Use of E-Banking and Customer E-Engagement in Developing Countries: Case of NFC Bank Cameroon ()
1. Introduction
Complex and ever-changing environments frame the banking industry today (Taneja & Ali, 2021). Due to the constant innovation and evolution of electronic services, banks are subject to many challenges. Access to technological advancements has changed the consumption habits of individuals, making them more alert to novelty (Tseng et al., 2020). The mobile phone plays a crucial role in this situation. It is a tool for staying connected with others, sharing knowledge, shopping, entertainment, and, most importantly, accessing online services (Hua et al., 2019; Khatoon et al., 2020). As such, the banking system must be flexible and capable of meeting the new challenges associated with it. With the presence of the internet, the banking sector is one of the most important in terms of online services (Talwar et al., 2020). The internet has provided banking marketers many opportunities to understand customers and their needs to revolutionize the design, communication, and delivery of products and services (Al-Shbiel & Ahmad, 2016).
E-banking has been widely studied in many contexts and markets worldwide in recent times (Anderson et al., 2014; Gupta & Kamilla, 2014; Wu et al., 2014; Al-Shbiel & Ahmad, 2016). Indeed, E-banking has become one of the fundamental concepts of modern banking that helps improve the quality of banking services and provides a competitive advantage to the bank. However, its adoption remains low in sub-Saharan African countries such as Cameroon (Kala Kamdjoug et al., 2021).
So far, the literature has primarily identified the factors influencing the adoption of E-banking in developed countries located in Europe (Themistocleous et al., 2015; Ismail & Alawamleh, 2017), America (Sánchez-Torres et al., 2018) and Asia (Yang et al., 2018). Simultaneously, some have focused on the African zone and few on the specific case of Central African countries (Kala Kamdjoug et al., 2021). However, this zone includes a set of countries with significant economic growth potential. Cameroon represents the leading economy, with the best representation in banking equipment and services (COBAC, 2018). Indeed, to build valuable services offer in the country, banks, the majority being foreign subsidiaries, have been equipped with technologies to implement E-banking. They rely on it to obtain a competitive advantage and align themselves with the strategy of parent companies. Meanwhile, a large part of the national banks has experienced a significant delay and then consequently has been forced to refocus their strategy on positioning their offer based on digital. This situation is the case of the National Financial Credit Bank (NFC Bank).
NFC Bank is a Cameroonian commercial bank operating in the Cameroonian banking sector. Endowed with and servicing over 56,000 customers, fourteen (14) branches, and two sales points, it is a privately owned company operating since 2006. By February 2015, NFC bank started issuing bank cards and introduced SMS banking. Currently, about 23,000 bank cards are distributed and 15,000 Automated Teller Machine (ATM) transactions are recorded monthly, summing up to about XAF 1.5 billion worth transactions monthly (Tchakounte, 2021). The implementation of E-banking took place in September 2017. The main reasons for this implementation decision are: 1) to reduce the displacement by its customers; 2) to reduce cash transactions; 3) to provide the application both on the national territory and abroad through Google Play Store and Appstore as well as on the web through and URL link. Since then, NFC Bank has rapidly increased its performance in terms of transaction volume, has significantly reduced operating costs, increased commissions by XAF 230 million in 2019, and has expanded the customer portfolio and users of E-banking (Tchakounte, 2021). NFC owns 5000 online customers all over the national territory, with an average of 3000 online banking transactions monthly.
In the Cameroonian context, where the level financial inclusion remains relatively low (27%) (Demirguc-Kunt et al., 2018) and where the development of digital services is nascent, it is crucial to identify the factors that lead to solid use of online banking services. Therefore, this study aims to identify the factors contributing to the Use of E-banking and analyze its impact on E-engagement through a combination of technology and service factors. Focusing on the case of NFC Bank, the study envisages answering the following questions: What are the drivers of E-banking applications? What is the impact of this use on customer E-engagement? To answer these questions, we developed a conceptual model that first examines the influence of E-banking technological features and service-related factors on Trust and Use. Next, we look at the impact of this use on Customer satisfaction and Usage continuance, components of E-engagement.
