Journal of Internet Banking and Commerce ISSN: 1204-5357
ISSN: 1204-5357
+44-175-271-2024Mehreen Malik*
Hailey College of Banking & Finance, University of the Punjab, Lahore, Pakistan
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The purpose of this review article is to execute and present a comprehensive and systematic literature review of research articles which have used UTAUT models (classic or extended) for studying factors effecting the adoption of internet and mobile banking from 2015 to April 2020 in developing countries.
UTAUT, UTAUT2, Electronic Banking, Mobile Banking, Internet Banking, E-Banking, M-Banking
The world is moving towards the ever-growing trend of technological adoption. Advancement in technology is far behind from what it used to be, global leaders are paving their ways for the adoption and usage of latest technologies [1]. Among other sectors, financial sector -especially banking sector is following this emerging trend and has introduced electronic/internet banking and mobile banking. In this article internet banking refers to the “availability of banking products and services via an electronic platform, such as an internet browser or a phone application” [1] while mobile banking refers to the banking activities which can be performed using mobile phones devices [3].The usage and acceptance of the internet and mobile banking among its users is increasing day by day but still it has not been fully adopted and accepted by its users. During the last two decades the consumer acceptance of internet and mobile banking technology, their actual usage and factors influencing their adoption is studied widely. The adoption and usage of technology is studied widely with the help of numerous theoretical models [4,5]. There are numerous theoretical models which have been used extensively in previous researches for studying human behavior towards the adoption of IS especially in internet and mobile banking.Researchers have developed many theories for studying the human behavior towards the usage and adoption of internet and mobile banking. In literature, there are eight prominent theories, each of these theories have pivotal role in the formation of “unified” theory. In order to progress towards unified theory of acceptance and use of technology (UTAUT) theory it is mandatory to “review and synthesis” the major theoretical models [6].The Innovation Diffusion Theory (IDT) studied the behavior of users and it has five main constructs: relative advantage, compatibility, complexity, trialability, and observability [7]. Theory of Reasoned Action (TRA) is the dominant theory used in various studies for studying human behavior of towards technology adoption [8,51]. Theory of Planned Behavior (TPB) is derived out of TRA with the addition of new construct of Perceived Behavioral Control and this theory was mainly used for studying human intentions and behaviors [9,10]. Technology Acceptance Model (TAM) has two main variables of perceived usefulness and ease of use, this model is comprehensively used in many studies of human behavior towards technology adoption [11]. TAM2 is an extension of TAM which includes an analysis of how the technology is perceived as useful and how the subjective norm impacts the usage intent [12]. Combined TAM-TPB is the model developed from the constructs of two main theories i.e. TAM and TPB, the main purpose of combining two theories was to do an advanced and improved research [13,52].Social Cognitive Theory (SCT) is mainly used on large scale, especially in the studies related to computer usage and its utilization [14]. Model of PC Utilization (MPCU) was primarily used for studying PC utilization and this theory is developed out of Theory of Human Behavior [15]. For studying human behavior in the field of Information and Communication Technology Motivational Model (MM) is used prominently [53]. In IT adoption and usage, the latest, most comprehensive and significantly used theory is Unified Theory of Acceptance and Use of Technology (UTAUT), which is a unified form of eight above mentioned theories. This model is used and tested extensively due to its thoroughness over the existing technological acceptance models [16,17]. “The tenants of UTAUT theory hold that the acceptance of research incorporates a series of four moderates that can be used to assess dynamic influences. These dynamic influences include organizational context, user experience, and demographic characteristics.” [1]. This model has four main variables Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions and two additional variables for studying the human intention and usage i.e., Behavioral Intention and Usage Behavior. These constructs are moderated by age, experience and voluntariness to use [18]. It is emphasized by various researchers [19] to use this model, as comparing to other IT models, only a little research is available on this model. The same UTAUT model was extended [16] which is named UTAUT2 with additional three constructs namely, hedonic motivation, price value, and habit.These two models (UTAUT & UTAUT2) have been employed widely in technology adoption researches for studying human behavior and intention to use that technology. This model is not only used in internet and mobile banking studies but also in the spectrum of e- government, e- health, e- education, hospital information system, tax payment system, internet, websites, mobile banking and technology [20]. Nonetheless, keeping in mind the larger acceptability and usage of these models in various dimensions, no study from 2015 to date has further explored the usage, findings, limitations and potential future research in particular reference to usage of UTAUT & UTAUT2 for studying the factors influencing the adoption of internet and mobile banking. Keeping in mind the other research reviews on UTAUT models [5,20,22,40], in conjunction, this study is likely to be of value which can assist researchers with particular reference to factors influencing the adoption of internet and mobile banking using UTAUT & UTAUT2 theory. This present study would help to understand the prior UTAUT- related findings in internet and mobile banking and would provide future research endeavors. The objective of this research is therefore, to provide such a review.
