Unlocking Financial Inclusion: Factors Shaping the Future of Agent Banking in Ethiopia
Dr. Mulugeta Negash Wodaje
University of Gondar,
Department of Marketing Management, Gondar, Ethiopia
Email: Mulugeta.Negash@uog.edu.et
mulugetanw@gmail.com
Dr. Sunday Adewale Olaleye
Jamk University of Applied Sciences,
Business School, Jyväskylä
Adjunct Staff, University of Gondar,
Marketing Management Department
Email: Sunday.olaleye@jamk.fi;
Sunday.Adewale@uog.edu.et
Abstract
This research aims to understand the factors influencing the adoption of agent banking in Ethiopia, specifically focusing on the Commercial Bank of Ethiopia branches in Gondar City. The study collected primary data through a questionnaire survey with 395 customers selected through purposive sampling. Descriptive and inferential statistical analyses, including linear regression, were used to analyze the data. The study found that perceived usefulness, risk, trust, social influence, and subjective norms are significant determinants in adopting agent banking. However, the study has limitations, as it only focuses on one city and employs a cross-sectional design. The study made a theoretical contribution and suggested that enhancing the functionality of agent banking in terms of perceived usefulness, risk, trust, social influence, and subjective norms can increase adoption rates. The findings have implications for policymakers, financial institutions, and stakeholders working towards financial inclusion.
Keywords: Agent banking, Adoption, influential factors, Ethiopia, Financial inclusion, Branchless Banking
Introduction
Agent banking is gaining momentum in Ethiopia and is supported by the National Bank of Ethiopia (NBE). This model involves utilizing agents, individuals or enterprises who provide banking services outside of traditional bank branches. These agents operate under the directives of the NBE and collaborate with financial institutions. The range of services offered by agent banking extends beyond the conventional branch network, encompassing cash deposit and withdrawal, fund transfer, payment services, balance inquiries, mini-statements, and the opening of Money-Wallet accounts. The primary objective of this innovative model is to enhance proximity between banks and customers, thereby promoting financial inclusion.
The banking industry has undergone significant transformations in recent years due to technological advancements, shifts in consumer preferences, and the global impact of the COVID-19 pandemic. Previous research, such as the study conducted by Osman, Ashraf & Hoque (2023), has investigated client satisfaction during the pandemic, focusing on service quality, security, transaction cost, trust, and convenience. Mwaiwa et al. (2022) have addressed a different but equally significant gap by examining the relationship between agent banking and sustainable competitive advantage. However, further research is required to systematically apply the bank-led theory in analyzing the complex dynamics and potential interventions, particularly considering the impact of regulatory factors on sustaining competitive advantages.
The emergence of branchless agent banking services in various regions, including Bangladesh and Kenya, highlights one noteworthy transformation in the industry. In the context of Bangladesh, Uddin & Sultana (2019) have focused on the advantages and challenges of agent banking, shedding light on motivators such as financial inclusion, remittance channeling, and transaction efficiency. Nevertheless, a comprehensive analysis utilizing statistical methods like Kendall's W test to uncover the factors shaping agent banking prospects in the country has yet to be fully explored.The significance of the existing studies lies in their multifaceted exploration of agent banking in diverse contexts. These studies have contributed to the theoretical understanding of client satisfaction in rural settings in Bangladesh and have provided depth to the discourse on sustaining competitive advantages for commercial banks in Kenya. In Bangladesh, which has significant experience with agent banking, the study utilizing PLS-SEM to assess rural consumers' satisfaction offers a fresh perspective on the existing literature. Additionally, the study by Pervin & Sarker (2021) anticipates future trends by forecasting the growth of agent banking using Holt's Double Smoothing Exponential methods, adding a valuable layer of foresight to the discussion. In Kenya, examining agent banking as a tool for sustaining competitive advantage is crucial, particularly considering the evolving regulatory landscape. The study by Mwaiwa et al. (2022) contributes to strategic decision-making in the banking sector by viewing the interplay of agent banking, regulatory interventions, and sustainable competitive advantage.
