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    Factors Influencing Employees’ Perceived Productivity Following ERP System Implementation: The Case of Segon-Marill International Movers
    (Addis Ababa University, 2026-10-02) Alula Eliyas; Kuribachew Gizaw (PhD)
    Enterprise Resource Planning (ERP) systems have become important tool for organiza tion that are trying to improve their organizational efficiency and create coordination be tween different units of their organization, however so far only limited amount of studies have been conducted to examine the effect of ERP system implementation on employees perceived productivity in logistics and relocation companies specially in Ethiopian con text. This study was conducted to examine the impact of ERP system implementation on employee’s perceived productivity at Segon-Marill international movers. This study em ploys a mixed method research design, and it is guided by two theoretical frameworks the (delone & mclean, 2003) IS Success Model for examining for the quantitative compo nent of the study and the Task-Technology Fit (TTF) Model (Goodhue & Thompson, 1995) for examining for the qualitative component of the study. For the statistical study 71 valid responses were collected from active ERP system users using questionnaire sur veys and for the qualitative component 10 employees were interviewed after selected from all departments. The quantitative findings has shown that user satisfaction signifi cantly and positively predicts employees perceived productivity (beta = 0.456, p < 0.001), and user satisfaction partially mediates the relationship between ERP quality di mensions and perceived productivity (indirect effect = 0.310, 95% CI [0.13, 0.51]) and the qualitative findings has revealed that there is partial task-technology fit at the compa ny because of employees are still continue to use manual workarounds alongside the sys tem and the system is still under continuous modification, considering this findings the study concludes that the ERP system quality dimensions collectively improves employees perceived productivity through user satisfaction but in order to get full productivity it is required to have better alignment between system capabilities and actual task require ments. And the finding of this study provides valuable information for Segon-Marill management and ERP System developing team and for future studies
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    Digital technology adoption and succession planning effectiveness: the mediating role of governance structure in ethiopian family-owned coffee export companies
    (Addis ababa universit, 2026-11-02) Bethelhem Molla; Kuribachew Gizaw (Ph.D)
    The purpose of this study is to examine the effects of digital technology adoption on succession planning effectiveness within family-owned coffee export companies in Ethiopia, focusing on the mediation of the governance structure variable. The current study employed quantitative research approach along with explanatory research design. Cross-sectional primary data was collected through standardized questionnaire from 184 respondents in 77 family-owned coffee export companies located in Addis Ababa, Ethiopia. To assure the representativeness of the data, a stratified random sampling has been conducted to select sample respondents among the targeted population. Structural equation modeling and mediation analysis (bootstrap approach with 5,000 resamples) were used to test the hypotheses. As a result, it has been proven that all four digital adoption dimensions have significant positive impact on succession planning effectiveness, management support and strategy (β = 0.363) and integration into operations (β = 0.337) being the strongest determinants. In turn, the governance structure partially mediates the link between the digital technology adoption and succession planning effectiveness (indirect effect = 0.110; 13.0% of total effect mediated). Hence, digital adoption affects succession planning not only directly but also indirectly via governance structures (total effect = 0.227; 97.0% of indirect effect; p<0.001). The overall model explains 62.5% of the variation in succession planning effectiveness. In conclusion, digital technology adoption enhances succession planning in Ethiopian family-owned coffee exporters, both directly and through governance structures, though weak infrastructure and limited training constrain outcomes. Owners should convert leadership support into digital budgets and integrate strategies across departments, while establishing governance mechanisms such as fam councils and advisory board
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    Behavioral determinants of information security policy compliance: evidence from ethswitch s.c
    (Addis Ababa University, 2026-08-02) Biniyam Gossaye; Meshesha Legasse (PhD)
    The security technology field has made progress, yet employee conduct continues to be the most important aspect which organizations need to protect their information security policies. So, understanding what drives or limits this behavior is especially important in financial institutions where risks are high. This research study investigates how staff members' behavioral patterns impact their adherence to information security policies, using both the Planned Behavior Theory and extended additional concepts of habit formation and anticipated future regret. The researchers conducted a study using a quantitative research approach which involved both descriptive and explanatory research designs. Data were collected through a 5-point Likert-scale questionnaire adapted from prior studies. Responses were collected from 186 employees online. The data were analyzed using descriptive statistics, correlation, multiple regression, and mediation analysis in SPSS. Both attitude and perceived behavioral control directly affect compliance on both direct and indirect pathways which lead to intention, while subjective norm affects compliance through its connection with intention. Intention shows a strong effect on actual compliance behavior. Habit has a direct effect on compliance but does not influence intention, whereas regret shows no significant effect on either intention or behavior. The study demonstrates that employee abilities together with their intention to achieve designated goals determine the success of ISP compliance, whereas emotional and habitual factors have minimal impact on ISP compliance success. It extends TPB by showing that not all additional behavioral variables are equally relevant in structured organizational environments, offering practical insight for improving compliance strategies in financial institutions.
