Abstract
In most studies related to product positioning, probabilistic consumer choice rules assume that a product always gains some market share no matter how small a product's utility value is or even if the utility value is negative. Some researchers have considered this problem in multidimensional-scaling-based model or share-of-surplus choice rule. In this study, we consider this problem for multinomial logit rule by introducing a piecewise function and establishing a conjoint-analysis-based one-step optimization model for product positioning. Interval analysis is applied to obtain the optimal price of the new product from the model, and the mathematical properties of the profit-maximizing model are analyzed. An interval-analysis-embedded Tabu Search (TS) algorithm is developed for solving the model. An industrial application employing the proposed model and the interval-analysis-based enumeration method is presented and sensitivity analysis is performed. An experiment for randomly created large-scale product positioning problems is carried out to evaluate the feasibility of the proposed TS algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 402-413 |
| Number of pages | 12 |
| Journal | Decision Support Systems |
| Volume | 54 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Dec 2012 |
Keywords
- Consumer choice rule
- Interval analysis
- Product positioning
- Tabu search
ASJC Scopus subject areas
- Management Information Systems
- Information Systems
- Developmental and Educational Psychology
- Arts and Humanities (miscellaneous)
- Information Systems and Management