Other studies have predominantly focused on the effects of branchless agents, such as mobile money and banking apps, in Africa, specifically their role in serving both banked and underbanked customers (Olaleye et al., 2018; Balogun & Olaleye, 2022; Olaleye et al., 2022a; Olaleye et al., 2022b). As the banking sector undergoes dynamic changes globally, exploring the role, challenges, and potential growth of agent banking becomes imperative.This study aims to address the gaps in the existing literature and provide nuanced insights that can inform academia and banking industry practitioners. Agent banking has emerged as a significant innovation in the banking industry, providing access to financial services to individuals in remote and underserved areas. This study aims to explore the factors influencing customers' adoption of agent banking services.
Agent banking has gained significant attention in recent years as a means of conducting financial transactions, especially in areas where traditional banking services are not easily accessible. It offers several advantages, including increased accessibility for underserved populations and reduced operational costs for financial institutions. Branchless banking, a related concept, refers to the delivery of financial services outside of traditional bank branches, often utilizing agents and technology such as mobile phones. This approach has been successfully implemented in various regions, including Latin America and Asia, but has yet to gain traction in African countries. However, countries like Kenya and Ethiopia have embraced agency banking as a cost-effective solution for providing financial services to people experiencing poverty.
Research suggests that agent banking offers economic benefits for financial institutions, particularly for accounts with high transaction frequency and low balances commonly found among low-income users. Various factors, including technological factors and customer perceptions, can influence the adoption of agency banking. Technological factors, such as the reduction in operational costs and improvement in revenue, play a crucial role in adopting agency banking. Factors such as perceived usefulness, ease of use, risk, trust, cost, subjective norms, and social influence predict customers' adoption of agency banking services. Effective implementation of agency banking requires the consideration of critical success factors, including the ability to create trust among clients, the availability of capable agents, and the effective management of challenges such as fraud.In Ethiopia, Dashen Bank and United Bank have pioneered agent banking. The National Bank of Ethiopia's regulation requiring agent banking has allowed banks to expand their services and meet the financial needs of the unbanked population. Adopting agent banking in Ethiopia has provided customers with 24-hour services and eliminated the conventional processes of money processing. While the literature highlights the potential benefits and challenges of agent banking, more research is needed to understand the factors influencing its adoption in specific contexts.
This study aims to fill the gaps in the existing literature by exploring the factors influencing customer adoption of agent banking services. The study utilizes a convenient sampling technique to gather primary data through surveys and interviews. The literature review provides an overview of the factors shaping customers' adoption decisions, including perceived usefulness, ease of use, cost, trust, risk, social influence, and subjective norms. The study's findings will contribute to the academic understanding of agent banking and provide valuable insights for banking industry practitioners. As the banking sector continues to evolve, it is crucial to explore the role, challenges, and potential growth of agent banking to ensure financial inclusion and accessibility for all customers.
Figure 1.Proposed Conceptual Framework
Source: Adopted from (Bastan et al., 2022) and (Githae et al., 2018)
Technological Factors
In e-banking, technological factors encompass the adopters' perception of the advantages and disadvantages of using electronic banking compared to traditional banking transactions. According to Rogers's diffusion of innovation theory (2003), the adoption of technology is influenced by the perceived usefulness and use. Perceived usefulness refers to individuals' belief in the superiority of e-banking over traditional banking. Extensive research conducted by Chong et al. (2010), Pikkarainen et al. (2004), and Wang et al. (2003) consistently demonstrates that perceived usefulness strongly influences e-banking adoption. Hence, a positive association exists between perceived usefulness and the adoption of e-banking.
