The revolution of information technology has transformed the financial services industry. Despite the undeniable importance of financial innovation in improving service delivery, there is inadequate understanding about the drivers of adoption of e-banking systems. The objectives of the study is to establish the influence of organizational capability, perceived technological risk, perceived usefulness, and perceived ease of use on the adoption and use of e-banking in Kenya. The study is grounded on the Technology Acceptance Model (TAM) and Technology-Organization-Environment (TOE) framework. The study used a descriptive research design to investigate the research questions. The population targeted were customers of 7 commercial banks classified as ‘large’ by Central Bank of Kenya in Nairobi County. Stratified random sampling was used to generate a sample size of 115 respondents. Data on factors influencing adoption was collected using questionnaires. Both descriptive and inferential statistics were used to analyze data. Descriptive statistics was used to summarize data into frequency, percentages, means and standard deviations. For inferential statistics, a linear regression model was used to establish the relationship between organizational capability, perceived technological risk, perceived usefulness, and perceived ease of use on the adoption of e-banking among commercial banks operating in Nairobi. Descriptive statistics show that the presence of electronic systems, databases, and applications; effective management and oversight, and financial capacity are prerequisite to adoption and use of e-banking services. The main risks perceived by respondents were the effect of incorrect entries, time taken to learn how to use the system, and system outages that may affect access to accounts. Nonetheless, e-banking were perceived to be faster, easier, and better than traditional systems, with many users’ comments on perceived ease of use confirming that the graphic user interfaces are clear, easy to use and do not demand much mental effort. Multiple regression coefficients indicated a statistically significant relationship between organizational capability and perceived usefulness and the adoption and use of e-banking services. There was no statistically significant relationship with perceived risk and perceived ease of use. The study recommends that banks should continue to allocate more resources to developing and upgrading e-banking platforms, invest in customer education and awareness campaigns, develop diverse e-banking products to meet the responsive needs of their customers, and ensure that e-banking graphic user interfaces remain simple, clear, and easy to use.
1.1. Background of the Study
E-banking refers to the use of the internet as a delivery channel for banking services, which includes all traditional services such as balance enquiry, printing statement, fund transfer to other accounts, bills payment and other forms of electronic payments (Frust, Lang, ; Nolle, 2000) without visiting a bank (Mukherjee ; Nath, 2003). Nami (2009) adopts a broad definition of e-banking as the provision of retail and small value banking products and services through electronic channels. These channels include automated teller machines (ATMs), telephone banking, mobile phone banking, internet banking (online), PC banking (offline) and TV-based banking. In this study, e-banking is limited to internet banking (online). Some online banks are traditional banks which also offer online banking, while others are online only and have no physical presence (Okiro ; Ndungu, 2013). In recent years, the adoption of e-banking as a channel of distribution for financial services has been fuelled by rapid advances in IT and increasing competition in the banking market (Mahdi and Mehrdad, 2010; Okibo ;Wario, 2014).
Globally, the strategic importance of the financial sector in modern economies has continued to fuel rapid innovation and evolution of new financial instruments to enhance competitiveness and customer service delivery. The adoption of e-banking technologies has been attributed to increasing globalization, deregulation of the world banking and financial system (Muiruri and Ngari, 2014). Adoption, both in the developed and developing world, has also been linked to increased access to information and communication technologies. Banking through internet has emerged as a strategic resource for achieving higher efficiency, control of operations and reduction of cost by replacing paper based and labour intensive methods with automated processes thus leading to higher productivity and profitability. The main drivers for adopting e-banking include: cost reduction, performance improvement, wider coverage, revenue growth, and customer convenience (Malhotra ; Singh, 2009). From the customer’s perspective, internet banking facilitates a convenient and effective approach to manage personal finances, as it is accessible 24 hours a day and 365 days in a year without visiting the bank and from any locations (Kombe & Wafula, 2015).
In Africa, a 2014 KPMG study reported that even though financial sectors on the continent remain underdeveloped, the banking industry continues to dominate the landscape in terms of total assets and services. The World Bank estimated that only 14.2% of adults in Sub-Saharan Africa had deposit accounts with commercial banks in 2012, and projected that retail banking in the region will grow at a compound annual rate of 15% between 2013 and 2020, fuelled by the uptake of innovative strategies and banking products that fit consumers’ rising financial sophistication needs as well as tap into the continent’s massive unbanked population (KPMG, 2014). Many commercial banks in Africa have adopted e-banking as a mechanism for differentiation from competitors, reach a wider market share, increase customer satisfaction and lower operational costs, while most customers are using this functionality to choose banking providers and services.
E-banking debuted in Kenya in the early 2000s. There has been a steady increase in use of e-banking technologies such as automated teller machine (ATM), mobile and Internet (online) banking, electronic funds transfer, direct bill payments and credit card (CBK 2008). ATM banking is one of the earliest and widely adopted retail-banking services in Kenya (Nyangosi et al. 2009). However, according to an annual report by Central Bank of Kenya (CBK), its adoption and usage has been surpassed by mobile banking (M-banking) in the last few years (CBK 2008). Currently, there are about 8 million users of M-banking services compared to 4 million people who hold accounts in conventional financial institutions in Kenya (CBK 2008). The tremendous increase in number of people adopting M-banking has been attributed to ease of use and high number of mobile phone users. This is consistent with the theory of consumer choice and demand as conceptualized in Au & Kauffman (2008) in relation to mobile payments. Based on their observation, customers can choose to adopt a particular banking technology such as M-banking, perceived to offer such advantages as ease of use (Kolodinsky & Hogarth, 2001).
With the introduction of e-banking in Kenya, financial institutions have witnessed many changes. Customers now have access to fast, efficient and convenient banking services. They have realized that a company that ignores customer needs and preferences in its products development would be deemed to fail (Agarwal et al. 2009). Njunguna et al (2012) noted that although there has been significant growth of internet users in Kenya, the number of financial transactions carried out over the internet remains low. This is also the trend globally. Even though banks are adopting e-banking platforms, potential users either do not adopt it or do not use it continually after adoption (Njunguna et al., 2012).
While the rapid development of ICT has made some banking tasks more efficient and cheaper, technological advancements have their fair share of problems. Aduda and Kingoo (2012) noted that despite the potential benefits of ICT and e-commerce, there is debate about whether and how their adoption improves bank performance. Use of and investment in ICT requires complementary investments in skills, organization and innovation and investment and change entails risks and costs as well as bringing potential benefits. There are positive impacts of e-banking on bank turnover and profitability and to a lesser extent on employment, most notably when e-commerce is part of larger business strategies of bank. The use of e-banking can contribute to improved bank performance, in terms of increased market share, expanded product range, customized products and better response to client demand. E-banking continues to influence banks activities and their income structure. Among the activities that may be subject to stronger pressures for change are those that, up to today, have remained relatively insulated from ICT developments. This applies mainly to some retail banking activities that are suitable for standardization, and also to developments in remote banking (Aduda & Kingoo, 2012).
Gupta (2000), Aladwani (2001) and Hwanget al. (2003), cited that internet security and customer related issues are the greatest challenges facing banking sectors. While there is a noticeable increase in marketing efforts of e-banking services, the number of online customers remains low (Gikandi & Bloor, 2010; Njunguna et al., 2012). One of the factors associated with the low penetration is perceived privacy and security of the platform (Gikandi & Bloor, 2010).This is true in Kenya since e-banking in Kenya is still developing thus the focus of most banks is on setting up the systems giving less attention to the industry technical issues. Thus there is a need to manage costs and risks associated with internet banking. It is crucial that internet banking innovations be made through sound analysis of risks and costs associated to avoid harm on banks performance (Kombe & Wafula, 2015)
1.1.1. The Banking Sector in Kenya
The Kenyan banking sector comprised of 43 commercial banks, 1 mortgage finance company, 6 deposit taking microfinance institutions, 2 credit reference bureaus, 3 representative offices and 124 foreign exchange bureaus (CBK, 2016). The 8 Kenyan financial sector has undergone tremendous changes in the last two decades (1990-2010). Misati, Njoroge, Kamau and Ouma (2010) for instance, document that financial products have increased, activities and organizational forms have also improved and the overall efficiency of the financial system has increased (CBK 2010).
The financial sector development in Kenya can be reviewed in three phases (Misati, Njoroge, Kamau and Ouma, 2010). The first phase is the 1970s to early 1980s. During this time, the financial sector was largely dominated by the banking sector, which was characterized by financial repression. The government played a key role in allocating credit to investments by utilizing direct instruments of monetary policy such as interest rate controls, exchange rate controls and allocation of credit to priority sectors among other government restrictions (Misati et al., 2010). The second phase began with the advent of Structural Adjustment Programmes and liberalization policies in the late 1980s and early 1990s. Over this period, relaxation of the interest rate, exchange rate and 9 capital accounts controls were witnessed. The essence of the financial sector reforms this time was to trigger narrow interest rates spreads, increase availability of financial resources through increased savings, enhance efficiency in credit allocation and increase investments. Liberalization was also meant to encourage usage of indirect tools in monetary policy formulation. The third phase which is the main focus of this study is the late 1990s to date and can be classified as the era of financial innovation and emerging financial instruments. The period witnessed emergence of new products such as Islamic banking, automatic teller machines (ATMs), plastic money and electronic-money (e-money) amongst others within the banking sector (Misati et al., 2010). Banking industry in Kenya is governed by the Companies Act, the Banking Act, the Central Bank of Kenya Act and other various prudential guidelines issued by the Central Bank of Kenya (CBK).
According to the Global Competitiveness Index (GCI) report of 2011-2012, Kenya ranked 102 overall of the 142 countries ranked with an overall score of 3.8 out of the maximum of 7 putting Kenya among the bottom 50 in terms of competitiveness in the world. Kenya’s innovative capacity is ranked 52nd, with high company spending on Research and Development (R;D) and good scientific research institutions collaborating well with the business sector in research activities. The economy is also supported by financial markets that are well developed by international standards (26th 11 position) indicating potential for growth of the Kenyan banking industry and a relatively efficient labor market (37th position) (WEF, 2011).