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    Effects of customer satisfaction, consumer trust, e-service quality, perceived value, and perceived security on consumer loyalty in electronic commerce
    (Addis ababa university, 2026-11-02) Buruke Mulate; Dr. Minale Ashagrie
    Merkato, Addis Ababa, Ethiopia by investigating the influence of customer satisfaction, consumer trust, e-service quality, perceived value and perceived security. With the fast proliferation of digital commerce in developing countries, understanding consumer loyalty in online shopping environment, particularly in developing contexts where trust is developing and infrastructure are limited has become increasingly imperative. A quantitative research method based on the positivist philosophy and using the deductive logic was adopted and the study used an explanatory cross-sectional survey research design. Data were collected from 373 online shoppers in the Merkato region of Addis Ababa using structured questionnaires with items scaled on a five point likert-scale. The data were analyzed using IBM SPSS Statistics Version 27. The analyses involved in testing the variables' association and hypothesis testing included descriptive analysis, Pearson correlation, and multiple linear regression. The results show that all five independent variables positively and statistically significantly influence consumer loyalty (p< .001). In terms of influencing power, the strongest determinant of consumer loyalty is consumer trust (β = 0.302), followed by consumer satisfaction (β =0.252), perceived security (β =0.250), e-service quality (β =0.238) and the least influential antecedent is perceived value (β =0.208). Multiple linear regression was also run for this investigation; the model has a strong explanatory power of 76% with a multiple correlation coefficient (R²) of 0.760. It is concluded that trust, satisfaction and security among others have the biggest role to play in enhancing customer loyalty in e commerce. Building and strengthening such factors may have an overall positive impact on customer retention and retention in online platforms. This result provides implications for e commerce entrepreneurs and policy-makers who aim at enhancing the development and sustainability of online trade in emerging economies such as Ethiopia.
