J
Jianmin Jia
Researcher at The Chinese University of Hong Kong
Publications - 47
Citations - 2854
Jianmin Jia is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Risk perception & Expected utility hypothesis. The author has an hindex of 18, co-authored 40 publications receiving 2431 citations. Previous affiliations of Jianmin Jia include Shenzhen University & Southwest Jiaotong University.
Papers
More filters
Journal ArticleDOI
Population flow drives spatio-temporal distribution of COVID-19 in China.
TL;DR: Modelling of population flows in China enables the forecasting of the distribution of confirmed cases of COVID-19 and the identification of areas at high risk of SARS-CoV-2 transmission at an early stage.
Journal ArticleDOI
What You Don'T Know About Customer-Perceived Quality: the Role of Customer Expectation Distributions
TL;DR: It is shown that some of the most common beliefs about customer-perceived quality are wrong, and a useful simplification of reality is provided that successfully predicts many aspects of the dynamics of consumer response to quality.
Journal ArticleDOI
A Generalized Utility Model of Disappointment and Regret Effects on Post-Choice Valuation
TL;DR: In this article, the authors show that regret can have a significant impact on post-choice valuation, i.e., the negative effect of regret was greater than the positive effect of elation.
Journal ArticleDOI
Simulation techniques for the sensitivity analysis of multi-criteria decision models
TL;DR: This study considers three cases: no information, order information, and partial information regarding the weights of multi-criteria decision models, and proposes a simulation approach that allows simultaneous changes of the weights and generates results that can easily be analyzed statistically.
Journal ArticleDOI
Attribute weighting methods and decision quality in the presence of response error: A simulation study
TL;DR: Simulation results suggest that it will usually be worth the extra time and effort required to assess ratio weights and rank order weights were substantially superior to the equal weights method in all cases studied.