Optimizing Pricing Strategies: Integrating Dempster-Shafer Method in Decision Support Systems for Uncertainty Management

Authors

  • Rey Feriantomi Fakultas Teknologi Informasi, Universitas Andalas, Padang Sumatera Barat
  • Syaifa Heksana Fakultas Ekonomi dan Bisnis, Universitas Andalas, Padang Sumatera Barat

Keywords:

Pricing Strategies, Dempster-Shafer Method, Decision Support Systems, Uncertainty Management, Evidence Synthesis

Abstract

This research explores the integration of the Dempster-Shafer method within decision support systems to revolutionize pricing strategies in dynamic business environments. The study investigates the method's efficacy in managing uncertainties, synthesizing diverse evidence sources, and fostering informed decision-making in pricing scenarios. Through a structured approach, the Dempster-Shafer method enables decision-makers to navigate uncertainties, integrate multifaceted evidence, and refine pricing strategies with greater precision and adaptability. Findings showcase its transformative potential, offering insights into risk management, holistic integration of information, structured conflict resolution, and agile responsiveness to market dynamics. While demonstrating significant contributions, challenges in computational complexity, interpretability, and integration emerge, presenting avenues for further research and refinement. This research signifies a paradigm shift, emphasizing the importance of innovative computational methodologies in empowering evidence-based, proactive decision-making in pricing strategies across industries.

References

Aqel, M. J., Nakshabandi, O. A., & Adeniyi, A. (2019). Decision support systems classification in industry. Periodicals of Engineering and Natural Sciences, 7(2), 774–785.

Ascough Ii, J. C., Maier, H. R., Ravalico, J. K., & Strudley, M. W. (2008). Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecological Modelling, 219(3–4), 383–399.

Cherubino, P., Martinez-Levy, A. C., Caratu, M., Cartocci, G., Di Flumeri, G., Modica, E., Rossi, D., Mancini, M., & Trettel, A. (2019). Consumer behaviour through the eyes of neurophysiological measures: State-of-the-art and future trends. Computational Intelligence and Neuroscience, 2019.

Courtney, J. F. (2001). Decision making and knowledge management in inquiring organizations: toward a new decision-making paradigm for DSS. Decision Support Systems, 31(1), 17–38.

Day, G. S., & Montgomery, D. B. (1999). Charting new directions for marketing. Journal of Marketing, 63(4_suppl1), 3–13.

Dixit, A. (1992). Investment and hysteresis. Journal of Economic Perspectives, 6(1), 107–132.

Doloi, H. K. (2011). Understanding stakeholders’ perspective of cost estimation in project management. International Journal of Project Management, 29(5), 622–636.

Filip, F. G. (2020). DSS—A class of evolving information systems. Data Science: New Issues, Challenges and Applications, 253–277.

Knabke, T., & Olbrich, S. (2015). Exploring the future shape of business intelligence: mapping dynamic capabilities of information systems to business intelligence agility.

Kohn, M. S., Sun, J., Knoop, S., Shabo, A., Carmeli, B., Sow, D., Syed-Mahmood, T., & Rapp, W. (2014). IBM’s health analytics and clinical decision support. Yearbook of Medical Informatics, 23(01), 154–162.

Mandelbaum, E. (2014). Thinking is believing. Inquiry, 57(1), 55–96.

Nagle, T. T., & Müller, G. (2017). The strategy and tactics of pricing: A guide to growing more profitably. Routledge.

Navlani, A., Fandango, A., & Idris, I. (2021). Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python. Packt Publishing Ltd.

Peñafiel, S., Baloian, N., Sanson, H., & Pino, J. A. (2020). Applying Dempster–Shafer theory for developing a flexible, accurate and interpretable classifier. Expert Systems with Applications, 148, 113262.

Piscopo, C., & Birattari, M. (2007). Philippe Smets and the Transferable Belief Model.

Power, D. J., & Sharda, R. (2007). Model-driven decision support systems: Concepts and research directions. Decision Support Systems, 43(3), 1044–1061.

Rathore, B. (2018). Allure of Style: The Impact of Contemporary Fashion Marketing on Consumer Behaviour. International Journal of New Media Studies: International Peer Reviewed Scholarly Indexed Journal, 5(2), 10–21.

Salem Khalifa, A. (2004). Customer value: a review of recent literature and an integrative configuration. Management Decision, 42(5), 645–666.

Sauter, V. L. (2014). Decision support systems for business intelligence. John Wiley & Sons.

Skoruchi, A., & Mohammadi, E. (2022). Uncertain portfolio optimization based on Dempster-Shafer theory. Management Science Letters, 12(3), 207–214.

Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.

Wangchuk, T., & Shah, T. (2022). Feeding the World with Data: Precision Agriculture and the Big Data Revolution in Food Supply Chains. Journal of Human Behavior and Social Science, 6(7), 1–15.

Zaman, M. S. (2020). Customer Satisfaction of Berger Paints Bangladesh Limited.

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Published

2024-01-28

How to Cite

Feriantomi, R., & Heksana, S. (2024). Optimizing Pricing Strategies: Integrating Dempster-Shafer Method in Decision Support Systems for Uncertainty Management. International Journal of Enterprise Modelling, 18(1), 1–10. Retrieved from https://ieia.ristek.or.id/index.php/ieia/article/view/83