How to Get Your PhD (Recommended): [Notes]
IS Literature Review:
Levy, Y., & J. Ellis, T. (2006). A Systems Approach to Conduct an Effective Literature Review in Support of Information Systems Research. Informing Science: The International Journal of an Emerging Transdiscipline, 9, 181–212. https://doi.org/10.28945/479: [Notes]
Readings in IS (Reading list of IBA8007 at CUHKSZ):
1. Alavi, M., & Carlson, P. (1995). A review of MIS research and disciplinary development. Journal of Management Information Systems, 11(4), 45–62. https://doi.org/10.1080/07421222.1992.11517938 [Notes]
2. Baesens, B., Bapna, R., Marsden, J. R., Vanthienen, J., & Zhao, J. L. (2016). Transformational issues of big data and analytics in networked business. MIS Quarterly, 40(4), 807–818. [Notes]
3. Banker, R. D., & Kauffman, R. J. (2004). The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science. Management Science, 50(3), 281–298. https://doi.org/10.1287/mnsc.1040.0206 [Notes]
4. Barki, H., Rivard, S., & Talbot, J. (1988). An information systems keyword classification scheme. MIS Quarterly, 12(2), 299–310. https://doi.org/10.2307/248855 [Notes]
5. Beck, R., Avital, M., Rossi, M., & Thatcher, J. B. (2017). Blockchain Technology in Business and Information Systems Research. Business and Information Systems Engineering, 59(6), 381–384. https://doi.org/10.1007/s12599-017-0505-1 [Notes]
6. Bélanger, F., Cefaratti, M., Carte, T., & Markham, S. E. (2014). Multilevel Research in Information Systems: Concepts, Strategies, Problems, and Pitfalls. Journal of the Association for Information Systems, 15(9), 614–650. [Notes]
7. Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433–1450. https://doi.org/10.4324/9780203010167-13 [Notes]
8. Bhattacherjee, A., & Premkumar, G. (2004). Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test. MIS Quarterly, 28(2), 229–254. [Notes]
9. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993–1022. https://doi.org/10.1016/B978-0-12-411519-4.00006-9 [Notes]
10. Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530-1534 [Notes]
11. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Manage. Sci., vol. 35, no. 8, pp. 982–1003, 1989. [Notes]
12. Davis, G. B. (1999). A Research Perspective for Information Systems and Example of Emerging Area of Research. Information Systems Frontiers, 1(3), 195–203. https://doi.org/10.1023/A:1010094126762
13. Fan, Shaokun, Noyan Ilk, Akhil Kumar, Ruiyun Xu, J. Leon Zhao, From Data Processing to Blockchain Networking: A Recount and Projection of Information Systems Research, Quarterly Journal of Economics and Management, 2022,1(1):169-194, Download at <https://ssrn.com/abstract=4392433> or <https://cbit.cuhk.edu.cn/wp-content/uploads/2023/03/2023032802122682.pdf>.
14. Fischer, M., Imgrund, F., Janiesch, C., & Winkelmann, A. (2020). Strategy archetypes for digital transformation: Defining meta objectives using business process management. Information & Management, 57(5), 103262. https://doi.org/https://doi.org/10.1016/j.im.2019.103262
15. Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2022). Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation. Information Systems Research, 33(2), 678–696. https://doi.org/10.1287/isre.2021.1079
16. Ge, R., Zheng, Z. (Eric), Tian, X., & Liao, L. (2021). Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending. Info. Sys. Research, 32(3), 774–785. https://doi.org/10.1287/isre.2021.1009
17. Goyal, S., Ahuja, M., & Guan, J. (2018). Information systems research themes: A seventeen-year data-driven temporal analysis. Communications of the Association for Information Systems, 43(1), 404–431. https://doi.org/10.17705/1CAIS.04323
18. Hendershott, T., Zhang, X., Leon Zhao, J., & Zheng, Z. (2021). Fintech as a game changer: Overview of research frontiers. Information Systems Research, 32(1), 1–17. https://doi.org/10.1287/isre.2021.0997
19. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS quarterly, 75-105.
20. Ilk, N., Shang, G., Fan, S., & Zhao, J. L. (2020). Stability of Transaction Fees in Bitcoin: A Supply and Demand Perspective. Management Information Systems Quarterly, Forthcoming.
21. Keen, P. G. W. (1980). Association for Information Systems AIS Electronic Library (AISeL) MIS Research: Reference Disciplines and a Cumulative Tradition. Proceedings of the First International Conference on Information System, 9–18. http://aisel.aisnet.org/icis1980/9
22. Kumar, A., Liu, R., & Shan, Z. (2020). Is Blockchain a Silver Bullet for Supply Chain Management? Technical Challenges and Research Opportunities. Decision Sciences, 51(1), 8–37. https://doi.org/10.1111/deci.12396
23. Lee, Z., Gosain, S., & Im, I. (1999). Topics of interest in IS: Evolution of themes and differences between research and practice. Information and Management, 36(5), 233–246. https://doi.org/10.1016/S0378-7206(99)00022-1
24. Leidner, D., Sutanto, J., & Goutas, L. (2022). Multifarious Roles and Conflicts on an Interorganizational Green IS. MIS Quarterly, 46(1), 591–608. https://doi.org/10.25300/misq/2022/15116
25. Nunamaker, J. F., Applegate, L. M., & Konsynski, B. R. (1988). Computer-aided deliberation: model management and group decision support. Operations Research, 36(6), 826–848. https://doi.org/10.1287/opre.36.6.826
26. Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50–69. https://doi.org/10.1287/isre.13.1.50.96
27. Sandberg, J., Holmström, J., & Lyytinen, K. (2020). Digitization and phase transitions in platform organizing logics: Evidence from the process automation industry. MIS Quarterly, 44(1), 129–153. https://doi.org/10.25300/MISQ/2020/14520
28. Senoner, J., Netland, T., & Feuerriegel, S. (2022). Using Explainable Artificial Intelligence to Improve Process Quality: Evidence from Semiconductor Manufacturing. Management Science, 68(8), 5704–5723. https://doi.org/10.1287/mnsc.2021.4190
29. Teodorescu, M. H. M., Morse, L., Awwad, Y., & Kane, G. C. (2021). Failures of fairness in automation require a deeper understanding of human–ml augmentation. MIS Quarterly, 45(3), 1483–1499. https://doi.org/10.25300/MISQ/2021/16535
30. Vessey, I., Ramesh, V., & Glass, R. L. (2002). Research in information systems: An empirical study of diversity in the discipline and its journals. Journal of Management Information Systems, 19(2), 129–174. https://doi.org/10.1080/07421222.2002.11045721
31. Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022). Fusing Blockchain and AI With Metaverse: A Survey. IEEE Open Journal of the Computer Society, 3, 122–136. https://doi.org/10.1109/OJCS.2022.3188249
32. Zhao, J. L., Fan, S., & Yan, J. (2016). Overview of business innovations and research opportunities in blockchain and introduction to the special issue. Financial Innovation, 2(1). https://doi.org/10.1186/s40854-016-0049-2
Editor's Comments:
Machine Leaning in Information Systems Research (MIS Quarterly): [Notes]
Question Practice: BBGRE