讲座主题：Living in a Simulation? An Empirical Investigation of the Smart Driving Test-Simulation System

　　主 讲 人：徐鑫 副教授 香港理工大学

　　讲 座 地 点：yL23411永利官网登录B228

　　讲 座 时 间：2018年10月10日，09:30---11:00

　　摘 要：

　　Internet of Things (IoT) generally refer to the embedment of computing and communication devices in various types of physical objects (e.g., automobiles) in people's daily work and life. These devices exchange data in real time over the Internet. Smart services can then be developed based on the real-time capture, tracking, and analysis of data streams about individual behaviors. The real-time analysis of IoT data streams enables the immediate feedbacks about details of individual task performance. This is one of the key features of smart services that we focus on in the current research. In particular, we draw from feedback intervention theory (FIT) to investigate the impact of an IoT-enabled immediate feedback intervention on individual task performance.

　　Our research context is a smart service based on the Internet of Vehicles (IoV) technology—a smart test-simulation system for trainees implemented by a large driver-training service provider in China. The system captures and analyzes data streams from on-board sensors and cameras installed in vehicles in real time and immediately provide information about both the total score of and the details of errors made by an individual trainee during the test simulation. We postulate that the focal smart service functions as a feedback intervention (FI) to improve individual trainees’ task performance (i.e., passing the formal driving test) by providing two types of real-time FI cues—the velocity cues about the overall performance and the corrective cues about the details of errors made by trainees in the test simulation. Furthermore, we hypothesize a trainee’s training mode as the moderator of the test-simulation effect. Finally, we propose the interaction effect of feedback timing and the amount of FI cues on formal test performance.

　　We collected data about trainees’ demographics, the records of their training sessions, and the key time points of their training and participations in the test simulation and/or the formal driving test. We utilized a quasi-experimental method together with propensity score matching (PSM) to empirically validate our research model. The Difference-in-Difference (DID) analysis and the multiple regression results supported the significant impact of the test simulation as a FI on trainees’ performance in the formal driving test. Results also supported the interaction effect of feedback timing and the amount of corrective FI cues on formal test performance. We discuss the theoretical contributions and the practical significance of our research at the end of the paper.

　　Keywords: Internet of Things, Internet of Vehicles, Feedback Interventions, Feedback Timing, Quasi Experiments, Driver Training

　　主讲人简介：

　　XU XIN is an associate professor in the Department of Management and Marketing, Faculty of Business at Hong Kong Polytechnic University. He received his Ph.D. in information systems from the Hong Kong University of Science and Technology. His research interests include IT innovation management, data science and social media analytics, Internet of Things and Smart Services, and Human–Computer Interaction. His works have appeared in leading journals such as Management Science, MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of the Association for Information Systems, IEEE Transactions on Engineering Management, and Information Systems Frontiers. He currently serves as Associate Editor for MIS Quarterly.