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    The Role and Impact of Digital Financial Services (DFS) in Advancing Financial Inclusion in Ethiopia
    (Addis Ababa University., 2026-11) Daniel Derese; Dr. Eyob Nigussie
    Financial inclusion—access to affordable formal financial services—is a key driver of poverty reduction and inclusive growth. In Ethiopia, Digital Financial Services (DFS) have grown rapidly since 2020, especially after regulatory reforms and the launch of Telebirr. This study examines six DFS channels (atms, POS, mobile banking, internet banking, agent banking, mobile money) and their impact on financial inclusion between 2020 and 2025 Using official UN population data (mid-2025 total: 135.47 million; adult 15-64: 78.5 million) and regional shares from the Ethiopian Statistical Service (ESS, 2024), the Sarma Index of Financial Inclusion (IFI) – Euclidean distance formula – suggests the national IFI increased from 0.087 (Low) in 2020 to 0.663 (High) in 2025, a 6.6-fold increase. Regional differences are substantial with Harari leading (0.748 Very High) while Oromia is the lowest (0.081 Low) followed by Amhara (0.092) and Central Ethiopia (0.193). , Low). Combined, agent banking and mobile money are the biggest drivers of IFI progress, accounting for 43%. The IFI is a good predictor of active usage (β = 56.38, p < .001, R2 = .722). However, 60% of mobile money accounts are dormant and women are substantially less included (male IFI 0.718 vs female 0.452). Scenario simulations show that the national IFI would increase to 0.75 by 2028 with active adult inclusion at 62% with full policy optimization. The study indicates that although DFS has greatly extended access, the next phase must focus on activating dormant accounts, reducing the gender gap and reaching lagging regions. Evidence-based, channel-specific suggestions are presented for regulators, financial institutions and development partners
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    Transformer-based complaint classification: evidence from 951 ivr line customer contact center of the commercial bank of ethiopia
    (. Addis ababa university, 2026-11-02) Dereje Getahun; Dr. Eyob Negussie
    Effective customer complaint handling is essential for delivering quality services in banks. CBE records thousands of complaints on a daily basis through its toll-free number 951 using the Interactive Voice Response (IVR). It has become clear from the current manual complaint classification strategy that there are significant problems within this system. Customer service agents were found to be classifying customer complaints randomly without paying attention to their contents, resulting in a classification accuracy of 7.0% and a macro F1 score of 6.0%. The DSR method has been used to create a Natural Language Processing (NLP) tool for classifying CBE 951 IVR customer complaints into one of the six categories: Operational Related, Behavioural Related, Fraud Related, General, Suggestion/Comment, and Product/Procedure Related. A total of 9,762 customer complaint cases were used to train and validate four transformer models such as BERT-base, finbert, afriberta, and XLM-R. The Triple-Stream Ensemble which is a combination of three transformers including finbert, afriberta, and XLM-R recorded a high validation accuracy of 88.2% and macro-F1-score of 87.5%. On the other hand, TF-IDF + SVM classical baseline experimented on the same dataset gained weighted F1 = 78.19%. The most performing transformer in this study was the finbert batch size 32 that reported a weighted F1-Score of 0.9025 and accuracy of 90.29%. In this case, the proposed solutions have resulted in a huge increase of 81.2% improvement over the baseline model. This shows the usefulness of using transformers designed specifically for certain languages/ domains.
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    Factors affecting the adoption of digital business technologies in organizations in addis ababa, ethiopia: a toe framework perspectiv
    (Addis ababa university, 2026-11-02) Epherata Bedada; Hailay Beyene (Ph.D.)
    Digital business technology adoption is becoming important for organizations for enhancing their organizational performance and improve competitiveness. However, organizations in Addis Ababa struggle with integrating those tools. This research examined the factors that affect digital business technology adoption in organization in Addis Ababa using Technology-Organization Environment (TOE) Framework. This study primarily employed a quantitative research approach supported by qualitative analysis. The data was collected using a structured questionnaire that distributed among 152 respondents from different organizations in Addis Ababa. The quantitative data was analyzed statistically using SPSS version 31, whereas the qualitative data were analyzed thematically. The results of this research indicated that the technological, organizational, and environmental factors have a significant impact on the adoption of digital business technologies in organizations. The technological factors were found to be the strongest predictor (β = 0.361, p < 0.001), followed by organizational factors (β = 0.353, p < 0.001), whereas the environmental factors have less impact but significant effect (β = 0.150, p = 0.022). The regression model accounted for 55.9% of the variation in the adoption of digital business technologies. This study also identified that the major challenges to the adopting digital business technology are poor technological infrastructures, lack of digital skills, limited budget, and organizational resistance to change. The study concludes that the successful digital business technology adoption depends on the technological readiness, organizational support, skilled human resources, and supportive external environments
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    Blockchain framework to strengthen knows your customer (kyc) processes and data transparency (in case of cooperative bank of oromia
    (Addis Ababa University, 2026-11-02) Eyob Tesfaye; Dr. Kuribachew Gizaw
