{"title":"Why are consumers dissatisfied? A text mining approach on Sri Lankan mobile banking apps","authors":"Maas Sherina Sally","doi":"10.1108/ijicc-02-2023-0027","DOIUrl":null,"url":null,"abstract":"PurposeThe motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ratings. Thus, these causes lead to the dissatisfaction of customers. Additionally, these insights reflect the overall rating of the app and it is a source of information to the executive management to contemplate on their services and take timely and effective decisions to improve their mobile app.Design/methodology/approachThis research was conducted on ten reputed Sri Lankan mobile banking apps to analyze the textual opinions of the customers. Data were collected from the Google Play Store considering the higher Android consumers in Sri Lanka. Each review was automatically classified into a relevant sentiment (positive, negative or neutral). These classified reviews were examined along with its rating to identify any discrepancies. The trends of the positive and negative reviews of each app were observed separately along with time. Topic modeling techniques were used to identify the causes of such behavior.FindingsAlthough banks expect to perpetuate good customer reviews all the time, there were aberrant negative trends observed during certain time ranges. The results revealed that unstable versions after recent updates, bad customer service, erroneous functional and nonfunctional features are the root causes toward the dissatisfaction of the customers.Originality/valueNo previous study has been done on the textual reviews of Sri Lankan mobile banking apps. Most studies had considered analyzing the reviews of the app on the entire period of its usage, whereas this research finds the trends where negative reviews surpass the positive reviews and analyze the causes of such behavior.","PeriodicalId":45291,"journal":{"name":"International Journal of Intelligent Computing and Cybernetics","volume":" ","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Computing and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijicc-02-2023-0027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 1
Abstract
PurposeThe motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ratings. Thus, these causes lead to the dissatisfaction of customers. Additionally, these insights reflect the overall rating of the app and it is a source of information to the executive management to contemplate on their services and take timely and effective decisions to improve their mobile app.Design/methodology/approachThis research was conducted on ten reputed Sri Lankan mobile banking apps to analyze the textual opinions of the customers. Data were collected from the Google Play Store considering the higher Android consumers in Sri Lanka. Each review was automatically classified into a relevant sentiment (positive, negative or neutral). These classified reviews were examined along with its rating to identify any discrepancies. The trends of the positive and negative reviews of each app were observed separately along with time. Topic modeling techniques were used to identify the causes of such behavior.FindingsAlthough banks expect to perpetuate good customer reviews all the time, there were aberrant negative trends observed during certain time ranges. The results revealed that unstable versions after recent updates, bad customer service, erroneous functional and nonfunctional features are the root causes toward the dissatisfaction of the customers.Originality/valueNo previous study has been done on the textual reviews of Sri Lankan mobile banking apps. Most studies had considered analyzing the reviews of the app on the entire period of its usage, whereas this research finds the trends where negative reviews surpass the positive reviews and analyze the causes of such behavior.