The remainder of the paper is organized as follows: Section 2 presents a literature review on E-banking adoption in developing countries. Section 3 highlights the conceptual framework of the research model and the hypotheses development. Section 4 develops the methodology used. Section 5 presents the main results, followed by discussions and implications in section 6. Limitations and directions for future research are presented in section 7, and finally, section 8 concludes.
2. Literature Review
2.1. E-Banking Adoption in Developing Countries
Launching the first Automated Teller Machine (ATM) in Finland marked the start of a new banking channel, making Finland the top country in E-banking before it became widely used in other developed and developing countries (Sharma, 2011; Fonseca, 2014). To this day, E-banking, or the delivery of financial services via electronic systems, continues to spread among customers due to banks’ rapid improvement in information technology and marketing strategies. Table 1 below shows some definitions of the term “E-banking” emerging from the literature.
In recent years, the development and deployment of Internet banking have transformed delivering of banking services to consumers. The Internet allows
Table 1. Some definitions of E-banking.
banks to better meet customer needs through enhanced interaction, data mining, and customization (Raza et al., 2015; Liang & Nguyen, 2018). In addition, banks seek to lower their costs and, at the same time, increase their revenue by attracting consumers to use Internet banking. On the other hand, consumers enjoy the comfort of carrying out banking operations regardless of time and place (Talwar et al., 2020).
Introducing new technologies has become essential for developing the banking sector in the world, particularly in developing countries. With the rise of the internet and the acquisition of mobile phones by a large part of the population, especially in Africa, electronic financial services have become a valuable service offer for customers. Faced with this challenge, banks have made considerable investments in the strategic deployment of the online banking platform. They have created great competition between banks (Hammoud et al., 2018).
E-banking in developing countries has met several challenges, including 1) the ability to adopt technologies that require adequate infrastructure and practical technical expertise; 2) the ability to provide an institutional and regulatory framework that ensures customer protection; and 3) the ability to lead small and medium-sized enterprises in the adoption of E-banking (Rupa Rege, 2003; Drigă & Isac, 2014). The applicability of these challenges has been more effective with the impact of e-commerce, which has motivated banks to implement E-banking for customer needs (Nikolina et al., 2021). Different authors have somewhat investigated the adoption of E-banking by customers in developing countries. They mainly conclude that E-banking services must be adapted to meet the desires and security of customers but also serve as an incentive for customers to engage in broader use. Similarly, banks must be able to anticipate market changes and invest more in E-banking as it positively affects profitability and bank growth in developing countries (Siddik et al., 2016).
2.2. E-Banking in Cameroonian Context
Cameroon effectively led the reform of its banking sector after the financial crisis and devaluation of the XAF (Central African CFA Franc) currency in 1994 (Tangakou & Mba, 2015; Kuikeu, 2021). According to COBAC (2018), with a population of more than 25 million inhabitants, sharing French and English as official languages, Cameroon alone has 47% of the banking network of the Economic and Monetary Community of Central Africa (CEMAC).1 Moreover, the creation of national banks helps supporting the country’s financial system following the failure of some foreign banking institutions after the crisis. We can cite bank institutions such as CCEI Bank (Caisse Communautaire d’Épargne et d’Investissement, now Afriland First Bank) in 1987 and NFC bank in 1989 (formerly National Financial Credit Company).
With an internet penetration rate of 30% by January 2020 (IAC, 2020), pioneering initiatives such as E-banking is an integral part of Cameroon’s enhanced banking offerings. For the specific case of NFC Bank, the services offered (NFC, 2021) are presented in Table 2.