Internet and mobile banking - the emerging technologies- are not fully adopted in many developing countries. Many studies have been conducted for studying the factors influencing the adoption of internet and mobile banking based on UTAUT models. Therefore, it is an attempt to provide the literature review to bring all relevant research together and to provide an opportunity for the future research. For this review 140 research articles were downloaded and studied initially; 100 articles were excluded because they did not fall in to the selection criteria. Out of 40 articles 28 articles were included in this review because they exclusively studied the factors effecting the adoption of internet and mobile banking using UTAUT models (classic or extended) in developing counties. According to [16] there are three different forms of research based on UTAUT models:
1: Classic UTAUT models, with the same exogenous variables that were used in the original study without any additional exogenous variables.
2: Extended UTAUT models, with the same exogenous variables that were used in the original study, along with some newly proposed exogenous variables
3: Partial UTAUT models, with a part of the exogenous variables used in the original study.
This review article has used Classic and Extended models research approach. There are many methods available in literature for writing review articles. This research has used the approach of [2] for positioning the Internet and mobile banking adoption in the literature (figure 1). Internet and mobile banking literature can be studied from the perspective of retail banking services, distribution channels, institutions viewpoint and the customer viewpoint. The systematic review of adoption can be further divided in the three main groups of papers, Descriptive, Relational and Comparative. This research has applied descriptive studies technique. According to [23,25] descriptive research is the “extract from each study certain characteristics of interest, such as publication year, research methods, data collection techniques, and direction or strength of research outcomes (e.g. positive, negative, or non-significant) in the form of frequency analysis to produce quantitative results”. There are strengths and weaknesses of this type of review for example [24] preferred meta-analysis review because it is more powerful while on the other hand descriptive method helps to “identify any interpretable trends or draw overall conclusions about the merits of existing conceptualizations, propositions, methods or findings” [25]. The author of this review has adopted the descriptive approach and has written a review with complete focus on the research articles which have employed UTAUT & UTAUT2 (either classic model or extended model) for studying the factors influencing the adoption of internet and mobile banking.
Figure 1: Positioning of IB within the literature.
This study has reviewed the research articles which have studied the factors influencing the adoption of internet banking & mobile banking using UTAUT & UTAUT2 (either classic model or extended model) from 2015 to April 2020 in developing countries. A comprehensive electronic research has been conducted by using search engines like Google Scholar, Yahoo, Base and ProQuest. This research has used the keywords of “Unified theory of Acceptance and Use of Technology”, “UTAUT”, “Unified theory of Acceptance and Use of Technology 2” “UTAUT” and “Factors influencing/effecting the adoption/usage of internet banking, Electronic/E-Banking or Mobile/M-Banking” for finding topic-based research articles. To represent the highest level of research, conference papers, master thesis, doctoral thesis, unpublished research work and books were excluded. Different types of journals publications (peer-reviewed, published, in press) were all included. There were 28 out of 140 articles which were selected for writing this review article. These articles have been published in famous journals. Journal of Internet Banking & Commerce (JIBC) was on top of the list with four articles on the specified topic.
Source of data by Country
The findings of this research revealed that there were total 13 countries (developing countries) where the UTAUT models-based research has been conducted from 2015 to April 2020 for studying the factors affecting the adoption of internet and mobile banking. Primary data has been used in all these countries for data collection. By far, according to figure 2, the most studies were conducted in Pakistan capturing the 36% of total followed by Indonesia and India with 11%, Jordan and Thailand 7%, and remaining 10% cumulatively in Taiwan, Bangladesh, Brazil, Fiji, Lebanon, Zambia, Philippines and Nigeria.
Figure 2: Countries Used for Data Collection.