On the other hand, perceived ease of use pertains to individuals' perception of effortless usage of e-banking services. Some studies, such as Amin et al. (2008), show a positive correlation between perceived ease of use and the adoption of e-banking. However, contrasting findings have been reported by Teklie (2021) and Sulaiman et al. (2007), suggesting insignificant effects. Considering the need for training in utilizing agency banking services and the technological advancements therein, it can be hypothesized that there is a positive relationship between perceived ease of use and the adoption of e-banking (H2).
Organizational Factors
Organizational factors influencing e-banking adoption include an organization's size, structure, culture, and resources. The Technology Acceptance Model (TAM) suggests that perceived ease of use and perceived usefulness are the most critical determinants of information system adoption (Davis, 1986). Therefore, factors influencing e-banking adoption within an organization can be related to the system's perceived ease of use and usefulness. Another organizational factor is cost. Perceived cost includes more than just the monetary price of a product or service; it also considers factors such as time spent, and inconvenience endured. Customers may perceive traditional branch-based banking as more time-consuming compared to the convenience of e-banking. Pricing strategies and the concept of perceived cost are subjects of interest among scholars, and further research is needed to understand their impact on e-banking service adoption behaviour.Hence, this study hypothesized that Perceived Cost positively relates to adopting Agency Banking (H3).
Environmental Factors
Environmental factors in the context of e-banking refer to the external conditions that influence individuals' adoption of e-banking services. Privacy and security concerns are significant barriers to e-banking adoption and trust in the technology and banking institutions plays a crucial role (Liébana-Cabanillas et al., 2016). Studies have shown that perceived trust positively influences the adoption of e-banking (Hassan & Hassanein, 2019). Therefore, it can be hypothesized that trust is positively related to adopting e-banking (H4).
Perceived risk is another important environmental factor that affects e-banking adoption. E-banking services involve risks such as potential loss and security concerns (Laukkanen & Cruz, 2009). Perceived risk is found to discourage the adoption of electronic banking services (Liao & Cheung, 2002). Hence, the hypothesis is that perceived risk positively relates to adopting e-banking (H5).
Social influence and subjective norms are also environmental factors that influence the adoption of e-banking. Social influence refers to the influence of others' beliefs on an individual's decision to adopt a new system. At the same time, subjective norms relate to an individual's perception of what important people think about using e-banking (Nguyen & Leclercq, 2018). Studies have shown that social influence and subjective norms significantly affect the acceptance of e-banking services (Shih & Fang, 2004; Liu et al., 2018). Therefore, social influence (H6) and subjective norms (H7) positively relate to adopting e-banking.
Various factors influence the adoption of e-banking, and the TOE framework provides a comprehensive understanding of these factors (Tornatzky& Fleischer, 1990). In addition to the environmental factors discussed, other essential factors include perceived usefulness, perceived ease of use, perceived cost, and perceived trust. However, the impact of these factors may vary depending on the specific context and population being studied. Further research is needed to explore these relationships in different contexts and populations.
Methodology
Research Design
The agent banking study employs an explanatory research design to investigate the factors influencing the adoption of agent banking among commercial banks in Gondar city branches in Ethiopia. According to Serakan (2003), explanatory research aims to confirm the characteristics of variables of interest. This design was chosen to delineate these characteristics and identify those significantly influencing the adoption of agent banking services.
Methods and Materials
A quantitative research approach focuses on generating numerical data for formal and inflexible analysis. This approach, as Creswell (2009) outlined, emphasizes numerical data and statistical tests to derive generalizable conclusions and test objective theories by examining relationships between variables. Given its suitability for addressing large-scale issues, quantitative methods, including experiments and surveys, are employed to collect data for this study.
Target Population
The study encompasses 19 branches of the Commercial Bank of Ethiopia (CBE) in Gondar city administration. These branches include Angereb, Mintwab, Guzara, Jantekel, Fasiledus, Atsebekafa, Kidamiegebeya, Mehal Arada, Ergibber, Zoble, Maraki, Jano, Ras Dashen, Atse Eyasu, Abajale, Abasamuel, Azezo, and Loza Mariam. Statistics from the National Bank of Ethiopia (NBE) report for the 2021/22 fiscal year confirmed that CBE had contracted 27 active agents.
