Understanding the Causes of High Labor Turnover and Absenteeism in the Ethiopian Textile and Garment Industry: Interviews with (Female) Workers and Management Personnel

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  • Michaela Fink 5  

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This chapter presents findings of a study on the Ethiopian textile industry with regard to the perceived major causes of absenteeism and turnover by both workers and management personnel. The findings premarily (derive) from qualitative data obtained through interviews. Interviews with female operators and human resource managers revealed mostly opposing views when explaining high rates of turnover and absenteeism: While the majority of the female workers interviewed blamed the mismatch between low pay and high workload, managers often referred to the workers’ ‘mindset’ and their ‘poor work ethic’s. The chapter highlights that effective measures to reduce employee turnover and absenteeism need to take both perspectives into consideration. The chapter concludes with actor-based recommendations for workforce stabilization.

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The BMZ supports the creation of fair and sustainable jobs in Ethiopia’s industrial parks through its project titled ‘Promoting Sustainable Growth in the Textile and Garment Industry in Ethiopia’ (eTex I). The project is aimed at job-effective growth, and improving the social and environmental sustainability of the textile and garment industry. The project was implemented from 2016 to 2020 by the German Corporation for International Cooperation (GIZ) GmbH in close collaboration with its political partners. BMZ’s efforts are currently being continued under the GIZ’s Sustainable Industrial Clusters (S.I.C.) project (2021–2024). S.I.C. is co-funded by the United Kingdom Foreign, Commonwealth & Development Office (FCDO) and continues to promote decent jobs and sustainable growth in Ethiopia’s manufacturing sector.

Michaela Fink (forthcoming): Labor turnover in Ethiopia’s textile industry. A hotspot of social transformation. Bielefeld: transcript.

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Fink, M. (2023). Understanding the Causes of High Labor Turnover and Absenteeism in the Ethiopian Textile and Garment Industry: Interviews with (Female) Workers and Management Personnel. In: Gronemeyer, R., Fink, M. (eds) Industrialization in Ethiopia: Awakening - Crisis - Outlooks. Sozialwissenschaftliche Zugänge zu Afrika. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-41794-9_2

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Causes and effects of Employee Turnover: the case Ethiopian Revenue and Customs Authority Jimma Branch Office

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dc.contributor.author Simbo Abebe
dc.contributor.author Shimelis Zewude
dc.contributor.author Hayelom Nega
dc.date.accessioned 2020-12-02T09:15:24Z
dc.date.available 2020-12-02T09:15:24Z
dc.date.issued 2015
dc.identifier.uri http://10.140.5.162//handle/123456789/1021
dc.description.abstract This study aims at analyzing the causes and impacts of turnover on Ethiopian Revenue and Customs Authority and particularly the case of Jimma branch office. In order to identify the causes and effects of the staff turnover in Ethiopian Revenue and Customs Authority Jimma Branch office, the research used both primary and secondary data. In order to make the study more reliable census method was used. With regard to primary data, first hand data was collected through questionnaire filled by twelve (12) terminated and all the existing nonmanagement and management staffs of the organization which is 172. Moreover data about the trend of both existing and terminated staff were collected from the organization's human resource department. The research is quantitative. Analysis was done using descriptive, correlation and regression techniques, by the use of SPSS version 20 for windows. From the study it was seen that the main causes of employee turnover emanates from internal factors prevailing in the organization on which the organization has control over. The study also finds the negative effect of employee turnover on organizational effectiveness and employee performance. en_US
dc.language.iso en en_US
dc.title Causes and effects of Employee Turnover: the case Ethiopian Revenue and Customs Authority Jimma Branch Office en_US
dc.type Thesis en_US

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  • Published: 08 July 2024

Work autonomy and its associated factors among health professionals in public hospitals of North East Ethiopia

  • Ali Yimer 1 ,
  • Amare Zewdie 2 ,
  • Amsalu Feleke 3 ,
  • Endalkachew Dellie 3 ,
  • Mohammed Ahmed 1 ,
  • Seada Seid 1 ,
  • Wubshet Debebe 3 ,
  • Hassen Ahmed 4 ,
  • Wolyu Korma 5 ,
  • Mohammed Adem 4 &
  • Abdulaziz Kebede 6  

Scientific Reports volume  14 , Article number:  15747 ( 2024 ) Cite this article

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  • Health care
  • Health occupations

A low level of work autonomy is the bottleneck for the health service delivery and the quality of the service. Although work autonomy is the pillar of organizational commitment and a means of employee retention mechanism, information about the magnitude of work autonomy among health professionals is limited in Ethiopia. Therefore, this study aimed to assess work autonomy and its predictors among health professionals working in public hospitals of Northeast Ethiopia. Institution-based cross-sectional study was conducted from March 24 to April 24, 2021, among health professionals using a stratified sampling technique. Variables with a p-value of < 0.25 in bivariable analysis were included in the multivariable analysis and variables with a p-value of < 0.05 in multivariable analysis were regarded as significantly associated factors. The overall good work autonomy in public hospitals (Dessie and Boru Meda Hospital) of North East Ethiopia was 54.5% (95% CI 54.48–54.53). Satisfaction with organizational policy and strategy (AOR 2.34, 95% CI 1.29–4.25), satisfaction with supervisor support (AOR 7.20, 95% CI 3.97–13.07), good health service delivery planning practice (AOR 1.88, 95%CI: 1.13–3.13), being married (AOR 4.26, 95%CI: 2.06–8.82) being pharmacy professionals (AOR 0.44, 95% CI 0.19–0.98), and being anesthesia and radiology professionals (AOR 4.66, 95% CI 1.65–13.19) were significantly associated with work autonomy of health professionals. More than half of the health professionals working in public hospitals in Northeast Ethiopia are autonomous in their work. Satisfaction with organizational policy and strategy, satisfaction with supervisor support, having good health service delivery planning practice, being married, and type of profession were significantly associated factors in public hospitals. Thus, strengthening strategies aimed at shaping poor health service delivery planning practices and dissatisfaction of employees concerning supervisor support and organizational policy might have a substantial contribution to improving the work autonomy of health professionals.

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Introduction.

Work autonomy refers to a degree of independence and freedom employees are required to do their work. Specifically, it relates to the pace at which work is completed, its order of completion, and a person’s freedom to work without micromanagement 1 . Autonomy doesn’t mean giving people the freedom to choose how to do their best work without completely removing accountability or regulations and processes 2 . Those things can still be observed, and in fact should be observed, to create proper autonomy. It’s more about empowering the individual to do their best work. When we talk about an autonomous workplace, we aren’t talking about “let’s go break all the rules,” but rather “let’s be transparent about the constraints we have to work around” 2 . It seems perspicuous that a feeling of volition and freedom positively underpins creative thinking, and most people who ever tried to understand out of the box under pressure and fault-finding control 3 , 4 . Health system organizations hire tremendous health professionals, employees who are using a set of professional norms 5 . Due to the characteristics of these employees' work nature, most administrative officials realize using Mintzberg’s theory 6 , that professionals should have a great level of autonomy from supervision at the time of applying their professional skills 7 .

Improving health professionals' work autonomy promotes their knowledge and experience 8 . Moreover, a health professional's work autonomy plays a significant role in patients, health professionals, and health institutions in terms of motivation, turnover reduction, and retention mechanisms of employees 8 , 9 , 10 . The critical and relevant characteristic of work autonomy is that it is based on a specific body of knowledge and skills that is not mastered by people outside the profession. Due to this case, the demand for autonomy is highly probable to emanate from the situation of the work itself. Professionals may find the effects of their organizational goals concerning the restriction of their freedom to provide care for their patients in their way, skills, and Knowledge 11 . Work situations that consider autonomy a part of basic the psychological needs of human beings go hand in hand with workplace health and emotional well-being. Various studies showed the importance of autonomy for health, creativity, and overall well-being 12 , 13 . Theories have also shown the role of autonomy in intrinsic motivation and well-being 14 .

