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ANALYSIS OF dynamic PRICING SCENARIOS FOR MULTIPLE-GENERATION PRODUCT LINES

Journal of Systems Science and Systems Engineering 2015年第1期24卷 107-129页

作者： Nil Kilicay-Ergin Chun-yuLin Gul E.Okudan Great Valley School of Graduate Professional Studies Penn State University Department of Industrial and Manufacturing Engineering Penn State UniversityUniversity Park School of Engineering Design Department of Industrial and Manufacturing EngineeringPenn State UniversityUniversity Park

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.

关键词： Multiple-generation product lines cannibalization agent-based modeling dynamic pricingscenarios

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