The target population comprises customers utilizing CBE's agent banking services in Gondar city administration. Based on data from CBE branches, there were a total of 32,281 customers adopting agency banking services. Therefore, all agency banking adopters constitute the target population from which the study sample is drawn, with respondents selected based on their availability within the researcher's local area.
Sample Size and Sampling Techniques
Sample Size
The below sample size (n) formula was utilized:
Where:
N = Total population (customers of CBE branches in Gondar city administration)
e = Precision degree/error (5% = 0.05)
Hence, the sample size is 395 customers from CBE branches in Gondar city administration.
Methods of Data Analysis
Quantitative data collected through questionnaires are processed using SPSS version 20 for the data analysis. Descriptive and inferential statistical analyses such as mean, percentages, tabulation, Pearson correlation, and linear regression were utilized in this study. The research model specifies the dependent and independent variables, adopting agency banking as the dependent variable and perceived usefulness, ease of use, cost, trust, risk, social influence, and subjective norms as the independent variables. Ethical considerations are paramount throughout the research process, and the study ensured the participants' consent, and measures were taken to ensure confidentiality and cultural sensitivity in data collection.
Response Rate
This study was conducted in Gondar city administration, focusing on 19 branches of commercial banks in Ethiopia. The branches included in the study are Angereb, Mintwab, Guzara, Jantekel, Fasiledus, Atsebekafa, Kidamiegebeya, Mehal Arada, Ergibber, Zoble, Maraki, Jano, Ras Dashen, Atse Eyasu, Abajale, Abasamuel, Azezo, and Loza Mariam. A sample of customers from these branches was used for data collection. Participants were requested to complete a questionnaire, which served as their contribution to the research. The study initially aimed to gather information from 395 customers; however, only 383 questionnaires were completed. This incompleteness resulted in a response rate of 96.96%, which was considered adequate for analysis purposes.
The following table presents the basic demographic profile of the respondents concerning their age and gender compositions.
Table 1. Age and sex composition of respondents
|
|
Age of respondents |
Total |
||||||
|
18 - 25 |
26-35 |
36-45 |
46-55 |
55 - 65 |
|
|||
|
Sex of respondents |
male |
Count |
12 |
86 |
38 |
7 |
4 |
147 |
|
% of Total |
3.1% |
22.5% |
9.9% |
1.8% |
1.0% |
38.4% |
||
|
female |
Count |
28 |
154 |
34 |
14 |
6 |
236 |
|
|
% of Total |
7.3% |
40.2% |
8.9% |
3.7% |
1.6% |
61.6% |
||
|
Total |
Count |
40 |
240 |
72 |
21 |
10 |
383 |
|
|
% of Total |
10.4% |
62.7% |
18.8% |
5.5% |
2.6% |
100.0% |
||
According to the data presented in Table 1, out of the 383 respondents, 147 individuals (38.4%) identified male customers, while the remaining 236 individuals (61.6%) identified female customers. The distribution of respondents across different age groups exhibited considerable variability. Among the male respondents, it was observed that 12 individuals (3.1%) were aged between 18-25 years. Additionally, within the surveyed population, 86 individuals (22.5%), 38 individuals (9.9%), and seven individuals (1.8%) of male respondents fell into the age categories of 26-35, 36-45, and 46-55 years, respectively. The remaining four individuals (1.0%) were above the age range of 56-65. Regarding female respondents, the majority (40.2%) were aged between 26-35 years, followed by 8.9% falling within the age range of 36-45 years. Notably, 28 (7.6%) and 14 (3.7%) respondents were 18-25 and 46-55 years, respectively. Finally, six individuals (1.6%) in the sample were aged between 56 and 65. Concerning the educational and occupational status of the respondents, it is worth noting that most participants possessed a substantial educational background. Additional details regarding the educational and occupational statuses of the respondents can be found in the subsequent table.