    The evolution of the KYC process has gone from a simple process to a more thorough one regulated by the regulatory authority of each country. The paper-based manual KYC process is neither cost-efficient,not fast nor customer-centered. In many countries, at least to some degree, the majority of financial institutions have to pay an estimated amount of approximately $550 million for conducting the process of KYC regulation. With the introduction of new laws and regulations concerning the process of KYC compliance in most parts of the world, there might be the chance that the cost for compliance will go up. The aim of this paper is to consider the case of Financial Institution and Cooperative Bank of Oromia through expert interviews and relevant literature analysis. As a result of the conducted analysis of the case study, factors like communication, source of information, validity of documentation, policy conformity, lengthy process, customer dissatisfaction, increased workload on the employees' side, inaccuracy, lengthy document searching process, lack of automation were identified as the main problems that arise as a result of the current process of KYC and hence render it outdated and unsuitable for business purposes. It becomes apparent that implementing blockchain technology in order to conduct KYC process would resolve all the above-mentioned problems. Some of the potential obstacles related to the implementation of blockchain could be legal risks, resistance to change, lack of trust, educating the customers, employees' training, redundancies, and energy consumption. Overcoming methods for these obstacles have been discussed in the results chapter. A number of suggestions with regard to the adoption of blockchain technology have been made including KYC automation, common KYC standards, conducting pilot projects, and linkages within the bank
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    Measuring the Impact of AI Tools on the Productivity of Staff in the Case of World Bank Ethiopia Office
    (Addis ababa university, 2026-10) Freweini Gebremedhin; Dr. Kuribachew Giza
    This study assessed the effect of Artificial Intelligence (AI) tools on the productivity of Staff of the World Bank Ethiopia Country Office. Data was collected from 70 employees to analyze the relationships between AI tool adoption, task features, AI literacy, organizational readiness and perceived performance impact. The study employed a quantitative cross-sectional survey design based on the task-technology fit (TTF) framework. From the data, we have witnessed the AI tools are making a big difference. They speed up and simplify routine tasks and which boost productivity. The study identified key gaps in prompting and practical user skills as well as a disconnect between leadership goals and the training provided to staff. The findings confirm that AI literacy is a stronger predictor of productivity gains than frequency of use. Highlighting the importance of investing in human capital to maximize returns on technology. The study concludes with practical recommendations for the organization to address these gaps. And also strengthen AI’s role in supporting knowledge work, including the development of transparent governance policies and tiered, skills-based training programs
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    Factors Affecting Job Search Efficiency on Ethio Jobs: A Study of Job Seekers in Addis Ababa
    (. Addis ababa university, 2026-11-03) Helen Girmay; Kuribachew Gizaw (PhD) _
    This paper is a research paper that focuses on factors that affects the efficiency of job search of job seekers. The study only includes candidates who actively use Ethio Jobs in Addis Ababa. The study uses a descriptive and explanatory research design to explore and understand the relationship between platform features and job search efficiency. A mixed-methods approach was used, combination of quantitative and qualitative data. The quantitative data were collected through structured questionnaires distributed to the job seekers using the Ethio Jobs platform in Addis Ababa. While qualitative data were collected through interviews conducted with the platform developers. A total of 292 valid responses were collected and analyzed using SPSS version 27 statistical software to address the research objective. From a sample of 300 job seekers. Participants were selected from active users of Ethio Jobs platform, including graduates, unemployed and employed individuals who are looking for new employment opportunities through Ethio Jobs platform. This explored the relationship of platform usability, job information quality, job matching effectiveness, digital literacy, and job search behavior on job search efficiency. And from qualitative side, participants were selected purposively from platform developers and experienced user. The study investigates the key factors affecting job search efficiency through multiple regression analysis. This explores the relationship between five independent variables and the dependent variable of job search efficiency. The independent variables include platform usability, job information quality, job matching effectiveness, digital literacy and job search behavior. The findings shows that job information quality, platform usability, job matching effectiveness, and job search behavior have statistically significant positive effects on job search efficiency. Among these variables, job information quality was the strongest predictor with a standard regression coefficient of (0.260). This suggests that clear, accurate, complete, and updated job information has the greatest positive influence on improving job search efficiency. However, digital literacy did not show a statistically significant effect, and the qualitative results shows that many job seekers face problems including job description that are incomplete or outdated, job postings that are outdated and a lack of feedback from employers after the job seekers submit there applications. Therefore, These issues can lower trust in digital recruitment platforms and negatively affect user satisfaction and long term engagement. The finding highlights the importance of improving employer responsiveness, x maintaining updated job listings, and strengthening platform monitoring systems to improve overall recruitment efficiency.
