m-Banking Quality and Bank Reputation

Evaluating the Perceived Quality of Mobile Banking Applications in Croatia: An Empirical Study

Mobile banking is nowadays a standard service provided by banks worldwide because it adds convenience for people. There is no more rushing to a bank or waiting in lines for a simple transaction that can be conducted from anywhere and at any time in the blink of an eye. To be consumed by a respective amount of bank clients regularly, mobile banking applications are required to be continuously improved and updated, be in line with recent security standards, and meet quality requirements. This paper tackles the perceived quality of mobile banking applications that are most commonly used in Croatia and has three objectives in that respect. The first one is to identify the extent to which pragmatic and hedonic dimensions of quality contribute to customers’ satisfaction and their behavioral intentions related to the continuous use of mobile banking applications. The second one is to determine if there are significant differences in the perceived quality between users of diverse mobile banking applications as well as between users who belong to different age groups. The last one is to uncover the advantages and disadvantages of evaluated mobile banking applications. For this purpose, an empirical study was carried out, during which data were collected with an online questionnaire. The sample was composed of 130 participants who are representative and regular users of mobile banking applications. The psychometric features of the proposed research model, which represents an interplay of perceived quality attributes, were tested using the partial least squares structural equation modeling (PLS-SEM) method. Differences in the perceived quality among different mobile banking applications and customers of various age groups were explored with Kruskal–Wallis tests. Pros and cons of mobile banking applications were identified with the help of descriptive statistics. Study findings indicate that, in the context of mobile banking applications used in Croatia, feedback quality and responsiveness contribute to the ease of use, usefulness is affected by both ease of use and efficiency, responsiveness has a significant impact on efficiency while ease of use, usefulness, and security of personal data are predictors of customers’ satisfaction which in turn influences their behavioral intentions. While no significant difference exists in the perceived quality of four examined mobile banking applications, we found a significant difference in the perceived quality among three age groups of users of mobile banking applications. The most commonly reported advantages of mobile banking applications were related to facets of their efficiency and usefulness, whereas their main drawback appeared to be the lack of features dealing with the personalization of offered services. The reported and discussed results of an empirical study can be used as a set of guidelines for future advances in the evaluation and design of mobile banking applications.

Predicting standardized absolute returns using rolling-sample textual modelling

Understanding how textual information impacts financial market volatility has been one of the growing topics in financial econometric research. In this paper, we aim to examine the relationship between the volatility measure that is extracted from GARCH modelling and textual news information both publicly available and from subscription, and the performances of the two datasets are compared. We utilize a latent Dirichlet allocation method to capture the dynamic features of the textual data overtime by summarizing their statistical outputs, such as topic distributions in documents and word distributions in topics. In addition, we transform various measures representing the popularity and diversity of topics to form predictors for a rolling regression model to assess the usefulness of textual information. The proposed method captures the statistical properties of textual information over different time periods and its performance is evaluated in an out-of-sample analysis. Our results show that the topic measures are more useful for predicting our volatility proxy, the unexplained variance from the GARCH model than the simple moving average. The finding indicates that our method is helpful in extracting significant textual information to improve the prediction of stock market volatility.