The banking industry is a key pillar to the achievement of vision 2030 (a long-term strategy to achieve sustainable growth by year 2030) through increased savings, encouragement of Foreign Direct Investment (FDI), safeguarding the economy from external shocks as well as propelling Kenya to become a leading financial centre in Eastern and Southern Africa. Within the Medium Term Plan (2008- 2012) under vision 2030, some of the target areas include development of a safe and reliable payments system that will ensure smooth transfer and settlement of funds between customers and banks as well as between banks. Towards this end, the use of mobile phone networks, internet, payment cards, operational resilience and security will be pursued in order to increase trust, integrity and confidence in the ICT based payment systems (Government of Kenya, 2008). In comparison with other East African economies, Kenya’s banking sector has for many years been credited for its size and diversification. Private credit to GDP, a standard indicator of financial development, was 23.7% in 2008, compared to a median of 12.3% for Sub-Saharan Africa. Based on the same indicator Kenya is ahead of Tanzania which has 12.3% and Uganda with 7.2% (Beck, Demirguc-Kunt and Levine, 2009).
1.2. Statement of the Problem
Despite the undeniable importance of financial innovation, there is inadequate understanding about the drivers of adoption and use of e-banking systems in the banking industry. In Kenya, traditional branch-based retail banking remains the most widespread, with the recent agency and mobile banking (M-Banking) models receiving wide adoption and usage. However, even though commercial banks have introduced internet banking systems to improve operational efficiency and reduce costs, these systems remain largely unnoticed by customers and remain seriously under-utilized in spite of their availability (Gikonyo, 2014). Studies show that e-banking is very low in Nairobi County, relative to the high rate of internet access (Njunguna et al., 2012). To address the disparity, more studies are needed on e-banking adoption in developing countries, with particular emphasis on the drivers and barriers impacting e-banking adoption, to identify factors which inhibit the adoption and diffusion of e-banking platforms.
Most studies in Kenya have focused on the effect of e-banking and mobile banking on the financial performance (Okigo & Ndungu, 2013; Aduda & Kingoo, 2012; Gichungu & Aloko, 2015); Kombe & Wafula, 2015; Cherotich et al., 2015), customer growth (Okibo & Wario, 2014). However, there is little research on the underlying factors which determine adoption and acceptance of e-banking. To address the current gap in literature, this research project assessed the adoption and performance of e-banking in commercial banks in Kenya using TOE and TAM models, for determining technology adoption and acceptance. According to Fleischer (1990), technology adoption within an organization is influenced by factors pertaining to the technological context, the organizational context, and the external environment, usually presented as the TOE framework (Baltum, 2014). The technology acceptance model (TAM) developed by Davis (1989) to measure the acceptance of technologies, conceptualized perceived usefulness (PU) and perceived ease of use (PEOU) as fundamental determinants of individual user’s adoption intentions and actual usage (Oluoch, 2012).
1.3. General Objective
An analysis of factors affecting the adoption and use of e-banking in Kenya
1.4. Specific Objectives
1.4.1. To establish the influence of organizational capability on the adoption and use of e-banking in Kenya
1.4.2. To establish the influence of perceived technological risk on the adoption and use of e-banking in Kenya
1.4.3. To establish the influence of perceived usefulness (PU) on the adoption and use of e-banking in Kenya
1.4.4. To establish the influence of perceived ease of use (PEOU) on the adoption and use of e-banking in Kenya
1.5. Research Questions
1.5.1. What is the influence of organizational capability on the adoption and use of e-banking in Kenya?
1.5.2. What is the influence of perceived technological risk on the adoption and use of e-banking in Kenya?
1.5.3. What is the influence of perceived usefulness (PU) on the adoption and use of e-banking in Kenya?
1.5.4. What is the influence of perceived ease of use (PEOU) on the adoption and use of e-banking in Kenya?
1.6. Research Hypotheses
1.6.1. H0: There is a significant influence of organizational capability on the adoption and use of e-banking in Kenya
H1: There is no significant influence of organizational capability on the adoption and use of e-banking in Kenya
1.6.2. H0: There is a significant influence of perceived technological risk on the adoption and use of e-banking in Kenya
H1: There is no significant influence of perceived technological risk on the adoption and use of e-banking in Kenya
1.6.3. H0: There is a significant influence of perceived usefulness (PU) on the adoption and use of e-banking in Kenya
H1: There is a significant influence of perceived usefulness (PU) on the adoption and use of e-banking in Kenya
1.6.4. H0: There is a significant influence of perceived ease of use (PEOU) on the adoption and use of e-banking in Kenya
H1: There is no significant influence of perceived ease of use (PEOU) on the adoption and use of e-banking in Kenya
1.7. Significance of the Study
E-banking includes the systems that enable financial institution customers, individuals or businesses, to access accounts, transact business, or obtain information on financial products and services through a public or private network, including the Internet or mobile phone. The study is therefore be beneficial to the banks, customers, and researchers.
The study is of benefit to the banking sector since it generated useful insight on e-banking. Commercial banks can utilize the information to develop suitable business models, awareness programs, and marketing strategies to guide the implementation of e-banking systems, and subsequently increase adoption and performance of e-banking.
E-banking allows customers to conduct banking transactions such as account enquiry printing of statement of account; funds transfer payments for goods and services. The findings of the study are therefore beneficial to customers intending to adopt e-banking. The information can be used to understand the benefits and risks of the technology and guide informed decision-making.
The adoption of e-banking platforms is still in a nascent phase, and is yet to reach the maturity phase in developed countries. As a result, the study identified the factors underpinning the success of e-banking. This knowledge can inform further research and act as a foundation for establishing the knowledge gaps in the field.
1.8. Scope of the Study
The scope of the study was limited to examining four factors influencing adoption and use of e-banking. They include: organizational capability, perceived risk of the technology, perceived usefulness, and perceived ease of use. The study was also restricted to commercial banks registered in Kenya, and operating within Nairobi County. The study will take place between February and April 2017.
1.9. Limitations and Delimitations
The responses to the study depended on self-reporting. There was a possibility of bias and inaccuracy as respondents may not have accurately presented the state of e-banking adoption or the challenges faced in utilizing the technology to access banking services. Further, the time for data collection was minimal as the study period only stretched from March to April 2017. As such, stringent time management practices was put in place during the process as there was no time to go back and collect additional data in case of either low response rates or low quality responses.
On the contrary, to achieve the objectives of the study, the customers represented the most appropriate source of data for the study. The questionnaire was standardized to eliminate ambiguities and ensure that it aligned with the objectives of the research. Standardization helped to reduce or eliminate internal and external validity issues. The chosen descriptive and inferential statistical measures were adequate to elucidate the relationship between perceived usefulness, perceived ease of use, perceived technological risk, and organizational capability on adoption of e-banking in the commercial banking sector in Kenya.
The section presents a critical review of the theories and studies that have been done on the relationship between internet banking and bank performance. The section comprehensively discusses the innovation diffusion theory, technology acceptance model, and the technology–organization–environment (TOE) framework. An empirical review covers studies that have been done on how organizational capability, perceived risk, perceived usefulness, and perceived-ease of use influences adoption and performance of internet banking.
2.2. Theoretical Framework
2.2.1. Innovation Diffusion Theory
According to Dillon and Morris (1996) the factors which influence the diffusion of an innovation include; relative advantage (the extent to which a technology offers improvements over currently available tools), compatibility (its consistency with social practices and norms among its users), complexity (its ease of use or learning), trialability (the opportunity to try an innovation before committing to use it), and observability (the extent to which the technology’s outputs and its gains are clear to see). These elements are not mutually exclusive thus unable to predict either the extent or the rate of innovation diffusion (Rogers, 1983; 2003).
Moore and Benbasat (1991) built on the work of Roger (1983), amongst others Tornatsky and Klein (1982) and Brancheau and Wetherbe (1990) and expanded the array of innovation characteristics to seven. Three of the seven innovation characteristics are directly borrowed from Rogers: relative advantage, compatibility, and trialability. The fourth characteristic, ease of use, is a close relative to Rogers’ complexity. It is worth noting that both relative advantage and ease of use are subjective characteristics since they can be viewed differently depending on an individual’s perceptions. Fishbein and Ajzen (1980) concur, attitudes towards an object and attitudes regarding a particular behaviour relating to that object can frequently differ.
Moore and Benbasat (1991) also derived three further characteristics. While Rogers (1983) included image as an internal component of relative advantage, Moore and Benbasat (1991) found it to be an independent predictor of adoption. Image is the self-perception that adopting an innovation could result in enhanced social status. By analyzing Rogers (2003) diffusion of innovation theory through the lens of the Dubin framework, some gaps in the theory emerge (Lundblad & Jennifer, 2003). Organizations are described as a social system, but within organizations, departments or teams can also serve as social systems. Yet the unique issues and elements of departments or teams within a larger organizational context are not addressed in terms of how these boundaries affect the adoption of innovation. In addition, boundaries are not addressed for instances when diffusion of innovation occurs across organizations, such as between schools of a school district or hospitals and clinics within a health care delivery system (Lundblad & Jennifer, 2003).
For diffusion of innovation theory in organizations, the only system state defined by the theory is what type of decision-making process is in place for adopting and implementing innovations, identified as optional, collective, authority, and contingent innovation-decisions. Rogers’ theory does not tell us whether the system states of organizations need to be in normal operating mode in order for the theory to apply, or whether the theory holds in all types of organizations or only in certain types (Lundblad ; Jennifer, 2003). Specifically, the theory begins to describe the innovation-decision process within organizations, but not to the level of addressing whether and how the characteristics of an innovation interact to affect its adoption within organizations, or whether organizational type, size, or industry affect adoption. In addition, while there is an innovation-decision process described for individuals and within organizations, there is no description of how the variables interact when innovations are diffused across organizations (Lundblad ; Jennifer, 2003).
