Jing Tang
Assistant Professor
Department of MIS, Marketing, and Analytics
Saunders College of Business
585-475-2015
Office Location
Jing Tang
Assistant Professor
Department of MIS, Marketing, and Analytics
Saunders College of Business
Bio
Jing Tang earned her Ph.D. in Design and Innovation, from Weatherhead School of Management, Case Western Reserve University. Her research primarily lies in digital innovations and digital strategies, with a current focus on the design of platforms and the interaction between humans and technologies. Her studies mainly adopt mixed methods and theories from Management Information Systems, Marketing, and Strategy. Jing is teaching Business Analytics and Marketing Analytics.
585-475-2015
Select Scholarship
Invited Article/Publication
Liu, M., Tang, J., Walton, S., Zhang, Y., & Zhao, X. (2023). Auditor sustainability focus and client sustainability reporting. Accounting, Organizations and Society. . .
Ma, J., Lu, Y., & Tang, J. (2023). The differential effect of learning from others on creative performance over individual tenure: Empirical evidence from open innovation communities. Journal of Knowledge Management. . .
Lyytinen, K., Topi, H., & Tang, J. (2023). MaCuDE IS Task Force: Final Report and Recommendations. Communications of the AIS. . .
Lyytinen, K., Topi, H., & Tang, J. (2023). MaCuDE IS Task Force Phase II Report: Views of Industry Leaders on Big Data Analytics and AI. Communications of the AIS. . .
Chen, Q., Lu, Y., Gong, Y., & Tang, J. (2022). Classifying and measuring the service quality of AI Chatbot in frontline service. Journal of Business Research. . .
Lyytinen, K., Topi, H., & Tang, J. (2021). Information Systems Curriculum Analysis for the MaCuDE Project. Communications of the Association for Information Systems (AIS). 49. 38.
Zhang, X., Wang, W., Ordonez de Pablos, P., Tang, J., & Yan, X. (2015). Mapping development of social media research through different disciplines: Collaborative learning in management and computer science. Computers in Human Behavior. . .
Invited Keynote/Presentation
Lyytinen, K., Topi, H., & Tang, J. (2021). MaCude: Phase II- Industry Needs. WORKSHOPS & ANCILLARY MEETINGS (International Conference on Information Systems 2021).
Published Conference Proceedings
Tang, J., Singh, J., & Lyytinen, K. (2020). When Regulating Negative Reviews Enhances their Value in a Digital Platform. AMA Conference.
Tang, J., Gong, Y., & Zhao, X. (2019). Configurations of distribution strategies: Evidence from Retailing Industry. 13th International Conference on Operations and Supply Chain Management (ICOSCM).
Amatullo, M., Lyytinen, K., & Tang, J. (2019). Measuring a Design Attitude in Accelerating Social Innovation: Scale Development and Validation. Academy of Management Annual Meeting.
Tang, J., Evans, J., Lyytinen, K., & Singh, J. (2019). IT Leader Effectiveness and Knowledge Use Mechanisms for Boundary Spanning. International Conference on Information Systems.
Tang, J., Singh, J., & Lyytinen, K. (2019). The Power of Negative Reviews on a Freemium Platform: An Event Study of Pay-for-Negative Regulation. International Conference on Information Systems.
Tang, J., & Zhao, W. (2016). A visual-rich bibliometric analysis of entrepreneurship research in strategy venue (1991-2015). Academy of Management Annual Meeting.
Currently Teaching
BANA-255
Data Literacy, Analytics, and Decision Making
3 Credits
This course serves as an introduction to the uses (and potential misuses) of data in a wide variety of social settings, including the exploration of contemporary techniques to analyze such data. Data acquisition, cleansing, management, analysis, and visualization will be addressed through hands-on projects. Project work will include contemporary social problems addressed using a dynamic set of resources and technologies. An emphasis will be placed on how insights gleaned from data analysis can be used to guide individual and group decision-making scenarios.
MGIS-650
Introduction to Data Analytics and Business Intelligence
3 Credits
This course serves as an introduction to data analysis including both descriptive and inferential statistical techniques. Contemporary data analytics and business intelligence tools will be explored through realistic problem assignments.