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    Assessing the Readiness of Ethiopian Audit Firms for Digital Transformation
    (Addis Ababa University, 2026-11-03) HermelaAdmassu; MinaleAshagrie (PhD)
    Digital transformation is transforming the audit profession globally, forcing audit firms to adapt new technology in order to raise audit quality and efficiency. Ethiopian audit firms’ readiness towards digital transformation has not yet adequately identified. This study examined digital transformation readiness of Ethiopian audit firms based on the effect of awareness & strategic understanding, adoption of technology, human capital development, risk management & audit quality, regulatory environment and client expectation. The research employed a cross-sectional descriptive and explanatory mixed methods approach. Data was gathered from 122 licensed auditors of Addis Ababa through a questionnaire and analyzed using descriptive statistics, correlation and multiple linear regressions. The finding shows that Ethiopian audit firms have a high to moderate digital readiness (Mean=3.76, SD=0.56). Regression model results proved to be statistically significant (R²=0.73, p<0.001) with 73 percent of variation in the digital readiness being explained by the 6 independent variables; and awareness & strategic understanding have a greater influence while regulatory environment is the weakest predictor; which emphasizes the institutional support. It is concluded that increasing the level of digital awareness, developing and increasing technology adoption capability, providing on-going training and updating the regulatory framework is significant to expedite digital transformation of Ethiopian audit firms. The findings have implications for audit firms, regulators and policy makers, and add on to literature on digital transformation in audit profession of developing economies.
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    Driving digital transformation through effective it service management:the case of ethio-telecom
    (Addis ababa university, 2026-11-03) Hilwa Yassin; Hailay Beyene (P.H.D)
    The purpose of this study is to examine the capacity effective IT Service Management has on driving Digital transformation in the nation's foremost network provider Ethio-Telecom.The success of internal IT service procedures is just as important to digital transformation (DT) in telecommunications as cutting-edge technologies. However, rather than empirically assessing ITSM's efficacy in generating quantifiable DT outcomes, previous research in developing-country contexts has mostly concentrated on ITSM adoption.A mixed-method explanatory design was used. 104 employees at the company's Addis Ababa headquarters completed a structured questionnaire to provide quantitative data, while contextual aspects were interpreted using the Technology–Organization–Environment (TOE) lens through qualitative interviews and observations. ITSM practices account for a significant amount of the diversity in digital transformation outcomes, according to multiple regression results (R2 = 0.661, p < 0.001). The greatest impact is seen in Continuous Service Improvement (β = 0.383), followed by Change Management (β = 0.228), Incident Management (β = 0.260), and Service Delivery Metrics (β = 0.201).Qualitative results show that, even with organized ITSM processes, transformation speed is restricted by reliance on external vendors and a lack of knowledge transfer. By connecting ITSM efficacy to DT outcomes and providing context-specific insights for telecom companies in emerging nations, the study makes a valuable contribution
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    Predictive analytics framework for decision support in ethiopia’s foreign exchange market
    (ADDIS ABABA UNIVERSITY, 2026-11-03) Hundera Belema; Kuribachew Gizaw (PhD)
    This research designs and tests a predictive analytics framework that can be used to support decision-making in Ethiopia's foreign exchange market. The research utilises data mining techniques along with conventional econometrics to better estimate and identify foreign exchange determinants under realistic institutional constraints. Daily USD/ETB and monthly macroeconomic indicators from August 2024 to December 2025 are used and xgboost, ARIMA, and Prophet models are compared. Among the models xgboost achieves the highest accuracy (MAPE 2.62%, R² 0.6329), marginally outperforming ARIMA (2.71%), while Prophet fails. Based on SHAP analysis inflation is identified as the dominant driver of foreign exchange with 55% of feature importance followed by exports and imports. The final decision support system is built to be modular, adaptive and scalable. Therefore this study showcases the possibility of using data mining in Ethiopia's foreign exchange market improvement
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    The Effect of Business Intelligence Tools on Strategic Decision Making: The Case of Ethiopian Banks
    (o Addis Ababa University, 2026-11-03) Marishet Solomon; Minale Ashagrie (Ph.D.)
