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A Generalized Norton-Bass Model for Multigeneration Product Diffusion and Pricing

发布日期:2016-05-23

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Zhengrui Jiang

爱荷华州立大学副教授

【主讲】爱荷华州立大学副教授Zhengrui Jiang

【题目】多代产品扩散和定价的广义Norton-Bass模型

【时间】2016年5月23日(周一)上午10:00-12:00

【地点】清华经管学院伟伦楼335

【语言】英文

【Speaker】Zhengrui Jiang, Associate professor, Iowa State University

【Title】A Generalized Norton-Bass Model for Multigeneration Product Diffusion and Pricing

【Time】May 23th, 10:00am-12:00pm

【Venue】Room 335,Weilun Building, Tsinghua SEM

【Language 】English

【Organizer】Department of Management Science and Engineering

【Abstract】In most industries, the information technology industry in particular, continuous product development and quality improvement lead to frequent releases of successive product generations. In the first study, we develop a multigeneration diffusion model, named Generalized Norton-Bass (GNB) model, to help understand the diffusion dynamics across product generations and predict future sales. The GNB model provides closed-form expressions for both the number of units-in-use and the adoption rate, and offers greater flexibility in parameter estimation, forecasting, and revenue projection. Empirical results show that the GNB model delivers better performance than previous models both in terms of model fit and forecasting performance. Furthermore, we demonstrate that the GNB model can incorporate the effect of marketing mix variables on the speed of diffusion for all product generations.In the second study, we extend the Generalized Norton-Bass model to incorporate the impact of pricing on multigeneration diffusion and then use the model to derive the optimal pricing policy for two product generations. We analyze two cases in this study: under the first, the price for the first generation remains the same after the introduction of the second generation; under the second, the price of the first generation can change after the second generation enters the market. For both cases, the market potential and production cost of each generation affect the optimal pricing of both generations. For instance, we find that a larger market potential or a higher production cost for the first generation leads to a higher optimal price for the second generation. Under the second case, contrary to popular belief, we find that under some market conditions, the firm can be better off by increasing the price of the old generation after the new generation is introduced.

【Bio】Zhengrui Jiang is an associate professor of information systems and the inaugural holder of the endowed Thome Professorship in Business at the College of Business, Iowa State University. He received his PhD in Management Science from the University of Texas at Dallas. His research projects cover broad areas including technical (design science) IS, economics of IT, and quantitative marketing. His primary research interests lie in business intelligence/analytics, diffusion of innovations, economics of information goods, software engineering, and project management. His research has been funded by the U.S. Agency for International Development (USAID) and National Natural Science Foundation of China (NFSC). He has published in leading academic journals including Management Science, Information Systems Research, IEEE Transactions on Knowledge and Data Engineering, and Journal of Management Information Systems. He currently serves as an associate editor for MIS Quarterly, and is serving or has served as special issue editors for Production and Operations Management and IEEE Transactions on Management Information Systems. In addition, he served as program co-chairs for the 2014 Midwest Association of Information Systems Conference and the 2015 Big XII+ MIS Research Symposium.

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