Frequency of Publications
This study has reviewed the research articles which have investigated the factors affecting the adoption of internet & mobile banking based on UTAUT models from the year 2015 to April 2020. This review has found an increasing trend in the usage of UTAUT models specifically with reference to mobile banking and internet banking. The findings indicated that there were two research articles in 2015, four research articles in 2016. Five articles in each 2017 and 2018. A peak was seen in the year 2019 with total nine articles. For the year 2020 there are three articles so far. It is assumed that this UTAUT-related research trend for studying the factors affecting the adoption of internet & mobile Banking would continue to rise.
Methodological Analysis
Methodological analysis (Table 1) revealed that all studies have used cross-sectional research approach. Majority of the studies have applied the survey/questionnaire method for data collection while [26] have used the Delphi method and the study [27] has used mixed method approached for data collection. The most commonly used data analysis methods were SEM, SEM-AMOS, SPSS, ANOVA and Factor Analysis. Additionally, analysis tools like SMART PLS, SPSS, AMOS and LISREL were frequently used.
Table 1: Methodological Analysis.
| Procedure | Description | Reference |
|---|---|---|
| Research Technique | Cross Sectional | De Sena et al., (2016), Sarfraz (2017), Alalwan (2018), Malik M., (2020), Iskandar et al., (2020) |
| Collection of Data | Survey/Questionnaire Delphi Method Mixed Method |
Huang & Kao (2015), Johar & Suhartanto (2019), Bhatiasevi (2016) |
| Analysis Technique | Structural Equation Modeling (SEM) SEM – AMOS SPSS 16.0 SPSS 20 ANOVA FACTOR ANALYSIS |
Abbas et al., (2018), Tarhini et al., (2016), Malik M., (2020), Rahi et al., (2019) |
| Software | SPSS AMOS SMART PLS LISREL |
Malik M., (2020), Rahi et al., (2019), Daka, & Phiri (2019), Iskandar et al., (2020) |
Internet & Mobile Banking Usage
The analysis of 28 subject specific studies revealed that 54% of research articles have used UTAUT models (either classic or extended) for studying the factors effecting the adoption of internet banking whilst 46% of research articles have used UTAUT models (either classic or extended) for studying the factors effecting the adoption of mobile banking. Figure 3.
Figure 3: Internet & Mobile Banking Usage.
Comparison of studies based on UTAUT models
The findings of 28 studies disclosed that from 28 research articles, 15 were on internet banking which have employed base-line UTAUT models for studying the factors effecting its adoption. The analysis of these 15 (54% internet banking) research articles revealed that 67% of these studies have extended the UTAUT model (figure 4) while more than a quarter of these studies have used the classic UTAUT model. Surprisingly, the studies which have integrated classic UTAUT2 is zero percent. The studies which have extended UTAUT2 contributed the percentage of 6%. The remaining 13 research articles were on m-banking which have employed UTAUT models for studying the factors effecting its adoption. The analysis of 13 (46% mobile banking) research articles represented that nearly 70% of studies have extended UTAUT model (figure 5) while only 8% studies employed the classic UTAUT model. The studies which have used classic UTAUT2 and extension UTAUT2 shared the percentages of 8% and 15% respectively. The overall analysis of this part showed a clear picture that these 2 models of UTAUT and UTAUT2 need further improvement and it is now time for the prospective researchers to develop a more comprehensive theory, all encompassing, for studying the adoption of internet banking or mobile banking.
Figure 4: Statistics of internet banking studies.
Figure 5: Statistics of mobile banking studies.
Extended UTAUT Variables
The analysis of figure 4 and figure 5 exhibited that 67% of the studies have used extended UTAUT model for investigating the factors effecting the adoption of internet banking while nearly 70% of the studies have used extended UTAUT model for investigating the factors effecting the adoption of mobile banking. Table 2 has presented a list of frequently used variables which have been utilized by various researchers for extending their UTAUT models in this specific field of research. The analysis showed that most recurring variable was Perceived risk which has occurred five times in different studies [1,28-31]. The frequent occurrence of risk factor has made it clear that the customers of IT adoption are more concerned about risk factor. The second repeatedly used variable was Website design which has been added in 4 distinct studies [32-35] The variables of Task Technology Fit [17,36,37] , Perceived Credibility [27,37,38], Perceived Cost [27,28,39] and Trust [1,21,29] have appeared three times equally in different research articles. The variables Assurance, Reliability, Customer service were used repeatedly in three individual studies [33,34,35]. The all-inclusive analysis has represented that among other variables (table 3) which have been used for extending UTAUT models, nine variables (table 2) have been used most frequently. This review suggests that these variables could be made a permanent part of either UTAUT models or could be used as variables for a new theory which would be for internet banking and mobile banking adoption studies.
