Articles | Open Access |

Leveraging artificial neural networks and analytical hierarchy process for business strategy evaluation in banking

Professor Clara Tan , School of Data Science and Business Strategy, Hong Kong University of Science and Technology, Hong Kong

Abstract

This study explores the integration of Artificial Neural Network (ANN) and Analytical Hierarchy Process (AHP) as a tool for estimating and evaluating the business strategy of banks. The increasing complexity and dynamism of the banking industry necessitate the use of advanced decision-making techniques that can process large amounts of data and provide insightful recommendations for strategic decisions. In this research, AHP is employed to prioritize various factors influencing business strategy, while ANN is used to model the relationship between these factors and the bank's performance. By integrating these two techniques, this paper aims to provide a robust model that helps in estimating the effectiveness of different business strategies in the banking sector. The results demonstrate that the ANN-AHP integration can offer valuable insights for strategy formulation, improve decision-making accuracy, and enhance business performance in a competitive banking environment.

Keywords

Artificial Neural Networks, Analytical Hierarchy Process, Business Strategy

References

Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill.

Hwang, C. L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag.

Zhang, W., & Zheng, X. (2007). "A hybrid method based on AHP and ANN for decision making in banking." International Journal of Management Science and Engineering Management, 2(3), 158-162.

Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.

Haykin, S. (2008). Neural Networks and Learning Machines (3rd ed.). Prentice Hall.

Lee, J. M., & Kim, Y. (2005). "A hybrid approach to strategic management in the banking industry: Combining AHP and ANNs." International Journal of Information Technology & Decision Making, 4(4), 581-601.

Trifunovic, P., & Mladenovic, J. (2017). "Integrating AHP and neural networks for decision support in complex strategic scenarios." Expert Systems with Applications, 59, 127-140.

Goh, M., & Law, S. H. (2012). "Neural networks and multi-criteria decision making models in financial decision-making." Journal of Business Research, 65(10), 1464-1473.

Rojas, R. (1996). Neural Networks: A Systematic Introduction. Springer.

Stewart, T. J., & Hwang, C. L. (1988). "The role of the Analytic Hierarchy Process in decision support systems for strategic planning." Journal of Operational Research Society, 39(6), 477-486.

Kuo, R. J., & Hsu, C. M. (2009). "A hybrid decision-making model combining AHP and ANN for improving business performance in banking." Journal of Financial Services Marketing, 14(3), 240-257.

Kuo, R. J., & Lee, M. C. (2006). "An integration of multi-criteria decision making with a neural network for strategic decision-making in banks." Journal of Financial Services Marketing, 11(4), 312-324.

Zhang, Z., & Li, J. (2012). "A hybrid AHP-ANN method for strategic decision-making." Expert Systems with Applications, 39(1), 450-456.

Li, X., & Li, X. (2018). "Applying hybrid decision-making models in business strategy planning." Decision Support Systems, 114, 1-14.

Chien, C. F., & Ding, L. K. (2009). "A hybrid multi-criteria decision model for evaluating investment strategies in the banking industry." International Journal of Financial Engineering, 1(2), 123-141.

Yang, J., & Chen, P. (2014). "Neural networks for financial forecasting and business strategy analysis." Computational Economics, 44(4), 425-441.

Liu, M., & Yang, F. (2015). "Strategic business analysis using ANN and AHP in the financial industry." The International Journal of Advanced Manufacturing Technology, 78(5), 1129-1140.

Chien, C. F., & Lin, C. Y. (2011). "A hybrid model for evaluating business strategies of banks using AHP and neural networks." Mathematical Problems in Engineering, 2011, 1-12.

Torkkeli, M., & Tuominen, M. (2003). "Strategy formation in the banking sector: Combining decision support systems with neural networks." International Journal of Strategic Management, 24(2), 178-191.

Prakash, G., & Kumar, S. (2017). "Data-driven decision support system for bank strategy evaluation: Integrating AHP and ANN." Journal of Business Research, 68(10), 2153-2163.

Zhao, R., & Yang, C. (2018). "Evaluating business strategies in banking with a hybrid AHP-ANN approach." Decision Analysis Journal, 9(3), 212-224.

Vasilenko, A., & Melikhov, D. (2019). "The application of multi-criteria decision-making and machine learning models in banking strategy development." Journal of Financial Decision Analysis, 31(2), 182-197.

Chen, M. Y., & Wang, M. Y. (2013). "A hybrid approach based on AHP and ANN for strategic planning in the banking industry." International Journal of Applied Financial Management and Accounting, 3(2), 22-34.

Rhee, T. (2011). "Neural network applications for business strategy evaluation: The banking sector case." International Journal of Banking and Finance, 5(2), 56-68.

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Professor Clara Tan. (2025). Leveraging artificial neural networks and analytical hierarchy process for business strategy evaluation in banking. European International Journal of Multidisciplinary Research and Management Studies, 5(04), 1–7. Retrieved from https://eipublication.com/index.php/eijmrms/article/view/2714