2.2.2. Technology–Organization–Environment (TOE) Model
The technology–organization–environment (TOE) model was developed by Tornatzky and Fleischer which is designed for studying the likelihood of adoption success of technology innovations. This framework is a comprehensive and well received framework in the context of innovation adoption by organizations and has been used in many studies. According to Tornatzky and Fleischer (1990), technology adoption within an organization is influenced by factors pertaining to the technological context, the organizational context, and the external environment.
Based on this model it is possible to framework to summarize possible key factors affecting the adoption of technological innovations. For instance, in the case of e-banking, the environmental context refers to the external environment in which an organization operates and its condition for supporting the development of e-banking services, while the organizational context refers to the organization’s characteristics that influence its ability
to adopt and use e-banking. The technological context refers to adopter’s perception of e-banking attributes. Typical characteristics of technology considered in technology adoption studies are based on Roger’s diffusion of innovation theory which includes relative advantages perceived benefits, compatibility, trialability, complexity and perceived risks.
2.2.3. Technology Acceptance Model
To understand, predict and explain why people accept or reject information systems; researchers have developed and used various models to understand the acceptance of users of the information systems. The technology acceptance model (TAM) that was introduced by Davis, Bagozzi, and Warshaw (1989) is one of the most cited models that researchers used to study underlying factors that motivate users to accept and adopt a new information system (Al Shibly, 2011). The primary goal of TAM is to provide an explanation of factors affecting
computer applications’ acceptance in general. In addition, this model helps researchers and practitioners to identify why a particular system is unacceptable (Davis, 1989).
Davis et al (1989) suggested that using an information system is directly determined by the behavioral intention to use it, which is in turn influenced by the users’ attitudes toward using the system and the perceived usefulness of the system. Attitude and perceived usefulness are also affected by the perceived ease of use. According to TAM, greater perceived usefulness and the perceived ease of use of an information system will positively influence the attitude toward this system. The attitude, in turn leads to a greater intention to use the system, which positively affects one’s actual use of the system. TAM supposes that, other thing being equal, perceived usefulness is influenced by the perceived ease of use because the easier a technology to use, the more useful it can be.
Therefore, the Technology Acceptance Model (TAM) model relates the individuals’ behavioural intentions and his/her ICT use (Davis 1989). Adopting the TAM model requires the understanding of end-users requirements regarding usefulness and user friendliness (Pedersen et al, 2002). From this model, usefulness and user friendliness affect users’ attitudes towards any service. Davis (1989; 1993) suggested that it is important to value user requirements based on perceived usefulness and the user friendliness of the technology rather than other objective measure.
Perceived usefulness (PU) is defined as the degree to which a person believes that using a particular system would enhance his or her job performance. Perceived ease of use (PEU) refers to the degree to which a person believes that using the system will be free of effort. Attitude (ATT) explains a person’s favourable or unfavourable assessment regarding the behavior in question. Intention (INT) is a measure of the strength of a person’s
willingness to use effort while performing a certain behaviour. The external variables in the model refer to a set of variables that can influence information system adoption indirectly through perceived ease of use and perceived usefulness (Davis et al., 1989).
According to Taylor and Todd (1995), constructs of TAM are almost measured in
the same way in every context. Furthermore, TAM is a reliable instrument and empirically sound. Several metaanalysis studies have provided sufficient data about TAM to be highly credible and rationally explain up to 40 percent of the behavioral intention to use (King and He, 2006; Yousafzai, Foxall, and Pallister, 2007). In addition, several studies have applied TAM to evaluate users’ adoption in different settings such as electronic commerce
(Gefen, Karahanna, and Straub, 2003); electronic learning (Arbaugh, 2000); internet banking (Al Sukkar and Hasan, 2005) and e-government (Alhujran, 2009).
Critiques of this model are directed to its inclination to the technological/technical aspects of the technology in question ignoring other factors such as social aspect of the users. In practice, constraints such as limited ability, time, environmental or organizational limits and unconscious habits will limit the freedom to act. According to the Technology Acceptance Model (TAM), perceived ease of use and perceived usefulness constructs are believed to be fundamental in determining the acceptance and use of various internet and information technologies. These beliefs may not fully explain the user’s behaviour toward newly emerging IT. In using TAM to investigate the factors determining acceptance of internet banking by users, Wang et al. (2003) introduced “perceived credibility” as a new factor that reflects the user’s security and privacy concerns in the acceptance of internet banking. Wang et al. (2003) examines the effect of computer self-efficacy on the intention to use internet banking. The results strongly support the extended TAM in predicting the intention of users to adopt internet banking. It also demonstrates the significant effect of computer self-efficacy on behavioural intention through perceived ease of use, perceived usefulness, and perceived credibility (Wang et al., 2003).
Figure 2.1: Theoretical framework
2.3. Empirical Review
2.3.1. Organizational Capability and Adoption and Use of E-banking
Organizations are different in their inclination to adopt innovation technology and they are in influenced by a number of factors (Chitura, 2008). Some of the main factors are firm size, financial and human resources, and top management support. Firm size has been widely recognized as an important factor determining an organization’s ability to adopt a new innovation as well as capitalizing on its benefit (Zhu et al., 2003; Anderson et al., 2003; Bertschek ; Fryges, 2002). Large organizations have the resources and skills to adopt new technologies and have enough business volume to justify the investment. Therefore, it is also expected to affect the adoption of e-banking by banking institutions.
Financial resources are an important factor in facilitating innovation adoption for any organization and they are often correlated with the firm size. Therefore, it is expected that the availability of financial resources within the adopting firms is important for e-banking adoption. These resources enable banking institutions to obtain human related resources including the required skills and expertise to develop and support e-banking services (Kurnia, Peng, ; Liu, 2011).
Top management of an organization is also commonly identified as an important factor for any technology adoption within an organization. If top management is assertive in their decision making regarding e-banking adoption and committed to it, the adoption is likely to take place. In addition, with the top management support through the provision of the
required resources, organization’s inclination to adopt e-banking or any new technology will be improved (Scupola, 2003).
Kurnia, Peng, and Liu (2011) explored factors which affect the adoption of electronic banking in China. The study noted that electronic banking was facilitated by various electronic commerce (EC) technologies which helped commercial banks to stay competitive through productivity gains, transaction cost reduction, and customer service management. However, the study realized that despite reported benefits of e-banking, adoption in developing countries continues to fall behind that of developed countries. In response to the paucity of studies on factors affecting e-adoption in China, the researchers used the technology-organizational-environmental framework to investigate the phenomenon. The results demonstrated that the benefits of the technology were recognized such as improved customer services, business efficiencies and cost reductions. By introducing e-banking services, the four banks analyzed in the study were able to successfully reduce the counter pressure and customer waiting time by diverting a portion of customers to the electronic service medium. E-banking also enabled the establishment of more efficient and effective business processes and allowed the banks to successfully address the rapidly
increasing retail banking transaction volumes without significant increases in staffing costs.
Daghfous and Toufaily (2007) investigated the success and critical factors in adoption of e-banking by 51 Lebanese banks, 31 of them operated internationally while 26 are strictly local. The study focused on the factors associated with successful adoption of e-banking as well as those acting as a barrier to its adoption. These factors were organizational, structural and strategic factors which can accelerate or, on the contrary, slow the adoption of this electronic mode of distribution and communication by the bank. The findings showed that the organizational variables (bank size, functional divisions, technical staff, technical infrastructure, perceived risks, decision makers` international experience and mastery of innovation) exerted significant impact on the adoption of E-banking. The structural characteristics, findings showed that the internal technological environment of the bank is a very important factor in determining the adoption of e-banking also the result shows that banks which are developing in the international scale are more likely to adopt e-banking innovations. Finally the result of the study indicated that extent of penetration of e-banking in the growth phase of an emerging market has an important correlation with the improvement
of commercial performance.
Shah et al. (2005) investigated the critical success factors (CSF) in e-banking conducted in United Kingdom. The purpose of the study was to determine the critical issues related to financial sector organizations when they establish businesses online. The finding of the study showed that understanding the critical success factors was important in helping banks improve their strategic planning process. The study demonstrated that the top six organizational factors responsible for adoption and use were a user-friendly website, systems security, support from top management, fast responsive customer service, promotion of electronic commerce within organization, and all time availability of services and rapid delivery of services.
Bultum (2014) investigated the factors affecting the adoption of electronic banking system in the Ethiopian banking industry. The sample consisted of four banks, one state-owned bank and three private banks. A mixed-method design was used in the study, with questionnaires used for data collection. The study was also grounded on the technology-organization-environment model (TOE) developed by Tornatzky and Fleischer. The findings of the study showed that the main factors affecting adoption are security risk, lack of trust, lack of legal and regulatory frame work, Lack of ICT infrastructure and absence of competition between local and foreign banks. As such, the study recommended that the governance challenges facing the organizations should be tackled, particularly the need to establish a legal framework governing e-banking and investing on ICT infrastructure.
2.3.2. Perceived Technological Risk and Adoption and Use of E-banking
One of the important risks faced by banking institutions in offering e-banking services is the
customers’ resistance to use the services which significantly hinder the growth of e-banking. The main issues related to this refusal are issues about security, which has been recognized as a recurrent concern during the introduction of new technology and can negatively affect e-banking transactions. As such, the perception of the risks regarding e-banking is expected
to influence the adoption and further growth (Kurnia, Peng, ; Liu, 2011). According to the TAM model, consumer behaviour studies define perceived risk (PR) in terms of the customer’s perception of the uncertainty and potential adverse consequences of buying a product or services. The degrees of risk that customers perceive and their own tolerance of risk tacking are factors that influence their purchase decision (Nasri, 2011). On another
hand, introducing a new technology may involve both benefits and risks to the user, and before deciding to adopt the technology, the individual may want to weigh risks and benefits. Electronic banking services will not be an exception to this general rule. A larger perception of risk will reduce the perceived benefit of the technology (Horst, Kuttschreuter, 7Gutteling, 2007).