Low work autonomy in every organization particularly health system organizations is still an existing problem that is a critical barrier to health service delivery and service quality at large 8 . Various epidemiological studies found a link between increased risk of cardiovascular disease and high job strain 15 , 16 . Undermining work autonomy affects not only workplace health at the level of an individual but also the workplace as an organization 17 . Based on a survey conducted in 1999, the European Commission estimated the yearly cost of work-related stress at €20 billion a year 18 . The magnitude of work autonomy is not well addressed yet according to scientifically available data. However; a study conducted in Oromia regional state revealed a magnitude of good work autonomy 46.13% 19 . Poor work autonomy could lead to several consequences. The main destructive consequences of inadequate work autonomy are poor job satisfaction, sluggish work engagement, low job performance, employees’ high turnover, conflict between health professionals and their managers, poor health service quality, and inefficient workflow 20 , 21 , 22 , 23 , 24 .

There are different factors known to affect work autonomy. Among these factors sex, age, marital status, educational status, experience, job satisfaction, and salary are the most fundamental factors with a significant role in health professionals’ work autonomy 11 , 19 , 21 , 25 , 26 . Other variables such as work unit and type of profession have also been considered as associated factors 19 , 27 .

The ultimate goals of the WHO health system building blocks of health care are health improvement, responsiveness, and financial and social risk protection 28 . This stated goal will only be possible if there are autonomous and committed health professionals who can translate the national aspirations and desires of the community into a reality 28 . The vision of the newly revised 2017 Ethiopian Government Health Policy is to see a healthy, productive, and prosperous generation. However; this can be effectively achieved when there are autonomous, experienced, and inspired staff who are accessible and responsible for providing the health service needs of the community 29 .

Some studies have been done on work autonomy. However; most of the studies are not on health professionals’ work autonomy 30 . No study addresses the whole health professionals’ work autonomy, particularly in Ethiopia. Some important variables such as supervision support, health service delivery planning practice, co-worker relationship, and organizational policy and strategy have not been included in previous studies 8 , 19 . Therefore; this study aims to assess work autonomy among health professionals working in public hospitals in Dessie City and Boru Meda General hospitals, Northeast Ethiopia.

Study design and setting

An institutional-based cross-sectional study was conducted between March and April 2021 at public hospitals in Dessie City. Dessie City is located 401 km far from Addis Ababa, the capital city of Ethiopia, and 488 km from Bahir Dar, the capital city of Amhara National Regional State 31 . In the city, there are five general private hospitals, two public hospitals, eight public health centers, and ten health posts to serve Dessie City and the catchment areas of more than 8 million residents from east Amhara, part of Tigray and Afar Region 32 . Boru Meda hospital currently (2021) has 40 beds for leprosy and other dermatology cases, in addition to other case teams. It also has three dermatology outpatient clinics with two dermatologists: a tropical dermatology professional and a health officer who has dermatology and leprosy training.

Populations

Those health professionals who served for a minimum of six months in the city’s public hospitals (Dessie Specialized Referral Hospital and Boru Meda General Hospital) were the population included in this study.

Eligibility criteria

Inclusion Criteria: All health professionals who work in the city’s public hospitals (Dessie Specialized Referral Hospital and Boru Meda General Hospital) during the study period.

Exclusion Criteria: Health professionals who work for less than six month was excluded from the study.

Sample size calculation

For the determination of work autonomy, the sample size was calculated based on the single population proportion formula. The calculation used a 46.13% proportion from a study conducted in Wollega 19 , a 5% margin of error, a 95% confidence level, and a 10% nonresponse rate with the following formula:

Z α/2  = confidence interval at 95%, n = 381.

d = level of significance at 5%

p = population proportion 46.13%

adding a 10% non-response rate, the total sample size was 419.

Sampling procedures and techniques

A stratified sampling technique based on profession type was followed to select health professionals from seven departments. Health professional Payrolls of Dessie Specialized Referral Hospital and Boru Meda General Hospital from the Human Resource Management were used as a frame for each professional category. Next, the sample size was proportionally allocated to number of the health professionals for each hospital. Finally, the study participants were selected by using a simple random sampling technique.

Study variables and their measurement

The dependent variable is work autonomy. Socio-demographic factors (age, sex, marital status, educational status, work experience, type of profession, monthly salary, living condition, and work unit), personal factors (manager’s attitude towards time management, health service delivery planning practice, and employees’ attitude towards time management) and organizational factors (retention and reward, co-worker relationship, organizational policy, and strategy and supervision support).

The dependent variable is the work autonomy of health professionals (Good/Poor) which describes the employees’ self-direction in initiating and continuing their work behaviors and making decisions. It was measured by four items having five Likert scales ranging from 1 strongly disagree to 5 strongly agree. It was categorized as good if the responses were greater than the mean value and poor if the responses scored equal to and below the mean value 33 .

Manager’s attitude towards time management indicates the managers’ outlook regarding time management. It was measured using five items having a five-point Likert scale. If a participant’s response scored above the mean value, it was represented as a good attitude if not a poor attitude 34 .

Employees’ attitude towards time management shows the likelihood of employees’ intention on effective time management utilization. It was measured by three items having a Likert scale out of five points. If the participant’s response score was above the mean value, it was represented as a good attitude if not a poor attitude 34 .

Co-worker relationship means the employee's interpersonal relationships with each other. This was measured by using 3 items each scored five-point Likert scale. It was categorized as good if the responses scored greater than the mean value and poor if the responses scored equal to and below the mean value 33 .

Supervisor support measured by six items having five Likert scales ranging from 1 strongly disagree to 5 strongly agree. It was categorized as good if the responses scored greater than the mean value and poor if the responses scored equal to and below the mean value 33 .

Recognition and reward describe the employees’ feelings towards the timeliness and fairness of recognition and reward. It was measured by using 4 items each scoring a 5-point Likert scale It was categorized as satisfied if the responses scored greater than the mean value and unsatisfied if the responses scored below and equal to the mean value 35 .

Organizational policy and strategy could be stated as the participants’ feelings on the application of organizational policies and strategies. It was measured by using 5 items each scored 5-point Likert scale. It was categorized as good if the responses scored greater than the mean value and poor if the responses scored equal to and below the mean value 35 .

Health service delivery planning practice describes setting goals, scheduling, and outlining tasks. It was measured by 4 items having five-point Likert scales. Those having above the mean value were regarded as having a good plan and those scoring below and equal to the mean value were represented as having a poor plan 35 .

Data collection tools and procedures

A structured and pretested questionnaire was used to collect the data. The self-administered questionnaire which was adapted from different studies was used 19 . Five trained Diploma Nurses and three Bachelor of Science (BSc) nurses collected and supervised the data respectively. Cron-Bach’s Alpha was done to check the internal consistency of the tools and each item scored above 0.7.

Data quality assurance

At Woldia General Hospital, 5% of the sample size was taken as a pretest to test the self-administered questionnaire before the actual data collection period. Amendments to the form, such as ambiguous terms and imprecise questions, were checked appropriately. The primary investigator provided a one-day training on the purpose of the study, the instrument, and the data collection procedures. Data collectors and supervisors were hired based on their research expertise. Experts in public health research also assessed the tool. The Principal Investigator and Supervisors reviewed each questionnaire once it was collected. Each data collector reviewed each participant's completed questionnaire daily to confirm the accuracy of the data. Every day, the Supervisors and Principal Investigator reviewed each questionnaire and verified its accuracy.

Data processing and analysis

The accuracy and consistency of each piece of information were examined before being collected and coded. It was finally entered into EPI-DATA version 4.6. The entered data was exported to the statistical package for social sciences (SPSS version 25) (IBM, USA) software for analysis. Tables were utilized to present the data and frequencies and cross-tabulations were employed to summarize the descriptive statistics of the data. With 95% confidence intervals, crude and adjusted odds ratios were used to determine the significance of the association. A binary logistic regression model was used to study the initial bivariable correlations between each independent variable and outcome variable to determine the relationship between the various predictor factors and the dependent variable. To exclude potential confounding variables, a multivariable analysis was performed on the independent variables with a p-value < 0.05 with a 95% confidence interval were regarded as factors significantly associated with work autonomy.