Table 2: List of extended UTAUT Variables.
| Variables | No.of Studies | Authors |
|---|---|---|
| Perceived Risk | 5 | De Sena et al., (2016), Sarfraz (2017), Alalwan (2018), Malik M., (2020), Iskandar et al., (2020) |
| Website Design | 4 | Giri & Wellang (2016), Rahi et al., (2019), Rahi et al., (2019), Rahi et al., (2019) |
| Task Technology Fit | 3 | Ahmed et al., (2017) Abbas et al., (2018) Tarhini et al., (2016) |
| Perceived Credibility | 3 | Tarhini et al., (2016), Bhatiasevi (2016), Gupta et al., (2019) |
| Perceived Cost | 3 | De Sena et al., (2016), Bhatiasevi (2016), Raza et al., (2019) |
| Trust | 3 | Sarfraz (2017), Khan et al., (2019), Malik M., (2020) |
| Assurance | 3 | Rahi et al., (2019), Rahi et al., (2019), Rahi et al., (2019) |
| Reliability | 3 | Rahi et al., (2019), Rahi et al., (2019), Rahi et al., (2019) |
| Customer Service | 3 | Rahi et al., (2019), Rahi et al., (2019), Rahi et al., (2019) |
Table 3: Summary of findings.
| Authors / Source | Theory | Country | Research Purpose | Main Variables | Extension of UTAUT/ UTAUT2 | Methodology | Results |
|---|---|---|---|---|---|---|---|
| Abbas et al., (2018) | UTAUT | Pakistan | To analyze user perception towards mobile banking adoption with concentration of “TTF” task technology fit and “UTAUT” | performance expectancy, effort expectancy, facilitating conditions, social influence, Task Technology fit (TTF) | Task Technology Fit | Questionnaire | They found positive relationship of Task Technology fit, performance expectancy, effort expectancy, facilitating conditions, social influence with the user intention to adopt technology. |
| Ahmed et al., (2017) |
UTAUT | Bangladesh | Integrated task technology fit (TTF) and UTAUT for examining users' perception and intentions to adopt m-Banking services | Task-technology fit, Performance expectancy, effort expectancy, social influence, facilitating conditions, | Task Technology Fit | Questionnaire | The research revealed that Social influence is significant factor in adopting m-Banking. Additionally, Task-technology fit, Technology characteristics, Performance expectancy facilitating conditions, Task characteristics, and User adoption have great impact on attitude towards mobile banking services. |
| Alalwan et al., (2018) | UTAUT 2 | Jordan | To identify the factors influencing Jordanian customers' intentions and adoption of Internet banking. | Performance expectancy, effort expectancy, hedonic motivation, price value, perceived risk, social influence & behavioral intention. | Extended UTAUT2 by adding “Perceived Risk” | Survey Questionnaire | Positive influence of performance expectancy, effort expectancy, hedonic motivation, price value and perceived risk on behavioral intention except, social influence |
| Bhatiasevi (2016) |
UTAUT | Thailand | Studied the factors effecting the adoption of mobile banking | performance expectancy, effort expectancy, facilitating conditions, social influence, behavioral intention, perceived credibility, perceived cost, and perceived convenience. | perceived credibility, perceived cost, and perceived convenience. | Mixed method approach | Results revealed that performance expectancy, effort expectancy, social influence, perceived credibility, perceived convenience, and behavioral intention to use mobile banking have positive relationship while hypotheses testing cost and facilitating conditions in the adoption of mobile banking were not significant |
| Boonsiritomachai, & Pitchayadejanant, (2017) | UTAUT | Thailand | Determined the factors affecting behavioral intention to adopt mobile banking among generation Y | performance expectancy, effort expectancy, facilitating conditions, social influence, Security, Self-Efficacy, used hedonic motivation has mediator | Security, Self-Efficacy, used hedonic motivation has mediator | Questionnaire | According to the study findings, facilitating conditions and self-efficacy in mobile banking application do not exhibit a direct effect on behavioral intention, they have a positive effect on hedonic motivation. In addition, security factor has a negative effect on hedonic motivation. |
| Daka, & Phiri (2019) | UTAUT | Zambia | Determined the factors underlying the adoption of e-banking | performance expectancy, effort expectancy, facilitating conditions, social influence | -- | Questionnaire | significant impact of performance expectancy, effort expectancy, facilitating conditions and behavior intention in the adoption of e-banking services. Social influence (SI) was non-significant to the user’s intention to adopt e banking services. |
| De Sena et al., (2016). | UTAUT | Brazil | evaluated the adoption of future mobile payment service using UTAUT. | performance expectancy, effort expectancy, social influence, perceived risk and perceived cost | perceived risk and perceived cost | Questionnaire | The results revealed that performance expectation, effort expectation, social influence and perceived risk have positive influence on behavioral intention while the opposite was true for Perceived cost |
