雷松亞 Soumya Ray

Distinguished Professor

https://soumyaray.com/

soumya.ray@iss.nthu.edu.tw

  • IT User Behavior

  • Information Security

  • Software Development

  • Computational Statistics

Brief Bio

現職 Employment

清華大學服務科學研究所特聘教授

Distinguished Professor, Institute of Service Science, NTHU

PhD Program Coordinator, Institute of Service Science, National Tsing Hua University, Taiwan


學歷 Education

PhD, Information Systems and Applied Statistical Methods, University of Wisconsin-Madison, USA

MSc, Industrial Engineering, University of Wisconsin-Madison, USA

BSc, Computer Science, University of Wisconsin-Madison, USA


研究興趣 Research Interests

IT User Behavior: online communities, engagement, resistance and switching costs, security perceptions, habit and addiction, privacy

Statistical Techniques: Predictive-inferential methods, Structural Equation Modeling, Simulation, Experimentation


Awards

  • MoST Outstanding Research Award – 2019 (Ministry of Science and Technology)

  • Outstanding Teaching Award – 2019 (National Tsing Hua University)

  • Outstanding Teaching Award – 2015 (National Tsing Hua University)

  • 2012 Wu Ta-You Award (National Science Council)

  • 2012 New Faculty Research Award, National Tsing Hua University

Select Publications

1. Danks, N.P., Ray, S., Shmueli, G. 2023. The Composite Overfit Analysis Framework: Assessing the Out-of-sample Generalizability of Construct-based Models Using Predictive Deviance, Deviance Trees, and Unstable Paths, Management Science (forthcoming).

2. Greene, T., Shmueli, G., Ray, S., 2023, Taking the Person Seriously: Ethically-aware IS Research in the Era of Reinforcement Learning-based Personalization, Journal of the Association of Information Systems (forthcoming).

3. Cano Bejar, A.H., Ray, S., Huang, Y.H. 2023. Fighting for the Status Quo: Threat to Tech Self- Esteem and Opposition to Competing Smartphones, Information & Management (forthcoming).

4. Sharma, P., Sarstedt, M., Shmueli, G., Danks, N., Ray, S. 2018. “Prediction-Oriented Model Selection in Partial Least Squares Path Modeling,” Decision Sciences, (21:1), pp. 243-241.

5. Kuem, J., Ray, S., Siponen, M., Kim, S. S. 2017. “What Leads to Prosocial Behaviors on Social Networking Services: A Tripartite Model,” Journal of Management Information Systems (34:1), pp. 40-70.

6. Shmueli, G., Ray, S., Estrada, J. M. V., Chatla, S. B. 2016. “The Elephant in the Room: Predictive Performance of PLS Models,” Journal of Business Research (69), pp. 4552–4564.

7. Ray, S., Kim, S.S., & Morris, J.G. 2014. “The Central Role of Engagement in Online Communities”, Information Systems Research, (25:3), pp. 528-546.

8. Ray, S., and Seo, D. 2013. “The interplay of conscious and automatic mechanisms in the context of routine use: An integrative and comparative study of contrasting mechanisms”, Information & Management (50:7), pp. 523-539.

9. Ray, S., Kim, S.S., & Morris, J.G. 2012. “Research Note – Online Users' Switching Costs: Their Nature and Formation” Information Systems Research (23:1), pp. 197-213.

10. Ray, S., Ow, T., & Kim, S.S. 2011. “Security Assurance: How Online Service Providers Can Influence Security Control Perceptions and Gain Trust”, Decision Sciences (42:2), pp. 391-412.

Teaching

  • Service Oriented Architecture: Develops skills to create robust and composable online services. Students will develop a habit of creating high quality code, publishing their work as open source, and deploying on cloud platforms. We will also learn how to use microservices and message queues as building blocks to larger SaaS architectures. This class favors the tools, practices, and learning habits of IT startups and the open source movement.


  • Business Analytics Using Computational Statistics: Learn how to use programmatic methods to infer knowledge from data. We learn how to match intuition and theory to data using simulation, visualization, and statistical techniques. This class favors marketing research methods. Students will handle both small and large volumes of data, and will analyze real data from partner companies.


  • Service Security: Gain a transformational understanding of information security, from the basics of information theory to cryptographic principles, secure software development and secure architectures. Students will learn to implement practical elements such as single sign-on for authentication, security policies, hardened databasing, and more.