University (NTU), Singapore. Prior to joining NTU, he worked as an economist at Luohan Academy and served as a visiting scholar at the Chinese University of Hong Kong. He earned his PhD in economics from the London School of Economics in 2020. His research interests include the digital economy, macroeconomics, and industrial organization.
Aravinda Garimella (“When Top-Down Meets Bottom-Up: Legislative Signals and Online Crowdfunding”) is an assistant professor of business administration at the University of Illinois Urbana-Champaign. She has a PhD in information systems from the University of Washington, Seattle. Her research examines the effects of technology on access to resources and artificial intelligence-augmented decision-making. Her work informs practitioners how to design effective and equitable digital platforms and systems.
Lin Ge (“Understanding and Mitigating the Robot Disadvantage in Luxury Services: The Role of Desire for Superiority”) is an assistant professor of global business and marketing at Hong Kong Metropolitan University. She received her PhD from the Chinese University of Hong Kong.
Ram D. Gopal (“Algorithms to the Rescue: Market Mechanisms for Consensual Trading of Unbiased Individual Data”) is the Information Systems Society’s Distinguished Fellow and a professor of information systems management and analytics at Warwick Business School. He also serves as the academic director of the Gillmore Centre for Financial Technology. His research spans big data analytics, health informatics, financial technologies, information security, privacy and valuation, intellectual property rights, online market design, and business impacts of technology.
Xunhua Guo (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is a professor of information systems at the School of Economics and Management, Tsinghua University. His research takes behavioral and design science approaches to topics on management information systems, electronic commerce, social networks, and business intelligence. His work appears in top journals such as Information Systems Research, INFORMS Journal on Computing, and Production and Operations Management.
Miaozhe Han (“Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks”) is an assistant professor of information systems at the Hong Kong University of Science and Technology Business School. Her research centers around the economics of artificial intelligence and digital platforms. She has published in top-tier academic journals, including Manufacturing & Service Operations Management and Proceedings of the National Academy of Sciences. She obtained a PhD in information systems from the Chinese University of Hong Kong Business School.
Yumei He (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is an assistant professor of management science at the A. B. Freeman School of Business, Tulane University. She focuses on how emerging technologies can enhance the market efficiency of digital platforms. Her research program encompasses areas such as digital interventions, human-AI collaboration, and the commercialization of generative AI and large language models. Her work has appeared in premier journals like Information Systems Research.
Hooman Hidaji (“Algorithms to the Rescue: Market Mechanisms for Consensual Trading of Unbiased Individual Data”) is an assistant professor of business technology management at Haskayne School of Business, University of Calgary. His research interests include the economics of information systems, data privacy and protection regulation, platforms, data markets, and information and communication technology supply chains and investments. He uses a wide set of methodologies in his research, including economic modeling, game theory, and econometrics. His publications have appeared in prestigious information systems journals.
Yili Hong (“Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming”) is a professor of business technology, centennial endowed chair, and associate dean for research at the Miami Herbert Business School, University of Miami. His research interests are in the areas of digital platforms and human–artificial intelligence interactions. His research has been published in premier journals such as Management Science, Information Systems Research, MIS Quarterly, Production and Operations Management, and INFORMS Journal on Computing.
Yuheng Hu (“Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming”) is the FCOB Distinguished Associate Professor in the Fisher College of Business, The Ohio State University. He previously held positions at the University of Illinois at Chicago and IBM Research. His research lies at the intersection of machine learning, digital media, and human-artificial intelligence interaction. His work has been published in leading journals such as Information Systems and MIS Quarterly, as well as top computer science conferences.
Lihua Huang (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) is a professor of information management and business intelligence at the School of Management, Fudan University. Her research interests include business intelligence and e-commerce. Her work has been published in MIS Quarterly, Information Systems Research, and the Journal of Management Information Systems, among others.
Ni Huang (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is an associate professor of business technology at the Miami Herbert Business School, University of Miami, Florida. Her expertise centers on understanding how digital technology can enhance user experiences and improve business outcomes. Her work has been published in top journals such as Management Science, Information Systems Research, MIS Quarterly, and Production and Operations Management.
He (Michael) Jia (“Understanding and Mitigating the Robot Disadvantage in Luxury Services: The Role of Desire for Superiority”) is an associate professor of marketing at the University of Hong Kong. He received his PhD from the University of Southern California.
