The TAM is based on the theory of reasoned action (Fishbein & Azjen 1975) and aims to better understand user acceptance or rejection of information technology systems by describing the motivational processes that mediate the system characteristics and user behaviour (Davis 1985). As presented in Figure 1, the TAM argues that a user’s perception of the usefulness and ease of use of the system will influence their attitude towards the system, which will influence the user’s behavioural intention to use the system and will result in the actual usage of the system (Davis et al. 1989). The external variables included refer to system characteristics, the nature of the implementation process, user participation design and user training (Venkatesh & Davis 1996). In addition to the variables included in the TAM of Davis et al. (1989), this research also investigated perceived trust as a higher level of trust increases a customer’s certainty perceptions about a specific behaviour when using online services (Nguyen & Nguyen 2016). The online banking environment also includes sensitive information and trust might be a concern for consumers who might influence their behaviour towards online banking (Sharma & Sharma 2019). The TAM is presented in Figure 1.

Using the TAM to better understand technology acceptance within the online banking environment is contemporary with various research that has adapted and extended the TAM in different parts of the world. Hossain et al. (2020), for example, extended the TAM by including governmental support and risk among online banking customers in Bangladesh were as Albort-Morant, Pedregosa and Paredes (2022) compared the factors that influence the adoption of online banking among Spanish online banking customers in towns and cities. Also, among Indian online banking customers, the various constructs of the TAM and also factors such as perceived security, self-efficacy, social influence and customer support proved to have a significant impact on customers’ behavioural intention to use mobile banking (Singh & Srivastava 2020).

External variables are important to consider while investigating the adaption of a technology system and are the set of variables that are used to address the characteristics of a system and influence the perceived usefulness and ease of use of the system (Davis et al. 1989; Wahab & Azzman 2019). This study included two external variables, namely social influence and system quality. Relevant to the online banking environment, social influence is the process where individuals affect others’ behaviour, feelings and beliefs and is a key determinant in individual behaviour intentions (Wang, Molina & Sundar 2020). Social influence is based on the social influence theory (Kelman 1958) and refers to compliance, identification and internalisation that change attitudes. Compliance refers to individuals accepting influences from others to achieve a favourable reaction, identification occurs when individuals accept influence because they want to maintain a relationship with others that defines them, and internationalisation refers to individuals accepting influences because it is rewarding and integrated into their belief system (Kelman 1958; Xu et al. 2017). All three elements of social influence are relevant to the online banking environment because the social context of an individual can act as a catalyst to adopt new technology and was therefore included in the conceptual model (Mohammadi 2015).

Malaquias and Hwang (2016) observe that if a consumer’s social network perceives the risks of online banking to be low, their trust in these services will increase, which, in turn, will affect the consumer’s likelihood of adopting the online banking services. In addition, Gong et al. (2019) established a positive correlation between the social influences and trust in the provider within an online health consultation services industry.

Consequently, it is plausible to argue that among Namibian online banking customers:

Perceived ease of use is the perceptions that an individual forms regarding the use of technology, how the use of the system could lead to a reduction in their mental stress levels as well as how efficiently their time will be spent in using the service (Raza, Umer & Shah 2017). Individuals will be more inclined to use online banking when they perceive the provided services are effortless, efficient and easy to use (Cho & Sagynov 2015; Davis et al. 1989). In addition, an individual’s opinions formulated by important referents do impact their perceptions of the system or services at hand. Therefore, if family members, friends or important others perceive online banking to be easy to use, it is most likely that individuals will also adopt these services; therefore, social influences significantly affect perceived ease of use on internet of things and mobile commerce (Bashir & Madhavaiah 2015; Chaouali, Yahia & Souiden 2016; Tsourela & Nerantzaki 2020).

Consequently, it is plausible to argue that among Namibian online banking customers:

Perceived usefulness is an important concept in user acceptance or rejection of systems and relates to the degree that an individual feels his or her job performance is enhanced by engaging in the usage of the system at hand (Davis 1985). Perceived usefulness is an important contributing factor in Internet banking adoption because of the flexibility of internet banking services and that these services are becoming more superior to traditional banking services resulting in an increase in Internet banking adoption (Rawwash et al. 2020). If an individual believes that his or her social context (family, peers, colleagues) assumes that they should make use of a system, the beliefs of the social circle are incorporated into their own beliefs and as such they perceive the specific system to be useful (Abdullah, Ward & Ahmed 2016).