According to Featherman and Pavlou (2003) perceived risk is the potentiality of loss in the pursuit of a desired outcome of using electronic services. It increases with the higher level of uncertainty or with an increased chance of negative consequences (Lu, Hsu, and Hsu, 2005). Customers’ perceived risk is a multi dimensional construct, and such dimensions may vary according to the product or service type. There are five dimensions of perceived risk have been identified in the previous studies. They are: performance risk, social risk, financial risk, privacy risk and time risk (Featherman ; Pavlou, 2003; Kuisma et al., 2007; Lu et
al., 2005; Natarajan et al., 2010). Performance risk refers to losses incurred deficiencies of electronic services. Customers are often worried that a break down in the system servers will occur while conducting electronic services, because these situations may result in unexpected losses (Kuisma et al., 2007). Littler and Melanthiou (2006) noted that a break down in the system could reduce customers’ willingness to use online banking. Social risk refers to the potential loss of status in one’s social group as a result of adopting a product or service
(Featherman MS and Pavlou PA, 2003). It is possible that one’s social standing may be enhanced or diminished depending on how electronic banking services are viewed. Yang, Park, and Park (2007) found that social risk has a negative impact on attitude for consumers. Financial risk is defined as the potential for monetary loss due to transaction error or bank account misuse. Many customers resist using online banking because they fear from such losses (Kuisma et al., 2007). Privacy risk refers to the potential loss of control over personal information which is used without knowledge or permeation (Featherman & Pavlou, 2003). Horst et al (2007) stated that the greatest challenge of the electronic banking sector will be winning the trust of customers over the issue of privacy and security. Finally, time risk refers to the loss of time in implementing, learning how to use and troubleshooting a new electronic service (Natarajan et al., 2010). Consumers are less likely to adopt an electronic service that they consider having high setup and maintenance costs (Featherman & Pavlou, 2003).
Khalfan et al (2006) carried out a descriptive case study on the factors influencing the adoption of internet banking in Oman. The purpose of the study was to identify the main potential factors or impediments that are currently inhibiting the incorporation or adoption of E-commerce applications in the Omani Banking sector. The results of the study demonstrated that security and data confidentiality issues have been a major barrier. The banking sector was reluctant to use e-commerce applications as they felt that transactions conducted electronically were open to hackers and viruses, which are beyond their control. Lack of top
management support is the other inhibiting factor in the adoption of electronic commerce applications.
Gerrard et al. (2006) in their study in Singapore identify risk to be an important factor for
internet banking adoption. All respondents who did not use internet banking services had a negative perception of the security of e-banking. The respondents perceived that there were many security risks when using the internet. They felt the privacy was a concern, feeling all their financial information could be in jeopardy. Risk was one of the two most frequently mentioned factors in their study. Concern about risk was mentioned by all respondents. An empirical investigation conducted by Sathye (1999) on the adoption of internet banking by Australian consumers also identified, security concerns as key factor in internet banking adoption. A report on internet banking in Australia established that security concerns among banks and customers are keeping both away from internet banking.
2.3.3. Perceived Usefulness and Adoption and Use of E-banking
Perceived benefits of e-banking cover both direct and indirect benefits for the banking institutions. Direct benefits include the savings on operational cost, improved organisational functionality, productivity gain, improved efficiency and increased profitability. Indirect benefits include the opportunity or intangible benefits such as improved customer’s satisfaction through improved services, improved banking experience and fulfilment of their changing needs and lifestyle (Kurnia, Peng, ; Liu, 2011).
Kerem (2003) explored the underlying consumer behaviour and critical success factors on the adoption of electronic banking in Estonia. The was intended to study the further
understanding of, how consumers perceive electronic banking in the heyday of interactive channels in Estonia, as Estonia is internationally renowned for being a pioneer in the acceptance of new technologies. A series of an in depth interviews was conducted with leading industry experts in Estonia. The selection criterion for the respondent was mainly their involvement with the development of Internet banking systems from the early days of its emergence. The survey conducted for this research addressed six different issues influencing the adoption of Internet banking (better prices, recommendations, better service, marketing efforts, better access and higher privacy). The most important factors in starting to use internet banking are first and foremost better access to the services (convenience), better prices and higher privacy. Better service (preferring self service over office service) was also of above the average importance. Two factors that the respondents did not consider
relevant to their adoption decision were banks’ marketing activities and personal recommendations from friends and colleagues.
Bichanga and Wario (2014) investigated the effects of e-banking services on growth of customer base in Kenyan banks for over the last 5 years and what factors hindered the effective utilization of E-banking service in Kenyan banks and its impact on growth of customer base. The study addressed issues that affected effective utilization of E-banking facilities by customers, particularly how lack of technological know-how, illiteracy, unreliability, and transaction limits has hindered growth of on-line customer base in Kenyan banks. Using a descriptive study approach, the researchers found out that e-banking provided enormous benefits to consumers in terms of time saving and cost of transactions, either through internet, telephone or other electronic delivery channels. For many consumers, electronic banking means 24-hours access to bank services. E-banking was found to enhance the growth of the customer base for the banking institutions in Kenya, by increasing service accessibility.
In another study in Kenya, Aduda and Kingoo (2012) investigated the relationship between e-banking and performance of Kenya banking system. Specifically, the researchers were interested in the relationship between investments in e-banking, number of ATMS and number of debits cards and performance measured by return on assets. The findings of the study showed that e-banking has strong and significance marginal effects on returns on asset in the Kenyan banking industry. Therefore, there is a positive relationship between e-banking and bank performance, and banks should invest in e-banking as a way of bringing services closer to its customers.
Okiro and Ndungu (2013) investigated the adoption of internet and information technology and mobile technology in 30 banks in Kenya. The researchers were interested in determining the effect of mobile and internet banking innovations on the performance of financial institutions. The results indicated that these technological innovations made banking tasks more efficient and cheaper. The most common use of e-banking was balance inquiry while the least common was online bill payment. Cash withdrawal was the most commonly used mobile banking service whereas purchasing commodities was the least commonly used.
Ernst and Young (2014) carried out a survey to determine customer’s satisfaction with e-banking. To stay competitive, financial institutions need to continue building out channel capabilities to provide 24/7 real-time access. The survey found out that in an online context, where human interactions are replaced by graphic user interfaces, the important role in customer satisfaction is fairness. Trust is identified as the key mediator of fairness to customer satisfaction. E-banking can be used to increase customer loyalty and consequently enhance customer satisfaction and build stronger relationships with customers. The integration of electronic banking into the multichannel strategy of financial institutions was found to correlate with higher quality service and greater satisfaction among clients.
Kombo et al (2015) investigated the perceived usefulness of e-banking, in terms of how it influenced customer satisfaction in Kenya and Czech banking sectors. The study used customer satisfaction surveys because this is the main source of information to set strategies aimed at meeting needs or understanding of customer perceptions, most importantly showing relationships and possible areas of improvement for customers. The banks drawn from the Czech Republic were ?eská spo?itelna, Komer?ní banka, GE Money Bank and UniCredit Bank, while the banks sampled in Kenya were Co-operative Bank, K-Rep Bank, Kenya Commercial Bank and Equity Bank. The results showed that the customers in Kenyan banks were less satisfied with e-banking when compared to customers in the Czech Republic. The level of dissatisfaction, however, differed depending on the democratic characteristics.
Al-Smadi (2011) investigated the impact of e-banking on the performance of Jordanian banks. The study examined the impact of electronic banking on performance in 15 Jordanian banks for the period 2000-2010. The findings of the study showed that electronic banking has a significant negative impact on banks’ performance. Electronic banking has not improved
the performance of these banks. Banks’ customers in Jordan depend on traditional
channels to carry out their banking operations. As a result, costs associated with
adopting electronic banking are still higher than revenues from provision electronic
services. Hence, banks should focus its work to promote the confidence of electronic
banking services and encourage the customers to use this kind of services.
2.3.4. Perceived Ease of Use and Adoption and Use of E-banking
Sahoo and Swain (2012) sought to establish whether e-banking is performing as per the perception amongst the customers and the employees or is there gap between the perceived value and the performance. The researcher disagreed with the position that customers using e-banking can access services more easily from banks abroad and through wireless communication systems, which are developing more rapidly than traditional “wired”
communication network. To disconfirm this notion, the researchers sampled customers and employees of Punjab National Bank of India. The findings showed that there is a gap is
exiting between perceived value and performance of e-banking services. As such the researchers recommended that e-banking services should be made available to customers, and banks implement product awareness to increase knowledge and adoption of e-banking services.
Gikonyo (2014) investigated the factors influencing the adoption of internet banking in Kenya. Specifically, the study sought to determine how awareness of IB by the consumers
affect adoption of internet banking, and how website security affects adoption of internet banking and to determine to what extent website features affect adoption of internet banking. A multi-linear regression analysis was used to analyze the data and the findings demonstrate that men have adopted banking than women; education level is not a barrier to the banking
services, the middle-aged people have embraced the banking services than any other age category; awareness, website features and security all affect the adoption of internet banking.
