Analysis of dynamic pricing scenarios for multiple-generation product lines
详细信息    查看全文
  • 作者:Nil Kilicay-Ergin (1)
    Chun-yu Lin (2)
    Gul E. Okudan (3)

    1. Great Valley School of Graduate Professional Studies
    ; Penn State University ; Malvern ; PA ; 19355 ; USA
    2. Department of Industrial and Manufacturing Engineering
    ; Penn State University ; University Park ; PA ; 16852 ; USA
    3. School of Engineering Design
    ; Department of Industrial and Manufacturing Engineering ; Penn State University ; University Park ; PA ; 16852 ; USA
  • 关键词:Multiple ; generation product lines ; cannibalization ; agent ; based modeling ; dynamic pricing scenarios
  • 刊名:Journal of Systems Science and Systems Engineering
  • 出版年:2015
  • 出版时间:March 2015
  • 年:2015
  • 卷:24
  • 期:1
  • 页码:107-129
  • 全文大小:917 KB
  • 参考文献:1. Arslan, H, Kachani, S, Shmatov, K (2009) Optimal product introduction and life cycle pricing policies for multiple product generations under competition. Journal of Revenue Management 8: pp. 438-451
    2. Bardhan, AK, Chanda, U (2008) A model for first and substitution adoption of successive generations of a product. International Journal of Modeling and Simulation 28: pp. 487-494
    3. Bonabeau, E (2002) Agent-based modeling: methods for first and substitution for simulating human systems. Proceedings of the National Academy of Sciences 99: pp. 7280-7287 CrossRef
    4. Chen, J, Chang, C (2013) Dynamic pricing for new and remanufactures products in a closed-loop supply chain. International Journal of Production Economics 146: pp. 153-160 CrossRef
    5. Danaher, PT, Bruce, GS, Putsis, H, Putsis, WP (2001) Marketing-Mix variables and the diffusion of successive generations of a technological innovation. Journal of Marketing Research 38: pp. 501-514 CrossRef
    6. Desai, P S (2001) Quality segmentation in spatial markets: When does cannibalization affect product line design. Marketing Science 20: pp. 265-283 CrossRef
    7. Druel, C T, Schmidt, G M, Souza, G C (2009) The optimal pace pf product updates. European Journal of Operational Research 192: pp. 621-633 CrossRef
    8. Dobson, G, Kalish, S (1988) Positioning and pricing a product line. Marketing Science 7: pp. 107-125 CrossRef
    9. Edelheit, LS (2004) Perspective on GE research and development. Research Technology Management 47: pp. 49-55
    10. Fruchter, G E, Fligler, A, Winer, R S (2006) Optimal product line design: genetic algorithm approach to mitigate cannibalization. Journal of Optimization Theory and Applications, Vol 131: pp. 227-244 CrossRef
    11. Gallego, G, Wang, R (2014) Multiproduct price optimization and competition under nested logit model with product-differentiated price sensitivities. Operations Research 62: pp. 450-461 CrossRef
    12. Harvey, MG, Kerin, RA (1979) Diagnosis and management of the product cannibalism syndrome. University of Michigan Business Review 31: pp. 18-29
    13. Hernandez, C, Frances, P H (2009) The launch timing of new and dominant multi-generation technologies: An application to the video-game systems market. ERIM Report Series Research in Management.
    14. Holland, J (1992) Complex adaptive systems. Daedalus, A New Era in Computation 121: pp. 17-30
    15. Huang, CY, Tzeng, GH (2008) Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method. Technology Forecasting & Social Change 75: pp. 12-31 CrossRef
    16. Jia, J, Zhang, J (2013) Dynamic ordering and pricing strategies in a two-tier multi-generation durable goods supply chain. International Journal of Production Economics 144: pp. 135-142 CrossRef
    17. Jiang, Z, Jain, D (2012) A generalized norton-bass model for multigeneration diffusion. Management Science 58: pp. 1887-1897 CrossRef
    18. Kim, N, Srivastava, R K, Hand, J K (2001) Consumer decision making in a multi-generational choice set context. Journal of Business Research 53: pp. 123-136 CrossRef
    19. Krankel, R M, Duenyas, I, Kapuscinski, R (2006) Timing successive product introductions with demand diffusion and stochastic technology improvement. Manufacturing and Service Operations Managament. Vol 8: pp. 119-135 CrossRef
    20. Kuo, C, Huang, K (2012) Dynamic pricing of limited inventories for multi-generation products. European Journal of Operations Research 217: pp. 394-403 CrossRef
    21. Li, H, Graves, SC (2012) Pricing decisions during inter-generational product transition. Productions and Operations Management 21: pp. 14-28 CrossRef
    22. Lin, C, Okudan, GE (2011) State-dependent behavioral models for designing a multiple-generation product line. Industrial Engineering Research Conference. Reno. NV.