Consequently, it is plausible to argue that among Namibian online banking customers:

System quality relates to the system’s overall performance following the needs and expectations of the consumer (Um 2021). Improving a retail bank’s online system quality increases customers’ trust perception (Namahoot & Laohavichien 2018). In addition, Ryu and Ko (2020) established that customers’ trust levels increase if the system provides them with credible and reliable information, whereas customers start to doubt the competence of a bank when they receive poor system quality. Also, good system quality within an online shopping environment results in higher trust in the online store (Qalati et al. 2021).

Consequently, it is plausible to argue that among Namibian online banking customers:

System quality has a positive and significant influence on perceived ease of use and perceived usefulness (Fearnley & Amora 2020; Koukopoulos et al. 2020). System quality characteristics such as reliability, availability, usability and adaptability influence the perceptions of customers relating to usefulness and the ease of use of a system as customers are more likely to find systems to be useful and easy to use when the system quality provided is acceptable (Mahande, Jasruddin & Nasir 2019). Therefore, if consumers receive the desired level of system quality, they are more likely to view the system as useful and easy to use (Fearnley & Amora 2020).

Consequently, it is plausible to argue that among Namibian online banking customers:

Trust forms an integral part of developing and maintaining successful relationships in the online banking environment. It is based on customer expectations, refers to the degree to which the system performs as expected and reinforces the intention to use the system (Bashir & Madhavaiah 2015; Chatzoglou et al. 2020). Consumers who perceive the bank and the online services provided as trustworthy will be more likely to engage in transactions because of the positive attitude formed towards the service that contributes to the adoption of e-commerce (Indarsin & Ali 2017; Marakarkandy, Yajnik & Dasgupta 2017). More recently, within the social media environment, Naqvi et al. (2020) determined that when customers use social media and trust the platform, they also have a positive attitude towards adopting social media services.

Consequently, it is plausible to argue that among Namibian online banking customers:

Perceived ease of use relates to the assessments made by individuals on the difficulty or ease of using a system with the focus on the process that leads to the outcome of using the specific system (Cho & Sagynov 2015; Lazard & King 2020). At the beginning of the century, Venkatesh and Davis (2000) established that perceived ease of use directly affects the perceived usefulness of technology because individuals who perceive the system to be effortless will most likely use the system more often. Subsequent to this research, various researchers such as Cho and Sagynov (2015) and more recently, Jatimoyo, Rohman and Djazuli (2021), established that the easier it is to use the system, the more useful users perceive the system to be.

Consequently, it is plausible to argue that among Namibian online banking customers:

Consumer attitude refers to the negative or positive feelings towards performing a specific behaviour (Elkheshin & Saleeb 2020). Consumer attitude towards online banking services depends on the perceptions formed while using the services; however, consumer perceptions are subject to change (Verma & Kumar 2020). If individuals believe that online banking services have attributes that could improve their job performance and increase their productivity, they will develop favourable attitudes towards using such services (Matikiti, Mpinganjira & Roberts-Lombard 2018). In addition to the usefulness of the system, when online banking customers perceive the system to be easy to use, they will also form positive attitudes towards the system (Normalini 2019; Rasull et al. 2020).

Consequently, it is plausible to argue that among Namibian online banking customers:

The TAM consists of a core relationship that determines the acceptance of a technology, and that core relationship is between an individual’s attitude and intention towards using a technology (Davis et al. 1989). Specifically, within an online banking environment, the key predictors that influence an individual’s acceptance or rejection of online banking services are the attitudes and intentions towards such services and are important to consider when evaluating the adoption of an online system (Ahmad, Bhatti & Hwang 2020; Mohammadi 2015; Rahi, Ghani & Alnaser 2017).

Consequently, it is plausible to argue that among Namibian online banking customers:

Actual use is defined as the degree or way that individuals capitalise on the capabilities of an information system or the time spent using and interacting with the system (Amin et al. 2019) compared with behavioural intention that is the subjective probability that an individual will engage in a specific behaviour (Ajzen & Fishbein 1975).

