IDEAS home Printed from https://ideas.repec.org/a/ibn/ibrjnl/v12y2019i10p86-97.html

Evaluation of Factors Affecting Employees' Performance Using Artificial Neural Networks Algorithm: The Case Study of Fajr Jam

Author

Listed:
  • Mohammad Rahmanidoust
  • Jianguo Zheng

Abstract

Human resources are the most valuable assets of any organization. Therefore, human resources performance has the greatest impact on the organization's performance and its ability to operate. Many factors affect the performance of employees in organizations. In this research, we seek to evaluate the factors affecting the performance of Fajr Jam refinery employees. For this purpose, firstly, the literature of the research, the indicators affecting the performance of employees were identified and the conceptual model of the problem was formed. Then, the required data were collected using a standard questionnaire based on the conceptual model of the problem among employees of FJG Company. After assessing the validity and reliability of the collected data, it is time to evaluate the performance of the indicators. For this purpose, an artificial neural network algorithm was used to estimate the efficiency boundary values. After calculating the efficiency values in the presence of all the indices, each indices were eliminated from the conceptual model and again the efficiency values were estimated. Now, by comparing the performance statistics in the state before and after the removal of each indicator from the conceptual model, the degree and the mode of its effect are determined. The results of this study indicate that the "payroll" indicators, "environmental conditions" and "reporting culture" are the strengths of the system under review, and are now at an appropriate level. Also, the results indicate a negative impact on the indicators of "awareness", "system planning and preparation for critical situations," "amenities," "training," and "job security" in the system under review.

Suggested Citation

  • Mohammad Rahmanidoust & Jianguo Zheng, 2019. "Evaluation of Factors Affecting Employees' Performance Using Artificial Neural Networks Algorithm: The Case Study of Fajr Jam," International Business Research, Canadian Center of Science and Education, vol. 12(10), pages 86-97, October.
    • Handle: RePEc:ibn:ibrjnl:v:12:y:2019:i:10:p:86-97
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ibr/article/download/0/0/40846/42168
    Download Restriction: no
    File URL: http://www.ccsenet.org/journal/index.php/ibr/article/view/0/40846
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thanassoulis, E. & Boussofiane, A. & Dyson, R. G., 1996. "A comparison of data envelopment analysis and ratio analysis as tools for performance assessment," Omega, Elsevier, vol. 24(3), pages 229-244, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liadaki, Aggeliki & Gaganis, Chrysovalantis, 2010. "Efficiency and stock performance of EU banks: Is there a relationship?," Omega, Elsevier, vol. 38(5), pages 254-259, October.
    2. María Victoria Uribe‐Bohorquez & Jennifer Martínez‐Ferrero & Isabel‐María García‐Sánchez, 2019. "Women on boards and efficiency in a business‐orientated environment," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 26(1), pages 82-96, January.
    3. Chrysovalantis Gaganis & Iftekhar Hasan & Fotios Pasiouras, 2013. "Efficiency and stock returns: evidence from the insurance industry," Journal of Productivity Analysis, Springer, vol. 40(3), pages 429-442, December.
    4. Felder, Stefan & Tauchmann, Harald, 2013. "Federal state differentials in the efficiency of health production in Germany: an artifact of spatial dependence?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14(1), pages 21-39.
    5. Le, Minh & Hoang, Viet-Ngu & Wilson, Clevo & Managi, Shunsuke, 2020. "Net stable funding ratio and profit efficiency of commercial banks in the US," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 55-66.
    6. Julian H. Tice & António C. Moreira & Cláudia Sarrico, 2008. "Economic Performance Of Portuguese Companies 1989-1999: A Dea Study," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 111-128.
    7. Eric Fosu Oteng-Abayie & Anthony Affram & Henry Kofi Mensah, 2018. "Corporate Governance and Efficiency of Rural and Community Banks (RCBs) in Ghana," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 3(2), pages 93-118, December.
    8. Andrew C. Worthington, 1998. "The Application of Mathematical Programming Techniques to Financial Statement Analysis: Australian Gold Production and Exploration," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 97-113, June.
    9. Piot-Lepetit, Isabelle & Nzongang, Joseph, 2014. "Financial sustainability and poverty outreach within a network of village banks in Cameroon: A multi-DEA approach," European Journal of Operational Research, Elsevier, vol. 234(1), pages 319-330.
    10. Filipe Amado, Carla Alexandra & Dyson, Robert G., 2008. "On comparing the performance of primary care providers," European Journal of Operational Research, Elsevier, vol. 185(3), pages 915-932, March.
    11. Giokas, Dimitris I., 2001. "Greek hospitals: how well their resources are used," Omega, Elsevier, vol. 29(1), pages 73-83, February.
    12. Sabri Boubaker & Thanh Ngo & Aristeidis Samitas & David Tripe, 2025. "An MCDA composite index of bank stability using CAMELS ratios and shannon entropy," Annals of Operations Research, Springer, vol. 353(1), pages 353-376, October.
    13. Leigh Drake & Richard Simper, 2001. "The Economic Evaluation of Policing Activity: An Application of a Hybrid Methodology," European Journal of Law and Economics, Springer, vol. 12(3), pages 173-192, November.
    14. Andrew Worthington, 1999. "An Empirical Survey Of Frontier Efficiency Measurement Techniques In Healthcare Services," School of Economics and Finance Discussion Papers and Working Papers Series 067, School of Economics and Finance, Queensland University of Technology.
    15. Gaganis, Chrysovalantis & Pasiouras, Fotios, 2013. "Financial supervision regimes and bank efficiency: International evidence," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5463-5475.
    16. Shrimal Perera & Michael Skully, 2012. "On the cross‐methodological validation of bank efficiency assessments," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 29(1), pages 26-42, March.
    17. Liu, W.B. & Zhang, D.Q. & Meng, W. & Li, X.X. & Xu, F., 2011. "A study of DEA models without explicit inputs," Omega, Elsevier, vol. 39(5), pages 472-480, October.
    18. Elena Beccalli & Barbara Casu & Claudia Girardone, 2006. "Efficiency and Stock Performance in European Banking," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(1‐2), pages 245-262, January.
    19. M. C. Gouveia & L. C. Dias & C. H. Antunes & M. A. Mota & E. M. Duarte & E. M. Tenreiro, 2016. "An application of value-based DEA to identify the best practices in primary health care," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 743-767, July.
    20. Drake, Leigh & Simper, Richard, 2000. "Productivity estimation and the size-efficiency relationship in English and Welsh police forces: An application of data envelopment analysis and multiple discriminant analysis," International Review of Law and Economics, Elsevier, vol. 20(1), pages 53-73, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ibn:ibrjnl:v:12:y:2019:i:10:p:86-97. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.