Ethical approval and consent to participate

Ethical clearance was obtained from the Institutional Review Board (IRB) of the University of Gondar with reference number IPH/1452/2013. A written permission letter was obtained from hospitals managers. Participants were formally informed about the purpose of the study. Confidentiality was maintained by omitting direct personal identifiers on the questionnaire, using code numbers, storing data locked with a password, and not misusing or wrongfully disclosing their information. Participants were also informed that participation was voluntary and they could withdraw from the study participation at any stage if they were not comfortable with the investigation. Written informed consent was obtained from the study participants before the study commencement.

A total of 409 participants responded to the self-administered questionnaire, resulting in a response rate of 97.6%. Among the participants, approximately 246 (60.1%) were male. The median age of the participants was 29 years, with an interquartile range of 27 to 33 years. Around 61.6% of the respondents were married and 71.6% of the participants resided with their families. The median monthly salary of study participants was 7071 (IQR: 6193, 9056) ETB. Furthermore, 50.6% of the participants were employed in inpatient work units within public hospitals (refer to Table 1 ).

Personal and organizational factors

Regarding personal and organizational factors, the majority of health professionals, specifically 363 individuals (88.8%), were satisfied with their co-worker relationships in public hospitals. However, a significant proportion of health professionals, particularly 57.5%, 66.3%, and 80.2% reported being dissatisfied with supervisor support, organizational policy and strategy, and recognition and reward systems respectively. Moreover, 42.1% of the respondents exhibited good practices in health service delivery planning (refer to Table 2 ).

The magnitude of work autonomy

The overall good work autonomy in public hospitals was determined to be 54.5% (95% CI 54.48–54.53), indicating a generally positive perception of work autonomy among the health professionals working in the study area.

Associated factors of work autonomy in public hospitals of Northeast Ethiopia

To identify factors associated with work autonomy in public hospitals in Northeast Ethiopia, logistic regression analysis was conducted using odds ratios (ORs) and 95% confidence intervals (CIs). Initially, bivariable logistic regression was performed to assess the association between each independent variable and the outcome variable. Thirteen variables with a p-value below 0.25 were selected as candidates for multivariable logistic regression analysis. Variables with a p-value less than 0.05 in the multivariable logistic regression analysis were considered statistically significant.

In the multivariable logistic regression analysis of public hospitals, five variables were found to be statistically significant. Health professionals who were satisfied with organizational policy and strategy had 2.34 times higher odds of having good work autonomy compared to those who were unsatisfied (AOR 2.34, 95% CI 1.29–4.25). Similarly, individuals who were satisfied with supervisor support had 7.20 times higher odds of having good work autonomy compared to their counterparts (AOR 7.20, 95% CI 3.97–13.07). Health professionals who demonstrated good health service delivery planning practices had 1.88 times higher odds of having good work autonomy (AOR 1.88, 95% CI 1.13–3.13). Furthermore, married health professionals were 4.26 times more likely to have good work autonomy compared to their unmarried counterparts (AOR 4.26, 95% CI 2.06–8.82). Additionally, anesthesia and radiology health professionals had 4.66 times higher odds of having good work autonomy compared to nurses (AOR 4.66, 95% CI 1.65–13.19). However, pharmacy health professionals had their work autonomy reduced by 56% compared to nurses (AOR 0.44, 95% CI 0.19–0.98) (refer to Table 3 ).

The present study's overall good work autonomy in public hospitals was 54.5% (95%CI: 54.48–54.53). It implies that those health professionals have above 50% work autonomy. However, healthcare practitioners need to have substantial work autonomy, which enables them to autonomously make decisions concerning patient care, treatment strategies, and other aspects of their professional responsibilities 36 .

According to this study; health professionals’ work autonomy in public hospitals could be impaired by organizational policy and strategy. Accordingly, the study revealed that health professionals in public hospitals who were satisfied with organizational policy and strategy were 2.34 times more likely to have good work autonomy than unsatisfied respondents. This finding was supported by the theory of Adam’s equity which stated that “if an employee is not fairly treated with organizational policy and strategy, the mistreatment could lead to undesired work autonomy and slow the pace of performance” 37 This similarity could be justified due to the reason that health professionals who were satisfied with the policy and strategy of their organization might have a strong attachment to their institution. Therefore; such a kind of inclusive organizational policy and strategy could incorporate work autonomy into consideration and adjust situations to ensure their work autonomy.

Similarly, study participants who were satisfied with supervisor support were 7.20 times more likely to have good work autonomy as compared with their counterparts. This finding was in agreement with Herzberg’s motivation-hygiene theory which stated that “the more employees are motivated by supervisor support and other factors, the more they prevent dissatisfaction and such a motivation could encompass work autonomy” 38 . Therefore; if employees were satisfied with their supervisor’s support of their work, this supervisor support could be in terms of work autonomy in whatever type of health institutions they are being employed.

On the other hand, health service delivery planning practice was significantly associated with work autonomy. Accordingly, the likelihood of good work autonomy was 1.88 times higher among participants who had good health service delivery planning practices than their counterparts. This finding was in line with Pareto’s theory of time management, which stated that “there is no sufficient time to do each and everything, but there is time to do urgent and important things”. The central idea of this theory shows the prioritization of tasks; which is one of the pillars of planning 39 . If health professionals had a good plan, this would enable them to be autonomous in their work as a means of motivation provided by their managers for having a good plan.

Likewise, the odds of good work autonomy of anesthesia and radiology health professionals were 4.66 times more likely as compared to nurses. However, the work autonomy of pharmacy health professionals was decreased by 56% as compared to nurses. This could be due to differences in educational status among health professionals as the findings of this study indicated. It revealed that most anesthesia and radiology professionals hold a degree and above whereas most of the pharmacy professionals are diploma holders as compared to nurses. It might be also due to a nationwide shortage of anesthesia and radiology health professionals as compared to nurses. This might trigger employers to keep the autonomy of such insufficient professionals on top of the others to retain them in their institutions.

Moreover, marital status was significantly associated with work autonomy. Accordingly, being married was 4.26 times more likely to have good work autonomy as compared to unmarried respondents. This might be due to variation in the educational status of respondents as pointed out in this study. It showed that most of the married participants have a degree and above educational status as compared to unmarried groups. This might enable them to be highly aware of the value of work autonomy and they might strive to break any barriers to their autonomy. Furthermore, married health professionals might get social support from their spouses, which improves their psychological well-being and subsequently work autonomy 40 , 41 .

Strengths and limitations of the study

Despite having typical limitations; this study tried to address extensively work autonomy by incorporating important variables that have been missed in previous studies; such as organizational policy, planning, supervisor support, living conditions, co-worker relationship, and working unit Besides, it was not separately studied work autonomy across specific health professional’s category which might affect a clearer picture of the relationship between work autonomy and profession.

The use of self-administered questionnaires may have some potential for reporting biases. Associated factors of work autonomy have been identified in this study. However, it would be more strong evidence if those factors were explored further using a qualitative study.

Conclusions

The work autonomy in public hospitals of Northeast Ethiopia was low. Satisfaction with organizational policy and strategy, satisfaction with supervisor support, having good health service delivery planning practice, being married and type of profession were significantly associated factors in public hospitals.

This low work autonomy could affect the work engagement of health professionals and compromise the health service coverage and quality unless timely and appropriate interventions are taken. Policymakers need to emphasize their policy and strategy in the way to break the bottleneck of dissatisfaction of employees concerning supervisor support and organizational policy and strategy. Hospitals administrators should also encourage and train professionals to prepare their plans in their respective working units. Further study concerning work autonomy is needed to address the problem extensively by supporting a qualitative method in wider study settings.

Data availability

The results of this study were analyzed using the collected primary data. All the relevant data are included in this paper.