Njunguna et al (2012) investigated internet adoption in Kenya, with particular interest in Nairobi County between 2010 and 2011. The researchers sought to identify factors such as perceived usefulness, perceived ease of use, self-efficacy, relative advantage, compatibility, and result demonstrability. The research was grounded in two models: technology acceptance model (TAM) and perceived characteristics of innovation (PCI) model. The findings showed that internet banking use in Kenya is very low, with only a quarter of the customers using internet services. The findings further show that internet banking use is popular to both the male and the younger generations. Internet banking is still at its nascent stages as demonstrated by the length of usage response. The results also reveal that perceived
usefulness, perceived ease of use, self-efficacy, relative advantage, compatibility, and result demonstrability have a significant association with intention to use internet banking, while risk, visibility and trialability are not significant. Both the modified TAM and PCI models used in the study have a similar explanatory power of slightly over 20% of the variance in intention. In the TAM model, perceived usefulness and self-efficacy are significant
variables, while compatibility is the only variable significant for the PCI model. Further, results indicated that users’ perceptions of various aspects of internet banking are more positive than non-users’ perceptions, except for risk. The researchers recommended additional studies that incorporate other variables and models to establish the benefits of internet banking.
2.4. Research Gap
There are various studies that have been done on technology adoption. However, in Kenya, most studies have focused on the effect of e-banking and mobile banking on the financial performance (Okigo ; Ndungu, 2013; Aduda ; Kingoo, 2012; Gichungu ; Aloko, 2015); Kombe ; Wafula, 2015; Cherotich et al., 2015), customer growth (Okibo ; Wario, 2014). However, there is little research on the underlying factors which determine adoption and acceptance of e-banking. To address the current gap in literature, this research project will assess the adoption and performance of e-banking in commercial banks in Kenya using TOE and TAM models, for determining technology adoption and acceptance. According to Fleischer (1990), technology adoption within an organization is influenced by factors pertaining to the technological context, the organizational context, and the external environment, usually presented as the TOE framework (Baltum, 2014). The technology acceptance model (TAM) developed by Davis (1989) to measure the acceptance of technologies, conceptualized perceived usefulness (PU) and perceived ease of use (PEOU) as fundamental determinants of individual user’s adoption intentions and actual usage (Oluoch, 2012).
2.5. Conceptual Framework
The following conceptual framework shows the relationship between the independent variables (organizational capability, perceived technological risk, perceived usefulness, and perceived ease of use) and adoption of e-banking.
Figure 2.2: Conceptual Framework
2.6. Operationalization of Variables
The first independent variable is organizational capacity, measured through the parameters: ICT infrastructure, human resources, and financial resources. Financial innovations such as ATMs, mobile banking, internet banking, and agency banking among other banking applications depend on the presence of an e-banking ICT infrastructure. In the study, the parameter, ‘ICT infrastructure’ examines the presence of an e-banking infrastructure through which e-banking services are accessed. In addition, the presence of adequate and well trained human resource personnel is responsible for the management, monitoring, and maintenance of the ICT infrastructure. Both the ICT infrastructure and human resources require adequate financial investment. Therefore, the technological, human, and financial resources influence the adoption and use of e-banking system.
The second independent variable is perceived risk. How customers perceive the uncertainty and potential adverse consequences of a product/service in the market influences whether they will adopt it. In the study, three types of risks will be examined: performance risk, time risk, and privacy risk. Performance risk refers to losses incurred deficiencies of electronic services. Customers are often worried that a break down in the system servers will occur while conducting electronic services, because these situations may result in unexpected losses. Such a breakdown has the potential of reducing the willingness to use e-banking services. Time risk is concerned with the possible loss of time in learning how to use the e-banking platform and how to troubleshoot in the process of accessing banking services. Lastly, privacy risk is the potential loss of control over personal information which is used without knowledge. Winning the trust of customers over the issue of privacy and security of their personal banking information lies at the core of perceived risk associated with a service.
The third independent variable is perceived usefulness. The variable is assessed through three parameters: system efficiency, adequacy in service options and usefulness in making transactions. Perceived usefulness is the degree to which a person believes a particular system will enhance his or her job performance. System efficiency implies that the customers are able to use the e-banking platform to accomplish their tasks over the shortest time possible. Further, there should be diverse service options to enable the customer to perform their tasks. Finally, the study looks into advantage of the service vis a vis other traditional options.
The last independent variable is perceived ease of use. This is concerned with the degree to which the person believes that using the system will be free of effort. Ease of use is determined by examining how easy customers can learn and use the system, how user-friendly the e-banking user-interface has been designed to ensure that customers do not invest a lot of mental effort, and finally, customers should not have to undergo extensive training to be able to use the services.
The dependent variable in the study is adoption of e-banking. There are common products and services that customers access from e-banking, such as: cash deposit, cash withdrawal, money transfers, loan payment, bills payment (e.g. electricity, school fees), mobile top up, and balance inquiry (mini statements). Adoption of e-banking is the frequency by which customers access these banking services through the e-platform.
Table 2.1: Operational Framework
Independent Variables Parameters Dependent Variable
Organizational capability ICT infrastructure Adoption and use of e-banking services
• E-banking components adopted by commercial banks
• Use of electronic banking services
Perceived technological risk Performance risk
Perceived usefulness System efficiency
Adequate service options
Minimal mental effort
Perceived ease of use Easy to learn
User interface navigation
Minimal training needs
Source: Researcher (2017)
This chapter presents the research design and justification, sample population, sample size, sampling procedures, operational definitions of variables, data collection methods, reliability and validity, and data analysis techniques.
3.2. Research Design
A descriptive design was used to investigate the phenomenon under study. Descriptive research design is employed to investigate situations where the researcher’s primary interest is describing and making interpretations about the research phenomenon. In descriptive research design, the phenomenon is investigated as it is without any artificial manipulation from the researcher (Mertler, 2006). It involves collecting quantitative information that can be tabulated and presented in numerical form to establish causal relationships between given variables. In most cases, data is collected using survey instruments such as questionnaires and interviews. The justification for using descriptive research design stems from the fact that it enables the researcher to establish relationships between variables and examine people’s beliefs, opinions, and perceptions on a set of questions under study (Golafshani, 2003).
3.3. Target Population
Cooper and Emory (1995) define population as the total collection of elements about which the researcher wishes to make some inferences. Element is the subject on which the measurement is being taken and is the unit of study (Cooper & Emory, 1995).
There are 44 licensed commercial banks operating in Kenya, however 1 bank (Charterhouse) is in statutory management and 2 banks (Imperial Bank and Chase Bank) are in receivership. According to the CBK Bank Supervision Annual Report (2015), the banks that are not under statutory management or receivership are classified into three peer groups: large, medium, and small, based on a weighted composite index (constituting net assets, customer deposits, capital and reserves, number of deposit accounts and number of loan accounts). As at 31st December 2015, there were 7 large banks representing a weighted market share of 58.21%, 12 medium banks representing a weighted market share of 32.42%, and 21 small banks representing a weighted market share of 9.24%. The criterion used for choosing the target population in this study is the weighted market share. The target population for this study are the 7 large commercial banks in Nairobi: Kenya Commercial Bank, Co-operative Bank of Kenya, Equity Bank, Barclays Bank, Standard Chartered Bank, Commercial Bank of Africa, and Diamond Trust Bank. These banks have the biggest market share, have the highest number of customers, and have made significant investments in e-banking. The population sample consists of the bank staff (senior managers and departmental managers) and a proportionate number of customers drawn from each selected bank.
Table 3.1: Population Sample
Category Population Sample Frequency
Senior Managers (Senior & Branch Managers) 14 9%
Department Managers (Corporate Affairs Manager, Customer relationship Manager, Credit Manager, Operations Manager, Brand Manager, ICT Manager) 42 26%
Customers 105 65%
TOTAL 161 100%
Source: Researcher (2017)
3.4. Sampling Procedure
A sample is a subset of a population that’s has been selected to reflect or represent characteristic of a population. Gerstman (2003) states that a sample is needed because a study that is insufficiently precise lacks the power to reject a false null hypothesis and is a waste of time and money. A study that collects too much data is also wasteful. Therefore, before collecting data, it is essential to determine the sample size requirements of a study.
The study used stratified random sampling technique to generate the sample size for the study. Yamane’s ransom sampling formula was used (Yamane, 1967).
n = N
n = the sample size
N= the size of the population
e = the error of 5 percentage points
95% confidence level (p = 0.05) are assumed.
Calculating for n:
Therefore, the sample size for the study was 115 respondents.
Table 3.2: Sample Size
Category Population Sample Sample Size Frequency
Senior Managers (Senior & Branch Managers) 14 10 9%
Department Managers (Corporate Affairs Manager, Customer relationship Manager, Credit Manager, Operations Manager, Brand Manager, ICT Manager) 42 30 26%
Customers 105 75 65%
TOTAL 161 115 100%
Source: Researcher (2017)
3.5.1. Research Instrument
Questionnaires were used to collect data. Questionnaires allow for the collection of standardized information that can either be expressed numerically or in short responses. The questionnaire contained questions on the four objectives: organizational capability, perceived technological risk, perceived usefulness, and perceived ease of use and how they relate to the adoption of e-banking in Kenya. The scoring for the question was based on a 5-point likert-type scale, using Strongly Agree (5), Agree (4), Neutral (3), Disagree (2) and Strongly Disagree (5) to determine the level of agreement with specific questions.
The choice of the questionnaire was informed by the fact that it is the most common data collection instrument in survey research and enables researchers to determine the characteristics of a sample, the motivations and beliefs, and their actions with respect to a specific research question. The main justification of choosing standardized questionnaires was that they eliminate uncertainties and ambiguities that may arise from irrelevant answers while increasing the validity and reliability of the results. Questionnaires also grant anonymity to respondents and eliminate the impacts of researcher obtrusiveness. Finally, questionnaires are relatively inexpensive to administer and significantly easier to analyze.
The researcher carried out a pilot study before the questionnaire was employed in the final and actual data collection process. The importance of the pilot study was to detect ambiguity, evaluate the type of answers given to determine whether they help the researcher to achieve the laid down objectives. The researcher administered a pre-test sample to 40 respondents (10% of the total sample). According to Mugenda & Mugenda (2003) a pre-test sample should be between 1% and 10% depending on the sample size. The findings from the pilot study was used to refine the questionnaire for final administration.
