Strategic management of new products Ex-ante simulation and market segmentation
- Authors
- Choi, Jae Young; Shin, Jungwoo; Lee, Jongsu
- Issue Date
- Mar-2013
- Publisher
- MARKET RESEARCH SOC
- Citation
- INTERNATIONAL JOURNAL OF MARKET RESEARCH, v.55, no.2, pp.289 - 314
- Indexed
- SSCI
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF MARKET RESEARCH
- Volume
- 55
- Number
- 2
- Start Page
- 289
- End Page
- 314
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/163162
- DOI
- 10.2501/IJMR-2013-024
- ISSN
- 1470-7853
- Abstract
- Among various methodologies for demand forecasting of new products, the random-coefficient discrete-choice model using stated preference data is considered to be effective because it reflects heterogeneity in consumer preference and enables the design of experiments in the absence of revealed-preference data. Based on estimates drawn from consumer preference data by structural hierarchical Bayesian logit models, this study develops the overall, strategic, demand-side management for new products by combining market share simulation and a rigorous clustering methodology, the Gaussian mixture model. It then applies the process to the empirical case of electronic payment instruments.
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