Regarding E-banking in Cameroon, studies have focused on customer perception and bank performance. Fonjai (2017) has shown that perceived reliability, trust, security, and accessibility significantly impact the perceived usefulness of E-banking adoption. It argues that banks need to increase E-banking security, accessibility, and trustworthiness and reduce the cost of E-banking services to encourage customers’ attitudes towards adopting E-banking services. Fonchamnyo (2013), who extends the TAM model, shows that security, cost of services, trust, usefulness, and accessibility of services significantly influence customers’ attitudes and adoption of E-banking. In the same vein, Tamajong (2020) concluded that many users complain about security and privacy, although they trust the service. Moreover, accessibility, convenience, and perceived ease of use motivate the acceptance of E-banking. Beloke et al. (2021) studied 10 of the 15
Table 2. NFC Bank E-banking services.
banks in Cameroon to examine how transactions via digital services affect bank performance. They point out that these services have a significant influence on the profitability of commercial banks.
This research complements existing studies by focusing on the customer of a specific bank. In addition, by proposing a research model based on the most salient factors of E-banking usage, the study also examines the effect of E-banking usage on consumer E-engagement.
3. Conceptual Background and Hypotheses Development
The growth of Internet-based services has stimulated many fraudulent practices that take advantage of some of the technology’s shortcomings (Abreu et al., 2016). These illicit practices have been most prevalent in the e-commerce sector (Carta et al., 2019), exposing users to various types of risk (identity theft, privacy violation, theft, fraud). Studies have shown that essential technological factors for recurrent use of technology are those capable of covering the risk associated with the use and providing security to the user (Sandal et al., 2020; Diniz et al., 2021). Therefore, when people use online services, such as E-banking, factors that undermine their confidence and willingness to use the service repeatedly become a threat (Emad & Hanan, 2017).
On the other hand, research shows that customers develop a kind of dependency on using a product when their expectation meets reliability. This dependency depends on the offering of the services compared to other providers present in their evaluation grid (Arvidsson, 2014; Wei et al., 2016). In terms of online services, the studies also reveal that customers are susceptible to three facts: 1) the quality of the service provided to them (Prentice et al., 2019), 2) the time taken in the execution of the requested transaction or to the rendering of the requested information (Roy & Moorthi, 2017), and 3) the cost incurred in the use of the service (Abu Elsamen, 2015).
In terms of user-related impact, the literature develops the concept of engagement. Indeed, engagement is an essential psychological concept that impacts the behavior of individuals (de Vreede et al., 2019). It refers to a long-term phenomenon (continuous engagement), especially with the digital evolution that makes the experiences between humans and technology faster and more engaging. It is a concept divided into three distinct phenomena: 1) emotional engagement, where individuals experience a positive psychological reaction or attachment to an activity or situation; 2) behavioral engagement, where individuals make efforts or show persistence to stay involved in an activity; and 3) cognitive engagement, where individuals are cognitively absorbed in a task or activity (Ganeh Badrabad & Ghanizadeh, 2019; Hepola et al., 2020). Engagement is a significant marketing factor in online services, ensuring a competitive advantage. In this context, E-engagement corresponds to the intensity with which a customer becomes an active user and develops an attachment to the service they use via the internet or information technology (Promtep et al., 2019). Some researchers define E-engagement in terms of satisfaction (Yu & Ramaprasad, 2019), a form of emotional engagement, while others recognize it as a prerequisite for the success of online services as users display a high level of intention to continue using (Chiu et al., 2019).
Based on this development, Figure 1 highlights the research model that presents technological features such as Perceived personal information protection and Perceived transaction security, as well as service-related factors such as Perceived time saving, Service quality, and Perceived cost saving. These factors
explain Trust and Use of E-banking in this study. Finally, Use of E-banking explains the impact on E-engagement in terms of Customer satisfaction and Usage continuance.
