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This study seeks to observe the association between mobile banking failures, use of m-banking and customer engagement to determine the contribution of user satisfaction towards m-banking as mediator between the aforementioned relationship.

This study proposes a Mobile Banking Failure Model (MBFM) by integrating four failure dimensions (functional, system, information and service) based on Tan's failure model and DeLone and Mclean's Information Success model. In this paper, data was gathered from 338 respondents, who were the customers of banks and regular users of m-banking services of their respective banks in India. A survey method was employed to collect data. Structure equation modelling (SEM) was used to analyse the collected data.

The results suggest that all m-banking failure dimensions (functional, system, information and service) affect the use of m-banking, which in turn affects user satisfaction towards m-banking and customer engagement. Additionally, this study found that user satisfaction towards m-banking acts as a partial mediator between the use of m-banking and customer engagement.

The banking failure and its use by customers have been examined in the context of mobile banking in India only and thereby limits the generalization of results to other industry and country contexts.

The results of this paper will guide bank managers and policy planners in implementing MBFM in the Indian banking context, specifically for their m-banking apps.

The use of m-banking, user satisfaction towards m-banking and customer engagement have been added as three supportive variables to the basic Tan's failure model and DeLone and Mclean's Information Success model to examine the impact of m-banking failure on bank customers' usage behaviour. This is a novel addition to the extant literature, as most empirical works in this domain are from industries other than banking (specifically m-banking) and with differing contexts.

The purpose of this paper is to provide a comprehensive insight into the deciding factors affecting an individual’s intention to adopt mobile banking (m-banking) services in Pakistan.

A survey approach was used with a sample of 189 responses from across Pakistan. Multi-group analysis was performed in order to detect gender differences among men and women in the process of adopting m-banking.

The paper found support for the positive effect of perceived behavioral control (PBC) and attitudes (ATT) toward m-banking adoption intentions. Significant differences between men and women were found to affect subjective norms (SN) on adoption intention, even though the combined sample of men and women was insignificant. The effect of SN on m-banking adoption is stronger for women than for men. Interestingly, the paper provides contradictory findings on the role of PBC on adoption intention. The effect of PBC on m-banking adoption intention was found to be significantly stronger for men than for women.

The results present implications of consumer behavior and marketing communication for bank marketing. Although men and women do not differ in their ATT toward m-banking service adoption in general, the succinct nuance between men and women in terms of the influence of SN and PBC with adoption intention calls for a strategic reorientation of how men and women as consumers of m-banking services should be appropriately segmented, targeted and communicated. The formulation of marketing strategies to target potential consumers and to reinforce the usefulness of m-banking to existing consumers should not be “one size fits all.” The marketing of m-banking services to segments of men and women should be approached strategically in order to increase adoption rates in developing/emerging economies.

This is the first study on m-banking services adoption in Pakistan to examine the role of gender in the innovation adoption process. The differences between the two genders and the insightful results that we found in our study help shed light on the uniqueness of the context. This study is also one of the first to test a combined technology acceptance model and theory of planned behavior model in the context of m-banking adoption in a developing country using a variance-based modeling technique.

The purpose of this paper is to determine barriers jeopardizing the adoption and usage intention of mobile banking (M-banking) in Pakistan and provide deeper insights to fix such deteriorating factors.

Data was collected in countrywide regional headquarters to mark the utmost generalizability of the results, which included seven largest cities of Pakistan. SEM path analysis was used to analyze data collected from Pakistan’s top 5 bank customers incorporating both users and non-users.

Results revealed that lack of awareness, initial trust and compatibility and perceived risk were the core barriers that stood out as obstacles to the adoption and usage of M-banking in Pakistan. It was also approved that having fixed these core barriers would outcome in existing users’ continuity intent besides raising new users’ inclination toward M-banking.

The study has unveiled the core barriers that have so far impeded the adoption and usage of M-banking. There is not a unified position concerning adoption and usage blockades. Factors differ with contexts, markets, time and kinds of innovations. However, this study is unlike past studies that merely studied students within a specified institute in a restricted jurisdiction. This is the first study to have nationally explored adoption and usage issues; thus, it is anticipated to potentially contribute to the prevailing literature especially in Pakistani context where a few studies prevail, addressing M-banking adoption and usage barriers.