    Today, banks use many technologies, and business intelligence (BI) is one of those tools that helps banks and many other industries to transform their raw data into information they can use to make their decisions. The main objective of this study is to examine the effect of BI tools on strategic decision-making and organizational performance in Ethiopian banks. To achieve this objective the researcher used quantitative research approach. Primary data were collected from employees of the five selected banks; Commercial Bank of Ethiopia, Enat Bank, Hibret Bank, Abay Bank, and Dashen Bank, using a five point Likert scale questionnaire. 192 response were returned from the distributed 200 questionnaires with 40 questionnaires to each bank. The data were analyzed using descriptive statistics, correlation analysis, multiple regression, and mediation analysis using SPSS version 27. The finding of the study revealed that system quality and BI usage were significantly and positively associated with decision-making quality, while information quality and service quality showed no significant direct association. The mediation analysis shows that BI maturity was significantly associated with the quality of decision-making. BI maturity partially mediates the relationship between system quality and decision-making quality, and fully mediates the relationships between information quality, service quality, BI usage, and decision-making quality. Furthermore, decision-making quality was found to be significantly associated with organizational performance
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    Institutional determinants and operational performance of public organizations: mediating role of enterprise resource planning adoption
    (Addis Ababa University, 2026-11-03) Amanuel Getachew; Meshesha Legesse (Ph.D.)
    This study examines the mediating role of Enterprise Resource Planning adoption in the relationship between institutional determinants and operational performance in public organizations based in Addis Ababa, Ethiopia. Based on Technology-Organization-Environment framework, Resource Based View, and Institutional Theory, the study focuses on five institutional determinants such as leadership commitment, organizational culture, institutional capacity, regulatory frameworks, and resource availability. A quantitative research methodology and explanatory design were adopted focusing on 440 employees from 88 public organizations to address the objectives. Stratified random sampling was used to obtain 188 valid responses (response rate is 89.5%), which were gathered by using structured questionnaires. The collected data were analyzed using descriptive statistics, Pearson correlation, and multiple regression analysis with the help of SPSS version 26. Mediation was tested using the PROCESS macro for SPSS with 5,000 bootstrap resamples. The findings show that all five institutional determinants have a significant impact on operational performance, accounting for 69.9% of its variance (R² = 0.699). The strongest predictor of operational performance is regulatory frameworks (β = 0.357), followed by organizational culture (β = 0.240), leadership commitment (β = 0.197), institutional capacity (β = 0.159), and resource availability (β = 0.121). ERP adoption plays a mediating role in the relationship between institutional determinants and operational performance that amounts to 0.108 (95% CI: 0.037–0.179). The findings supported its statistically significant partial mediation effect, as the direct effect of institutional determinants remained significant (β = 0.719, p < 0.001) after mediation. It highlights the need to strengthen regulatory frameworks, enhance organizational culture, and address resource constraints to improve operational performance in Ethiopia’s public organization
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    Predictive Analytics in ATM Cash Demand Forecasting Using Machine Learning Approach: A Case Study of the Commercial Bank of Ethiopia
    (Addis Ababa University, 2026-11-03) Merdiya Taha; Minale Ashagrie (PhD)