Wei Jiang (“Irrationality-Aware Human Machine Collaboration: Mitigating Alterfactual Irrationality in Copy Trading”) is professor of management science at Antai College of Economics and Management, Shanghai Jiao Tong University. He received his PhD in industrial engineering and engineering management from Hong Kong University of Science and Technology. His research focuses on big data and business analytics, data quality and risk management, logistics, and supply chain management. He has published more than 100 papers in premier journals and won a National Science Foundation CAREER award.
Zhengrui Jiang (“A Study of Ride-Hailing Platforms’ Business Models in the Presence of Surge Demand”) is a professor of information systems at the School of Management and Economics, The Chinese University of Hong Kong, Shenzhen. His research interests cover business intelligence, diffusion of innovations, and economics of information technology. His research has appeared in leading journals including Management Science, MIS Quarterly, and Information Systems Research.
Jan Jöhnk (“Beyond Digital vs. IT: The Untold Story of Their Relationship from an Organizing Logic Perspective”) is a product owner at the commercial insurance company HDI Global SE in Hanover, Germany, and an affiliated researcher at the FIM Research Institute for Information Management. In his research, he is especially interested in questions of digital transformation at the interface of information technology (IT) organization, IT management, and emerging technologies.
Karthik Kannan (“Strategic Best-Response Fairness Framework for Fair Machine Learning”) is the Halle Chair of Leadership and Dean of Eller College of Management, University of Arizona. His research interests include studying digital transformation, analyzing digital traces for managerial insights, and also investigating the issues related to the nature of future work. He received his PhD in information systems from Carnegie Mellon University in 2003.
Weiling Ke (“Routine and Innovative Use of Enterprise System: Intricacy of Change Management Levers, System Characteristics, and Regulatory Focus”) is a professor of information systems and management engineering at College of Business, Southern University of Science and Technology. Her research interests have primarily focused on the management of information technology–enabled innovations, such as digital transformation, digital innovations, and platform ecosystems. She has published in MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of Operations Management, and Personnel Psychology.
Warut Khern-Am-Nuai (“Strategic Best-Response Fairness Framework for Fair Machine Learning”) is an associate professor of information systems at Desautels Faculty of Management, McGill University. His research interests include platforms for online marketplaces, predictive analytics, and management information security. He received his PhD in management information systems from the Krannert School of Management, Purdue University, in 2016. His research has appeared in numerous journals, including Management Science, Information Systems Research, and MIS Quarterly.
Youngjin Kwon (“Social Media and Political Affiliation: How Expressing Hot-Button Opinions Affects Raters’ Assessments of Job Applicants”) is an assistant professor of information systems at the Carson College of Business at Washington State University. He received a PhD in management information systems from Temple University.
Heeseung Andrew Lee (“To Split or to Merge? How Partitioning Affects Consumption and Engagement with Digital Content”) is an assistant professor of information systems at the Jindal School of Management at the University of Texas at Dallas. His research interests include the economics of information systems, artificial intelligence and human collaboration, digital content consumption, and digital marketing. His research has been published in premier journals, including Information Systems Research and Journal of Marketing Research.
Beibei Li (“Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention”) is the Anna Loomis McCandless Chair and Professor of IT & Management at the H. John Heinz III College of Carnegie Mellon University. She received her PhD with distinction from NYU Stern School of Business. She has extensive experience at leveraging large-scale observational data analytics and experimental analysis with a strong focus on modeling individual user behavior across online, offline, and mobile channels for decision support.
Minqiang Li (“A Study of Ride-Hailing Platforms’ Business Models in the Presence of Surge Demand”) is a professor of information management and management science at the College of Management and Economics, Tianjin University. His major research interests cover management science and decision support, electronic commerce, data mining, business intelligence, and evolutionary computation. His papers have been published in academic journals including Management Science, MIS Quarterly, Journal of Management Information Systems, and others.
Yongjun Li (“Ephemeral State-Dependent Recommendation for Digital Content”) is an associate professor at Management School, University of Science and Technology of China. His research mainly focuses on the causal inference, data envelopment analysis methodology, and their applications.
De Liu (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is a Xian Dong Eric Jing Professor of Information and Decision Sciences at the Carlson School of Management, University of Minnesota. His general research interests lie in analyzing and designing mechanisms for digital markets and platforms. His research has appeared in outlets such as MIS Quarterly, Information Systems Research, Journal of Marketing, and Production and Operations Management.
Jin Liu (“Ephemeral State-Dependent Recommendation for Digital Content”) is an assistant professor at Beijing Jiaotong University, specializing in digital platforms and the impact of artificial intelligence (AI). She graduated with a degree in management science and engineering from the University of Science and Technology of China. Her research interests lie at the intersection of AI technologies and digital platforms, particularly exploring how AI influences consumer behavior and decision-making processes.