| Giri & Wellang, (2016) | UTAUT | Indonesia | determined the effect of expectancy effort, social influence, performance expectancy, website design, experience on the usage of Internet banking | performance expectancy (as mediator), effort expectancy, social influence, website design, prior experience | website design, prior experience | Questionnaire | Results revealed that performance expectancy has a significant effect on effort expectancy and social influences in the adoption of e-banking. Website design has impact on the usage of e-banking. Prior experience has in effort expectancy in the adoption of e-banking. |
| Gupta et al., (2019) | UTAUT | India | Studied the factors influencing the behavioral intention to adopt banks services | performance expectancy, effort expectancy, facilitating conditions, social influence, perceived credibility, | perceived credibility | Questionnaire | The results revealed that all factors are direct determinants of behavioral intention additionally there is still need of improvement and the constructs like hedonic motivation, perceived risks and trialability would be a good path for future |
| Huang & Kao (2015) | UTAUT2 | Taiwan | Explored and predicted the intentions and use behaviors of mobile banking devices like Phablets. | performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, price value, social influence, habit behavioral intention | -- | Delphi Method | The results revealed that behavioral intention, hedonic motivation, and performance expectancy are the most important dimensions in the adoption if mobile banking technology |
| Iskandar et al., (2020) | UTAUT2 | Indonesia | Investigated factors influencing behavioral intention to use Mobile banking | performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, price value, social influence, experience, perceived risk and observability | perceived risk and observability | Questionnaire | The results revealed, observability, performance expectation, hedonic motivation, facilitating conditions have significant impact on behavior intentions while perceived risk, and price value have negative impact on behavior intention. |
| Johar & Suhartanto (2019) | UTAUT | Indonesia | Identified the factors effecting online internet banking from the customers of Islamic Banking | performance expectancy, effort expectancy, facilitating conditions, social influence, religiosity | Religiosity | Questionnaire | The results revealed that expected performance and religious factor are the most important factors for Islamic banking customers to adopt online services |
| Khan et al., (2017) |
UTAUT 2 | Pakistan | Identified the key elements in the adoption of e-banking in developing country | performance expectancy, effort expectancy, hedonic motivation, price value, perceived security, social influence, habit behavioral intention. Moderating role of Individualism/Collectivism and uncertainty avoidance | Extended UTAUT 2 by adding perceived security and Individualism/Collectivism and uncertainty avoidance as moderator | Survey Questionnaire | performance expectancy, facilitating conditions, habit, perceived security, and price value have positive influence on behavioral intentions. The cultural dimensions, collectivism, and uncertainty avoidance were significant moderators in explaining behavioral intention and usage behavior for online banking. |
| Khan et al., (2019) |
UTAUT | Pakistan | Identifying key factors effecting the adoption of e-banking in rural areas of Pakistan | performance expectancy, effort expectancy, facilitating conditions, social influence, personality openness and trust as moderator | Added Personality openness and use trust as a moderator between behavioral intention and usage | Survey Questionnaire | performance expectancy, social influence, and effort expectancy have significant and positive impact on behavioral intentions of rural customers in Pakistan. Moreover, personality openness significantly shapes behavioral intentions and trust on the internet moderates between customers’ intentions and their usage of e-banking. |
| Malik M., (2020) |
UTAUT | Pakistan | Identified the elements influencing the adoption of e-banking | performance expectancy, effort expectancy, facilitating conditions, social influence, security, risk and trust | Extended model by adding security, risk and trust | Survey Questionnaire | significant impact of performance expectancy, effort expectancy, facilitating conditions, social influence, security, risk and trust on behavior intention and actual usage in the adoption of e-banking services. |
| Morales & Trinidad (2019) |
UTAUT | Philippines | Investigated the digitization of mortgage banking using the UTAUT | performance expectancy, effort expectancy, facilitating conditions, social influence and behavioral intention | -- | Survey Questionnaire | Results revealed that determinants of behavioral intention to adopt digital mortgage banking were facilitating conditions, performance expectancy and effort expectancy. |
| Olasina (2015) |
UTAUT | Nigeria | Identified factors influencing m-banking adoption in Nigeria | Perceived usefulness, perceived ease of use, social influence, ICT skills and behavioral intention | modified | Survey Questionnaire | Findings depicted the positive correlation between customer service, type of bank and perceived ease of use and the use of m-banking. |