3.1. Technological Features, Trust and Use of E-Banking Services
Perceived personal information protection
Customers who conduct financial transactions online may face all kinds of uncertainties and risks. In this case, the bank must adopt a sufficient information protection culture to comply with data privacy requirements (Da Veiga & Martins, 2015). This measure implies that the bank must be able to reassure customers about the level of provision made to avoid exposure to risk (Makarević et al., 2014). So, when customers have a high level of assurance about their personal information, they feel they have more control over online transactions. They pay attention primarily to those related to electronic transactions whose information should not be disclosed, viewed, stored or manipulated by inappropriate parties during their interaction with a system. This requirement increases their use level (Hodjat & Saba, 2017; Fei et al., 2018). Conversely, if the bank lacks to fulfil privacy, customers lose confidence and may abandon the use of the service. Either, we enounce the following hypotheses:
Hypothesis 1a. Perceived personal information protection has a positive influence on users’ trust in E-banking.
Hypothesis 2a. Perceived personal information protection has a positive influence on the use of E-banking.
Perceived transaction security
The development of digital technologies in the banking field implies the implementation of mechanisms focused on security (Mwiya et al., 2017). As the level of control of the technology does not belong to the user, the person relies on the measures provided to him, such as authentication, passwords, and confidentiality clauses (Zimmermann & Gerber, 2020). Nevertheless, an user of E-banking only has the guarantee of excellent security practices from the service provider. Customers’ Perceived transaction security is therefore a essential factor that depends on the user experience. Nowadays, customers are more interested in security regarding online transactions. If incongruities appear during the use, then they influence their confidence and their effective use. Therefore, we propose the following hypotheses:
Hypothesis 1b. Perceived transaction security has a positive influence on users’ trust in E-banking.
Hypothesis 2b. Perceived transaction security has a positive influence on the use of E-banking.
3.2. Services Factors, Trust and Use of E-Banking Services
Perceived time saving
Consumers derive utility value from fast and efficient service delivery (Ngina, 2016). This situation concerns mobile devices, allowing consumers to gather information and conduct transactions anytime and anywhere (de Sousa & Sandro, 2014; Günther & Bernd, 2015). The faster and easier access to internet banking is, the more impact it has on users’ daily routines and activities. This ubiquity in using E-banking in the service evaluation signals credibility and the establishment of effective trust (Baolin et al., 2017). Hence the following hypotheses are put forward:
Hypothesis 3a. Perceived time saving has a positive influence on users’ trust in E-banking.
Hypothesis 4a. Perceived time saving has a positive influence on the use of E-banking.
Service quality
Service quality is a crucial variable for measuring success. It indicates the information system’s ability to meet the user’s different needs (Delone & McLean, 2003). With the Internet, customers can compare various services and make decisions quickly. So, an electronic service such as E-banking with good quality harmonizes the relationship between customers and the achievement of business objectives necessary to obtain a competitive advantage, especially in the banking sector (Rashid et al., 2019). As a result, we propose the following hypotheses:
Hypothesis 3b. Service quality has a positive influence on users’ trust in E-banking.
Hypothesis 4b. Service quality has a positive influence on the use of E-banking.
Perceived cost saving
According to Anouze and Alamro (2020), cost includes the typical costs associated with internet use and bank fees. Perceived cost saving is one of the essential factors in adopting online services (Yang et al., 2016). Customers always expect the cost of transactions to be low. So, a recurrent variation in costs leading them to additional monetary expenses can reduce the influence on the usage behavior and the trust they have attributed to the service (Nguyen & Khoa, 2019). We, therefore, put the following hypotheses forward:
Hypothesis 3c. Perceived cost saving has a positive influence on users’ trust in E-banking.
Hypothesis 4c. Perceived cost saving has a positive influence on the use of E-banking.
3.3. Trust and Use of E-Banking Services
Trust is a critical element in using technologies (Siau & Wang, 2018). In the E-banking literature, it is a challenge as it builds a long-term relationship between the bank and its customers. When customers believe the bank is trustworthy and will act in their interests, they are willing to carry out transactions via the medium provided, expecting the bank to fulfil its monitoring and control obligations (Yu et al., 2015). We, therefore, enounce the following hypothesis:
Hypothesis 5. Trust has a positive influence on the use of E-banking.