Jing Liu (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) is an associate professor at the School of Management Science and Engineering, Tianjin University of Finance and Economics. Her research interests include large language models, deep learning, and business intelligence. Her work has been published in IEEE Intelligent Systems, Electronic Commerce Research and Applications, and the International Conference on Information Systems, among others.
Xiao Liu (“Post-Earnings-Announcement Drift Prediction: Leveraging Postevent Investor Responses with Multitask Learning”) is an assistant professor at the Department of Information Systems at Arizona State University. She received her PhD in management information systems from the University of Arizona. Her recent work focuses on designing a scalable machine learning approach for health social media analytics, incorporating state-of-the-art deep learning methods to improve the understanding of texts, images, and videos and devising novel learning architectures to integrate human intelligence with machine intelligence for further performance improvement.
Mingfeng Lu (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) received her BS degree in information management and information systems from the School of Management at Hefei University of Technology in 2020. She is currently pursuing her doctoral degree in management science and engineering at the same institution. Her research interests include deep learning, sales forecasting, and intelligent manufacturing.
Yingda Lu (“Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming”) is an associate professor at the College of Business Administration, University of Illinois. He has a PhD in information systems. His research leverages economic theory with state-of-the art empirical methods to provide actionable policies to improve the design of social media platforms and the use of artificial intelligence. His research appears in top academic journals such as Management Science, Information Systems Research, and MIS Quarterly.
Shuang Ma (“Understanding and Mitigating the Robot Disadvantage in Luxury Services: The Role of Desire for Superiority”) is a professor of information system management at the University of International Business and Economics. She received her PhD from the University of International Business and Economics.
Tengteng Ma (“Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming”) is an assistant professor at the Muma College of Business, University of South Florida. She earned a PhD in management information systems from the University of Illinois at Chicago in 2023. Her research focuses on studying human behavior on digital platforms with large-scale data and designing interpretable artificial intelligence models for complex business problems. She also conducts empirical analyses to investigate individual decision making on digital platforms.
Kevin D. Matthews (“Social Media and Political Affiliation: How Expressing Hot-Button Opinions Affects Raters’ Assessments of Job Applicants”) (he/him) is an assistant professor of information systems at the Cameron School of Business at the University of North Carolina Wilmington. His research interests surround the intersections of personal identity, uses of technology, and organizational decisions. He has published in the Journal of Applied Psychology, European Journal of Information Systems, Journal of Information Systems Education, and Journal of Decision Systems. He earned his PhD from Clemson University.
Jiahui Mo (“Framing of Seeker-Generated Information and New Solver Participation in Open Innovation Contests: An Empirical Analysis of the Temporal Effects”) is an assistant professor of information systems in the Department of Management at the Wilbur O. and Ann Powers College of Business, Clemson University. She received her PhD from the Naveen Jindal School of Management at the University of Texas at Dallas. Her current research interests are in open innovation, crowdsourcing, online labor markets, digital platforms, and social media. Her contributions have appeared in MIS Quarterly.
Mohammad Amin Morid (“Healthcare Cost Prediction for Heterogeneous Patient Profiles Using Deep Learning Models with Administrative Claims Data”) is an assistant professor in the Department of Information Systems and Analytics at the Leavey School of Business, Santa Clara University. His research lies at the intersection of information systems and biomedical informatics, where he applies machine learning techniques to temporal patient big data. Through advanced predictive analytics, he aims to enhance healthcare decision making and improve public health outcomes.
Teagen Nabity-Grover (“Social Media and Political Affiliation: How Expressing Hot-Button Opinions Affects Raters’ Assessments of Job Applicants”) is an assistant professor at Boise State University. Her research focuses on online self-disclosure and social media. Whereas recent work focuses on the social calculus of information sharing behaviors, she’s also interested in corporate use of social media and information systems education. She enjoys baking and musical theater.
Wonseok Oh (“To Split or to Merge? How Partitioning Affects Consumption and Engagement with Digital Content”) is the K. C. B. Chair Professor in the College of Business at the Korea Advanced Institute of Science and Technology. He received his PhD in information systems from the Stern School of Business at New York University. His research interests include the economics of information systems, artificial intelligence business strategy, and digital marketing. His research has been published in premier journals, including Information Systems Research, MIS Quarterly, and Management Science.
