INTEGRATED REVENUE MANAGEMENT INFORMATION PLATFORM FOR ENTERPRISES
Abstract
This article is devoted to issues of importance of integration processes in the implementation of revenue management at the enterprises. Implementation of the revenue management into management processes allows to streamline the processes of pricing, selection of distribution channels, and integration of the information and communication system of decision-making. The integration of the innovative model will increase the use of finished goods inventory, since the enterprises, unlike service enterprises, usually have the ability to store finished goods to meet short-term demand, which is usually more profitable than long-term demand. It has been substantiated that revenue management solves the problem of finding the optimal maximum level of stocks in the context of a compromise between the cost of maintaining stocks and the additional profit that can be obtained through a higher level of stocks. The purpose of this article is to research the directions of integration processes in the revenue management of the enterprises. The article uses the method of synthesis and generalisation, which helps to define the specific features of using the revenue management tools at industrial enterprises. To determine the degree of integration and select a model of revenue management at the enterprises, the classification method and the graphical method are chosen. The modelling method is used to create an information and communication model of inventory management. It is determined that enterprises, unlike service enterprises, rarely use revenue management systems. It is determined that the selection and differentiation of customer segments allows to decide on the integration of modules of the revenue management system for demand analysis and seasonality determination. The main reason for the lack of specialized revenue management software at enterprises is the high cost of its installation and maintenance. An information and communication model is proposed. The model provides respond to market changes in a timely manner to increase the ability to collect and analyse information about competitors, suppliers and customers. We have proposed areas for integrating the revenue management system at the enterprises.
References
Ammirato, S., Felicetti, A. M., Linzalone, R., Volpentesta, A. P., & Schiuma, G. (2020). A systematic literature review of revenue management in passenger transportation. Measuring Business Excellence, no. 24(2), pp. 223–242.
Klein, R., Koch, S., Steinhardt, C., & Strauss, A. K. (2020) A review of revenue management: Recent generalizations and advances in industry applications. European journal of operational research, no. 284(2), pp. 397–412.
Zhu, W., & Topaloglu, H. (2024) Performance guarantees for network revenue management with flexible products. Manufacturing & Service Operations Management, no. 26(1), pp. 252–270.
Khorshidvand, B., Soleimani, H., Sibdari, S., & Esfahani, M. M. S. (2021) Revenue management in a multi-level multi-channel supply chain considering pricing, greening, and advertising decisions. Journal of Retailing and Consumer Services, no. 59.
Rane, N. L., Mallick, S. K., Kaya, O., & Rane, J. (2024) Applications of machine learning in healthcare, finance, agriculture, retail, manufacturing, energy, and transportation: A review. Applied Machine Learning and Deep Learning: Architectures and Techniques, pp. 112–131.
Boada-Collado, P., & Martínez-de-Albéniz, V. (2020) Estimating and optimizing the impact of inventory on consumer choices in a fashion retail setting. Manufacturing & service operations management, no. 22(3), pp. 582–597.
He, T., & Tawarmalani, M. (2024) Discrete nonlinear functions: formulations and applications in retail revenue management. arXiv preprint arXiv:2408.04562.
Boiko, M., Bosovska, M., Vedmid, N., Melnychenko, S., & Stopchenko, Y. (2022) Digitalization: Implementation in the tourism business of Ukraine. Problems and Perspectives in Management, no. 20 (4), pp. 24–41.
Mazaraki A., Boiko M., Bosovska M. and Kulyk M.,(2022) Revenue Management Data Digital Transformation. 2022 IEEE 4th International Conference on Modern Electrical and Energy System (MEES), Kremenchuk, Ukraine, pp. 1–5. DOI: https://doi.org/10.1109/MEES58014.2022.10005639