3.4. Use and Customer E-Engagement
Usage continuance
Usage continuance reveals the success of products or services with customers. The more they use the service, the more they develop an attachment to using it soon. Therefore, with the experience and continuous measurement of the product according to their expectations over time, they display a behavior that is a psychological attachment to the E-banking service offered by the bank (Yasin et al., 2020). This attachment, which can be considered loyalty, stimulates an expression of commitment to continue using E-banking (Chaouali et al., 2016; Thakur, 2019). Therefore, we propose the following hypothesis:
Hypothesis 6. Use of E-banking has a positive impact on Usage continuance.
Customer satisfaction
Khatoon et al. (2020) defined customer satisfaction as the consumer’s response to the evaluation of the perceived difference between expectations and performance following consumption. Satisfaction is crucial because it implies the willingness to repeat the action of using the service (Izogo & Ogba, 2015). Meeting customers’ needs and expectations reveals a favorable acceptance of the service offered by the bank. This acceptance, combined with the recurrent use of the service, is a sign of satisfaction. Therefore, we propose the following hypothesis:
Hypothesis 7. Use of E-banking has a positive impact on customer satisfaction.
4. Methodology
4.1. Data Collection
For the data collection phase, a questionnaire was developed based on a review of the existing literature. The design principle of the questionnaire is to look for items for each construct provided by studies that have already explored them in their analysis. Because these items are already confirmed in the literature as being reliable for quantitative analyses, we identified and selected some of them and adapted them to our study. Appendix A presents these measurement items and the references of the studies to which they were adapted. We use thirty-seven (37) items to measure the nine (09) research model’s constructs. A 7-point Likert scale—ranging from “completely disagree” to “completely agree”—serves as a measurement of each item. In order to determine if the questionnaire is understandable, well-structured and not open to other interpretations, it is important to conduct a pre-test before collecting the data. To do this, we used a sample of sixteen (16) people, composed of students and banking professionals. Their role was to read the questionnaire and check for errors, incomprehensible sentences and inconsistent organization of the questionnaire. From them, we received positive feedback which confirms that the questionnaire is reliable and understandable, without any ambiguity. Afterwards, we determined our minimum sample size.
By inserting parameters such as effect size, probability error, the power of the effect, and the number of predictors or latent explanatory variables, it is possible to obtain the sample size necessary to test the model effectively. For this study, we determine the minimum sample size through the GPower 3.1.9.2 software, which has the particularity of calculating the statistical power for various statistical tests (Kang, 2015). With a total of seven (07) predictors, a probability of error α = 0.05, an effect power (1 − β) = 0.80, and an effect size of f2 = 0.15, the minimum total sample size is one hundred and three (103) individuals.
After designing the questionnaire, we have made a Google Forms version intending to reach a large majority of users via their smartphones or computers. Before we proceed to massive data collection, we first collect a sample of 50 responses from our target population to conduct a pilot test. The purpose of the pilot test is to ensure that the measurement items are statistically reliable and valid in order to guarantee the stability of the model. If the pilot test shows that certain measurement items have a low value of some measurement criteria such as outer loading according to the PLS-SEM methodology, they should be removed from the questionnaire. Thus, after conducting the pilot test, we found that all measurement items met the recommended thresholds. Thus, we began the collection in a broader way.
In collaboration with the E-banking department of NFC Bank, the online questionnaire was sent via WhatsApp and via email to E-banking products’ customers, as they rarely come to bank branches. An introduction at the beginning of the questionnaire guides the respondents of the survey. This text introduces them to the study’s purpose, the anonymity of the questionnaire, and the use of the data strictly for academic research purposes.
Additionally, definitions of each construct permit a better understanding of each item of the questionnaire. At the end of this collection, which took place from October to November 2020, we retained 346 responses for the analyses. Table 3 presents the demographic profiles of the respondents. This demographic representation shows the repartition of our target respondents by gender, age, level education, occupation and E-banking experience. We noticed that the data is predominantly represented by men and women, people between the ages of 18 and 35, people with higher education, people working in the private sector, and those with one to three years of E-banking experience.
