Strategic Management of New Products: Ex-Ante Simulation and Market Segmentation

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 revealedpreference 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.

Consumer preference structure of online privacy concerns in an IoT environment

“…In this study, the coefficients of all attributes—except for reward—is assumed to follow a normal distribution. The coefficient of reward is assumed to follow a log-normal distribution because generally consumers would have a preference for higher value for reward (Choi et al, 2013; Train & Sonnier, 2005). In summary, in a mixed logit model with this utility function, the choice probability that consumer n will select an alternative j in the choice set t takes the form which is multiplied by the coefficient distribution of the attribute and the choice probabilities of the simple logit model, as shown in equation (4)…”

Capturing heterogeneous decision making processes: the case with the E-book reader market

“…In other words, when the market is segmented based on consumers’ decision-making path, the size of market—or market share—is one of the important factors in the implementation of market segmentation and targeting strategy. Because the proposed statistical model is an extended application of the standard Gaussian mixture model, the market share can be easily evaluated statistically (Choi et al, 2013; Fader, 1993). We can perform statistical inference on market share using the conjugate prior relationship between Dirichlet—a multinomial distribution (see fourth step, Appendix 2).…”

Factores de gestión que permiten una eficiente administración financiera en las universidades privadas, perspectiva teórica

“…Uno de los objetivos de la dirección estratégica en la generación de nuevos productos es que los usuarios gestionen sus transacciones de manera eficiente y con menos riesgo, así los mercados financieros se vuelven más grandes y más líquidos. El medio de pago es más eficiente cuando los costos de transacción de un intercambio económico son bajos (Choi, Shin, & Lee, 2013).…”