The purpose of this paper is to identify and examine the most important factors that could predict the Saudi customer’s continued intention towards adoption of mobile banking.

The proposed conceptual model was based on the technology acceptance model (TAM) and task-technology fit (TTF) model. This is also expanded by considering two additional factors: perceived privacy and perceived security. By using a self-administered questionnaire, the data were collected from a convenience sample of Saudi banking customers from different parts of Saudi Arabia.

The main results based on structural equation modelling analyses supported the impact of perceived privacy, perceived security, perceived usefulness and TTF on the customers’ continued intention to use mobile banking.

The moderation influence of the demographic factors (i.e. age, gender, income level, educational level) was not tested. The data were also collected using a self-report questionnaire; however, it would be more accurate to utilise more statistics from the bank database about the users of m-banking.

This study represents a worthy attempt to test such novel technology (m-banking) in the KSA where there is a scarcity of literature. A considerable theoretical contribution was also made by integrating the TTF model with the TAM in addition to consider privacy and security in one single model. Moreover, considering both perceived privacy and security in the current model creates an accurate picture about the adoption of m-banking especially as there are a limited number of m-banking studies that have considered privacy and security alongside the TTF model and TAM in the same model.

The purpose of this paper is to examine the potential influence of the mobile banking (M banking) servicescape on customer attitude and engagement. The stimulus-organism-response framework was adapted to formulate a conceptual model, in which the M banking servicescape was modelled as an antecedent (stimulus) of customer attitudes towards M banking (organism), in turn directing customer behaviour (response), namely, customer engagement.

A web-based survey of 345 M banking users was conducted to gather data. The structural equation modelling technique was employed to analyse the conceptual model and test the proposed set of hypotheses.

The results of data analyses showed that M banking servicescape is a strong predictor of customer attitude towards M banking, which then influences customer engagement. The findings also demonstrate that customer attitudes towards M banking mediate both the M banking servicescape and engagement.

The extension of servicescape literature from the physical to the online context of M banking provides a notable new realm in which academicians can extend the current paradigms. This study also enhances understanding of potential improvements to customer attitude towards and engagement with M banking.

This paper aims to investigate the barriers for adopting mobile banking services. From a methodological perspective, this paper seeks to build on two widely used models for technology adoption, the Technology Acceptance Model (TAM) and Innovation Diffusion Theory and to test a model that is better able to predict consumers' intention to use mobile banking.

A research model extends the TAM model by additionally examining the effects of compatibility, trust, credibility, perceived risk and cost on behavioural intention. The empirical approach was based on an online survey of 263 young people in Germany, undertaken during August/September 2009. The data were analysed using structural equation modelling.

The results of the study indicated that compatibility, perceived usefulness, and risk are significant indicators for the adoption of m‐banking services. Compatibility not only had a strong direct effect but was also identified as an important antecedent for perceived ease of use, perceived usefulness and credibility. Trust and credibility are crucial in reducing the overall perceived risk of m‐banking.

The results of this study have implications for researchers and practitioners. The proposed model explains 65 per cent of the variance in intention to adopt mobile phone banking, which is more than the 40 per cent of variance typically found in other studies using the TAM. This study provides a basis for further refinement of models to predict technology adoption, in particular the inclusion of compatibility as a predictor of behavioural intention. In terms of behavioural and demographic data, the study focuses on segments of individuals who are most likely to adopt m‐banking.

This study is a systematic review of mobile banking services. Its main objective is to provide a state-of-the-art review of this particular growing type of services. It inventories and assesses the most significant determinants of and barriers to consumers' adoption of mobile banking. Moreover, it identifies the most common consequences of this adoption.

By using three major academic databases (ABI/INFORM global, Web of Science and Business Source Premier), this paper selected 76 manuscripts and produced a systematic review that exposes the main theories, conceptual frameworks and models used to explain consumers' adoption of mobile banking.

