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All Journal Journal of Management and Business Review Journal of Asian Social Sciences Research
Huang, Hui-Hsin
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Expectation Disconfirmation, Ideal Point and Kano Models of Customer Satisfaction: A Comparison Huang, Hui-Hsin
Journal of Asian Social Science Research Vol. 5 No. 2 (2023): JASSR Vol. 5, No. 2, 2023
Publisher : Centre for Asian Social Science Research (CASSR), Faculty of Social and Political Sciences, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jassr.v5i2.79

Abstract

This article compares three customer satisfaction models: expectation disconfirmation, ideal point, and Kano. It depicts the details of the three types of satisfaction stochastic models. A beauty shop's e-commerce database is used as empirical data for parameter estimates and model comparisons. The model calibration uses both root-mean-square deviation (RMSD) and the Chi-square test. The results demonstrate that the expectation disconfirmation model has the maximum fitness in the RMSD index, but the lowest goodness of fit in the Chi-square test. In contrast, the ideal point model produces opposite findings on the RMSD index and the Chi-square test. The expectation model, which has a larger number of parameters than the other two models, can be used for elastic changes to explain varied situational elements of pleasure, but it also requires more data to be stable. However, the ideal point model has a simpler structure than the other two models. There is only one parameter to estimate, which makes it easy to apply. However, it is less accurate than the other two models when measuring dynamic satisfaction.
Investigating the Influence of Indecision on Customer’s Decision Satisfaction Huang, Hui-Hsin
Journal of Management and Business Review Vol 21, No 1 (2024)
Publisher : Research Center and Case Clearing House PPM School of Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34149/jmbr.v21i1.473

Abstract

Indecision behavior usually appears in daily life, especially on purchase occasions. This trait in the decision process will influence customers' decision satisfaction. This research proposes a Bayesian model to portray the phenomena of indecision and decision satisfaction. The decision satisfaction is a random variable with the prior density in which the parameter given in the density function is demonstrated as indecision. The empirical data of Google Analytics is used to measure indecision behavior and model calibration. Finally, the conclusion is shown to make an application in actual consumer behavior research. This research can help managers control the tendency of indecision to achieve higher decision satisfaction. In advance, the impact factors of indecision can be investigated to design more incentive and attractive platforms to accelerate the payment process
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