Abbreviations

Adjusted odd ratio

Confidence interval

Institute of Public Health

Institutional Review Board

Statistical Package for Social Sciences

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Acknowledgements

First, we would like to thank all study participants for their contribution in providing the necessary information. We would also thank data collectors and supervisors for their commitment to the accomplishment of this work

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Department of Public Health, College of Health Sciences, Woldia University, Woldia, Ethiopia

Ali Yimer, Mohammed Ahmed & Seada Seid

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Amare Zewdie

Department of Health Systems and Policy, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia

Amsalu Feleke, Endalkachew Dellie & Wubshet Debebe

Department of Biomedical Science, School of Medicine, College of Health Sciences, Woldia University, Woldia, Ethiopia

Hassen Ahmed & Mohammed Adem

Department of Public Health, College of Medicine and Health Sciences, Werabe University, Werabe, Ethiopia

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Conceptualization: Ali Yimer, Amsalu Feleke, Endalkachew Dellie, Mohammed Ahmed, Abdulaziz Kebede, Amare Zewdie, Seada Seid, Hassen Ahmed, Wubshet Debebe Negash, Mohammed Adem. Data curation: Ali Yimer, Amsalu Feleke, Endalkachew Dellie, Mohammed Ahmed, Amare Zewdie, Seada Seid, Wubshet Debebe Negash. Formal analysis: Ali Yimer, Mohammed Ahmed. Methodology: Ali Yimer, Amsalu Feleke, Endalkachew Dellie, Mohammed Ahmed, Abdulaziz Kebede, Amare Zewdie, Seada Seid, Hassen Ahmed, Wubshet Debebe Negash, Mohammed Adem. Writing—original draft: Ali Yimer, Amsalu Feleke, Endalkachew Dellie, Mohammed Ahmed, Abdulaziz Kebede, Amare Zewdie, Seada Seid, Hassen Ahmed, Wubshet Debebe Negash, Mohammed Adem. Writing—review & editing: Ali Yimer, Amsalu Feleke, Endalkachew Dellie, Mohammed Ahmed, Abdulaziz Kebede, Amare Zewdie, Seada Seid, Hassen Ahmed, Wubshet Debebe Negash, Mohammed Adem. All authors reviewed the manuscript.

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Yimer, A., Zewdie, A., Feleke, A. et al. Work autonomy and its associated factors among health professionals in public hospitals of North East Ethiopia. Sci Rep 14 , 15747 (2024). https://doi.org/10.1038/s41598-024-66865-6

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research on employee turnover in ethiopia

Talent at a turning point: How people analytics can help

Employees are quitting. The talent gap is widening. And leaders are grappling with the hybrid dilemma—what an imminent return to the office might look like and why.

In this episode of McKinsey Talks Talent , HR expert David Green, coauthor (with Jonathan Ferrar) of Excellence in People Analytics (Kogan Page, July 2021), speaks with McKinsey’s Bryan Hancock and Bill Schaninger about a talent market in the throes of changes—and how HR leaders can use people analytics to navigate the current inflection point successfully.

The McKinsey Talks Talent podcast is hosted by Lucia Rahilly.

HR in the spotlight

Lucia Rahilly: So, David, we are closing in on two years of the COVID-19 pandemic. It’s obviously been a massively challenging crisis that has put both lives and livelihoods at risk for employees across the globe. What has this crisis meant for the role of HR?

David Green: Well, I suppose it’s been HR’s chance to shine, and in many companies, it has. There’s an elevated role for the CHRO, 1 Chief human resources officer. which means more expectations for the function, a thirst for data to drive decisions around people, more interest from the C-level, and more demands from the C-level as well. Good people analytics teams have been more focused around employees and understanding how employees are feeling at the various stages of the pandemic, and then are building that into their approach to hybrid work.

Bryan Hancock: I think that the role of HR and the role of the CHRO is going to continue to be elevated for the next few years. The pandemic was a unique human event that affected individuals, that affected people. Now, as we come back and we adjust to the new normal, HR has an opportunity to continue to step up, to continue to innovate and continue to use data, facts, and insights in how they guide, not just intuition.

Bill Schaninger: There’s a little bit of “watch what you wish for.” Because now—while HR is unbelievably front and center, with critical roles and critical pools and “how are we going to respond to the return to the office,” et cetera—that same light shines on deficiencies in the function.

Where maybe in the past HR might’ve carried some folks who were pleasant or good order takers or good caretakers, what HR is demanding now is being numerate, understanding the value tree, really knowing how to use analytics—all that kind of stuff. It’s all laid bare now. So, it is a wonderful time for the function, but the bar for individuals has been raised dramatically.

Rising resignations, rising pressures

Lucia Rahilly: In the US we hear so much about what some are calling the Great Resignation and we are calling the Great Attrition : employees reassessing their priorities and quitting their jobs at record rates.

David Green: There’s a lot of column inches devoted to it here, and in Europe as well, although maybe not quite as much as in the US. We 2 David Green is managing partner of Insight222. work with around 90 large global organizations, about half of them headquartered in the US. The person I’m speaking to is usually the head of people analytics. They’ve had a lot of panicked executives saying, “Oh my God, everyone’s leaving.” When they actually look at their data, in most cases it’s not more than they would normally expect it to be. They’re seeing the numbers—maybe a little bit higher, in some cases, than in 2019—but maybe what we would expect as almost a correction from 2020. In most cases, certainly, the companies that I’ve spoken to, they’re not seeing numbers that justify some of the panic at the moment.

Bryan Hancock: I think what we are seeing is that some people are choosing to leave the workforce and not necessarily go to another job. When you look in the US at workforce participation rates, they’re down. If you look at who is leaving, it’s disproportionately women , and it is disproportionately people toward retirement age. When we start looking at other populations, that’s where you need a real focus on the facts and the insights that let you solve the problems around flexibility, comfort of coming to work—whatever it may be. Which is to say, let’s not necessarily paint with a broad brush. Although we do see dissatisfaction broadly, let’s really dive into who’s leaving and why.

Employee expectations have gone up. It’s been happening for a while, but maybe the pandemic acts as a bit of a catalyst to this. David Green

Bill Schaninger: One of the things I’ve been toying with, and I don’t know that we have a great answer, is do we have to do a fundamental reset, almost, on the offer? We’re facing this moment where there’s been a fixation on wages, but even as the wages have gone up, in many cases to $25, $30 an hour, you’re missing the point, which is “who I work for, the conditions I work under, the nature of the interactions—it has to be better.” I’m curious as to your experience of that part. It’s beyond the data, you know what I mean? This idea of a higher calling.

David Green: I definitely think there’s a purpose  that people want to have at work, and that’s now coming out. Employee expectations have gone up. It’s been happening for a while, but maybe the pandemic acts as a bit of a catalyst to this. What’s fascinating is some of the research that you’ve been doing at McKinsey. There’s a growing disconnect between executives around the return to work and employees who aren’t ready yet. Generally, there are large numbers that want more hybrid work  moving forward.

I wonder if one of the consequences of the Great Resignation and all the press around it is that maybe some of these executives will start to be a bit more flexible and come closer to what employees are looking for in the hybrid workplace, which actually will benefit executives in the long run. Maybe there’ll be a good consequence of all the column inches that have been written about the Great Resignation.

I like the way that you guys have kind of reframed it as the Great Attraction , depending on the way a company approaches it.

Lucia Rahilly: Bill or Bryan, are you seeing that shift in mindset among employers—toward embracing, or at least being more accepting of, a hybrid culture?

Bill Schaninger: I think two-thirds are still in the stage of “it’s either transitory or slowly they’ll come to their senses, and we’re going to bring them back.” Maybe a third are wrapping their heads around the hybrid model and saying, “Well, this could be pretty interesting.”

What people analytics can do

Lucia Rahilly: David, tell us a little bit about what we’re talking about when we discuss people analytics and how it helps HR leaders improve retention during this interval of churn.

David Green: Excellence in People Analytics has got 30 case studies of real-life people analytics in companies. There’s a couple that touch on attrition. What can people analytics do? I think that the key thing is to separate the signal from the noise. It can help organizations understand if they actually have a problem with attrition and, if so, where, what job families, what locations? Is it people that have been tenured for a certain time? Is it certain groups? As Bryan said, it is women who are disproportionately leaving the workplace.

If attrition is a problem, what can you do about it? If it’s in parts of the business that you’re either looking to divest or invest in less, attrition  can arguably be your friend. If it’s in areas of the business that you’re really trying to grow, and people are leaving and going to your competitors, then clearly it’s a problem that you want to try and address. But you need to understand why people are leaving—if they are leaving—before you can even think about what you can do to solve it.

Subscribe to the McKinsey Talks Talent podcast

What employers get wrong about the great attrition.

Lucia Rahilly: Bryan, walk us through some of the Great Attrition/Great Attraction research that we did.

