International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
권호 표지
DOI QR코드

DOI QR Code

Role of Decision Support Systems in Marketing Management

  • Arshi Naim (Department of Information Systems, King Khalid University) ;
  • Kholood Alqahtani (Department of Information Systems, King Khalid University)
  • 투고 : 2024.08.05
  • 발행 : 2024.08.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper is an extended paper showing the role of Decision Support Systems (DSS) in other fields of Marketing Management (M.Mgnt). DSS facilitates in decision making many M.Mgnt concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model.

키워드

참고문헌

  1. Raab, G., Ajami, R. A., & Goddard, G. J. (2016). Customer relationship management: A global perspective. CRC Press.
  2. Peppers, D., & Rogers, M. (2004). Managing customer relationships: A strategic framework. John Wiley & Sons.
  3. Chan, S. L., & Ip, W. H. (2011). A dynamic decision support system to predict the value of customer for new product development. Decision support systems, 52(1), 178-188.
  4. Grover, V., Chiang, R. H., Liang, T. P., & Zhang, D. (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems, 35(2), 388- 423.
  5. Filip, F. G. (2020). DSS-A Class of Evolving Information Systems. In Data Science: New Issues, Challenges and Applications (pp. 253- 277). Springer, Cham.
  6. Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29-44.
  7. Pavoine, S., Vallet, J., Dufour, A. B., Gachet, S., & Daniel, H. (2009). On the challenge of treating various types of variables: application for improving the measurement of functional diversity. Oikos, 118(3), 391-402.
  8. Kaiser, R., Spiegel, P. B., Henderson, A. K., & Gerber, M. L. (2003). The application of geographic information systems and global positioning systems in humanitarian emergencies: lessons learned, programme implications and future research. Disasters, 27(2), 127-140.
  9. O'brien, J. A., & Marakas, G. M. (2005). Introduction to information systems (Vol. 13). New York City, USA: McGraw-Hill/Irwin.
  10. Arnott, D. (2004). Decision support systems evolution: framework, case study and research agenda. European Journal of Information Systems, 13(4), 247-259.
  11. Watson, H. J. (2018). Revisiting Ralph Sprague's framework for developing decision support systems. Communications of the Association for Information Systems, 42(1), 13.
  12. Aronson, J. E., Liang, T. P., & MacCarthy, R. V. (2005). Decision support systems and intelligent systems (Vol. 4). Upper Saddle River, NJ, USA:: Pearson Prentice-Hall.
  13. Sharkey, U., & Acton, T. (2012). Innovations in information systems from transaction processing to expert systems.
  14. Polkowski, L., Tsumoto, S., & Lin, T. Y. (Eds.). (2012). Rough set methods and applications: new developments in knowledge discovery in information systems (Vol. 56). Physica.
  15. Jia, P., Cheng, X., Xue, H., & Wang, Y. (2017). Applications of geographic information systems (GIS) data and methods in obesity-related research. Obesity reviews, 18(4), 400-411.
  16. Sigala, M. (2018). Implementing social customer relationship management. International Journal of Contemporary Hospitality Management.
  17. Watanabe, C., & Hobo, M. (2004). Co-evolution between internal motivation and external expectation as a source of firm self-propagating function creation. Technovation, 24(2), 109-120.
  18. Alt, R., & Puschmann, T. (2004, January). Successful practices in customer relationship management. In 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the (pp. 9-pp). IEEE.
  19. Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
  20. Foss, B., Stone, M., & Ekinci, Y. (2008). What makes for CRM system success-Or failure?. Journal of Database Marketing & Customer Strategy Management, 15(2), 68-78.
  21. Cuthbertson, R., & Laine, A. (2003). The role of CRM within retail loyalty marketing. Journal of Targeting, Measurement and Analysis for Marketing, 12(3), 290-304.
  22. Collins, K. (2001). Analytical CRM: Driving Profitable Customer Relationships. Strategic Planning.
  23. Friday, D., Ryan, S., Sridharan, R., & Collins, D. (2018). Collaborative risk management: a systematic literature review. International Journal of Physical Distribution & Logistics Management.
  24. Eom, S. (2020, May). DSS, BI, and Data Analytics Research: Current State and Emerging Trends (2015-2019). In International Conference on Decision Support System Technology (pp. 167-179). Springer, Cham.
  25. Rupnik, R., & Kukar, M. (2007). Decision support system to support decision processes with data mining. Journal of information and organizational sciences, 31(1), 217-232.
  26. Asemi, A., Safari, A., & Zavareh, A. A. (2011). The role of management information system (MIS) and Decision support system (DSS) for manager's decision making process. International Journal of Business and Management, 6(7), 164-173.