| Rahi et al., (2018) |
UTAUT | Pakistan | Investigated the role of unified theory of acceptance and use of technology (UTAUT) in internet banking adoption context | performance expectancy, effort expectancy, facilitating conditions, social influence | -- | Questionnaire | findings confirmed that all four variables performance expectancy, effort expectancy, social influence and facilitating condition had significant amount of variance in predicting user’s intention to adopt internet banking |
| Rahi et al., (2018) |
UTAUT2 | Pakistan | Developed an integrated technology adoption model with extended UTAUT2 model and perceived technology security to predict and explain user’s intention to adopt internet banking and intention to recommend internet banking in social networks. | performance expectancy, effort expectancy, social influence, hedonic motivation and perceived technology security | Added perceived technology security in the existing model | Questionnaire | Convergence and divergence with earlier findings were found, confirming that performance expectancy, effort expectancy, social influence, hedonic motivation and perceived technology security had significant influence on user’s intention to adopt internet banking. Additionally, IPMA analysis show that among all construct’s hedonic motivation and perceived technology security had the highest impact on user’s intention to adopt internet banking |
| Rahi et al., (2019) |
UTAUT | Pakistan | Evaluated the integration of UTAUT model (UTAUT+ESQ) effects on user intention to adopt internet banking. | performance expectancy, effort expectancy, facilitating conditions, social influence, assurance, reliability, website design, customer service | Added Assurance, reliability, website design, customer service | Questionnaire | The results of this study provided theoretical and empirical support for newly developed integrated model. Importance performance matrix analysis (IPMA) revealed that assurance is the most influential factor among all others to determine user's intention to adopt internet banking |
| Rahi et al., (2019) |
UTAUT | Pakistan | Studied adoption of internet banking using unified theory of acceptance and use of technology (UTAUT) and electronic service (e-service) quality | performance expectancy, effort expectancy, facilitating conditions, social influence, assurance, reliability, website design, customer service | Added Assurance, reliability, website design, customer service | Questionnaire | UTAUT model had significant influence on user intention to adopt internet banking |
| Rahi et al., (2019) |
UTAUT | Pakistan | Incorporated the unified theory of acceptance and use of technology factors, and e-service quality (E-SQ), as theoretical lens for this study | performance expectancy, effort expectancy, website design, customer service, assurance and reliability | Added Website design, customer service, assurance and reliability | Questionnaire | Results revealed that approximately 79 percent of variance in user intention to adopt internet banking was explained by predictors. In addition, the mediating role of performance expectancy and effort expectancy among website design, customer service and user intention were also confirmed |
| Rajendran et al., (2017) | UTAUT | India | Studied the customer attitude towards the adoption of online banking using UTAUT. | performance expectancy, effort expectancy, facilitating conditions, social influence | -- | Questionnaire | The study found positive relationship among all is variable and found UTUAT the best fitted model for e-banking studies |
| Raza et al., (2019) |
UTAUT | Pakistan | Studied the factors which affect mobile banking adoption using UTUAT | performance expectancy, facilitating conditions, social influence, effort expectancy, perceived value, habit and hedonic motivation, intention to adopt M-banking (mediator), and actual usage | perceived value, habit and hedonic motivation | Survey method | Results showed a significant positive effect on intention and actual usage except for social influence |
| Sarfraz (2017) |
UTAUT | Jordan | Studied mobile banking adoption using (UTAUT) | performance expectancy, effort expectancy, social influence, risk and trust | Risk and trust | Questionnaire | Results revealed that performance expectancy; effort expectancy and risk perception have influence on user's intention to adopt mobile banking services while, no significant relations found for social influence and trust |
| Sharma et al., (2020) | UTAUT | Fiji | To Investigate the behavioral intention to adopt internet banking (IB) in Fiji | Performance expectancy, effort expectancy, perceived risk, social influence facilitating conditions. Moderating role of Individualism and uncertainty avoidance | Added customer satisfaction and perceived risk constructs and cultural moderators of individualism and uncertainty avoidance | Questionnaire | Results revealed that e-banking adoption is positively influenced by the levels of performance expectancy, effort expectancy, social influence and facilitating conditions while perceived risk negatively influences IB usage intention. |