4.2. Data Analysis
This study used the partial least square-structural equation modeling (PLS-SEM) to analyze the model. We use SmartPLS version 3.3.9 (Ringle et al., 2015) to perform the data analysis. This method is quite relevant for understanding the behavior of individuals, especially in evaluating complex causal relationships. It is a well-known method widely used in research conducted in a variety of fields
of management science (Hair Jr. et al., 2014; Khan et al., 2019), including information systems (Hair et al., 2017; Foka Nzaha et al., 2022), marketing (Arvidsson, 2014; Liang & Nguyen, 2018), management (Gadedjisso-Tossou et al., 2022), finance (Siddik et al., 2016; Avkiran, 2018; Ndassi Teutio et al., 2021), to name few. We proceed in two steps to assess the relevance of the results. The first step evaluates the measurement model to attest to the reliability and validity of the constructs. The second one considers the structural model through the validity of the relationships (hypotheses) between the constructs (Hair et al., 2019).
5. Results
5.1. Assessment of Measurement Model
Table 4 below shows the values of outer loading, rho_A, composite reliability (CR), and the average variance extracted (AVE) obtained after running the PLS algorithm in SmartPLS 3. According to Hair Jr. et al. (2016), the values of the
Table 4. Construct’s validity and reliability.
outer loading of each item, the value of Cronbach’s alpha, rho_A, and the composite reliability (CR) determine the internal consistency reliability. They must all be greater than 0.7. The AVE gives the convergent validity of the model, which must be greater than 0.5. Based on these criteria, we find that most items have values greater than 0.7. We deleted the items CS2, PC3, PT2, TR1, TS2, and UC2 because they have low values. The internal reliability criteria also meet the threshold of 0.7 except for the construct “Perceived transaction security”, which has a value of Cronbach’s alpha and rho_A close to 0.7. We preserve this construct due to its good composite reliability and AVE level. We also deleted the items PI3, PI4, TS3, and TS4 to correct the correlations between “Perceived personal information protection” and “Perceived transaction security”.
In addition to internal reliability and convergent validity, it is essential to test the discriminant validity. We chose the Fornell-Lacker criterion which suggest that the square root of the AVEs, along with the diagonal, must be greater than all the values below and left (Fornell & Larcker, 1981). Table 5 presents the correlation matrix according to the Fornell-Lacker criterion. It indicates the extent to which each of the constructs in the research model is unique and different from other constructs (Dutot et al., 2019). Concerning this result, we conclude that the discriminant validity is not an issue in this research model.
5.2. Assessment of Structural Model
The evaluation of the structural model requires first the analysis of the coefficient of determination (R2), which is a measure of the model’s explanatory power. The R2 measures the variance explained in each of the endogenous constructs. R2 values of 0.75, 0.50, and 0.25 are considered substantial, moderate, and weak (Hair Jr. et al., 2016; Hair et al., 2019). Table 6 shows that the Use of E-banking is explained at 39.6% (R2 = 0.396), that Trust is explained at 61.5% (R2 = 0.615) and finally, that the Use of E-banking explains Customer satisfaction at 48% (R2 = 0.480) and Usage continuance at 60.3% (R2 = 0.603).
We perform the blindfolding procedure to get the Q2 values to evaluate the accuracy of the predictive model. Unlike the R2 value, which indicates the
Table 5. Discriminant validity - Fornell-Larcker Criterion.
US = Use of E-banking; CS = Customer satisfaction; PC = Perceived cost saving; PT = Perceived time saving; PI = Perceived personal information protection; SQ = Service quality; TS = Perceived transaction security; TR = Trust; UC = Usage continuance.
in-sample explanatory power of the model, the Q2 value reveals his predictive accuracy. The Q2 values must be greater than 0 for low predictive accuracy, greater than 0.25 for medium predictive accuracy, and greater than 0.50 for highly predictive accuracy (Hair et al., 2019). Table 6 reports the Q2 values of the endogenous constructs of our research model. It shows that Use of E-banking (Q2 = 0.310), Customer satisfaction (Q2 = 0.398) and Trust (Q2 = 0.436) have a medium predictive accuracy. Usage continuance, on the other hand (Q2 = 0.503), has a large predictive accuracy.