Raymond A. Patterson (“Algorithms to the Rescue: Market Mechanisms for Consensual Trading of Unbiased Individual Data”) is a professor of business technology management at University of Calgary. His primary research interests include information systems, analytics, privacy and security, quantitative decision algorithms, and artificial intelligence and machine-learning technologies. He has published extensively in premier journals, such as Information Systems Research, Journal of Management Information Systems, MIS Quarterly, INFORMS Journal on Computing, Operations Research, Production and Operations Management, and many others.
Marc Pinski (“Team-Enacted Use vs. Developer-Needed Use of Agile Practices: How Perceptual (In-)Congruence and Team Feedback-Seeking Shape Developer Well-Being”) is a postdoctoral researcher in the field of information systems and a management consultant. He earned his PhD from the Technical University of Darmstadt before working at the Boston Consulting Group. His research focuses on human-artificial intelligence (AI) interaction and AI literacy. He has published in information systems, management, and human-computer interaction journals and conference proceedings, such as Computers in Human Behavior: Artificial Humans, Electronic Markets, CHI, and MIT Sloan Management Review.
Philip L. Roth (“Social Media and Political Affiliation: How Expressing Hot-Button Opinions Affects Raters’ Assessments of Job Applicants”) is the Trevillian Distinguished Professor of Management at Clemson University. His research interests involve employee selection/talent acquisition, political affiliation, social media in organizations, and meta-analysis. He is a fellow of the Academy of Management, American Psychological Association, and the Society for Industrial and Organizational Psychology. He earned his PhD from the University of Houston.
Hongchuan Shen (“Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks”) is an assistant professor in the Department of Accounting and Information Management, University of Macau. His research focuses on the economics of information systems, including information design on online platforms, online advertising, two-sided markets, and the social impacts of artificial intelligence. His research has appeared in top-tier academic journals, including Information Systems Research, Nature Communications, and Proceedings of the National Academy of Sciences.
Zhe Shen (“Irrationality-Aware Human Machine Collaboration: Mitigating Alterfactual Irrationality in Copy Trading”) is a PhD candidate in management science and engineering, information systems concentration, at Antai College of Economics & Management, Shanghai Jiao Tong University. Her research interests include Fintech (e.g., social trading), artificial intelligence (AI), and human-machine collaboration. She earned her bachelor’s degree from Huazhong University of Science and Technology. Her methodological expertise primarily lies in design science approaches to developing AI/machine learning models.
Olivia R. Liu Sheng (“Healthcare Cost Prediction for Heterogeneous Patient Profiles Using Deep Learning Models with Administrative Claims Data”, “Post-Earnings-Announcement Drift Prediction: Leveraging Postevent Investor Responses with Multitask Learning”) is a professor and W.P. Carey Distinguished Chair of Information Systems with the W.P. Carey School of Business, Arizona State University. She received her PhD in computers and information systems from the University of Rochester. Her research focuses on methods and applications of predictive and prescriptive analytics, some based on deep learning methods and decision modeling, to address the needs in healthcare, marketing, social media, business relationship and performance, human resource, supply chain, resilience, and risk management.
Lanfei Shi (“Ephemeral State-Dependent Recommendation for Digital Content”) is an assistant professor at the McIntire School of Commerce, University of Virginia. She earned her PhD from the Smith School of Business at the University of Maryland. Her research focuses on AI and information mechanisms in digital multisided platforms. Her work has been published in Information Systems Research and MIS Quarterly and has earned awards including the ISS Nunamaker-Chen Dissertation Runner-up Award, the INFORMS e-Business Best Paper Runner-up Award, and the ISR Best Reviewer of the Year.
Hajime Shimao (“Strategic Best-Response Fairness Framework for Fair Machine Learning”) is an assistant professor of data analytics at Pennsylvania State University, with prior affiliations at the Santa Fe Institute and McGill University. His interdisciplinary research focuses on artificial intelligence (AI) and machine learning (ML) applications in social science. Current projects explore the computational complexity of interactive AI agents, organizational structures of collaborative AI teams, and fairness and accountability in AI/ML systems. He earned his PhD in economics from Purdue University.
Kalina S. Staykova (“Beyond Digital vs. IT: The Untold Story of Their Relationship from an Organizing Logic Perspective”) is an assistant professor at the Information Systems Management and Analytics Group at Warwick Business School (WBS). Her research focuses on studying digital platforms, digital transformation, and digital entrepreneurship, particularly in the contexts of FinTech and PropTech. She collaborates closely with industry practitioners and is affiliated with the Gillmore Centre for Financial Technology and the FutureFinance.AI Research group at WBS.