| Tarhini et al., (2016) | UTAUT | Lebanon | To investigate the factors that may hinder or facilitate the acceptance and usage of IB in Lebanon. | Performance expectancy, effort expectancy, perceived risk, social influence facilitating conditions perceived credibility and task-technology fit | Added perceived credibility and task-technology fit | Questionnaire | Results revealed that performance expectancy, social influence, PC and TTF are significant predictors in influencing customers’ behavioral intention (BI) to use IB |
| Varma, A. (2018) |
UTAUT | India | This study investigated the entrepreneurial usage of mobile banking services | performance expectancy, effort expectancy, social influence, facilitating conditions | -- | Questionnaire | The results revealed that mobile banking intentions mediates the relationship effort expectancy and use behavior, performance expectancy and use behavior and social influence and use behavior additionally they found no gender differences among entrepreneurs |
Discussion of Results
The overall results of the 29 studies have found the main variables namely performance expectancy, effort expectancy, social influence and social influence are the key indicators of human behavior for studying the actual usage of the internet banking and mobile banking.The findings of [30] found the Positive influence of performance expectancy, effort expectancy, hedonic motivation, price value and perceived risk on behavioral intention except, social influence. The research findings of [17] revealed that Social influence is significant factor in adopting m-Banking. Additionally, Task-technology fit, Technology characteristics, Performance expectancy facilitating conditions, Task characteristics, and User adoption have great impact on attitude towards mobile banking services.The findings of [36] found positive relationship of Task Technology fit, performance expectancy, effort expectancy, facilitating conditions, social influence with the user intention to adopt technology. Results of [27] revealed that performance expectancy, effort expectancy, social influence, perceived credibility, perceived convenience, and behavioral intention to use mobile banking have positive relationship while hypotheses testing cost and facilitating conditions in the adoption of mobile banking were not significant. According to the study findings of [41] facilitating conditions and self-efficacy in mobile banking application do not exhibit a direct effect on behavioral intention. The results of [28] revealed that performance expectation, effort expectation, social influence and perceived risk have positive influence on behavioral intention while the opposite was true for Perceived cost. Results of [42] have found significant impact of performance expectancy, effort expectancy, facilitating conditions and behavior intention in the adoption of e-banking services. Social influence (SI) was non-significant to the user’s intention to adopt e banking services.The findings of [32] revealed that performance expectancy has a significant effect on effort expectancy and social influences in the adoption of e-banking. Website design has impact on the usage of e-banking. Prior experience has in effort expectancy in the adoption of e-banking. The results of [38] revealed that all factors are direct determinants of behavioral intention additionally, there is still need of improvement and the constructs like hedonic motivation, perceived risks and trialability would be a good path for future.The results of [26] revealed that behavioral intention, hedonic motivation, and performance expectancy are the most important dimensions in the adoption if mobile banking technology. The study [31] has found observability, performance expectation, hedonic motivation, facilitating conditions have significant impact on behavior intentions while perceived risk, and price value have negative impact on behavior intention. The results of [44] revealed that expected performance and religious factor are the most important factors for Islamic banking customers to adopt online services.The findings of [45] suggests that performance expectancy, facilitating conditions, habit, perceived security, and price value have positive influence on behavioral intentions. The cultural dimensions, collectivism, and uncertainty avoidance were significant moderators in explaining behavioral intention and usage behavior for online banking. The results of [21] revealed that performance expectancy, social influence, and effort expectancy have significant and positive impact on behavioral intentions of rural customers in Pakistan. Moreover, personality openness significantly shapes behavioral intentions and trust on the internet moderates between customers’ intentions and their usage of e-banking.The results of [46] revealed that determinants of behavioral intention to adopt digital mortgage banking were facilitating conditions, performance expectancy and effort expectancy. The study of [1] found significant impact