We use the bootstrapping method to test the hypotheses of the research model. Table 7 shows the different relationships constituting each of the hypotheses and their level of significance. The results show eleven accepted hypotheses and
****p < 0.001; ***p < 0.01; **p < 0.05; *p < 0.1; n.s. not significant; US = Use of E-banking; CS = Customer satisfaction; PC = Perceived cost saving; PT = Perceived time saving; PI = Perceived personal information protection; SQ = Service quality; TS = Perceived transaction security; TR = Trust; UC = Usage continuance.
two rejected hypotheses. Perceived personal information protection (β = −0.184; p < 0.01), Perceived transaction security (β = 0.185; p < 0.05), Perceived time saving (β = 0.155; p < 0.05), Service quality (β = 0.288; p < 0.001) and Perceived cost saving (β = 0.144; p < 0.1) significantly influence the Use of E-banking. On the other hand, Trust is significantly influenced by Perceived personal information protection (β = 0.237; p < 0.001), Perceived time saving (β = 0.323; p < 0.001), Service quality (β = 0.218; p < 0.001) and Perceived cost saving (β = 0.122; p < 0.05) apart from Perceived transaction security (β = 0.028; p = 0.745). Finally, the results also show that Use of E-banking significantly impacts Usage continuance (β = 0.777; p < 0.001) and Customer satisfaction (β = 0.692; p < 0.001). Figure 2 presents the estimation results of the structural model.
Table 8 presents the specific indirect effects of the relationships between the
Figure 2. Result of model estimation and highlight paths.
****p < 0.001; ***p < 0.01; **p < 0.05; *p < 0.1; n.s. not significant; US = Use of E-banking; CS = Customer satisfaction; PC = Perceived cost saving; PT = Perceived time saving; PI = Perceived personal information protection; SQ = Service quality; TS = Perceived transaction security; TR = Trust; UC = Usage continuance.
constructs in the model. The results show that there are no mediating effects between technology features, service factors and Trust.
6. Discussion and Implications
6.1. Discussion
The technological features highlighted in this study are Perceived personal information protection and Perceived transaction security. The results show that the assurance of information confidentiality that the bank provides to its customers strongly influences the Use of E-banking. However, although this affects Trust, customers are still somewhat reticent about the security of transactions offered by the bank. Therefore, they do not completely trust the bank and believe monetary loss or fraud is possible. They think their confidential information is protected, although risks may occur during their transacting sessions. These results are consistent with those of Damghanian et al. (2016), Ataya and Ali (2019), and Nguyen and Huynh (2018).
The service factors highlighted in this study are Perceived time-saving, Service quality, and Perceived cost saving. The results show that all these factors influence Trust and Use of E-banking. They also show that quality of service is the factor that most strengthens customer confidence and leads them to use E-banking services (Masoud & AbuTaqa, 2017; Pambudi et al., 2021). The results are also somewhat surprising in that the perception of time-saving influences Trust more than Use of E-banking. It seems that customers trust the bank’s E-banking when it meets their immediate needs while providing a quality service at a lower cost. Although this trust does not directly influence their use, there are still considerations to be made on its fundamental importance in the Use of E-banking (Bahmanziari et al., 2003; Lăzăroiu et al., 2020).
Indeed, the results show that Trust does not act as a mediating effect leading to Use of E-banking. We can explain this because, although digital banking solutions exist, customers are still strongly present in bank branches to carry out their operations. As a result, despite their experience in using E-banking, they have not yet sufficiently developed a behavior that leads them to use it repeatedly. Therefore, E-banking is still an intermediate solution to the bank branch. Hence, customers may have a high level of confidence in E-banking but a low or medium level of use.
