Skip to main navigation menu Skip to main content Skip to site footer

Peer Reviewed Article

Vol. 5 (2018)

AI-enabled Decision Support Systems and Reciprocal Symmetry: Empowering Managers for Better Business Outcomes



To empower managers and improve business outcomes in organizations, this paper explores the revolutionary potential of AI-enabled Decision Support Systems (DSS) combined with reciprocal symmetry. The study aims to investigate how integrating AI improves managerial skills, encourages cooperative decision-making through reciprocal symmetry, and spurs creativity and operational efficiency. The methodology includes a thorough analysis of secondary data sources and published literature on artificial Intelligence (AI) in reciprocal symmetry and decision assistance. To summarize the main conclusions and insights, scholarly articles, peer-reviewed journal articles, and pertinent reports were examined and evaluated. The main findings emphasize how Artificial Intelligence (AI) can improve managerial decision-making accuracy, promote cooperative cultures through reciprocal symmetry, and stimulate innovation and operational efficiency inside businesses. The report also outlines policy implications for ethical issues, data protection, and organizational preparedness for effective AI integration. In today's fast-paced business world, this study emphasizes how crucial it is to strategically use AI technology within a framework of mutually beneficial interactions to empower managers, promote innovation, and achieve sustainable success. The results provide insightful information that may be used to establish corporate plans and policies for using AI to improve business outcomes.


  1. Arnott, D., & Pervan, G. (2005). A Critical Analysis of Decision Support Systems Research. Journal of Information Technology, 20(2), 67-87.
  2. Liu, S., Duffy, A. H. B., Whitfield, R. I., & Boyle, I. M. (2010). Integration of Decision Support Systems to Improve Decision Support Performance. Knowledge and Information Systems, 22(3), 261-286.
  3. Metaxiotis, K., Ergazakis, K., Samouilidis, E., & Psarras, J. (2003). Decision Support through Knowledge Management: The Role of Artificial Intelligence. Information Management & Computer Security, 11(5), 216-221.
  4. Mullangi, K. (2017). Enhancing Financial Performance through AI-driven Predictive Analytics and Reciprocal Symmetry. Asian Accounting and Auditing Advancement, 8(1), 57–66.
  5. Tejani, J. G. (2017). Thermoplastic Elastomers: Emerging Trends and Applications in Rubber Manufacturing. Global Disclosure of Economics and Business, 6(2), 133-144.
  6. Walczak, S. (2016). Artificial Neural Networks and Other AI Applications for Business Management Decision Support. International Journal of Sociotechnology and Knowledge Development, 8(4), 1-20.
  7. Wu, C. H., Ho, G. T. S., Lam, C. H. Y., Ip, W. H. (2015). Franchising Decision Support System for Formulating a Center Positioning Strategy. Industrial Management & Data Systems, 115(5), 853-882.
  8. Ying, D., Patel, B., & Dhameliya, N. (2017). Managing Digital Transformation: The Role of Artificial Intelligence and Reciprocal Symmetry in Business. ABC Research Alert, 5(3), 67–77.
  9. Zaffalon, M., & Miranda, E. (2018). Desirability Foundations of Robust Rational Decision Making. Synthese, 1-42.

Similar Articles

1-10 of 29

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)