3.5.3. Instruments Validity
Validity was established by determining whether the questionnaire contents are measuring what they are supposed to measure. The first stage of ensuring validity was refining and improving on the survey instrument before and after the pilot study as a means of enhancing instrument repeatability and internal consistency. By using standardized measures to capture the different experiences and perspectives of the target sample population, the researcher fitted all these differences into predetermined response categories. Validity of the questionnaire was ascertained by making sure that its items sufficiently cover the research objectives. To enhance validity, the questionnaire was subjected to experts for judgment and peers for review.
3.5.4. Instruments Reliability
Reliability is a measure of the degree to which a measuring instrument yields consistent result or data after repeated trials, Mugenda & Mugenda (2003). Pearson product moment correlation coefficient (r) was used to test reliability of the questionnaire. The correlation coefficients of the halves were corrected by Spearman Brown Prophesy formula and the Cronbach’s Alpha Reliability Coefficient above 0.7 will be used to judge whether the reliability level is satisfactory. Nunnaly (1978) indicated 0.7 to be an acceptable reliability coefficient.
3.5.5. Ethical Considerations
The first step of ensuring that the research complies with all relevant ethical considerations involved seeking authorization from the faculty and the bank from which the customers were drawn. The researcher confirmed to all participating respondents that the study was primarily for academic purposes only. Finally, the researcher adhered to the ethical principles of voluntary participation, obtained informed consent, eliminated any potential for harm, and maintained anonymity and confidentiality.
3.5.6. Data Collection Methods
For primary data, the questionnaires were administered by the researcher with the help of two assistants to the bank customers of the main branches of the sampled banks: Kenya Commercial Bank, Co-operative Bank, Equity Bank, Barclay Bank, Standard Chartered Bank, Commercial Bank of Africa, and Diamond Trust Bank. The research assistants had undergraduate-level education and were trained by the researcher before the commencement of the data collection process. Completed questionnaires were collected and stored for data analysis.
Secondary data will also be collected on the various components of e-banking platforms that have been adopted by commercial banks in Kenya. E-banking systems vary in their configurations depending on a variety of factors, both internal and external, hence financial institutions choose and build unique e-banking system configurations. Secondary data will be collected from publicly available organizational documents published by commercial banks as well as industry reports.
3.6. Methods of Data Analysis
The data collected from the questionnaires was analyzed using both descriptive and inferential statistical measures. All the data collected was coded and entered into an Excel sheet, organized and cleaned for any inconsistencies. The Statistical Packages for Social Sciences software (SPSS 21) was used for descriptive and inferential analysis. Descriptive statistics are ways of summarizing large sets of quantitative (numerical) information such as means, modes, medians, and standard deviations and presenting analysis in tables, charts, and graphs that describe, organize, and summarize the data. Since descriptive statistics do not allow for generalizations, inferential statistics were used to determine whether there was any form of linearity, homogeneity, normality, and independence in the data. Therefore, inferential statistics are statistics which are used to make inferential statements about a population.
Multiple regression was used to establish the relationship organizational capacity, perceived technological risk, perceived usefulness, perceived ease of use and the adoption and use of e-banking services in commercial banks operating in Nairobi County. The following regression model took the form of:
y = ? + ?1×1 + ?2×2+?3×3+?4×4 + ?
y intercept is the endogenous variable
? denotes the y intercept where x is zero; ?1, ?2, ?3, ?4 are regression weights attached to the exogenous variables: x1, x2, x3, and x4; and ? is the error term.
Replacing for the variables:
P = ? + ?1OC + ?2PR+?3PU+?4 PEOU+ ?
P denotes e-banking adoption and use
OC denotes organizational capacity
PR denotes perceived technological risk
PU denotes perceived usefulness, and
PEOU denotes perceived ease of use.
DATA ANALYSIS AND INTERPRETATION
This chapter presents the analysis and interpretation of the data. Both descriptive and inferential statistics were used to analyze the data collected using questionnaires administered to the customers of Kenya’s 7 largest banks, namely, Kenya Commercial Bank, Cooperative Bank of Kenya, Equity Bank, Barclays Bank of Kenya, Standard Chartered Bank, Commercial Bank of Africa, and Diamond Trust Bank.
4.2. General Information
4.2.1. Response Rate
A total of 115 questionnaires were administered to customers sampled from the 7 biggest banks. From questionnaires collected, 113 were complete and had all the questions answered. This represents a response rate of 98.3%. All completed questionnaires proceeded to data analysis.
The gender distribution was relatively even with male making 56.6% of the total population sample and female 43.4%. Table 2 below show the descriptive frequency and percentage of gender in the survey.
Table 4.1: Gender
Male 64 56.6
Female 49 43.4
Total 113 100.0
Source: Author’s computations (2017)
Most participants in the study were between the ages of 21- 30 years (50.4%) and the least participants were from the ages of Over 51 years (13.3%). Respondents under the age bracket of 31-40 years and under 20 years constituted 18.6%, 17.7 % respectively.
Table 4.2: Age
Under 20 years 20 17.7
21- 30 years 57 50.4
31-40 years 21 18.6
over 51 years 15 13.3
Total 113 100.0
Source: Author’s computations (2017)
4.2.4. Level Education
The findings shows the highest number of respondents had a Degree as the highest level of education. Respondents with degrees constituted 59.3%, followed by 16.8% with secondary certificate, 15.9% with certificate/ diploma, master’s degree 6.2% and lastly people with PHD constituted 1.8% of the total respondents. The pie chart below show the distribution in percentage. Table 4.3 below show the distribution of the level of education of the respondents
Table 4.3: Level of education
Secondary 19 16.8
Certificate/Diploma 18 15.9
Degree 67 59.3
Masters 7 6.2
PhD 2 1.8
Total 113 100.0
Source: Author’s computations (2017)
4.2.5. Duration as a Customer with the Bank
The customer distribution in the table (8) above shows that most participants in the survey have been customers of respective banks for a period between 1- 5 years (42.5%) , followed by those who have less than 1 year (24.8%). people with 6-11 years membership institute (19.5%) and 4.4% of respondents have over 15 years customer relation with the banks. The table below shows the distribution.
Table 4.4: Duration as a Customer with the Bank
Less than 1 year 28 24.8%
1- 5 years 48 42.5%
6- 10 years 22 19.5%
11- 15 years 10 8.8%
over 15 years 5 4.4%
Total 113 100.0
Source: Author’s computations (2017)
4.2.6. Electronic Banking Services
The table 4.5 above shows that that majority of the respondents in the study (106 customers) know about the ATM service as a mode of e- banking service. The internet banking services is the least known e-banking service with only 70 people having the knowledge of the service. The mobile banking and credit card E-banking services come as second and third respectively with 103 and 84 customers knowing the services. Despite the ATM services being the most known E-banking service, most participants use the Mobile banking E- banking. 91 respondents recorded to use Mobile banking while 88 participants recorded to use ATM, 43 used credits cards and the least used service is the internet banking with 40 people.
Table 4.5: Electronic Banking Services
Know ATM 106 17.0
Use ATM 88 14.1
Know internet banking 70 11.2
Use internet banking 40 6.4
Know mobile banking 103 16.5
Use mobile banking 91 14.6
Know credit cards 84 13.4
Use credit cards 43 6.9
Source: Author’s computations (2017)
4.2.7. Usage of the Banking Services
The most used banking service was the Cash withdrawal service (mean score 3.58) and the least used service is the Loan payment service (2.73). Briefly, the Cash deposit service (3.51), balance enquiry (3.35), Credit top up (3.17), Bill payment (3.08), Money transfer (3.07) follow Cash Withdrawal in a descending order. The ? (standard deviation) show that Cash withdrawal has the lowest dispersion while Mobile Airtime Recharging has the highest dispersion among the Bank customers. In essence, most people Very frequently use the Balance Enquiry service similarly most people don’t use the Loan payment service. People frequently use cash deposit, cash withdrawal, money transfer and Mobile airtime Recharging. Additionally customer rarely use the Bill payment service.
Table 4.6: Usage of the Banking Services
Cash deposit Cash withdrawal Money transfers Loan payment Bill payment Mobile airtime recharging Balance inquiry
Mean 3.51 3.58 3.07 2.73 3.08 3.17 3.35
Std. Deviation 1.158 1.208 1.341 1.363 1.370 1.511 1.382
Source: Author’s computations (2017)
4.3. Organizational Capability and Adoption and Use of e-Banking
Most people feel that the banks have put in effective financial capacity to ensure the availability of E-banking services compared to other variables like necessary E-banking systems and effective management. The computed mean from the 5-Likert scale, 1 being the lowest and 5 the maximum value. The mean score of respondent on the on the effective financial capacity put in place to facilitate E-banking services scores 3.53, necessary E banking systems comes second with 3.51 and effective management come last with a mean score of 3.42. From the table, most banks in Kenya have established a strong financial base for the effectiveness of E-banking but have lagged behind on management of the service and putting in place necessary E-banking systems, database and applications.
Table 4.7: Organizational Capability
N Mean Std. Deviation
The bank has put in place necessary e-banking systems, databases, and applications 113 3.51 .992
The bank has established effective management and oversight over the risks associated with electronic banking services 113 3.42 .904
The bank has effective financial capacity to ensure the availability of e-banking services 113 3.53 .946
Source: Author’s computations (2017)
4.4. Perceived Risk and Adoption and Use of e-Banking
A majority of the people feel that other people accessing their accounts is the most risky factor in the E-banking services (mean score 2.81). The E-banking performing wrongly and making the incorrect payment comes as second (mean 2.73) and lastly the lots of time taken to learn to use E-banking services is the least risk (2.49). The average mean score of the 3 options (2.68 ; 2.5) shows that people find it risky to use the E-banking services (5 and 1 is maximum and minimum risk values). The high risk level show that people are less confident in using the E- banking services making the adoption of the services slow.