The results show that the TAM (technology of acceptance model), followed by the UTAUT (unified theory of acceptance and usage of technology), are still the main conceptual frameworks and models adopted and adapted by scholars to explain consumers' use or intention of using mobile banking. Using the vote counting method, a myriad of antecedents and consequences that are frequently used in the literature of mobile banking are reported. These were categorized into five main perspectives: (1) m-banking attributes-based perspective, (2) customer-based perspective, (3) social influence-based perspective, (4) trust-based perspective and (5) barriers-based perspective.

An integrated model regrouping and relating the five perspectives is proposed, leading to intriguing implications for both academics and practitioners.

The primary purpose of this research is to analyze the online user reviews, where real customer experiences can be observed, with text mining and machine learning approaches, which are seen as a gap in the related literature. This study aims to compare the latent themes uncovered by the topic modeling approach with studies focused on both mobile banking (m-banking) adaptation and service quality features, suggest new aspects and examine the effect of latent topics on customer satisfaction.

This study analyzed 21,526 reviews posted by customers of private and state banks operating in Türkiye. An unsupervised machine learning method, Latent Dirichlet algorithm (LDA), was conducted to reveal topics, and the distribution of all reviews was visualized with the t-SNE algorithm. Random Forest, logistic regression, k-nearest neighbors (kNN) and Naive Bayes algorithms were utilized to predict user satisfaction through the given score.

In total, 11 topics were revealed by considering user reviews based on their experience. Among these topics, perceived usefulness and convenience and time-saving are much more important in the scoring given to m-banking apps. Furthermore, in more detail, seven topics have been identified related to technical and security problems related to m-banking apps.

This paper is a pioneer study regarding the method used and sample size reached in the m-banking literature. The findings also provide fresh insight into the post-Covid-19 era, both academically and practically, by providing new features for mobile bank adoption.

Mobile banking (m-banking) can be defined as a service offered by a bank or any other financial institution that allows the customers of such establishments to carry out a variety of banking operations via a mobile device, such as a mobile phone, tablet or personal digital assistant. The purpose of this paper is to examine factors that influence customers to adopt and subsequently use m-banking services in Ghana using the unified theory of acceptance and use of technology 2 (UTAUT2) model with age, educational level, user experience and gender as moderators.

Using questionnaire survey, the study sampled 300 users of m-banking services in Ghana as respondents. The primary data collected were analyzed using SmartPLS software.

Findings of the study indicate that Habit, Price Value and Trust are the main factors influencing adoption and use of m-banking in Ghana. Individual differences of gender, age, educational level and user experience responded differently as they moderate the relationship between UTAUT2 constructs and use bahaviour. The applicability of UTAUT2 model was confirmed in the context of the research.

M-banking is a new phenomenon in Ghana’s financial industry, thus it is imperative to understanding the customer adoption behavior. The outcome will aid financial institutions to develop strategies that will sustain the interest of consumers to embrace m-banking.

This paper is among the first ever known attempts to examine m-banking adoption in Ghana using UTAUT2 model.

The extended unified theory of acceptance and use of technology (UTAUT2) model has been adapted and applied by scholars to gain insight into mobile banking (m-banking) usage. By combining three perspectives, UTAUT2, gamification (GM) and generational cohort theory, this study aims to investigate the factors which impact m-banking usage and examine the moderating effect of generations Y and Z on the relationship between GM and intention to use m-banking.

The adopted model was tested in a quantitative study by using partial least square structural equation modelling. A total of 380 valid questionnaires from a transition country, Albania, have been examined.

In the study, scientific evidence concerning the UTAUT2 model and GM elements are provided. Thus, facilitation conditions, habit and hedonic motivation were found to be significant determinants of GM. Moreover, the results revealed that age moderates the relationship between GM and behavioural intention (BI). Compared to generation Z, individuals born prior to 1996 (generation Y), exhibited a much stronger relationship.

Although Albania bears similarities with other transition countries in terms of regional, economic and political environments, the generalisation of these results to another context is rather limited.

This paper offers a model integrating UTAUT2, GM and generational cohorts in the context of a transition country. The findings can be applied in the form of guidelines for a number of financial institutions.

Besides identifying the determinants of m-banking adoption and GM, this study notably reveals the importance of generational cohorts because it governs the effect of GM on m-banking BI.