Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia

Natnael Mamuye

doi:doi:10.11648/j.ajtas.20180704.12

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Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia

Natnael Mamuye

Published in American Journal of Theoretical and Applied Statistics (Volume 7, Issue 4)

Received: 17 March 2018 Accepted: 30 March 2018 Published: 3 May 2018

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Abstract

The purpose of this study is to assess the employee turnover rate and cause in the case of Moret and Jiru Wereda. In light of this objective the study adopted quantitative and qualitative method of research approaches to test a series research hypothesis and subjective analysis respectively. Specifically, the study used survey of questionnaire analysis of Moret and Jiru Wereda. 326 respondents were selected based on stratified random sampling method. Data was then analyzed on quantitative basis using binary logistic regression and descriptive statistics; however, qualitative basis was used to subjective data. The result of this paper indicates that among the respondents 39.9 % of them do not want to quit their current job but majority of them (60.1%) said they seriously consider quitting their job very often. And furthermore the logistic regression found that Age of respondent, income of the respondents, experience of the respondents, educational level, satisfaction and incentive to be significantly related with turnover intension of the respondents and other factors such as gender, working hour and stress are found to be insignificant predictors of the turnover intension of the employees.

Published in	American Journal of Theoretical and Applied Statistics (Volume 7, Issue 4)
DOI	10.11648/j.ajtas.20180704.12
Page(s)	139-146
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Moret and Jiru Wereda, Turnover Intension, Logistic Regression

References

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[4]	Asmamaw Aregeta (2011). Professional employee’s turnover and retention practices of Ethiopian public sector Organizations of ministries of finance and economic development. Unpublished Master’s Thesis, Addis Ababa University.
[5]	Yared Debebe (2007), Staff Turnover in International Non-Governmental Organizations (NGOs).
[6]	Solomon Aberra (2007). Skilled Manpower Turnover and Its Management.
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[8]	Kevin MM, Joan LC, Adrian JW (2004). “Organizational change and employee turnover” Personnel Rev. 33 (2):161-166.
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[18]	Lai, C. (2009). Motivating employees through incentive programs. Jyvaskyla University of Applied Science.

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APA Style

Natnael Mamuye. (2018). Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. American Journal of Theoretical and Applied Statistics, 7(4), 139-146. https://doi.org/10.11648/j.ajtas.20180704.12

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ACS Style

Natnael Mamuye. Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. Am. J. Theor. Appl. Stat. 2018, 7(4), 139-146. doi: 10.11648/j.ajtas.20180704.12

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AMA Style

Natnael Mamuye. Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. Am J Theor Appl Stat. 2018;7(4):139-146. doi: 10.11648/j.ajtas.20180704.12

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@article{10.11648/j.ajtas.20180704.12,
  author = {Natnael Mamuye},
  title = {Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {4},
  pages = {139-146},
  doi = {10.11648/j.ajtas.20180704.12},
  url = {https://doi.org/10.11648/j.ajtas.20180704.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180704.12},
  abstract = {The purpose of this study is to assess the employee turnover rate and cause in the case of Moret and Jiru Wereda. In light of this objective the study adopted quantitative and qualitative method of research approaches to test a series research hypothesis and subjective analysis respectively. Specifically, the study used survey of questionnaire analysis of Moret and Jiru Wereda. 326 respondents were selected based on stratified random sampling method. Data was then analyzed on quantitative basis using binary logistic regression and descriptive statistics; however, qualitative basis was used to subjective data. The result of this paper indicates that among the respondents 39.9 % of them do not want to quit their current job but majority of them (60.1%) said they seriously consider quitting their job very often. And furthermore the logistic regression found that Age of respondent, income of the respondents, experience of the respondents, educational level, satisfaction and incentive to be significantly related with turnover intension of the respondents and other factors such as gender, working hour and stress are found to be insignificant predictors of the turnover intension of the employees.},
 year = {2018}
}

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TY  - JOUR
T1  - Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia
AU  - Natnael Mamuye
Y1  - 2018/05/03
PY  - 2018
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JO  - American Journal of Theoretical and Applied Statistics
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Author Information

Natnael Mamuye

Department of Statistics, College of Natural and Computational Science, Debre Berhan University, Debre Berhan, Ethiopia

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APA Style

Natnael Mamuye. (2018). Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. American Journal of Theoretical and Applied Statistics, 7(4), 139-146. https://doi.org/10.11648/j.ajtas.20180704.12

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ACS Style

Natnael Mamuye. Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. Am. J. Theor. Appl. Stat. 2018, 7(4), 139-146. doi: 10.11648/j.ajtas.20180704.12

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AMA Style

Natnael Mamuye. Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia. Am J Theor Appl Stat. 2018;7(4):139-146. doi: 10.11648/j.ajtas.20180704.12

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@article{10.11648/j.ajtas.20180704.12,
  author = {Natnael Mamuye},
  title = {Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {4},
  pages = {139-146},
  doi = {10.11648/j.ajtas.20180704.12},
  url = {https://doi.org/10.11648/j.ajtas.20180704.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180704.12},
  abstract = {The purpose of this study is to assess the employee turnover rate and cause in the case of Moret and Jiru Wereda. In light of this objective the study adopted quantitative and qualitative method of research approaches to test a series research hypothesis and subjective analysis respectively. Specifically, the study used survey of questionnaire analysis of Moret and Jiru Wereda. 326 respondents were selected based on stratified random sampling method. Data was then analyzed on quantitative basis using binary logistic regression and descriptive statistics; however, qualitative basis was used to subjective data. The result of this paper indicates that among the respondents 39.9 % of them do not want to quit their current job but majority of them (60.1%) said they seriously consider quitting their job very often. And furthermore the logistic regression found that Age of respondent, income of the respondents, experience of the respondents, educational level, satisfaction and incentive to be significantly related with turnover intension of the respondents and other factors such as gender, working hour and stress are found to be insignificant predictors of the turnover intension of the employees.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Statistical Assessment of Employee’s Turnover and Its Causes; In the Case of Moret and Jiru Wereda, North Shoa, Amhara, Ethiopia
AU  - Natnael Mamuye
Y1  - 2018/05/03
PY  - 2018
N1  - https://doi.org/10.11648/j.ajtas.20180704.12
DO  - 10.11648/j.ajtas.20180704.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 139
EP  - 146
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20180704.12
AB  - The purpose of this study is to assess the employee turnover rate and cause in the case of Moret and Jiru Wereda. In light of this objective the study adopted quantitative and qualitative method of research approaches to test a series research hypothesis and subjective analysis respectively. Specifically, the study used survey of questionnaire analysis of Moret and Jiru Wereda. 326 respondents were selected based on stratified random sampling method. Data was then analyzed on quantitative basis using binary logistic regression and descriptive statistics; however, qualitative basis was used to subjective data. The result of this paper indicates that among the respondents 39.9 % of them do not want to quit their current job but majority of them (60.1%) said they seriously consider quitting their job very often. And furthermore the logistic regression found that Age of respondent, income of the respondents, experience of the respondents, educational level, satisfaction and incentive to be significantly related with turnover intension of the respondents and other factors such as gender, working hour and stress are found to be insignificant predictors of the turnover intension of the employees.
VL  - 7
IS  - 4
ER  -

Copy | Download