Bryan Hancock: There’s a disconnect  between what an employer and an employee think the main issue is. The employer is saying, “Hey, people must be leaving for another job, a better job, and better pay.” Employees are saying, “No, I’m leaving because I don’t feel valued at work.” Even asking the right questions and getting the right frame can—before you get more advanced forms of analytics on it—bring a fact-based and broader lens to make sure we’re having the right conversation.

A really good people analytics function combines the broad view—the broad understanding of organizational research, the broad understanding that this is a field that’s been around for a while, and we know what motivates people—and then brings that to bear to highlight individual facts.

Bill Schaninger: We started getting the data back, and I said, “Isn’t it an interesting pattern here, all the things that the managers are saying are exogenous: ‘the employee is maximizing for the money, my competitor is being foolish about raising the floor.’” It’s everything that was outside them, that allowed them to point the finger at someone else. Managers should just hold up the mirror to themselves and realize that they’ve caused this environment where employees don’t feel valued. They don’t feel well looked after. They feel like they’re a piece of machinery.

Asking the right questions and getting the right frame can—before you get more advanced forms of analytics on it—bring a fact-based and broader lens to make sure we’re having the right conversation. Bryan Hancock

I’m hopeful we can help managers without, maybe, poking them in the eye so much, but maybe it takes a little poke in the eye.

David Green: Microsoft has published some research that they’ve been doing during the pandemic. They found that managers  are even more important in a remote or hybrid work environment. They need to be checking in, to be doing one-on-ones regularly. If they’re not, don’t be surprised if people get demotivated and decide to leave. Understanding that is the job of people analytics.

Then we can start doing something about attrition, which is a problem in organizations, and start to nudge managers and leaders around behaviors that will actually encourage people to stay because they feel valued, they feel looked after, they’re given a great employee experience. If you do these sorts of things, then people are going to be much less inclined to look elsewhere.

Yes, people sometimes will get a 40 percent pay raise on a new job. That’s just going to happen. There’s not much you can do about that. You can obviously make sure that you’re paying market rates or above-market rates, if that’s what you want to do. But I think that by creating the right culture in the organization and making people feel more valued, you can keep people more than you lose.

Bryan Hancock: The point of the research on the middle manager  is exactly what we’re seeing at our clients. In the course of the pandemic, what we saw is that some people are naturally very good managers—they knew how to check in, how to use the one-on-ones. Then, on the other end of the spectrum, there are some people that never checked in.

At one point during the pandemic, there was a survey, and 40 percent of the employees surveyed said that no one had called to check in on them—no manager, no individual. And those people were 40 percent more likely to be exhibiting some sign of mental distress. I think companies are now recognizing that and saying, “Hey, if the role of the manager got elevated during the pandemic, what does it mean in a hybrid world?” And a number of organizations are now saying, “Gosh, if it mattered when everybody was remote, doesn’t it matter at least as much, if not more, when we’ve got a mixed model, with some people in the office, some remote? Don’t we need to have those one-on-one coaching skills, as well as intentionality about when we’re all coming together as a team and when we’re separated?”

David Green: That, again, is where people analytics teams come in—listening to employees, conducting regular pulse surveys, looking at some of the passive data as well. By looking at some of the metadata, people analytics teams can see the managers who are checking in regularly with their employees and understand the behaviors that drive engagement, that drive performance from teams.

Making a difference in diversity, equity, and inclusion

Lucia Rahilly: David, in our Women in the Workplace  research, we saw that women managers were much likelier than men managers to call to see how their reports were doing. We also know from other research that women and people of color  have been among the most affected during the pandemic and that people of color, in particular, are more likely than White employees to attribute quitting to a lack of a sense of belonging in the organization. Do you see analytics as playing a role in promoting diversity, equity, and inclusion in the workplace?

David Green: We conducted annual research among over a hundred organizations this year. And one of the questions we asked was, “What are the top three areas in your organization where people analytics is adding the most value?” Diversity, equity, and inclusion came out on top—54 percent of respondents included that in their top three. And that’s gone up significantly since we did that research last year.

Now we’re seeing that people analytics is really helping organizations move beyond counting diversity, to measuring inclusion. We’re still at the early stages of that, in many respects. Companies are starting to understand the importance of inclusion and belonging. They’re measuring it in surveys, and they’ve got people analytics teams that can be on top of that as well.

Second, by looking at some of the passive network analysis as well, you can start to understand the links and the strength of relationships within teams and between teams. I think that is helping. Leaders want to be better at diversity, equity, and inclusion and to meet the expectations of the employees. They also want their organizations to be better at diversity, equity, and inclusion.

Bill Schaninger: That pivot toward moving upstream and asking, “What’s the felt experience”—that really encouraged us to go back and look at how we were measuring inclusion, not just to ask a few “engagement-y” questions but instead to ask, “What’s your sense of the organization overall; what are you personally experiencing in your company and team and with your manager?”

That pivot toward moving upstream and asking, “What’s the felt experience”—that really encouraged us to go back and look at how we were measuring inclusion. Bill Schaninger

From complex data to compelling story

Bill Schaninger: When you think about the advanced math, how do you get some of these insights without losing people in the math? At some of our clients, you get some really cool quant jocks, and they lose everyone on the third word.

David Green: It’s turning that complex math into a compelling story that’s going to resonate with whichever audience you’re delivering it to and the impact that it has on the objective. I wonder if, in addition to the kind of active-based network analysis that’s been going on for years, we now have the technology to do this at scale, looking at some of the metadata. Of course, you need to be careful about the ethics and the privacy and make sure there’s benefit for employees, of course, as well. But you’re right. You’ve got to take quite complicated insights and turn them into a compelling story that drives action you can then measure.

Bryan Hancock: We took our new inclusion assessment and put it in our inaugural Race in the Workplace survey. Our focus was on Black leaders in corporate America. What became clear is that more Black workers  in corporate America were leaving before they ever got promoted. But the numbers were so small, in terms of the absolute—maybe out of every hundred workers, you might’ve had one or two more Black workers than expected leave and one or two fewer White workers.

So from an awareness standpoint, an individual manager wouldn’t pick it up. But when you look at the data you say, “This is like an invisible revolving door. What’s going on in there?” That’s something that makes an executive say, “OK, I now know what I need to do with our new entry-level diverse talent. I know I need to focus on that. Now, let me go back and figure out the next level of detail. What are the levels of initiatives? How do I check up on this? How do I follow up?”

David Green: Another thing from network analytics is that I’ve seen a few examples where high-performing women who don’t have strong networks at the senior level don’t get promoted and leave the organization. Men, who are quite good, generally, at changing their networks as they move up an organization, were getting promoted. I think the academic research backs this up. When you make people aware of that, then they might change their behaviors and consciously build those networks.

Managing privacy risks

Bill Schaninger: David, you said something earlier that was interesting about the challenges with privacy. The US has some challenges on the data front, often around security and what you’re doing with hashing and things like that. Europe, I’ve always found to be way more sensitive to the idea of a “Big Brother-ish” tracking of my movements. In your experience, what’s the balance there, because the insight you can get from this is pretty awesome.

David Green: I think you’re right. There is a balance there. At any organization that wants to use people analytics, it’s OK to start small, be transparent right from the start, think about the benefit for the employees, and ask, “What are the benefits that we’re trying to drive out of this? What is the business problem we’re trying to solve?”

You’ve got to speak to your privacy team. You’ve got to engage with works councils in Europe. You have to clearly articulate the benefit for employees and how you’re going to protect that data. It can be frustrating in terms of time because it slows up the process at the start. But as you say, you can get some really, really rich insights out of some of these technologies that actually have a really clear and direct benefit for employees and the business.

Rethinking the workplace

Bryan Hancock: Are you seeing a link now between the people analytics team and the real-estate team? We’re hearing a lot of organizations start to ask, “What should the workspace look like? What does it do?” Are you seeing linkages across the teams or are they existing in silos?

David Green: They’re definitely starting to see linkages, particularly in the companies that are maybe more advanced in people analytics. They are bringing exactly that sort of data together. And they’re thinking, “OK, in some parts of the world, our people are back in the office, but we’ve got these hybrid work models in place now. People are using the office differently. We need to measure how people are using the office and then redesign the workplaces with intention.” And I think we’ll see more of that in the next 18 months, two years.