In an online environment, behavioural intention directly influences the use of technology and information systems (Mashroofa, Jusoh & Chinna 2019). Therefore, when an online banking customer intends to use the online banking system, they will use it (Ahmad et al. 2020; Marakarkandy et al. 2017).

Consequently, it is plausible to argue that among Namibian online banking customers:

Based on the hypotheses formulated, the conceptual model of this study is presented in Figure 2.

The questionnaire included five sections: the preface, screening questions, construct measurement, demographic information and postscript. The preface explained the aim of the study and indicated how the data would be used. The screening questions were used to confirm that the respondents were older than 18 years, used online banking and resided in Namibia. The constructs were measured using existing and reliable measurement statements. Respondents had to indicate their level of agreement with each of the statements using a six-point labelled Likert scale, where ‘1’ indicated strongly disagree and ‘6’ indicated strongly agree. Table 1 indicates the measurement statements’ sources for each of the constructs.

This study was approved as a minimal risk study by the Economic and Management Sciences Research Ethics Committee (EMS-REC) of the North-West University on 15 February 2022 (No. NWU-00888-20-A4).

A total of 441 usable questionnaires were obtained. The demographic profile of the Namibian banking customers who participated in this study is presented in Table 2.

It is evident from Table 2 that a good spread among the different demographic variables participated in this research.

The reliability and validity of the measurement instrument were determined by calculating the Cronbach’s alpha values and performing a confirmatory factor analysis (CFA). The Cronbach’s alpha values of all the measurement constructs were greater than 0.70, indicating satisfactory internal consistency (Hair et al. 2021:178). As indicated in Table 3, the Cronbach’s alpha values ranged between 0.83 and 0.97.

Convergent and discriminant validity were tested through a CFA. Convergent validity was tested by calculating the standard factor loadings, average variance extracted (AVE) and the construct reliability (CR) values of the measurement model (Hair et al. 2019:676). The factor loadings of Social influence 3 (SOCIF 3), Perceived ease of use 3 (PEOU 3) and Actual usage 2 (USAGE 2) were lower than 0.50; therefore, these items were omitted from the data analysis. As indicated in Table 3, the AVE values of the measurement model’s constructs were above the recommended cut-off value of 0.50, thus indicating acceptable convergence of the measured statements. It is furthermore evident from Table 3 that internal consistency is present for all the measured constructs, and the CR values of the measurement model’s constructs were above the recommended cut-off value of 0.70. Based on the examination of the standardised factor loadings, the calculation of the AVE and CR values of the measurement model, it can be concluded that all eight constructs of the measurement model have convergent validity.

The Fornell and Larcker criterion (1981) and the heterotrait–monotrait (HTMT) ratios were accessed to test for discriminant validity. For the Fornell and Larcher criterion, AVE of any two constructs was compared with the squared correlation (R²) estimate between the two constructs and should the AVE of two constructs is greater than the squared correlation between them, discriminant validity is confirmed (Hair, Page & Brunsveld 2020). The results obtained from the correlation matrix (AVE and squared correlation values) are presented in Table 4. The HTMT ratio values are presented in Table 5. Heterotrait–monotrait ratio values higher than the threshold indicates a lack of discriminant validity. This study used a threshold of 0.85 (Kline 2015).

It is evident from Table 4 and Table 5 that the discriminant validity was achieved.

The measurement model was tested by using a two-step SEM process. The model fit was tested through a CFA, and once and acceptable model was obtained, the structural model was tested. Structural equation modelling was used to examine the interrelationships and hypotheses between the constructs of the measurement model (Hair et al. 2019:703). Google forms were used to collect the data, and therefore there were no missing values to manage. Table 6 provides the model fit statistics of the structural model. The model fit indices revealed that the model has an acceptable fit.

Using SEM, the theoretical relationships were transformed into hypotheses and empirically tested. The standardised regression weights (standardised path coefficients) and structural parameter estimates of the structural paths in the model were investigated, and the results of the hypotheses testing are presented in Table 7.

Based on the results presented in Table 7, the structural model for this study is shown in Figure 3.