FinMARS: A Mobile App Rating Scale for Finance Apps

Mobile apps increasingly replace face-to-face interactions between financial service providers and their customers. Therefore, it is critical for developers of finance apps to understand users' perception thereof, and to be able to assess the quality of their own app and their competitors' apps. Star ratings as provided by mobile app stores suffer from multiple shortcomings and are not detailed enough to fulfil this purpose. In this work, we thus developed a reliable, objective, multidimensional measure of the quality of mobile finance apps, which includes both generic and domain-specific aspects. We used an iterative approach and expanded on related work in the Health domain, and validated the scale empirically. The resulting app rating scale for finance apps is a reliable, objective measure of app quality, comprised of six subscales and a total of 34 items. It exhibits excellent internal consistency (alpha=.93) and very good interrater reliability (ICC=.74).

[1]  Harald C. Gall,et al.  Analyzing reviews and code of mobile apps for better release planning , 2017, 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER).

[2]  M. Kuehnhausen,et al.  Trusting smartphone Apps? To install or not to install, that is the question , 2013, 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA).

[3]  Ahmed E. Hassan,et al.  An Examination of the Current Rating System used in Mobile App Stores , 2017 .

[4]  Stoyan R. Stoyanov,et al.  Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS) , 2016, JMIR mHealth and uHealth.

[5]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[6]  Elgar Fleisch,et al.  What People Like in Mobile Finance Apps: An Analysis of User Reviews , 2018, MUM.

[7]  Ross P. Buckley,et al.  The Evolution of Fintech: A New Post-Crisis Paradigm? , 2015 .

[8]  Walid Maalej,et al.  On the automatic classification of app reviews , 2016, Requirements Engineering.

[9]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[10]  Ning Chen,et al.  AR-miner: mining informative reviews for developers from mobile app marketplace , 2014, ICSE.

[11]  Ahmed E. Hassan,et al.  What Do Mobile App Users Complain About? , 2015, IEEE Software.

[12]  Xin Li,et al.  What in Consumer Reviews Affects the Sales of Mobile Apps: A Multifacet Sentiment Analysis Approach , 2015, Int. J. Electron. Commer..

[13]  Heikki Karjaluoto,et al.  Mobile banking adoption: A literature review , 2015, Telematics Informatics.

[14]  Oksana Zelenko,et al.  Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps , 2015, JMIR mHealth and uHealth.