    . Reliable cash availability at Automated Teller Machine (ATM) is important for customer service and for controlling the cost of holding and moving cash. The purpose of this study was to examine if predictive analytics and machine learning models can forecast daily ATM cash demand at CBE and support better replenishment planning. We used quantitative predictive approach to achieve the objective of the study. Secondary data was collected from the bank. Daily ATM transaction records from 15 atms covering two years period were used. Based on the raw data from the bank, data were cleaned preprocessed and new features were created. Three machine learning models were trained and compared namely, Linear Regression as baseline, Random Forest and Extreme Gradient Boosting (xgboost). Model performance was measured using MAE, RMSE, R2 and MAPE with using MAE and R2 as primary metrics. Xgboost was the best model with MAE of 268,821 and R2 of o.6682 and Random Forest was a close second. The analysis showed that recent demand history is the strongest driver of future demand, while salary days, pre-holiday days holiday events also shaped withdrawal. The study concludes that CBE already holds that data needed to move from experience based to data driven cash management and recommends adopting the model as a decision support tool supported by stronger data governance and staff capacity
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    The effect of job satisfaction on employee performance: in the case of fahem general trading plc. By: ametelaziz muhammed
    (Addis Ababa University, 2026-10-03) Ametelaziz Muhammed; Seifu mamo (PhD)
    Job satisfaction is a key factor influencing employee performance and organizational productivity. This study examined the effect of job satisfaction on employee performance at Fahem General Trading PLC, a private coffee trading company operating in Addis Ababa and Jimma, Ethiopia. The study was motivated by the limited empirical evidence on job satisfaction within Ethiopia’s private coffee trading sector. A quantitative research approach employing descriptive and explanatory research designs was used. From a population of 745 employees, a sample of 260 respondents was determined using Yamane’s (1967) formula, and 234 valid questionnaires were collected, yielding a 90% response rate. Primary data were gathered through structured questionnaires and analyzed using descriptive statistics, Pearson correlation, and multiple linear regression analysis with IBM SPSS version 27. The study examined six dimensions of job satisfaction: salary and benefits, working environment, supervision, promotion opportunities, recognition, and work relationships. The regression model was statistically significant (F = 13.431, p < 0.001) and explained 26.2% of the variation in employee performance (R² = 0.262). The findings revealed that working environment (β = 0.269, p = 0.013) and recognition (β = 0.297, p < 0.001) had significant positive effects on employee performance, while promotion opportunities had a significant negative effect (β = −0.473, p < 0.001). Salary and benefits, supervision, and work relationships were not statistically significant predictors of employee performance. The study concludes that improving the working environment, strengthening recognition practices, and establishing fair promotion systems can enhance employee performance and organizational effectiveness at Fahem General Trading PLC.
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    Impact of Security Awareness Program on Employee Phishing Resilience: A Case Study at Commercial Bank of Ethiopia
    (Addis Ababa University, 2025-10-26) Daniel Kelemewor; Meshesha Legesse
    This study investigates the effectiveness of security awareness training and the role of Protection Motivation Theory (PMT) constructs in shaping phishing resilience among employees of the Commercial Bank of Ethiopia. Despite technological protections, phishing remains a significant threat to organizations due to its psychological exploitation of human vulnerabilities. A quantitative approach was employed using structured questionnaires and organizational phishing report data from 396 randomly selected employees. Descriptive statistics, correlation, reliability testing, exploratory factor analysis (EFA), and multiple regression analyses were conducted using SPSS. The findings reveal that self-efficacy, response efficacy, response cost, and participation in security training significantly predict phishing resilience. Among these self-efficacy was the strongest contributor emphasizing the importance of users’ confidence in avoiding phishing threats. In contrast, perceived threat severity and threat vulnerability were not statistically significant. Moderation analysis showed that job role significantly influenced the relationship between training and phishing resilience, with non-technical staff who participated in security awareness program showed more phishing resilience. This research highlights the need for training programs to focus not only on threat awareness but also on building user confidence and practical coping strategies. The study contributes to the application of PMT in cybersecurity and provides actionable recommendations for improving phishing awareness interventions in the banking sector in Ethiopia.