Ramanath Subramanyam (“When Top-Down Meets Bottom-Up: Legislative Signals and Online Crowdfunding”) serves as a professor of business administration and William N. Scheffel Faculty Fellow at the University of Illinois Urbana-Champaign. He earned his PhD from the University of Michigan–Ross School of Business. His research interests include data-driven decision-making, software management, technology governance, and environmental sustainability. His research has been published in leading management and information systems journals.
Tianshu Sun (“To Split or to Merge? How Partitioning Affects Consumption and Engagement with Digital Content”) is the Dean’s Distinguished Chair Professor of Information Systems at Cheung Kong Graduate School of Business (CKGSB). He is also the founding director of the Center for Digital Transformation at CKGSB and the Academic Director of the CKGSB Doctor of Business Administration (DBA) Program.
Yan Sun (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is an industry collaborator who used to work for the Alibaba Group in Hangzhou, China.
Chuan-Hoo Tan (“Routine and Innovative Use of Enterprise System: Intricacy of Change Management Levers, System Characteristics, and Regulatory Focus”) is an associate professor at the National University of Singapore. His research centers on digital transformation and innovation to improve business operations and societal well-being. He has published in top journals like MIS Quarterly and Information Systems Research, where he also serves as an associate editor. He has received several awards, including the INFORMS ISS Design Science Award (2013) and the MIS Quarterly Outstanding Associate Editor Award (2016).
Jason B. Thatcher (“Social Media and Political Affiliation: How Expressing Hot-Button Opinions Affects Raters’ Assessments of Job Applicants”) holds the Tandean Rustandy Esteemed Professorship at the Leeds School of Business at the University of Colorado Boulder. He is also a professor of information systems and digital transformation at the Alliance Manchester Business School at the University of Manchester. He received degrees from the University of Utah and Florida State University. His work appears in Information Systems Research, Management Information Systems Quarterly. He is an avid fan of frog legs.
Amrit Tiwana (“Exaptation in Platforms: A Theory of Origins, Mechanisms, and Consequences”) is the Fuqua Distinguished Chair of Internet Strategy at the University of Georgia. He has served as a senior editor at MIS Quarterly and Information Systems Research and serves on the boards of Strategic Management Journal and Journal of Management Information Systems. His work has appeared in various management information systems, strategy, software engineering, finance, and marketing journals.
Gang Wang (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) is a professor at the School of Management, Hefei University of Technology. He received his PhD degree in management science and engineering from the School of Management, Fudan University. His current research interests include generative artificial intelligence, deep learning, and business analytics. His work has been published in MIS Quarterly, Decision Support Systems, IEEE Transactions, and in proceedings of the International Conference on Information Systems, Pacific Asia Conference on Information Systems, and Hawaii International Conference on System Sciences, among others.
Lingli Wang (“Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform”) is an assistant professor at the School of Information, Renmin University of China. She received her doctoral degree from the School of Economics and Management, Tsinghua University. Her primary research areas include human-artificial intelligence interaction and user behavior in information systems. She has published multiple papers in leading academic journals and conferences, including Information Systems Research and Production and Operations Management.
Wen Wang (“Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention”) is an assistant professor at the Department of Decision, Operations and Information Technologies, Smith Business School, University of Maryland, College Park. She obtained her PhD in information systems at the Heinz College of Carnegie Mellon University. Her research interests lie in using innovative and interpretable deep learning and AI algorithms to improve business decisions and social welfare.
Yonggui Wang (“Understanding and Mitigating the Robot Disadvantage in Luxury Services: The Role of Desire for Superiority”) is the president and Changjiang Chair Professor of Zhejiang Gongshang University, the director of the Institute of Intelligent Management in China, and a professor at Daosheng Business School. He received his PhD from Nankai University and the City University of Hong Kong.
Shaobo Wei (“Routine and Innovative Use of Enterprise System: Intricacy of Change Management Levers, System Characteristics, and Regulatory Focus”) is a professor in the School of Management, Hefei University of Technology. He obtained a PhD degree in information systems from 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 in Journal of Operations Management, Information Systems Research, Journal of Business Ethics, Decision Sciences, and Journal of Information Technology.