of performance expectancy, effort expectancy, facilitating conditions, social influence, security, risk and trust on behavior intention and actual usage in the adoption of e-banking services. The findings of [47] depicted the positive correlation between customer service, type of bank and perceived ease of use and the use of m-banking.The study of [48] found positive relationship among all is variable and found UTUAT the best fitted model for e-banking studies. The findings of [49] confirmed that all four variables performance expectancy, effort expectancy, social influence and facilitating condition had significant amount of variance in predicting user’s intention to adopt internet banking.The results of [50] found that performance expectancy, effort expectancy, social influence, hedonic motivation and perceived technology security had significant influence on user’s intention to adopt internet banking. Additionally, IPMA analysis show that among all construct’s hedonic motivation and perceived technology security had the highest impact on user’s intention to adopt internet banking.The results of [33] provided theoretical and empirical support for newly developed integrated model. Importance performance matrix analysis (IPMA) revealed that assurance is the most influential factor among all others to determine user's intention to adopt internet banking. The findings of [34] revealed that UTAUT model has significant influence on user intention to adopt internet banking. The study of [35] found that approximately 79 percent of variance in user intention to adopt internet banking was explained by predictors. In addition, the mediating role of performance expectancy and effort expectancy among website design, customer service and user intention were also confirmed.The results of [39] showed a significant positive effect on intention and actual usage except for social influence. The results of [29] revealed that performance expectancy; effort expectancy and risk perception have influence on user's intention to adopt mobile banking services while, no significant relations found for social influence and trust. The results of [43] revealed that e-banking adoption is positively influenced by the levels of performance expectancy, effort expectancy, social influence and facilitating conditions while perceived risk negatively influences IB usage intention.The study of [37] revealed that performance expectancy, social influence, PC and TTF are significant predictors in influencing customers’ behavioral intention (BI) to use IB. The results of [3] revealed that mobile banking intentions mediates the relationship effort expectancy and use behavior, performance expectancy and use behavior and social influence and use behavior additionally they found no gender differences among entrepreneurs.
The aim of this research was to provide a comprehensive and systematic literature review of internet and mobile banking studies which have used UTAUT models (classic or extended) from 2015 to April 2020 in developing countries. The extensive literature review and desk research approach was used using various search engines such as Google, Base, Yahoo and ProQuest for finding the relevant literature within a prescribed relevant field. This study ended up with 28 research articles which were exclusively for internet and mobile banking using UTUAT models. The findings of this research were concluded under the headings of source of data by country, frequency of publications, methodological analysis, internet and mobile banking usage, comparison of studies based on UTAUT models and extended UTAUT variables. The findings have concluded that 36% data collection was from Pakistan followed by India additionally, Journal of Internet Banking and Commerce has most publications on this topic. Majority of the researchers have modified the UTAUT models which means that there is need and time for potential researchers to present a subject specific standalone theory for studying the factors affecting the adoption of the emerging technologies like internet and mobile banking.The intention to conduct this review was to provide a useful and usable resource for future researchers by providing information on the key areas. UTAUT has evolved and been empirically tested extensively, and by introducing new variables in various contexts, cultures and environments. There is still ample space for the researchers to develop a comprehensive standalone model in the field of internet and mobile banking adoption. This research was limited to the subject specialist topic in the developing countries and has studied only one theory. The author has tried to fill gap to provide a literature review in subject-specialist area and tried to cover all relevant studies under it but still the author fully acknowledged that there could be some other studies in the same context which might have been skipped unintentionally. A comparative study can further be undertaken to investigate the factors influencing adoption of internet banking and mobile banking in developed countries and developing countries.
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