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    Assessing the Impact of Digital Banking Service quality on Customer Satisfaction: A Study of Selected Branches of A bay Bank S.C.
    (Addis Ababa University, 2025-10-26) Eyersalm Kasay; Minale Ashagare
    Despite technological advancements in digital banking, financial institutions continue to face challenges in ensuring customer satisfaction. In Ethiopia, research on digital banking service quality has produced inconclusive findings, particularly concerning cultural and behavioral aspects within financial institutions. This study aimed to assess the impact of digital banking service quality on customer satisfaction at selected branches of Abay Bank S.C. in Addis Ababa. The study investigated six independent variables reliability, responsiveness, assurance, empathy, tangibility and security & privacy with customer satisfaction as the dependent variable. A quantitative approach was adopted, using descriptive and explanatory research designs. Data were collected throughstructured 5-point Likert scale questionnaires distributed to 384 digital banking customers, with 339 valid responses analyzed. Using SPSS Version 26, the study applied descriptive and inferential statistics, including multiple linear regression analysis. The findings indicated that customers were generally moderately to highly satisfy with Abay Bank’s digital services. Among quality dimensions, Assurance (β = 0.252) and Security & Privacy (β = 0.217) had the most significant positive impact on customer satisfaction, followed by Empathy, Tangibility, Responsiveness, and Reliability.. The overall model was statistically significant (R² = 0.800, F = 221.545, p < 0.001), explaining 80% of the variance in customer satisfaction. The study concludes that digital banking service quality significantly affects customer satisfaction, especially in the areas of assurance and security and privacy, with moderate contributions from other service dimensions.
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    Exploring Opportunities and Barriers to Entry in The Online Gig Economy for Ethiopians: In the Case of Upwork
    (Addis Ababa University, 2024-10) Addis Moges; Eyob Nigussie
    The online gig economy has emerged as a significant source of employment opportunities globally. This study focuses on exploring the opportunities and barriers to entry in the online gig economy for Ethiopians, with a specific focus on the case of Upwork. Through a mixed-methods approach involving surveys, interviews, and data analysis, this research identifies the factors that facilitate or hinder Ethiopians' participation in the gig economy on platforms such as Upwork. This study examines the skills and qualifications demanded in the online gig economy and how well-aligned they are with the Ethiopian workforce. Additionally, this study investigates the barriers faced by Ethiopians, such as internet access, infrastructure limitations, and competition. The study seeks to provide valuable insights into the challenges faced by Ethiopians seeking to engage in online freelancing, as well as the potential benefits and opportunities that this mode of work offers. Based on gathered data the findings of the study suggest a complex interplay between opportunities, challenges, and support systems for freelancers on Upwork. There are an abundance of opportunities, but also significant barriers that need to be overcome. While challenges are faced, they might be perceived as less daunting than the initial hurdles. This study employed exploratory factor analysis (EFA) using Principal Component Analysis (PCA) to investigate the underlying structure of relationships between 15 variables in a dataset of 117 observations. Analysis of correlations revealed both positive and negative relationships between variables. Several variables exhibited strong positive correlations, suggesting they tend to change together. On the other hand, some variables showed strong negative correlations, indicating opposing trends. Keywords: Gig Economy, Online gig economy, Ethiopia, Freelancers, Upwork