Table 2. Education and occupational status of respondents
|
Education and occupational status |
Frequency |
Percent |
|
|
Education levels |
Less than or equal to 12 grades |
37 |
6.3 |
|
Diploma |
178 |
30.2 |
|
|
First Degree |
157 |
26.6 |
|
|
Above first degree |
11 |
1.9 |
|
|
Type of work |
Temporary |
105 |
17.8 |
|
Government employee |
267 |
45.3 |
|
|
Private employee |
11 |
1.9 |
|
Source: survey result (2022)
To examine group equivalence, a commonly employed statistical method involves conducting simple analyses of means and standard deviations, as proposed by Marczy, Dematteo & Festinger (2005). The mean value indicates the overall level of agreement or disagreement regarding various statements within a given sample. A lower mean value suggests a greater degree of disagreement among respondents, whereas a higher mean value indicates a higher level of agreement. Conversely, the standard deviation measures the extent of variation in responses observed within a specific sample. Table 3 presents each variable's mean values and corresponding standard deviations.
Table 3.Descriptive Statistical Analyses for variables
|
Variables |
Mean |
Std. Deviation |
N |
|
Agent banking Adoption |
2.3877 |
0.78587 |
383 |
|
Perceived usefulness |
2.7963 |
1.02385 |
|
|
Perceived cost |
3.2343 |
0.96677 |
|
|
Perceived ease of use |
2.8520 |
0.84822 |
|
|
Perceived risk |
2.4421 |
0.94588 |
|
|
Perceived trust |
2.4846 |
0.54374 |
|
|
Social influence |
2.4987 |
0.89430 |
|
|
Subjective Norms |
2.4604 |
1.00874 |
Source: Survey result (2022)
Table 3 presents the mean values and standard deviations of perceived usefulness, cost, ease of use, risk, trust, subjective norm, social influence, and adoption of agent banking services within the study area (see Table 3). The perceived usefulness of agent banking services received a moderate rating, with a mean value of 2.7963 (SD=1.02385) (refer to relevant literature studies for previous data), suggesting a medium level of perceived usefulness among respondents. Similarly, the perceived cost of agent banking services was reported to be at a medium level, with a mean value of 3.2343 (SD=0.96677), indicating a moderate impact of perceived cost on adoption. The influence of perceived ease of use on agent banking adoption was also rated at a medium level, with a mean value of 2.8520 (SD=0.84822).
Furthermore, perceived risk was found to have a low impact on adopting agent banking services, with a mean value of 2.4421 (SD=0.94588). Moreover, perceived trust was rated low, with a mean value of 2.4846 (SD=0.54374), indicating low levels of trust within the study area. Subjective norm and social influence were also rated low, with mean values of 2.4604 (SD=1.00874) and 2.4987 (SD=0.89430), respectively. These findings suggest low levels of subjective norm and social influence. Finally, the adoption of agent banking services was rated low, with a mean value of 2.3877 (SD=0.78587), indicating a low level of adoption in the study area.
These results provide insights into the perceived usefulness, cost, ease of use, risk, trust, subjective norm, social influence, and adoption of agent banking services. It is essential to consider these factors when developing strategies to promote adopting agent banking services in the study area.
Figure 2.Proposed Conceptual Framework Results
Linear regression analysis
Linear regression analysis was employed in the study to examine the factors influencing the adoption of agent banking services. The table below showcases the impact of the constructed variables on agent banking service adoption in the study area. All explanatory variables, namely perceived usefulness, perceived cost, perceived ease of use, perceived trust, perceived risk, social influence, and subjective norms, were calculated with a 95% confidence interval. Hence, the table presents the outcomes of linear regressions that assess the effects of the independent variables on the adoption of agent banking services. The model summary and coefficients are included to elucidate the variances of the constructed independent variables.
