Journal article
Modeling relationships between retail prices and consumer reviews: A machine discovery approach and comprehensive evaluations
Decision Support Systems, Vol.145, p.113536
06/2021
DOI: 10.1016/j.dss.2021.113536
Abstract
Setting the retail price as a part of marketing would affect customers' cognition regarding products and affect their post-purchase behavior of review writing. To deeply understand the relationships between retail prices and reviews, this paper designs an intelligent data-driven Generate/Test Cycle using a machine learning technique to automatically discover the relationship model from a huge amount of data without a prior hypothesis. From a unique dataset, various free-form relationship models with their own structures and parameters have been discovered. By the comprehensive evaluations of candidate models, a guided map was offered to understand the relationship between dynamic retail prices and the volume/valence of reviews for different types of products. Experimental results show that 37.69% of products in our sample exhibit the following trend: When the price is increased to a certain level, the volume of reviews shifts from a decreasing trend to an increasing trend. Results also demonstrate that a linearly increasing relationship model between prices and the valence of reviews is more suitable for the low-involvement products than for the high-involvement products. In addition to the new findings, this research provides a powerful tool to assist domain experts in building relationship models for decision making in a highly efficient manner.
•A novel data-driven Generate/Test Cycle was designed to automatically discover feasible models.•A Monte Carlo simulation was performed to validate the designed approach.•Models were built to describe relationships between retail prices and reviews for one product at the individual level.•A guided map was offered by using the comprehensive evaluations of the candidate models.
Details
- Title: Subtitle
- Modeling relationships between retail prices and consumer reviews: A machine discovery approach and comprehensive evaluations
- Creators
- Xian Yang - Dongbei University of Finance and EconomicsGuangfei Yang - Dalian University of TechnologyJiangning Wu - Dalian University of TechnologyYanzhong Dang - Dalian University of TechnologyWeiguo Fan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Decision Support Systems, Vol.145, p.113536
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.dss.2021.113536
- ISSN
- 0167-9236
- eISSN
- 1873-5797
- Grant note
- DOI: 10.13039/501100001809, name: National Natural Science Foundation of China
- Language
- English
- Date published
- 06/2021
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380443002771
Metrics
3 Record Views