Related Experiment Video
Updated: Aug 20, 2025
04:54
Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq
Published on: March 19, 2021
4.7K
A novel multi-attribute decision-making for ranking mobile payment services using online consumer reviews
Adjei Peter Darko1, Decui Liang1, Zeshui Xu2
1School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China.
Expert Systems with Applications
|November 21, 2022
Summary
The COVID-19 pandemic increased mobile payment (m-payment) use, driven by online reviews. This study introduces a new model using these reviews and decision-making techniques to evaluate and rank m-payment services effectively.
Area of Science:
- Consumer Behavior Analysis
- Decision Science
- Information Systems
Background:
- The COVID-19 pandemic significantly altered consumer behavior, accelerating the adoption and usage of mobile payment (m-payment) services.
- Online consumer reviews (OCRs) play a crucial role in shaping consumer perceptions and usage of m-payment services.
- Evaluating and selecting m-payment services from a vast number of OCRs presents a significant research challenge.
Purpose of the Study:
- To develop a novel decision evaluation model integrating OCRs with multi-attribute decision-making (MADM) and probabilistic linguistic information.
- To identify key m-payment usage attributes from consumer reviews and use them for service evaluation and ranking.
- To provide a robust methodology for informed selection of m-payment services.
Main Methods:
- Extraction of m-payment usage attributes from OCRs using Latent Dirichlet Allocation (LDA) topic modeling.
- Calculation of sentiment scores for extracted attributes using an unsupervised sentiment algorithm.
- Conversion of sentiment scores into probabilistic linguistic elements based on probabilistic linguistic term set (PLTS) theory.
- Development of a probabilistic linguistic indifference threshold-based attribute ratio analysis (PL-ITARA) for attribute weighting.
- Application of a positive and negative ideal-based PL-ELECTRE I methodology for service evaluation and ranking.
Main Results:
- Successfully extracted key m-payment usage attributes from a large corpus of OCRs.
- Quantified consumer sentiment towards specific m-payment attributes using probabilistic linguistic terms.
- Determined attribute weights using the novel PL-ITARA method.
- Ranked m-payment services based on the integrated evaluation framework.
- Validated the proposed model through a case study in Ghana.
Conclusions:
- The proposed decision evaluation model effectively integrates OCRs and advanced MADM techniques for m-payment service selection.
- The methodology provides a quantitative approach to understanding consumer sentiment and its impact on m-payment usage attributes.
- The study offers a practical and applicable framework for consumers and researchers to evaluate and rank m-payment services, particularly in emerging markets.
Related Concept Videos
01:09Decision Making: P-value Method
5.6K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.6K
01:14Decision Making: Traditional Method
4.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.1K
01:20Decision Making
177
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
177
01:21Friedman Two-way Analysis of Variance by Ranks
274
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
274