題目：System Dynamics Modeling for Information Systems Research- Theory Development and Practical Application
主講人：Yulin Fang 教授 (City University of Hong Kong)
時間：2018年1月17日（星期三）上午10:00
地點(diǎn)：主樓132
主講人介紹：
Yulin Fang is a full professor at Department of Information Systems, City University of Hong Kong. He earned his PhD at Richard Ivey School of Business, The University of Western Ontario in Canada. His current research interests include strategic and managerial aspect of information systems and analytics. He is currently serving as a Senior Editor for Information Systems Research and Information Systems Journal, and a co-editor-in-chief for Information Technology & People. He is also on the Editorial Board of Journal of Strategic Information Systems. He was an Associate Editor for several leading journals, including MIS Quarterly (2013-2016), Information Systems Research (2013-2016), and Information Systems Journal (2012-2015). He was awarded the Associate Editor of the Year at Information Systems Research in 2015.
Professor Fang has published 50 research articles in renowned management and information systems journals, including MIS Quarterly (MISQ), Information Systems Research (ISR), Journal of Management Information Systems (JMIS), Journal of the Association for Information Systems (JAIS), Journal of Operations Management (JOM), Strategic Management Journal (SMJ), Journal of Management Studies (JMS), Organizational Research Methods (ORM), among others. Many of them are included in UT Dallas and Financial Time journal lists. His research on open source software communities won the 2009 Senior Scholars Best IS Publication Award by the Association for Information Systems (AIS), one out of the five in that year. His work on e-commerce published at MIS Quarterly was one of the Citation of Excellent Winners of Emerald Citations of Excellence in 2017.
內(nèi)容介紹：
Most information systems (IS) research develops theory for explanation and prediction based on a variance logical structure that assumes one-way, time invariant causal relationships. This approach largely misses the opportunity to extend theory from alternative logical structures that build upon reciprocal and temporal causal mechanisms; for example, the system perspective. This paper introduces system dynamics (SD), a modeling tool capable of capturing the reciprocal and temporal causal mechanisms that underlie many complex and dynamic systems, and demonstrates its ability to extend existing variance theory from a system perspective. To do so, we first describe the basic tenets of SD and discuss the status quo of existing SD applications in the field. Then, we demonstrate how to model SD’s unique theoretical logic of reciprocal and temporal causal structure to extend existing variance theory. To demonstrate the use of SD in theory development, we develop and validate an SD model of the e-commerce resource endowment of a click-and-mortar firm and simulate dynamic causal relationships between the e-commerce resource endowment and firm performance over time, under various scenarios. This case demonstrates how we can extend an existing variance theory by reconciling the inconsistent findings of prior research from a system perspective using the SD approach. The paper concludes by discussing how SD can help IS researchers develop dynamic theories.
（承辦：技術(shù)經(jīng)濟(jì)與戰(zhàn)略管理系，科研與學(xué)術(shù)交流中心）
