主讲人

（单位）

章骏

（Monash University）

主持人

（单位）

邵秀燕

（电影网站 ）

讲座时间

2025年6月25日14：00

讲座地点

腾讯会议：

539-683-559

主讲人简介

Jun Zhangis a Senior Lecturer in the Department of Human-Centered Computing, Faculty of Information Technology at Monash University. He received his Ph.D. in Information Systems from the City University of Hong Kong. Prior to joining Monash, he held faculty positions at Wuhan University and the University of Science and Technology of China. His research interests lie at the intersection of human-computer interaction, information privacy and security, and online deviant behavior. His work has been published in leading IS journals and conferences, including Information Systems Research (ISR), Journal of Management Information Systems (JMIS), Information & Management (I&M), Computers in Human Behavior (CHB), Information Technology & People (IT&P), Behaviour & Information Technology (BIT), ICIS, and PACIS. He has served as the principal investigator on multiple research projects funded by the National Natural Science Foundation of China. He currently serves as an Associate Editor for Communications of the Association for Information Systems (CAIS) and Data and Information Management (DIM), and has served as Guest Associate Editor for JMIS, EJIS, JGIM, ICIS, PACIS, ECIS, AMCIS, and ICEB.

讲座内容摘要

Longitudinal repeated-measures experiments track the same individual perceptions and behaviors across multiple waves, delivering unparalleled leverage for detecting within-person change, modeling dynamic treatment effects, and ruling out confounds—thereby strengthening causal interference. Despite these strengths, the approach remains under-utilized in Information Systems (IS) research. Practical barriers—including the high expense, complexity of multi-wave scheduling, and advanced analytic requirements—have left the discipline with few established design or analysis standards.

This seminar aims to address the gap. It provides actionable guidelines for designing, executing, and modeling longitudinal repeated-measures experimental studies. Drawing on several examples from published work and my ongoing research projects, I will illustrate how longitudinal repeated-measures designs uncover the treatment effects of IT-based design interventions on users’ health behavior and information security management behavior change. Attendees will be presented with a roadmap for deploying multi-wave experiments that not only establish stronger causal inferences, but also reveal the nuanced temporal patterns that drive sustained behavioral change.