Valley International Journal Digital Library

2024: VIJ Digital library
Articles

Customer Resource Management and Salesperson Behavior Optimization: The Application of Dynamic Pricing Systems

PDF
  • Huiying Li
Huiying Li
Cooperat Electronic Tech Co., Limited
Published in : International Journal of Scientific Research and Management (IJSRM) , Vol. 12 No. 11 (2024)

Submission to VIJ 2024-11-29

Keywords

  • Customer Resource Management and Salesperson Behavior Optimization

Copyright (c) 2024 Huiying Li

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This paper explores the importance of Customer Resource Management (CRM) in modern business environments, analyzes common issues faced by traditional salespeople in CRM, and examines how dynamic pricing systems can optimize the utilization of customer resources. Through a detailed case study and comprehensive analysis, the paper demonstrates the effectiveness of dynamic pricing systems in actual applications, providing new approaches and methods for companies to manage customer resources and enhance salesperson behavior.

 

PDF

References

  1. 1. Phillips, R. L. (2021). Pricing and revenue optimization. Stanford university press.
  2. 2. Chen, Y., & Farias, V. F. (2018). Robust dynamic pricing with strategic customers. Mathematics of Operations Research, 43(4), 1119-1142.
  3. 3. Badrinarayanan, V., Ramachandran, I., & Madhavaram, S. (2019). Resource orchestration and dynamic managerial capabilities: focusing on sales managers as effective resource orchestrators. Journal of Personal Selling & Sales Management, 39(1), 23-41.
  4. 4. Nagar, G., & Manoharan, A. (2024). UNDERSTANDING THE THREAT LANDSCAPE: A COMPREHENSIVE ANALYSIS OF CYBER-SECURITY RISKS IN 2024. International Research Journal of Modernization in Engineering Technology and Science, 6, 5706-5713.
  5. 5. Saharan, S., Bawa, S., & Kumar, N. (2020). Dynamic pricing techniques for Intelligent Transportation System in smart cities: A systematic review. Computer Communications, 150, 603-625.
  6. 6. Aviv, Y., Levin, Y., & Nediak, M. (2009). Counteracting strategic consumer behavior in dynamic pricing systems. Consumer-driven demand and operations management models: a systematic study of information-technology-enabled sales mechanisms, 323-352.
  7. 7. Kephart, J. O., Hanson, J. E., & Greenwald, A. R. (2000). Dynamic pricing by software agents. Computer Networks, 32(6), 731-752.
  8. 8. Aydin, G., & Ziya, S. (2009). Personalized dynamic pricing of limited inventories. Operations Research, 57(6), 1523-1531.
  9. 9. Nagar, G. (2024). The Evolution of Ransomware: Tactics, techniques, and mitigation strategies. International Journal of Scientific Research and Management (IJSRM), 12(06), 1282-1298.
  10. 10. Chen, M., & Chen, Z. L. (2015). Recent developments in dynamic pricing research: multiple products, competition, and limited demand information. Production and Operations Management, 24(5), 704-731.
  11. 11. Chen, M., & Chen, Z. L. (2015). Recent developments in dynamic pricing research: multiple products, competition, and limited demand information. Production and Operations Management, 24(5), 704-731.
  12. 12. Levin, Y., McGill, J., & Nediak, M. (2007). Price guarantees in dynamic pricing and revenue management. Operations Research, 55(1), 75-97.
  13. 13. Chen, Y., Farias, V. F., & Trichakis, N. (2019). On the efficacy of static prices for revenue management in the face of strategic customers. Management Science, 65(12), 5535-5555.
  14. 14. Nagar, G. (2024). Leveraging Artificial Intelligence to Automate and Enhance Security Operations: Balancing Efficiency and Human Oversight. International Journal of Scientific Research and Management (IJSRM), 6(07).
  15. 15. Levin, Y., McGill, J., & Nediak, M. (2007). Price guarantees in dynamic pricing and revenue management. Operations Research, 55(1), 75-97.
  16. 16. Karlinsky-Shichor, Y., & Netzer, O. (2024). Automating the b2b salesperson pricing decisions: A human-machine hybrid approach. Marketing Science, 43(1), 138-157.
  17. 17. Narahari, Y., Raju, C. V. L., Ravikumar, K., & Shah, S. (2005). Dynamic pricing models for electronic business. sadhana, 30, 231-256.
  18. 18. Abrate, G., Nicolau, J. L., & Viglia, G. (2019). The impact of dynamic price variability on revenue maximization. Tourism Management, 74, 224-233.
  19. 19. Chen, K., Zha, Y., Alwan, L. C., & Zhang, L. (2020). Dynamic pricing in the presence of reference price effect and consumer strategic behaviour. International Journal of Production Research, 58(2), 546-561.
  20. 20. Lee, S., Illia, A., & Lawson‐Body, A. (2011). Perceived price fairness of dynamic pricing. Industrial Management & Data Systems, 111(4), 531-550.
  21. 21. Nagar, G. The Evolution of Security Operations Centers (SOCs): Shifting from Reactive to Proactive Cybersecurity Strategies.
  22. 22. Zhang, D., & Lu, Z. (2013). Assessing the value of dynamic pricing in network revenue management. INFORMS Journal on Computing, 25(1), 102-115.
  23. 23. Hinz, O., Hann, I. H., & Spann, M. (2011). Price discrimination in e-commerce? An examination of dynamic pricing in name-your-own price markets. Mis quarterly, 81-98.
  24. 24. Nagar, G., & Manoharan, A. (2022). THE RISE OF QUANTUM CRYPTOGRAPHY: SECURING DATA BEYOND CLASSICAL MEANS. 04. 6329-6336. 10.56726. IRJMETS24238.
  25. 25. Gönsch, J., Klein, R., Neugebauer, M., & Steinhardt, C. (2013). Dynamic pricing with strategic customers. Journal of Business Economics, 83, 505-549.