Bill Schaninger: Maybe six months ago, Bryan, you and I had a run of webinars. There was an architect from Atlanta talking about “repurposing the space.” So much of this was around flexibility. I think the consensus was that we’d been on a two- or three-decade run about increasing the density and lowering the square footage per person, and we were perfectly happy when we had teleworkers and remote workers. Now we may need to go in another direction and pay a little bit more for configurability if we’re talking about a combination of individual work, team-based work, or even lecture hall kind of communication.

The people agenda now is almost stemming the tide of dramatically increasing the span of bosses, increasing the density of office space, hoteling—that whole thing. So much of this had almost gone unchecked. Now we’re saying, “Hey, if we want to bring them back, we’ve got to use the workspace differently.”

I’ve found in Europe that you often have a bit more intervention on things like sunlight. Are you seeing that or is that a US thing and we’re just late to the party?

David Green: We’re definitely seeing that. It makes sense, doesn’t it? Part of understanding people is understanding how they use workspaces. If we can make workspaces more productive, then that’s good. People become more productive; hopefully, more engaged; and maybe less likely to leave, as well.

Recruiting beyond the usual suspects

Lucia Rahilly: What’s the role of analytics in helping HR leaders to fill the surging volume of open roles as folks quit and the talent gap widens?

David Green: The two big use cases of people analytics, going back years, have been attrition and recruiting. It’s almost like coming back full circle now in many respects. The people analytics teams have access to technology that can really help companies. We’re using analytics to automate parts of the recruitment process. In many respects, that actually widens the funnel. By automating, you can potentially open up the process and get a more diverse set of people applying in the first place, which is obviously good.

One big investment bank that I spoke to recently is using analytics to help hiring managers understand that if they use education and experience in their role profiles, how many applicants they’re likely to get and, if they tweak one or two things, how that might make a change to the applicants. If they maybe change the language that they’re using in the effort, they might get more female applicants, for example, if they’re looking for a software engineer. I think analytics is playing a big, big role in that. You can look at analytics across the recruitment process. You can start to see where you might be suffering significant candidate drop-off. You can start to understand if you have a problem around offer to accept.

I would argue that recruiting doesn’t stop once the person starts. You also need to think about onboarding. You need to think about understanding where managers are having one-to-ones with new starters in the first week, two weeks. Does that have an impact on people’s time to productivity? Does that have an impact on first-year attrition? There’s so much that analytics can do.

And then the other bit that I haven’t mentioned is bringing some of that external data in to understand things like supply of talent, demand of talent, locations where we might want to hire talent—particularly now that hybrid’s potentially opening the game around that as well.

Bill Schaninger: You mentioned framing the description of the job as a way of making it more appealing to candidates. I’m assuming that the lexicon you’re using triggers different behavior. That’s great.

David Green: Using natural-language processing helps to understand words that may put off female applicants or other groups. There’s academic research which says if you put bullet points on a job description, men will apply if they meet half of them; women tend not to apply unless they feel they meet at least 90 percent of them. So the more bullet points, the more you can have a very biased male slate, perhaps.

What types of data and insight matter?

Bryan Hancock: Have you seen organizations navigate and manage through all of the new offerings and make sure that they pick the types of data and types of insights that will matter most to them, not just the ones that seem cool to a person who heard about them on a podcast?

David Green: You probably need someone in your team spending half the time scanning the market and understanding the market, trying to get proof of concepts. A lot of the smaller vendors will do that, but you’re right; it’s not there everywhere. So now the regulators are coming in. There’s regulation in New York recently around using AI in the hiring process. The US Equal Employment Opportunity Commission is looking into it as well—the use of algorithms in hiring and people management generally. But, of course, the most important thing is you’ve got to make sure that what talent acquisition professionals are telling you is actually valid. You’ve got to be careful around bias. Particularly if you’ve got a problem with diversity in your organization, you don’t want to perpetuate that through hiring as well.

Moving people analytics to the center of your HR strategy

Lucia Rahilly: Last question: Where do HR leaders stand in terms of their own skills in data-driven decision making? Do you see that there’s work to be done?

David Green: I think there’s work to be done. We did a survey with a focus on data-driven culture. Over a hundred companies participated. Ninety percent said that their CHROs have now communicated that people analytics was a core component of HR strategy, but only 42 percent said that their companies have a data-driven culture for HR at the moment. You could argue that the first sign is that the CHRO says it’s important. They use these data in their conversations with executives. Maybe they celebrate people in the HR team who are using data, setting that as an example to others, making it very clear that it’s expected.

And there are technologies coming in that are enabling organizations to democratize the data, both for HR’s business partners, who are particularly important in this, but also for managers in the business. This is a big change for HR, so you’ve got to bring in change management and support people through that process. Data literacy is a core skill that they need to have.

Bryan Hancock: I think HR is well along the journey. We now have an understanding that HR is no longer just in the business of feeling good about people. It is in the business of bringing data, facts, and insight into the people side of work. I think there is a real understanding and appreciation of that across the board.

What we’re doing is shifting the skills of folks who used to deal with transactional issues and may have dealt with investigations—a number of things that required a different skill set. Now we’re shifting them not just to have data literacy but also to ask the right questions, to synthesize in the right way, and to compellingly advocate for solutions. The next push on analytics isn’t just the analytics but how to equip the team to use it.

David Green: It’s absolutely key. There is this mistaken idea that suddenly everyone in HR needs to become a data scientist or a statistician. But as you said, the important thing is the ability to ask the right questions and maybe to work with the business to develop hypotheses you can test with analytics. Then it’s communicating the insights and driving the change in order to implement them.

Lucia Rahilly: Let’s close there. David, thanks so much for being with us today.

David Green: Well, it’s been a pleasure. I’ve really enjoyed the conversation.

Bryan Hancock

David Green is managing partner of Insight222.  Lucia Rahilly is global editorial director of McKinsey Global Publishing and is based in McKinsey's New York office.

Comments and opinions expressed by interviewees are their own and do not represent or reflect the opinions, policies, or positions of McKinsey & Company or have its endorsement.

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DETERMINANTS OF EMPLOYEE TURNOVER IN SELECTED PUBLIC AND PRIVATE COMMERCIAL BANKS OF ETHIOPIA

Profile image of Mikiyas Gebreyohannes

2023, DETERMINANTS OF EMPLOYEE TURNOVER IN SELECTED PUBLIC AND PRIVATE COMMERCIAL BANKS OF ETHIOPIA

The intention of this paper is to determine the determinants that originate the employee turnover by pointing out variables including work setting, profession development, payment and job fulfillment. Using descriptive study, survey technique was employed for data collection to discover out the determinants. A sample of five public and private banks branches in Nifas Silk Lafto Addis Ababa was selected. The data was analyzed by using Cronbach's Alpha, correlation and regression in Statistical Packages for Social Science (SPSS) version 20 software. The independent variables work setting and job stress having heavily associated with dependent variable employee turnover whereas professional development and payment have fewer pressures on employees' turnover.

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IAEME Publication

This study gives much emphasis on reasons and impacts of employees’ turnover in commercial bank of Ethiopia. The banking industry in Ethiopia dominated by this public bank and its branches spread throughout the country while the government also opened the door for private investors to engage in the industry since the dawn fall of the Dergue Regime. While employee turnover dramatically increased after the private sector engaged in the industry. The study also tries to examine the consequences of employee turnover in detailed manner. The researcher employed descriptive survey research method to reveal the current state of turnover, consequence and management in CBE. Descriptive survey design helped the study to gather varieties of data to attain the aim of the study by describing the situation as it is. The research methods used for this study were both qualitative and quantitative approaches were utilized in order to describe the issue very well. This method was selected because it is planned method of data collection which helps to gather the necessary information on the issue under study. The study also used stratified random sampling method for existing employees. The respondents are stratified on the basis of the bank’s job category. The list of employees used as sample frame of 258 of available branches. The study found that low salary and benefit, unsuitable working environment, lack of recognition and bad relationship with superiors are among the reasons of employee turnover in the bank. Loss of highly specialized work force, high hiring and training costs are identified as the main impacts of employees’ turnover in the bank.

research on employee turnover in ethiopia

Majeed Mohammed

Firms spend a lot on their employees in areas of orientation and training, developing, preserving them in their organization. Therefore, managers must endeavor to reduce worker's turnover. The study intended to identify the causes of employee turnover, the findings eventually came out with the effects of turnover and strategies adopted by GCB to curb turnover. The study is descriptive study, survey method was adopted for data collection to find out the issues and factors. A sample of 48 GCB staff was selected for the survey. Data was analyzed by using Cronbach's Alpha, correlation and regression in SPSS software. The paper reveals their existing relationship between the employee turnover and factors affecting in Ghana Commercial Bank (training and development, job satisfaction, reward and pay, leadership style, the job, career development). It was concluded that turnover has some striking effects on the banking sector. These effects include; cost of hiring, loss of valuable employees, cost of training and development, low productivity, and low performance.