Table 4.8: Perceived Risk
N Mean Std. Deviation
Electronic banking services may not perform well and process payment incorrectly 113 2.73 1.094
It would take me lots of time to learn how to use electronic banking services. 113 2.49 1.111
I am worried to use electronic banking services because other people may be able to access my account. 113 2.81 1.327
Source: Author’s computations (2017)
4.5. Perceived Usefulness and Adoption and Use of e-Banking
Most participants in the survey accepted that E- banking services enable them accomplish their task more easily (99 respondents) followed by E-banking is advantageous to the traditional banking (97) and finally it makes them carry their tasks easily (96). However, 16 respondents felt that E-banking services is not useful. The respondents either choose Strongly Disagree (5) or Disagree (11). The means show that there was similar agreement on the usefulness of e-banking in accomplishing tasks more quickly (4.16) and that it was advantageous to traditional banking. In the same vein, respondents also agreed that e-banking services made it easier to accomplish tasks (4.11).
Table 4.9: Perceived Usefulness
N Mean Std. Deviation
I think that using the electronic banking services would enable me to accomplish my tasks more quickly. 113 4.16 .774
I think that using the electronic banking services would make it easier for me to carry out my tasks. 113 4.11 .783
I think the electronic banking services are advantageous compared to traditional banking. 113 4.16 .912
Source: Author’s computations (2017)
4.6. Perceived Ease of Use and Adoption and Use of e-Banking
The data analysis above shows that most respondents feel E-banking services are ease to use. A majority of participants feel that E- banking is easy to learn (3.77 mean) compared to other options like it does not require a lot of mental effort (3.38 mean) and does not require training (2.74). The above results show that as much as the E- banking is easy to learn, it requires some mental capability and training. The table below shows the mean results of each individual option.
Table 4.10: Perceived Ease of Use
N Mean Std. Deviation
I think that learning to use electronic banking services would be easy. 113 3.77 .991
I think that interaction with electronic banking services does not require a lot of mental effort. 113 3.38 1.270
I think use of electronic banking services does not require any training. 113 2.74 1.280
Source: Author’s computations (2017)
4.7. The Effect of the Factors on the Adoption and Use of e-Banking Services
4.7.1. Level of Adoption of E-Banking Services by Customers
The table 4.11 show the frequency of each E-banking services. The frequency of each service helps the research in identifying the specific service has slowed or fastened the adoption of e-banking service. The most used service is the balance enquiry and cash withdrawal service which recorded a total of 72 and 70 users respectively. Balance enquiry had 37 frequently and 35 very frequently use it, 49 users choose frequent and 21 choose very frequent in the cash withdrawal. The least used service in e-banking is the loan payment (43 users) and cash deposit (58 users) that frequently or very frequently used the service. Mobile top up came up as the 3rd frequently used service (66 users) followed by money transfer (60 users) then bill payment with (59 users). A large number (27 customers) recorded not to use the e-banking service in loan payment. the mean of the responses (1 don’t use as the minimum value and 5- very frequent as the maximum value) shows that balance enquiry is the most used service (3.63), followed by cash withdrawal (3.46), followed by mobile airtime recharging, then cash deposit (3.28), then bill payment (3.27), then money transfer (3.18) and lastly loan payment (2.95).
Table 4.11: Adoption and Use of E-Banking Services
N Mean Std. Deviation
Cash deposit 113 3.28 1.285
Cash withdrawal 113 3.46 1.261
Money transfers 113 3.18 1.377
Loan payment 113 2.95 1.381
Bill payment 113 3.27 1.309
Mobile airtime recharging 113 3.45 1.389
Balance inquiry 113 3.63 1.317
Source: Author’s computations (2017)
From secondary data analysis, Kenya Commercial Banks, one of the 7 big banks included in the survey, has shifted from the traditional brick and mortar banking channels to alternating channels; notably, digital platforms such as mobile banking, mobile loans, KCB-MPESA, KCB Mobi Bank, KCB diaspora banking, KCB Bankika, internet banking cards, amongst others. These platforms allow customers to make transfers, payments, apply for loans, get bank statements, and transfer money, among others.
As part of its digital transformation, Co-operative Bank of Kenya launched MCo-op Cash mobile application in 2014. The application allows users to access on-net and interbank cash transfers as well as pay utility bills. Co-op Net allows personal and institutional account holders to perform various transactions and monitor their accounts through the internet. Customers can print account statements; start, stop, or amend standing orders, transfer money, pay utility bills, as well as make bulk payments, such as salaries, dividends, and disbursements.
Equity Bank has also launched e-banking solutions. The Eazzy Banking includes applications such as Eazzy App, an interoperable payment platform, and a retail internet portal allowing customers to manage bank accounts. Equity Bank also has a digital platform for SMEs designed for joint account holders, chamas, and investment groups. There is also a mobile lending platform, Equitel, which is steadily replacing the bank’s traditional banking model.
Barclays Bank Kenya operates a mobile banking platform modelled on the bank’s online banking system. Using both the online and mobile systems, customers can access account information, download bank statements, transfer funds, link to accounts, carry out foreign exchange transactions, and pay utility bills.
The Standard Chartered Bank is transforming to a fully digital bank. The Bank is in the process of setting up a video banking system over the next 3 years to enable the bank to serve its customers through video and audio links or through a web chat instead of the current across the counter model. The Standard Chartered also operates a mobile banking platform called SC Mobile that allows customers to transfer money, pay bills, and check bank balances. The bank has also implemented a wealth management portal that customers can access to build their investment profiles and choose preferred investment products.
Commercial Bank of Africa has a mobile banking platform, both application and USSD, and an internet banking platform. They provide a secure, fully transactional, internet-based banking platform that enables customers to transact at all times. Commercial Bank of Africa has adopted a PesaLink platform that gives customers an instant bank money transfer.
The Diamond Trust Bank digital platform has two components: mobile banking and DTB iBank. The mobile banking platform utilizes Masterpass, a QR based banking service, links to PesaLink, and enable customers to process unlimited free bank enquiries and mini statements. The platform also allows bank to Mpesa transactions, bill payment, airtime purchase, stop check services, as well as cheque status requests. DTB iBank is an online banking platform that allows for online statements and balance requests, multi-currency online transaction, automated scheduled payments, account reports, and payroll system.
4.7.2. Regression Results
Multiple regression was used to establish the relationship organizational capacity (OC), perceived technological risk (PR), perceived usefulness (PU), perceived ease of use (PEOU) and the adoption of e-banking services such as cash deposit, cash withdrawal, money transfers, loan repayment, bill payment, mobile airtime charging, and bank balance inquiry among the 7 largest commercial banks in Nairobi County.
Regression analysis is technique for mathematical modelling that is used to establish the relationships between the variables in the study. The analysis sort outs which independent variables have an impact on the dependent variable, and it helps in understanding how changes in the independent variables influence the dependent variable in the study. In testing a multiple regression model, customarily, the degree to which two or more predictors (independent or X variables) are related to the dependent (Y) variable is expressed in the correlation coefficient R, which is the square root of R-square. In multiple regression, R can assume values between 0 and 1.
The regression model summary shows that 27.6% of the variation in the level of adoption of e-banking services are influenced by organizational capability, perceived risk, perceived ease of use, and perceived usefulness, as shown in Table 4.12.
Table 4.12: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .525a .276 .249 .85309
a. Predictors: (Constant), PEOU, OC, PU, PR
Source: Author’s computations (2017)
In regression techniques, analysis of variance (ANOVA) is a statistical method that is used in testing the differences between two or more means. It is called ‘Analysis of Variance’ rather than ‘Analysis of Means’ because the inferences about means are determined by analysing variance. In regressions, ANOVA shows the levels of variability within the regression model and forms a basis of testing significance levels. The F-ratio is used to determine whether the overall regression model is a good fit for the data. From the findings, the table 4.13 shows that the independent variables statistically significantly predict the dependent variable, F (4,108) =10.291, p value = 0.000, implying that the regression model is good for the data at p; 0.05 (95% confidence level).
Table 4.13: ANOVA
Model Sum of Squares Df Mean Square F Sig.
1 Regression 29.959 4 7.490 10.291 .000b
Residual 78.599 108 .728
Total 108.558 112
a. Dependent Variable: Adoption
b. Predictors: (Constant), PEOU, OC, PU, PR
Source: Author’s computations (2017)
The purpose of multiple regression is to determine the relationship between several independent or predictor variables and a dependent or criterion variable. It also allows the researcher to understand the direction of the relationship between variables, by examining the signs (+ or -) of the B coefficients. If a B coefficient is positive, then the relationship of this variable with the dependent variable is positive; if the B coefficient is negative then the relationship is negative. If the B coefficient is equal to 0 then there is no relationship between the variables. Therefore, the findings in table 4.14, show that, with regard to the regression model;
P = ? + ?1OC + ?2PR+?3PU+?4 PEOU+ ?
The predictions of B from the unstandardized coefficients column are;
Adoption and Use = 0.721 + (0.276 x OC) + (0.144 x PR) + (0.376 x PU) – (0.75 x PEOU)
This shows that there is a positive relationship between adoption and use of electronic banking services and organizational capability, perceived risk, and perceived usefulness, but a negative relationship with perceived ease of use.
To test for statistical significance in the relationship, t-tests and corresponding p-values are used. T-tests test whether the unstandardized or standardized coefficients are equal to zero in the population, and if the corresponding p < 0/05 then it can be concluded that the coefficients are statistically and significantly different to zero. From the findings in table 4.14, there is a statistically significant relationship between organizational capability (OC) and the adoption and use of e-banking services among the largest commercial banks in Kenya, t=2.471, p-value = 0.015 at 0.05 significance level. There was also a statistically significant relationship between perceived usefulness (PU) and the adoption and use of e-banking services, t = 0.4.097, p-value 0.000 at 0.05 significance level. However, there was no statistically significant relationship between perceived risk (PR) (t = 0.270, p-value = 0.270) and perceived ease of use (PEOU) (t = -0.767, p-value 0.445) and the adoption and use of e-banking services in Kenya.