Table4.Hypotheses Tested Results
|
Hypotheses |
Path Coefficient |
Beta |
Std. Error |
T-Statistics |
P-Value |
Results |
|
H1 |
PU→AaoB |
0.281 |
0.049 |
4.421 |
0.001 |
Passed |
|
H2 |
PEoU→AaoB |
0.037 |
0.041 |
0.842 |
0.400 |
Not Passed |
|
H3 |
PC→AaoB |
0.035 |
0.052 |
0.547 |
0.585 |
Not Passed |
|
H4 |
PT→AaoB |
0.341 |
0.070 |
7.079 |
0.001 |
Passed |
|
H5 |
PR→AaoB |
0.270 |
0.037 |
4.987 |
0.001 |
Passed |
|
H6 |
SI→AaoB |
0.151 |
0.015 |
6.222 |
0.001 |
Passed |
|
H7 |
SN→AaoB |
0.191 |
0.019 |
7.854 |
0.001 |
Passed |
Note: Perceived Usefulness (PU); Perceived Ease of Use (PEoU); Perceived Cost (PC); Perceived Trust (PT); Perceived Risk (PR); Social Influence (SI); Subjective Norms (SN); Adoption of Agency Banking (AAoB).
The regression analysis results yield important insights into the factors influencing the adoption of agent banking services in the study area. The findings reveal that perceived cost and ease of use do not significantly impact agent banking adoption, suggesting that these variables are not meaningful predictors. On the other hand, perceived trust emerges as the most influential factor, positively and significantly affecting agent banking adoption. This finding indicates that higher levels of perceived trust correspond to increased adoption. Perceived usefulness, perceived risk, subjective norms, and social influence affect agent banking adoption.
Notably, these findings explain 78% of the variance in agent banking adoption, leaving 22% unaccounted for in the model. Other variables not included in this study may contribute to this unexplained variance. Nevertheless, the identified factors provide valuable insights for policymakers and financial institutions seeking to enhance the adoption of agent banking services in similar contexts.
The coefficients table above reveals that the coefficient for variable B is 0.216. With a t-value of 4.421 (degrees of freedom: 7, 375) and a p-value less than 0.001, these findings indicate a positive and significant relationship between perceived usefulness and adopting agency banking when controlling for other explanatory variables. Consequently, the hypothesis positing that perceived usefulness positively and significantly affects the adoption of agency banking is accepted. This finding is consistent with previous studies by Chong et al. (2010), Pikkarainen et al. (2004), Wang et al. (2003), Anuwar et al. (2015), and Desalegn & Yemataw (2017).
Contrary to expectations, the coefficients table indicates that the coefficient for variable B is 0.34, while the t-value (375) is 0.842, and the p-value is more significant than 0.05. The analysis reveals that perceived ease of use lacks a statistically significant association with the adoption of agent banking. Therefore, the hypothesis is not supported. While this finding contradicts Dandena et al. (2020) and Gebreyohans & Ali (2019), it aligns with Teklie (2021) and Sulaiman et al. (2007), suggesting that perceived ease of use might not be a significant factor due to the novelty of agent banking in Ethiopia.
Based on the examination of the coefficients table, it is observed that B=0.29, t (375) = 0.547, and p > 0.05. When controlling for other explanatory factors, the coefficient for perceived cost is not statistically significant regarding agent banking adoption. Thus, this finding does not support the hypothesis. This result contradicts Dandena et al. (2020) and Gebreyohans & Ali (2019), indicating that perceived financial cost significantly impacts the adoption of agency banking.
The result from the coefficients table shows that the coefficient for variable B is 0.185. With a t-value of 4.987 and a p-value less than 0.001, there is a positive and statistically significant relationship between perceived risk and agent banking adoption when holding other independent variables constant. The hypothesis is accepted, aligning with Toroitich & Jelaga (2016; Cull et al., 2018; Mosoti & Mwaura, 2014).