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In the recent environment every corporate leader faces the turnover intention problems. Every organization tries to minimize it and accumulate their cost. The purpose of the study is to face the find out how job satisfaction, employees demographic and family commitment consequence on the employees turnover intention. We conduct a research assessment with the target population layyah, D.G.Khan and Rajn Pur and took 150 quantities of sample sizes. All the data are collected from respondent through the questionnaires. For find out the research objective 26 different types of the questionnaires are distributed. By using of the SPSS-19 we revile the reliability test, descriptive test and correlation analysis for measuring the relationship of the dependent variable and independent variables. Finding of our research provide complete understanding and clearly indicate that there is association between the dependent variable and independent variables. Finding and recommendation will help the manager for decline the turnover intention rate in the banking sector.

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sindhu pillai

Employee turnover is a crucial issue for banking organizations as it is regarded with more workers quitting the banks. It is a tough task for all HR professionals. The employee turnover is the proportion of employees who depart from organization during a specified period. Therefore employee turnover in the organizations or companies has been a topic of interest in both academicians and industry. In this regard this paper is an effort to understand what are the major influencers of employee turnover in banking sector of Chidambaram Taluk.

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The purpose of this study was to investigate the role of employees&#39; engagement on their turnover intentions: the case of Commercial Bank of Ethiopia. The study used quantitative research method and employed both descriptive and explanatory research design to objectively answer the proposed research questions. To achieve the study objective, 368 sample respondents were selected through multistage sampling technique. Accordingly, data were collected through self-administered questionnaire from sample respondents. Out of 368 respondents, workable data were obtained from 335 respondents. The data, then, analyzed through descriptive, inferential statistics and independent samples T test. The finding of descriptive analysis revealed that more than half percentage of employees are under the category of neither engaged nor disengaged, and the mean score for the overall turnover intentions of employees is slightly above average. The independent samples T test revealed that both employees...

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The quality of service delivery of any organization depends on the presence of committed and talented employees. Employees are main sources for organizations in meeting objectives in both public and private sector organizations. Therefore, giving emphasis for employees become a big issue particularly in public sector organizations. Professional employees&#39; turnover in public sector organizations is more common than other organizations. Having this in mind, the present study is aimed to explore the professional employees&#39; turnover and retention practice focusing on MoFED. Theoretical framework and models of other scholars was used by modifying in our country context to know the real causes of turnover Both qualitative and quantitative method are employed the present study. In order to collect primary data, a self-completed questionnaire is designed and administered to both current and ex-employees of the organization. In addition, interview was conducted with management of the...

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This research paper exploits relationship between job satisfaction dimensions and turnover intensions among Nigerian banks’ employees in Osogbo metropolis, south western Nigeria. Simple random sampling technique was adopted to collect data from one hundred and five (105) respondents from different fifteen banks through structured questionnaire. Both Pearson Product Moment Correlation Coefficientand Multiple Regressions Analysis were used to analysis the data with the aid of statistical package for social sciences (SPSS). The result showed that job satisfaction dimensions have negative relationship with turnover intensions.It was also found that job satisfaction dimensions jointly predict employee turnover intensions, which accounted for 7.5% variance of turnover intensions. The study concluded thatmanagement of Nigerian banks should use these job satisfaction dimensions as policy instruments for retention and as strategies which have the tendency to reduce employee turnover and enhance job satisfaction in the organization. Key words: Turnover intention, Job satisfaction, pay, Nature of work, Recognition and Bank

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Why People Really Quit Their Jobs—and How Employers Can Stop It

By Polly Kang, David P. Daniels, and Maurice Schweitzer

High employee turnover remains a key problem facing many organizations across a broad range of industries.  For example , despite making high salaries, 66% of senior product managers and 58% of IT program managers say they are planning to quit their jobs. Meanwhile, 60% of emergency room nurses and 58% of critical care nurses report that  they  are planning to quit, too—despite having already invested a huge amount of time, effort, and money on specialized training for their current job. Turnover is costly because, when workers quit, it can be difficult to replace them. Therefore, it’s essential to understand  why  workers quit, especially when it can help organizations find effective ways to reduce turnover.

While workers decide to quit their jobs for a variety of reasons, our new research has identified one trigger of quitting that seems to be a mistake on the part of workers. Intuitively, it seems like being assigned to do many “hard tasks” should make a worker much more likely to quit. Surprisingly, however, this isn’t really the case. Instead, it was being assigned to do a streak of many hard tasks in a row that really made workers quit. This means that managers can reduce turnover by a substantial amount by simply re-ordering their workers’ tasks, so as to break up hard streaks. We call this strategy “task sequencing.”

Read the full article

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IMAGES

  1. (PDF) Revolving Door Paradox of Textile Industry in Ethiopia

    research on employee turnover in ethiopia

  2. (PDF) Employee Engagement in Ethiopia as a Result of Corporate Ethos

    research on employee turnover in ethiopia

  3. (PDF) DETERMINANTS OF EMPLOYEE TURNOVER IN SELECTED PUBLIC AND PRIVATE

    research on employee turnover in ethiopia

  4. (PDF) Turnover intention among healthcare workers in Ethiopia: a

    research on employee turnover in ethiopia

  5. (PDF) Performance management system and its role for employee

    research on employee turnover in ethiopia

  6. (PDF) Assessing the rationales and impacts of Employees Turnover in

    research on employee turnover in ethiopia

VIDEO

  1. Proof Research Employee Build

  2. Accounting for Employee Benefits

  3. Employee Excuses From Different Countries

  4. የስራ አጥ ቁጥር መጨመር ማህበራዊና ኢኮኖሚያዊ ተፅዕኖ ምን ይመስላል? Etv

  5. Women defy gender norms, access vocational training on hard labour occupations in Ethiopia

  6. Frehiwot Tamru: Ethio Telecom CEO, on how Telebirr gained 37M mobile money users in 2 years

COMMENTS

  1. PDF An Assessment of Professional Employees Turnover and Employee Retention

    AN ASSESSMENT OF PROFESSIONAL EMPLOYEES TURNOVER AND ... SMU JANUARY 2017 ADDIS ABABA ETHIOPIA . AN ASSESSMENT OF PROFESSIONAL EMPLOYEES TURNOVER AND EMPLOYEES RETENTION PRACTICES: THE CASE OF ETHIOPIAN REVENUE AND CUSTOMS AUTHORITY, EASTERN ADDIS ABABA ... department were helpful in determining the turnover trend. This research investigated the

  2. PDF School of Graduate Studies an Assessment of Factors Affecting Employees

    ADDIS ABABA, ETHIOPIA. ... the research advisor. This study has not been submitted for any degree in this University or any other University. ... Employee turnover, as defined by Hom and Griffeth (1994), is 'voluntary terminations of members from organizations'. On the other hand, Loquercio (2006), observed that staff turnover

  3. The Effect of Employee Turnover on The Organizational Performnace of

    employee turnover is one of them. Employee turnover is the rotation of workers around the labor market; between firms; jobs and occupation and between the state of employment and unemployment (Abassi et al., 2000).Though this movement is seen as a normal cycle of

  4. PDF Determinant of Employees' Turnover Intention: the Case of Addis

    hence causing employee turnover (Shukla, and Sinha, 2013). Professional employees‟ turnover is an important and pervasive feature of the labor market. Employee turnover is the rotation of worker around the labor market. The term turnover also defined by Price (1977) as: "the ratio of number or organizational members who have left during

  5. (PDF) The Impact of Employee Turnover on Organizational Performance: A

    The Impact of Employee Turnover on Organizational Performance: A Case Study of Mada Walabu University, Bale Robe, Ethiopia. MadaWalabu University, school of Natural science, Department of ...

