Examination of Cover Evaluation Results of Teacher’s Certificate Renewal Classes about Injury Prevention: Application of Text Mining and Customer Satisfaction Analysis

Farmers satisfaction in joining Rice Farming Insurance illustrates the program performance. The satisfaction of Rice Farming Insurance program can be measured through some attributes of satisfaction. Satisfaction attributes are assessed ranging from dissatisfied to very satisfied. This research aimed to determine the level of farmer satisfaction on Rice Farming Insurance program. This research was conducted in January – February 2020. Slovin method used for sampling method with total sample of 100 respondent, consist of 53 respondents were taken in Dukuhwaru District and 47 respondents were taken in Warureja District using proportional allocation. Locations in this research was choose with purposive method. Importance Performance Analysis and Customer Satisfaction Index were used to analyze. The result showed that Farmers were satisfied with the implementation of the Rice Farming Insurance program with CSI score of 79%. The attributes that need to be improved are the compensation requirements, the amount of coverage, the submission procedure, reviewing, and payment procedure of claims, and the time of approval and payment of claims. Those attributes were considered important by farmers yet still have low performance.

Download Full-text

Determining banking service attributes from online reviews: text mining and sentiment analysis

International Journal of Bank Marketing ◽

10.1108/ijbm-08-2021-0380 ◽

2022 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Divya Mittal ◽

Shiv Ratan Agrawal

Keyword(s):

Text Mining ◽

Customer Satisfaction ◽

Sentiment Analysis ◽

Banking Sector ◽

Online Reviews ◽

Socioeconomic Background ◽

Content Type ◽

Customer Reviews ◽

Banking Service ◽

The Interest Rate

PurposeThe current study employs text mining and sentiment analysis to identify core banking service attributes and customer sentiment in online user-generated reviews. Additionally, the study explains customer satisfaction based on the identified predictors.Design/methodology/approachA total of 32,217 customer reviews were collected across 29 top banks on bankbazaar.com posted from 2014 to 2021. In total three conceptual models were developed and evaluated employing regression analysis.FindingsThe study revealed that all variables were found to be statistically significant and affect customer satisfaction in their respective models except the interest rate.Research limitations/implicationsThe study is confined to the geographical representation of its subjects' i.e. Indian customers. A cross-cultural and socioeconomic background analysis of banking customers in different countries may help to better generalize the findings.Practical implicationsThe study makes essential theoretical and managerial contributions to the existing literature on services, particularly the banking sector.Originality/valueThis paper is unique in nature that focuses on banking customer satisfaction from online reviews and ratings using text mining and sentiment analysis.

Download Full-text

Agro-Tourism Customer Satisfaction Analysis Based on the Theory of Attractive Quality

Interdisciplinary Perspectives on Operations Management and Service Evaluation - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-7998-5442-5.ch015 ◽

2021 ◽

pp. 290-312

Author(s):

Maria Lachnidaki ◽

Evangelos Grigoroudis ◽

Constantin Zopounidis

Keyword(s):

Customer Satisfaction ◽

Critical Issue ◽

Large Set ◽

Kano Model ◽

Tourism Sector ◽

Weak Points ◽

Quality Dimensions ◽

Potential Improvement ◽

The Cost ◽

Satisfaction Analysis

Customer satisfaction measurement is an important and critical issue of all businesses in the tourism sector, since it gives a better understanding of the needs and requirements of tourists. The Kano model is one of the most widely used approaches in analyzing customer satisfaction, aiming to categorize the quality attributes of products/services in different quality dimensions. The main aim of this chapter is to analyze customer satisfaction from an agro-tourism farm and prioritize potential improvement actions. The preliminary analysis has identified a large set of customer satisfaction criteria that refer to the location, the personnel, the activities, the cost, and the “green” aspects of the agro-tourism farm. The MUSA method has been applied in the context of Kano's theory of attractive quality. The main results show which satisfaction criteria mostly affect satisfaction and/or dissatisfaction, identifying the strong and the weak points of the farm. Finally, combining the previous results, it is possible to prioritize improvement actions.

Download Full-text

Looking beyond the stars: A description of text mining technique to extract latent dimensions from online product reviews

International Journal of Market Research ◽

10.1177/1470785319863619 ◽

2019 ◽

Vol 62 (2) ◽

pp. 195-215

Author(s):

Frederik Situmeang ◽

Nelleke de Boer ◽

Austin Zhang

Keyword(s):

Text Mining ◽

Customer Satisfaction ◽

Research Methodology ◽

Latent Dirichlet Allocation ◽

Online Reviews ◽

Product Reviews ◽

Marketing Literature ◽

Mining Technique ◽

Online Product Reviews ◽

The Relationship

The purpose of this study is to contribute to the marketing literature and practice by describing a research methodology to identify latent dimensions of customer satisfaction in product reviews, and examining the relationship between these attributes and customer satisfaction. Previous research in product reviews has largely relied only on quantitative ratings, either stars or review score. Advanced techniques for text mining provide the opportunity to extract meaning from customer online reviews. By analyzing 51,110 online reviews for 1,610 restaurants via latent Dirichlet allocation, this study uncovers 30 latent dimensions that are determinants of customer satisfaction. Furthermore, this study developed measurements of sentiment and innovativeness as moderators of the effect of these latent attributes to satisfaction.

Download Full-text

Analyzing the Relationship between Consumer Satisfaction and Fresh E-Commerce Logistics Service Using Text Mining Techniques

Sustainability ◽

10.3390/su11133570 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3570 ◽

Cited By ~ 4

Author(s):

Wei Hong ◽

Changyuan Zheng ◽

Linhai Wu ◽

Xujin Pu

Keyword(s):

Text Mining ◽

Customer Satisfaction ◽

Consumer Satisfaction ◽

Rapid Development ◽

Digital Information ◽

Logistics Service ◽

Communication Reliability ◽

Fresh Products ◽

Mining Model ◽

The Relationship

The rapid development of the Internet and the transformation of consumption patterns have prompted consumers to purchase fresh products online. For fresh e-commerce enterprises, logistics is an important aspect of customer satisfaction. Therefore, this study focused on online review information and used a convolutional neural network text mining model for its analysis. Logistics service elements concerned with customer satisfaction are convenience, communication, integrity, responsiveness, and reliability. Thereafter, comment information was converted to digital information using sentiment analysis. Finally, a correlation analysis was carried out to compare the significance of various influencing factors. The results confirm that convenience, communication, reliability, and responsiveness had a significant impact on customer satisfaction, whereas integrity had none. Fresh e-commerce logistic services need to improve for the development of the companies.

Download Full-text