The coefficients table indicates a B value of 0.493, a t-value of 7.079 (7, 375), and a p-value less than 0.001. The result suggests a positive and significant association between perceived trust and the adoption of agent banking. Therefore, the researcher accepts the hypothesis. This result aligns with Mulualem (2018) and Alelign (2019), emphasizing the influential role of perceived trust in agent banking adoption.
The table of presented coefficients shows that the coefficient for the variable "B" is 0.149. A one-unit increase in subjective norm corresponds to a 0.149-unit increase in agent banking adoption. With a t-value of 7.854 (7,375) and a highly significant p-value < 0.001, the researcher accepts the hypothesis that subjective norm has a positive and significant association with agent banking adoption. This finding contradicts Riquelme & Rios (2010) but aligns with Puschel et al. (2010), emphasizing the importance of subjective norms in influencing users' decisions to adopt mobile banking services.
In the coefficients table, B=0.096, t (7,375) = 6.222, p < 0.001. While controlling for other variables, there is a significant and positive association between social influence and the adoption of agent banking. This result is consistent with Karahanna and Straub (1999), Martins et al. (2014), and Abbasi et al. (2011), emphasizing the influential role of social influence in technology adoption.
Theoretical Contribution
The study presented here aims to elucidate the critical determinants in adopting agent banking services, focusing on perceived trust, perceived ease of use, and subjective norms. These factors have been examined considering established technology adoption theories, such as the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB).The results of this study indicate that perceived trust plays a crucial role in individuals' decision-making processes when it comes to adopting agent banking services. This finding aligns with previous research emphasizing the significance of trust in technology adoption. In the context of agent banking in Ethiopia, where the service is relatively novel, establishing trust becomes even more vital, as it helps mitigate any uncertainties or apprehensions that potential adopters may have.
By integrating these findings into a comprehensive model, this study enhances our understanding of the factors influencing agent banking adoption. It contributes to the existing literature on this topic, particularly relevant in the Ethiopian context, where agent banking is still in its early stages. These insights can inform policymakers, financial institutions, and other stakeholders in developing effective strategies to promote the widespread adoption of agent banking services. This study provides valuable insights into the determinants of agent banking adoption and lays the groundwork for future research in this area.
Managerial Implication
It is recommended to the Agent Banking managers, specifically the commercial banks in Ethiopia. The banks should focus on fostering a customer-centric approach to agent banking services. This strategic step entails actively seeking customer feedback to identify pain points and areas for improvement. By incorporating customer feedback into service enhancements, banks can better meet their clientele's evolving needs and expectations, ultimately building stronger relationships and enhancing customer loyalty.Moreover, commercial banks must invest in continuous training and development programs for staff and customers. Staff training should encompass comprehensive education on the features and benefits of agent banking services and effective communication techniques to address customer inquiries and concerns. On the other hand, customer education programs should aim to increase awareness and understanding of agent banking functionalities, security measures, and the broader implications for financial inclusion.
Study Limitations
While the study focused on Gondar city administration, it is essential to acknowledge that this narrow geographical scope may introduce sample bias, limiting the generalizability of the findings. The demographics, economic conditions, and banking behaviors in Gondar may differ from other regions in Ethiopia, thus it is important to expand the study to include a more diverse sample across multiple cities or regions within Ethiopia to ensure a more representative nationwide analysis of agent banking adoption.
Future Studies
Future research should broaden its geographical scope, adopt longitudinal designs, integrate qualitative and quantitative methods, and examine external factors and cultural influences. Exploring the impact of income levels, assessing the effectiveness of educational campaigns, and understanding evolving customer perceptions are suggested avenues for further investigation. Addressing these gaps will contribute to a more comprehensive understanding of agent banking adoption in Ethiopia, ultimately guiding the development of effective strategies for financial inclusion.
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