    23. Lin, C, Okudan, GE (2012) Application of dynamic state variable models for multiple-generation product lines with cannibalization across generations. Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Chicago, IL.
    24. Lin, C, Kilicay-Ergin, N, Okudan, GE (2012) Agent-based modeling of dynamic pricing scenarios to optimize multiple-generation product lines with cannibalization. Proceedings of the Complex Adaptive Systems Conference, Chicago IL, Procedia Computer Science 6: pp. 311-316
    25. Lin, C, Okudan, GE (2013) Planning for multiple-generation product lines using dynamic state variable models with data input from similar products. Expert Systems with Applications 40: pp. 2013-2022 CrossRef
    26. Lin, C, Okudan Kremer, G E (2014) Strategic decision making for multiple-generation product lines using dynamic state variable models: The cannibalization case. Computers in Industry 65: pp. 79-90 CrossRef
    27. Macy, M W, Willer, R (2002) From factors to actors: computational sociology and agent-based modeling. Annual Review of Sociology 28: pp. 143-166 CrossRef
    28. Mahajan, V, Muller, E (1996) Timing, diffusion, and substitution of successive generations of technological innovations: The IBM mainframe case. Technological Forecasting and Social Change 51: pp. 109-132 CrossRef
    29. Mazumdar, T, Sivakumar, K, Wilemon, D (1996) Launching new products with cannibalization potential: an optimal timing framework. Journal of Marketing Theory and Practice 4: pp. 83-93
    30. Meredith, L, Maki, D (2001) Product cannibalization and the role of prices. Applied Economics 33: pp. 1785-1793 CrossRef
    31. Morgan, LO, Morgan, R M, Moore, WL (2001) Quality and time to market trade-offs when there are multiple product generations. Manufacturing & Service Operations Management 3: pp. 89-104 CrossRef
    32. Murphy, D (2011) Windows 7 finally beats Windows XP鈥檚 U.S. desktop share.
    33. Nagle, TT, Hogan, J E, Zale, J (2010) The Strategy and Tactics of Pricing: A Guide to Growing More Profitability. Prentice Hall, New Jersey
    34. Norton, J A, Bass, F M (1987) A diffusion theory model of adoption and substitution for successive generations of high-technology products. Management Science 33: pp. 1069-1086 CrossRef
    35. Ofek, E, Savary, M (2003) R&D, Marketing and the success of next-generation products. Marketing Science 22: pp. 355-370 CrossRef
    36. Schon, C (2010) On the optimal product line selection problem with price discrimination. Management Science 56: pp. 896-902 CrossRef
    37. Srinivasan, S R, Ramakrishnan, S, Grassman, S E (2005) Identifying the effects of cannibalization on the product portfolio. Marketing Intelligence & Planning 4: pp. 359-371 CrossRef
  • 刊物类别:Engineering
  • 刊物主题:Systems and Information Theory in Engineering
    Game Theory and Mathematical Methods
    Operation Research and Decision Theory
    Chinese Library of Science
  • 出版者:Systems Engineering Society of China, co-published with Springer-Verlag GmbH
  • ISSN:1861-9576
文摘
In technology-intensive markets, it is a common strategy for companies to develop long-term multiple generation product lines instead of releasing consecutive single products. Even though this strategy is more profitable than sequentially introducing single product generations, it can also result in inter-product line cannibalization. Cannibalization of multiple-generation product lines is a complex problem that needs to be taken into account at the early product line planning stage in order to sustain long-term profitability. In this paper, we propose an agent-based model that can simulate the potential cannibalization scenarios within a multiple-generation product line. We view a multiple-generation product line (MGPL) as complex adaptive system where each product generation in the MGPL adjusts its sales price over time based on the shifts in the market demand. The proposed model provides insights into how various pricing strategies impact the overall lifecycle profitability of MGPL and can be used to assist companies in developing appropriate dynamic pricing strategies at the early product line planning stages.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700