Finally, the results reveal rather good E-engagement behavior of NFC Bank customers. This result shows that E-banking usage has strongly increased consumer’ E-engagement (Thakur, 2016). Use of E-banking has a significant impact on Usage continuance and Customer satisfaction.
6.2. Implications
Theoretical implications
This study makes three overarching contributions to the E-banking literature: First, it identifies and confirms the critical place of trust in E-banking in developing countries (Vaidya, 2016). The results show that customers positively perceive E-banking, but Trust does not necessarily imply high usage of E-banking.
Second, the study highlights the concept of E-engagement by focusing on aspects related to Customer satisfaction and Usage continuance. We thus demonstrate that banking customers have a high level of E-engagement with E-banking products. These results complete the studies on E-engagement and contribute to the non-existent literature on its link to E-banking.
Third, this study contributes to understanding the Use of E-banking in developing countries, particularly in Central Africa, with Cameroon’s example. As Cameroon is the pioneer economy in the Central African zone, the study provides an essential key to understanding the behavior of individuals in this zone. The results can be used to explore similar contexts or be compared to others.
Managerial implications
This study provides some managerial and practical implications. There is already evidence that E-banking meets customer needs. However, banks need to inform customers about risk management policies concerning transaction security to build trust. Banks must set up alert processes or informative sections within the applications that highlight regulations and security requirements.
Banks also need to consider customer trust while developing strategies that will drive customers to adopt further the digital channels that the bank offers. Banks must therefore motivate their offer by lowering the cost of accessing their services. Bank managers can conduct surveys or evaluations to assess, at given periods, customers’ opinions on the evolution of electronic banking offerings.
Bank managers should consider the influence of the changing environment on customers. The E-engagement of customers in using E-banking could encourage them to recommend and talk about the products they use. Thus, to enhance the attractiveness of E-banking platforms, they need to consider the image they give off to the public and the effect of word-of-mouth value among users (Shankar et al., 2020).
7. Limitations and Future Research
This study has some functional limitations that command future research. First, this research focused on NFC Bank customers. We encourage future studies to expand the research by conducting comparative analyses across banks. It may be helpful to know if there is a significant difference between the offerings to discern their strategic and commercial relevance to the banking sector in Central Africa. Second, a qualitative study is necessary to understand whether the results achieved are a consequence of the bank’s strategic actions and how it plans to improve its offering and build customer confidence. Thus, we encourage future studies to take a qualitative approach to capture the views of the bank’s managers. We also encourage further exploration of E-engagement by adding other components to the E-banking literature. Finally, an analysis by gender and level of experience in E-banking could have provided a more specific understanding of the topic.
8. Conclusion
This study examined how technological features (Perceived personal information protection and Perceived transaction security), service factors (Perceived time saving, Service quality, and Perceived cost saving), and Trust influence Use of E-banking and how this affects E-engagement through Customer satisfaction and Usage continuance. The study shows that Trust is strongly influenced by Perceived personal information protection and the service factors (Perceived time saving, Service quality, and Perceived cost saving). However, Trust in E-banking does not necessarily lead to its Use. On the other hand, Use of E-banking influenced by both technological features of electronic financial services (Perceived personal information protection, Perceived transaction security) and service factors (Perceived time saving, Service quality, and Perceived cost saving).
This research contributes to the literature by developing a model that integrates the main drivers of Use of E-banking developed in the literature and adapts it to a specific context in developing countries such as Cameroon. The limitations it identifies will help encourage other researchers to explore other avenues of analysis to understand E-banking adoption better. It also provides practical implications for banks to improve their marketing and customer relations approach.
Acknowledgements
We are grateful to NFC Bank and their E-banking department staff for their cooperation and involvement in the success of the data collection from the bank’s customers.
Appendix A
NOTES
1CEMAC is composed of six countries: Cameroon, Central African Republic, Congo, Gabon, Equatorial Guinea and Chad.