  6. PDF JIMMA UNIVERSITY College of Business and Economics Department of Management

    Currently, employee turnover permeates most of the organizations in both developed and developing nations (Tariq et al, 2013). The CIPD (2011) survey report on employee turnover rate in the UK indicated that the nationwide turnover rate in 2006 was 18.1 percent. According to the report, employees' turnover varies from sector to sector. On ...

  7. (PDF) DETERMINANTS OF EMPLOYEE TURNOVER IN SELECTED ...

    The intention of this paper is to determin e the determinants that originate the employee turnover by poi nting. out variables including work setting, profession development, payment and job ...

  8. PDF Assessing Rationales and Impacts of Employees' Turnover in Commercial

    Assessing Rationales and Impacts of Employees‟ Turnover in Commercial Bank of Ethiopia maintain high first-rate levels of carrier provision regardless of having a excessive turnover charge.

  9. Understanding the Causes of High Labor Turnover and ...

    Information on the actual extent of labor turnover and absenteeism varies to some extent in the research literature. For instance, recent studies on the expanding manufacturing industry in Ethiopia report employee turnover rates of around 80 to 100% annually (Blattman and Dercon 2018; Yost and Shields 2017). In her study, Halvorsen (2021, p. 3 ...

  10. Full article: Demographic and job satisfaction variables influencing

    Employee turnover can be extremely devastating for any institution (Kemal, Citation 2013). The turnover rate of academic staff in Ethiopian universities has been increasing from time to time. The effect of employee turnover results in an extra workload on the remaining employees.

  11. The Effect of Job Satisfaction on Employees' Turnover

    Therefore, employee job satisfaction affects turnover rate in organization as it has closely linked to turnover intention. (Ahmad, 2012). A number of scholars Benko (2007), Spector (1997), Weisberg and Lambert (2001) stressed the importance of employee satisfaction and its influence on employee turnover. They explained that

  12. Factors Influenecing Employee Intention to Turnover at Commercial Bank

    The main objective of this research is to identify the major factors influencing employee turnover in commercial bank of Ethiopia(CBE) and provide professional advices that would help the bank to reduce turnover and retain its competent personnel.

  13. (PDF) The Impact of Employee Turnover on ...

    Based on the result of inferential statistical analysis, the research found employee's turnover has a significant cause on performance of the organization. ... 51-63, 2020 5) Demissu Gemeda. (2007). Academic freedom in Ethiopia: Perspectives of Teaching Personnel, the case of Addis Ababa Dar University, Forum for Social Studies, a Gemeda Adis ...

  14. PDF FACTORS AFFECTING EMPLOYEE TURNOVER INTENTION in DEVELOPMENT BANK OF

    2.2.2.1 Personal Factors. According to Yanjuan (2016),personal factors include age, gender, education level, marital status, years of working, individual ability, responsibility and so on. Another fact is that the female employee turnover rate is higher than male employees.

  15. Causes and effects of Employee Turnover: the case Ethiopian Revenue and

    The research is quantitative. Analysis was done using descriptive, correlation and regression techniques, by the use of SPSS version 20 for windows. From the study it was seen that the main causes of employee turnover emanates from internal factors prevailing in the organization on which the organization has control over.

  16. The Impact of Employee Turnover on Organizational Performance: A Case

    Employee retention is the process in which employers take steps to prevent the job switching of their key talents. This paper examines the total effect of co-worker relationship, work environment, remuneration job satisfaction, and organizational commitment on employee retention using data from 297 employees holding a position of professional science (PS) from headquarters of public ...

  17. (Pdf) Assessing Rationales and Impacts of Employees' Turnover in

    This study gives much emphasis on reasons and impacts of employees' turnover in commercial bank of Ethiopia. The banking industry in Ethiopia dominated by this public bank and its branches spread throughout the country while the government also opened the door for private investors to engage in the industry since the dawn fall of the Dergue Regime.

  18. Employee Turnover in Non-Profit Organizations in Jimma Prefecture, Ethiopia

    employee retention in Kenya and r ecommend more policy developed around rewarding of employees. According to Joseph M (2016) study fi nding the main factors that affected the rate of employee ...

  19. Work autonomy and its associated factors among health ...

    The main destructive consequences of inadequate work autonomy are poor job satisfaction, sluggish work engagement, low job performance, employees' high turnover, conflict between health ...

  20. 42% of Employee Turnover Is Preventable but Often Ignored

    Self-reported employee turnover risk is at its highest point since 2015. Gallup's latest measure in May shows half of U.S. employees (51%) are watching or actively seeking a new job, continuing ...

  21. I Want to Break Free: The Influence of Perceived Entrapment on Employee

    We extend turnover research by proposing and testing the counterintuitive idea from the suicide literature that a type of attachment to one's workplace can increase turnover intentions. Specifically, we argue that employees' perceptions of perceived entrapment - a negative form of attachment to their workplace - arise from perceptions of defeat at work and ultimately lead to turnover ...

  22. Full article: Assessing gender equity among businesses in Ethiopia

    2. Existing research. The importance of gender in entrepreneurship research is widely recognized as a result of its far-reaching implications transcending the individual. A number of studies indicate the prevalence of gender inequality in the performance of business enterprises, disproportionately affecting women.

  23. Effects of Human Resource Management Practices on Employee Turnover

    7 H4. Work place environment have a significant effect on employees' turnover intention. RESEARCH METHODOLOGY Study Area According to Central Statistics Agency (CSA 2017) projection report, Ethiopia is country with the total population 94, 351,001 of which 47, 364,009 are males and 46,986,992 are females.

  24. PDF AN ASSESSMENT OF FACTORS AFFECTING EMPLOYEES' TURNOVER

    services, employees work attitude and absenteeism are likely to determine the performance of the organization (Park and Shaw, 2013). NGOs, like any business or government organizations, experience staff turnover, which in turn affect their organizational performance. AMREF Ethiopia is one of the leading NGOs working in

  25. Empowering Leadership and Employee Well-being in Extreme Context: The

    Emergency service organizations are currently grappling with challenges related to the poor well-being of their staff and higher turnover intention. Limited research investigates the factors that may increase work engagement and decrease turnover intention among those working in extreme contexts. Drawing from the Job Demands-Resources model, this study examines the relationship between ...

  26. PDF Employee Turnover in Non-Profit Organizations in Jimma Prefecture, Ethiopia

    This study aimed to investigate the factors that affects staff turnover in nonprofit organizations operate in Jimma area. Descriptive design was used. Data were collected via questionnaires with ...

  27. David Green on people analytics and talent

    What employers get wrong about the Great Attrition. Lucia Rahilly: Bryan, walk us through some of the Great Attrition/Great Attraction research that we did. Bryan Hancock: There's a disconnect between what an employer and an employee think the main issue is. The employer is saying, "Hey, people must be leaving for another job, a better job, and better pay."

  28. Determinants of Employee Turnover in Selected Public and Private

    This study gives much emphasis on reasons and impacts of employees' turnover in commercial bank of Ethiopia. The banking industry in Ethiopia dominated by this public bank and its branches spread throughout the country while the government also opened the door for private investors to engage in the industry since the dawn fall of the Dergue Regime.

  29. Why People Really Quit Their Jobs—and How Employers Can Stop It

    High employee turnover remains a key problem facing many organizations across a broad range of industries. ... While workers decide to quit their jobs for a variety of reasons, our new research has identified one trigger of quitting that seems to be a mistake on the part of workers. Intuitively, it seems like being assigned to do many "hard ...

  30. PDF St. Mary University School of Graduate Studies Causes and Effect of

    causes and effect of employee turnover in bottling companies: a particular reference ... bethlhem alemu asfaw august, 2020 addis ababa, ethiopia . causes and effect of employee turnover in bottling companies: a particular reference with one-water bottling company a thesis submitted to st. mary's university, school of ... research questions ...