Anqi Wu (“When Top-Down Meets Bottom-Up: Legislative Signals and Online Crowdfunding”) is an assistant professor of information systems and business analytics at Florida International University. She earned her PhD in business administration, specializing in information, operations, supply chain, and analytics, from the University of Illinois Urbana-Champaign. Prior to her PhD, she worked in legal financial services. Her research focuses on regulation and public policy, with an emphasis on healthcare, education, and responsible technology.
Jing Wu (“Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks”) is an associate professor in the Department of Decisions, Operations, and Technology, Chinese University of Hong Kong. His expertise lies in global supply chains, operations-finance interface, and business intelligence. His research has been published in top-tier academic journals, including Management Science, Manufacturing & Service Operations Management, and Information Systems Research. He obtained a PhD in operations management from Booth School of Business, University of Chicago.
Ling Zhang (“A Study of Ride-Hailing Platforms’ Business Models in the Presence of Surge Demand”) is an assistant professor at the School of Management, Shijiazhuang Tiedao University. She received her PhD in management science and engineering from Tianjin University (2024). Her research interests include platform business model, the sharing economy, and business analytics.
Nila Zhang (“Framing of Seeker-Generated Information and New Solver Participation in Open Innovation Contests: An Empirical Analysis of the Temporal Effects”) is an assistant professor at Fudan University’s School of Management whose research interests focus on digital innovation. With expertise in econometrical modeling and computational methods, including text mining and deep learning, her work examines digital product development, online labor markets, and digital entrepreneurship. Her research appears in California Management Review and premier conferences like the International Conference on Information Systems and Academy of Management. She earned her PhD from Nanyang Technological University in 2020.
Xiaoquan (Michael) Zhang (“Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks”) is the Wei Lun Professor of Business AI at the Chinese University of Hong Kong. He has a PhD in management from MIT Sloan School of Management. His works study the pricing of information goods and the use of artificial intelligence in financial markets. His research has appeared in American Economic Review, Management Science, Marketing Science, MIS Quarterly, and Information Systems Research.
Huimin Zhao (“Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting”) is a professor of information technology management at the Lubar College of Business, University of Wisconsin-Milwaukee. He received his PhD degree 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.
Keran Zhao (“Lost in the Crowd: How Group Size and Content Moderation Shape User Engagement in Live Streaming”) is an assistant professor in the Department of Supply Chain and Information Systems at Pennsylvania State University. His research focuses on the design and user behavior within online digital platforms and healthcare communities, utilizing machine learning, deep learning, and econometrics methods. His work has been published in Information Systems Research and Journal of the Association for Information Systems, among others.
Zhiqiang (Eric) Zheng (“Irrationality-Aware Human Machine Collaboration: Mitigating Alterfactual Irrationality in Copy Trading”) is the Ashbel Smith Professor of Information Systems and Finance at University of Texas at Dallas. He received his PhD from the Wharton School. His current research interests center around artificial intelligence methods, Fintech, digital asset technology, and blockchain analytics. He authored a textbook, Blockchain Technology Fundamentals. He serves and has served as a senior editor for MIS Quarterly and Information Systems Research and is an INFORMS ISS Fellow.
Mi Zhou (“Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention”) is an assistant professor of information systems at the UBC Sauder School of Business. Her research focuses on analyzing individual behavior in technology-enabled markets using both structured and unstructured data (e.g., video, image, text, audio). She is particularly interested in understanding how technology influences user behavior in markets for digital learning. Prior to joining UBC Sauder, she received a PhD in information systems and management from Carnegie Mellon University.
Yu Zhu (“Post-Earnings-Announcement Drift Prediction: Leveraging Postevent Investor Responses with Multitask Learning”) is an assistant professor in the Department of Accounting and Management Information Systems at the University of Delaware. He holds a PhD in finance from Zhejiang University, China, and a second PhD in information systems from the University of Utah. His research focuses on the convergence of information systems, finance, business analytics, and deep learning, with an emphasis on incorporating business domain knowledge into artificial intelligence methodologies.
Honglei Zhuang (“Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention”) currently works at Google Research. His general research interests include data mining, machine learning, and information retrieval. Before he joined Google, he obtained his PhD from the University of Illinois at Urbana-Champaign and his bachelor’s degree from Tsinghua University.
Markus P. Zimmer (“Beyond Digital vs. IT: The Untold Story of Their Relationship from an Organizing Logic Perspective”) is a postdoctoral researcher at Leuphana University and adjunct professor at University of Turku. He conducts research at the intersection of organizational change, digital technologies and responsibility. His work has been published in Journal of Strategic Information Systems, Journal of the Association for Information Systems, Information Systems Research as well as leading conferences.