Table 4.14: Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) .721 .669 1.077 .284
OC .276 .112 .211 2.471 .015
PR .144 .130 .102 1.109 .270
PU .376 .092 .366 4.097 .000
PEOU -.075 .097 -.064 -.767 .445
a. Dependent Variable: Adoption
Source: Author’s computations (2017)
These finding show that there is a positive and statistically significant relationship between organizational capability and perceived usefulness and the level of adoption and use of electronic banking services. There was also a positive but not statistically significant relationship between perceived technological risk and the level of adoption and use. Finally, even though the relationship between perceived ease of use and adoption of electronic banking services was negative, it was not statistically significant.
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
This chapter provides the findings of the study, conclusions, and recommendations arising from the findings of the study.
5.2. Summary of Findings
5.2.1. Organization Capability and the Adoption and Use of E-Banking in Kenya
The study assessed the strategies, financial capacity and management of e-banking systems. Many respondents feel the management has the financial capability in place to ensure e-banking works effectively. Most banks have a strong financial stability for e-banking services provision. However the problem comes on the service management and the effectiveness of the system to sustain the service. The security of the database and its applications from hackers is a necessary factor that boost the confidence of using the e-banking. Organizations should also have effective management to sustainably offer the service without any fault. They need skilled manpower to hand the system in terms of operation and customer care and additionally avoid cases of fraud and hackers. According to Shih (2006) the failure of a bank to adopt to E-banking will lead to expenses of opening so many brunch banks across the country.
These findings corroborate Kurnia, Peng and Liu (2011) findings which determined that financial resources are an important factor in facilitating innovation adoption for any organization and they are often correlated with the firm size. ). Large organizations have the resources and skills to adopt new technologies such as e-banking. These resources also enable them to acquire human resource needed to maintain the functioning of e-banking platforms. A study by Daghfous and Toufaily (2007) also reported that organizational variables (bank size, functional divisions, technical staff, technical infrastructure, perceived risks, decision makers` international experience and mastery of innovation) exert significant impact on the adoption of e-banking.
5.2.2. The Perceived Risk and the Adoption and Use of E-Banking in Kenya
This research analyses the consumer’s perception on the risks that they face while using E-banking services. The data obtained showed that trust for the service is wanting because of risks of exposing PIN numbers while transacting, making wrong transactions and the fear of hackers into accounts. The risks influence most people’s decisions on the adoption of e-banking. Another risk that was highlighted was if the bank is not very stable financially customers may fear to adopt other services of the bank in this case e-banking. Poon (2007) published many books and the risks that he addresses on e-banking is that some people access online accounts through hyperlinks in search engines, pop-up windows and even emails which lead to hacking. Poon (2007) warns that one should be aware of websites that seem suspicious.
According to Nasri (2011), customer’s perception of the uncertainty and potential adverse consequences of buying a product or services is very important. The degrees of risk that customers perceive and their own tolerance of risk tacking are factors that influence their purchase decision (Nasri, 2011). Customers are often worried that a break down in the system servers will occur while conducting electronic services, because these situations may result in unexpected losses (Kuisma et al., 2007). Khalfan (2006) notes that there are instances where banks are reluctant to use e-commerce applications as they felt that transactions conducted electronically were open to hackers and viruses, which are beyond their control.
5.2.3. Perceived Usefulness and the Adoption and Use of E-Banking in Kenya
The arguments on how effective e-banking services are recognized by many individuals is rampant. The global rapid technological growth, qualifies the argument. From my analysis there is a realization that e-banking services are user friendly and very swift in accomplishing most tasks especially urgent transactions that have time limits. Most of the respondents said the services are more effective as compared to the tradition way of banking. The traditional way of banking required one to go to the bank and fill lots of papers for them to access services. The e-banking has eased the procedure by providing only the essentials and saving the customer time. In the traditional banking people waste time in filling the banking slip with bio details which is the case in e-banking. The bio details are fed once and anytime you use e-banking your details are automatically identified in the card or using the mobile number. According to Professor Staniewski Marcin, e-banking and online banking are a condition that is essential for the development of the society and business as well (Ackah & Agboyi, 2016). Results also revealed that security and privacy matters are important factors that determine the approval of e-banking but it depends on the education levels and age groups.
The findings show that the factors that facilitate internet e-banking are; the widespread use of technology, in most cases internet services. This provides the advantage to easily adopt and opt for online banking services and also builds the trust for commercial banks. Some of the products that mostly facilitate online banking and electronic banking are credit cards, ATM and mortgage. The reasons got from respondents on what impacts their adoption of e-banking services were convenience and accessibility makes them feel satisfied. If the e-banking services such internet banking, ATM, Mobile banking and Credits cards are convenient and accessible the adoption of the technology would be easy and progressive. Additionally, other common factors like speed, a reasonable fee that is affordable and availability of product features also contribute to usefulness and easy adoption of a particular service. Another concern was that GPRS, WAP and 2G, 3G mobile features significantly influence the adoption of electronic banking.
Other studies within the Kenyan market also agree with the findings. E-banking platforms are not only useful to the customers. Aduda and Kingoo (2012) confirmed that e-banking has strong and significance marginal effects on returns on asset in the Kenyan banking industry. Okiro and Ndungu (2013) noted that such technological innovations have made banking tasks more efficient and cheaper. Bichanga and Wario (2014) reported that effective utilization of e-banking facilities was associated lack of technological know-how, illiteracy, unreliability, and transaction limits. However, it is important to note that previous research by Kombo et al (2015) established that customers in Kenyan banks were less satisfied with e-banking when compared to customers in the Czech Republic.
5.2.4. The Perceived Ease of Use and the Adoption and Use of E-Banking in Kenya
The study reported a negative relationship between perceived ease of use and adoption and use of e-banking services. Sahoo and Swain (2012) also disagreed with the position that customers using e-banking can access services more easily from banks abroad and through wireless communication systems, which are developing more rapidly than traditional “wired”
Njunguna et al (2012) was categorical that internet banking is still at its nascent stages as demonstrated by the length of usage response. Nonetheless, the results revealed that perceived ease of use have a significant association with intention to use internet banking. Perceived ease of use is also related to the amount of time spent in learning how to use and troubleshooting a new electronic service. Natarajan et al., (2010) noted that consumers are less likely to adopt an electronic service that they consider having high setup and maintenance costs. Website features which provide full information about the service, awareness of the service and usefulness can make the service considered easy to use.
5.3. Conclusion of the Study
5.3.1. Organizational Capability and Adoption and Use of E-Banking Services
The findings show that a majority of the banks had necessary e-banking systems, databases and applications; had established effective management and oversight of e-banking risks; and had the financial capacity to ensure that customers can access e-banking services. The capability of a bank influences its ability to install e-banking systems. The regression coefficients show that organizational capability has a statistically significant relationship with the adoption of e-banking systems.
5.3.2. Perceived Risk and Adoption and Use of E-Banking Services
With regard to perceived risk, there was demonstrably moderate level of agreement that electronic banking services may not perform well and process payments may be entered incorrectly. Others were worried that they may not be able to access their accounts. Almost half of those surveyed felt that it takes a lot of time to learn how to use e-banking. These results imply that the level of perceived risk made customers less confident to adopt and use e-banking services. The regression results indicate that there is, however, no statistically significant relationship between perceived technological risk and the level of adoption and use of e-banking services.
5.3.3. Perceived Usefulness and Adoption and Use of E-Banking Services
E-banking is perceived as being useful, as shown by the high level of agreement on all the questions posed to customers. A majority stated that electronic banking enables them to accomplish tasks quickly, easily, and it was advantageous compared to traditional banking. The sense of perceived usefulness was supported by regression results. The findings indicate that there is a statistically significant relationship between perceived usefulness and the adoption and use of e-banking services.
5.3.4. Perceived Ease of Use and Adoption and Use of E-Banking Services
The findings on the perceived ease of use further supported sentiments on perceived usefulness. Most customers stated that learning to use e-banking services is easy and that it does not require much mental effort. There was also a moderate level of agreement that using e-banking platforms does not require any training. However, multiple regression findings showed that the perceived ease of use did not have a statistically significant effect on the adoption and use of e-banking services.
5.4. Recommendations for Further Research
5.4.1. Organizational Capability and Adoption and Use of E-Banking Services
Putting in place e-banking systems, databases and applications demands that the organization must have adequate financial and non-financial resources. The fact that organizational capability influences the adoption and use of e-banking services means that banks should continue to allocate resources to continual development and upgrades as a way of achieving competitive advantage.
5.4.2. Perceived Risk and Adoption and Use of E-Banking Services
The perception among respondents is that there is still a possibility of incorrect entries when banking, and that it takes a lot of time to learn how to use the systems. Even though perceived risk is not one of the main influencers of adoption, as the study suggests, banks should invest in relevant product awareness campaigns to educate potential customers to alleviate the risk of incorrect entries and to deal with the perception that it takes a long time to learn how to use e-banking systems.
5.4.3. Perceived Usefulness and Adoption and Use of E-Banking Services
A majority of customers perceived e-banking as useful in the modern age and better that traditional banking platforms. This market confidence in the benefits of the technology means that banks should become increasingly innovative and create a diverse portfolio of e-banking products and services that are responsive to the growth of a dynamic, an informed, and demanding customer base.
5.4.4. Perceived Ease of Use and Adoption and Use of E-Banking Services
The study shows that most respondents feel that e-banking platforms are easy to use and do not require much mental effort, as such it is not one of the main influencing factors in adoption as shown by the regression results. Banks should therefore maintain interactive and easy to use user graphic interfaces, and should not develop platforms that present great difficulty to their customers.