IDEAS home Printed from https://ideas.repec.org/a/sae/vision/v23y2018i1p12-21.html

Predictive Modelling of Employee Turnover in Indian IT Industry Using Machine Learning Techniques

Author

Listed:
  • Shikha N. Khera
  • Divya

Abstract

Information technology (IT) industry in India has been facing a systemic issue of high attrition in the past few years, resulting in monetary and knowledge-based loses to the companies. The aim of this research is to develop a model to predict employee attrition and provide the organizations opportunities to address any issue and improve retention. Predictive model was developed based on supervised machine learning algorithm, support vector machine (SVM). Archival employee data (consisting of 22 input features) were collected from Human Resource databases of three IT companies in India, including their employment status (response variable) at the time of collection. Accuracy results from the confusion matrix for the SVM model showed that the model has an accuracy of 85 per cent. Also, results show that the model performs better in predicting who will leave the firm as compared to predicting who will not leave the company.

Suggested Citation

  • Shikha N. Khera & Divya, 2018. "Predictive Modelling of Employee Turnover in Indian IT Industry Using Machine Learning Techniques," Vision, , vol. 23(1), pages 12-21, March.
    • Handle: RePEc:sae:vision:v:23:y:2018:i:1:p:12-21
    DOI: 10.1177/0972262918821221
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972262918821221
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0972262918821221?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ravi Bapna & Nishtha Langer & Amit Mehra & Ram Gopal & Alok Gupta, 2013. "Human Capital Investments and Employee Performance: An Analysis of IT Services Industry," Management Science, INFORMS, vol. 59(3), pages 641-658, November.
    2. Kristen DeTienne & Bradley Agle & James Phillips & Marc-Charles Ingerson, 2012. "The Impact of Moral Stress Compared to Other Stressors on Employee Fatigue, Job Satisfaction, and Turnover: An Empirical Investigation," Journal of Business Ethics, Springer, vol. 110(3), pages 377-391, October.
    3. Neeraj Pandey & Gagandeep Kaur, 2011. "Factors influencing employee attrition in Indian ITeS call centres," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 4(4), pages 419-435.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simon De Vos & Christopher Bockel-Rickermann & Jente Van Belle & Wouter Verbeke, 2025. "Predicting Employee Turnover: Scoping and Benchmarking the State-of-the-Art," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(5), pages 733-752, October.
    2. Esmael Ahmed, 2024. "Detection of honey adulteration using machine learning," PLOS Digital Health, Public Library of Science, vol. 3(6), pages 1-25, June.

    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. Rajesh Srivastava & Thomas Tang, 2015. "Coping Intelligence: Coping Strategies and Organizational Commitment Among Boundary Spanning Employees," Journal of Business Ethics, Springer, vol. 130(3), pages 525-542, September.
    2. Najda Hayajneh & Taghrid Suifan & Bader Yousef Obeidat & Mohammd Abuhashesh & Raed Kareem Kanaan, 2020. "The relationship between organizational changes and job satisfaction in the Jordanian telecommunication industry," Journal of Social Sciences (COES&RJ-JSS), , vol. 9(1), pages 1-20, January.
    3. Erik Brynjolfsson & Wang Jin & Kristina McElheran, 2021. "The power of prediction: predictive analytics, workplace complements, and business performance," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 217-239, October.
    4. Robert Cialdini & Yexin Jessica Li & Adriana Samper & Ned Wellman, 2021. "How Bad Apples Promote Bad Barrels: Unethical Leader Behavior and the Selective Attrition Effect," Journal of Business Ethics, Springer, vol. 168(4), pages 861-880, February.
    5. Timothy Kiessling & Lars Isaksson & Burze Yasar, 2016. "Market Orientation and CSR: Performance Implications," Journal of Business Ethics, Springer, vol. 137(2), pages 269-284, August.
    6. Larissa Fuchs & Matthias Heinz & Pia Pinger & Max Thon, 2024. "How to Attract Talent? Field-Experimental Evidence on Emphasizing Flexibility and Career Opportunities in Job Advertisements," ECONtribute Discussion Papers Series 332, University of Bonn and University of Cologne, Germany.
    7. Li, Guangzhong & Fujiyama, Keishi & Wu, Cen & Zheng, Ying, 2024. "Employment protection, corporate governance, and labor productivity around the World," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    8. Lars E. Isaksson, 2025. "Corporate Social Responsibility Trajectory: Mining Reputational Capital," Administrative Sciences, MDPI, vol. 15(3), pages 1-25, March.
    9. Mohammad Abuhashesh & Suleiman Jamal Mohammad & Mohammad Al Khasawneh, 2019. "The attitude of Jordanian customers towards virtual stores," International Journal of Islamic Marketing and Branding, Inderscience Enterprises Ltd, vol. 4(1), pages 59-75.
    10. Nishtha Langer & Ram D. Gopal & Ravi Bapna, 2020. "Onward and Upward? An Empirical Investigation of Gender and Promotions in Information Technology Services," Information Systems Research, INFORMS, vol. 31(2), pages 383-398, June.
    11. Ta-Kai Yang & Min-Ren Yan, 2020. "The Corporate Shared Value for Sustainable Development: An Ecosystem Perspective," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    12. Isaksson, Lars E. & Woodside, Arch G., 2016. "Modeling firm heterogeneity in corporate social performance and financial performance," Journal of Business Research, Elsevier, vol. 69(9), pages 3285-3314.
    13. Ma, Li & Zhai, Xin & Zhong, Weiguo & Zhang, Zhi-Xue, 2019. "Deploying human capital for innovation: A study of multi-country manufacturing firms," International Journal of Production Economics, Elsevier, vol. 208(C), pages 241-253.
    14. Kong, Dongmin & Liu, Shasha & Xiang, Junyi, 2018. "Political promotion and labor investment efficiency," China Economic Review, Elsevier, vol. 50(C), pages 273-293.
    15. Kuldeep Singh & Madhvendra Misra, 2021. "Developing an agricultural entrepreneur inclination model for sustainable agriculture by integrating expert mining and ISM–MICMAC," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5122-5150, April.
    16. Ge, Chunmian & Huang, Ke-Wei & Kankanhalli, Atreyi, 2020. "Platform skills and the value of new hires in the software industry," Research Policy, Elsevier, vol. 49(1).
    17. Tim Reilly & Amit Saini & Jenifer Skiba, 2020. "Ethical Purchasing Dissonance: Antecedents and Coping Behaviors," Journal of Business Ethics, Springer, vol. 163(3), pages 577-597, May.
    18. Huake Liu & Frank Min Song & Yulin Yang & Yuyan Li, 2025. "Intellectual property education and corporate collaborative innovation: evidence from China," Empirical Economics, Springer, vol. 69(6), pages 3663-3716, December.
    19. Karina Nielsen & Claire Agate & Joanna Yarker & Rachel Lewis, 2024. "“It’s Business”: A Qualitative Study of Moral Injury in Business Settings; Experiences, Outcomes and Protecting and Exacerbating Factors," Journal of Business Ethics, Springer, vol. 194(2), pages 233-249, October.
    20. G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2022. "Analyzing the Impact of Companies’ Investment on Skill Upgradation in Improving their Resilience amidst COVID-19," MPRA Paper 112425, University Library of Munich, Germany.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:sae:vision:v:23:y:2018:i:1:p:12-21. 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: SAGE Publications (email available below). General contact details of provider: .

    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.