IDEAS home Printed from https://ideas.repec.org/a/sae/vision/v22y2018i4p387-394.html
   My bibliography  Save this article

A Study on Role of Moderating Variables in Influencing Employees’ Acceptance of Information Technology

Author

Listed:
  • Payal Dutta
  • Ashima Sharma Borah

Abstract

Penetration of information technology (IT) in almost every sector of the Indian economy is occurring at a very rapid pace. This has brought about a great transformation from a paper world to a digital world. Employees face new technological changes in their workplace almost every day. Some employees welcome the changes brought about by technology while others resist it and become defensive. These differences in employees’ reactions are influenced by a host of moderating variables existing in the environment. For the purpose of the present study, the researchers have adopted three moderating variables, namely, age, gender and experience (from the unified theory of acceptance and use of technology [UTUAT] model of Venkatesh, Morris, Davis, and Davis (2003, MIS Quarterly , 27, 3, 425–478). Hence, the article attempts to study the influence of the aforementioned moderating variables on the employees’ acceptance of IT at their workplace. The study has been conducted in the post offices falling under the Nalbari-Barpeta division of the Assam postal circle. The study is based on both the primary and secondary data.

Suggested Citation

  • Payal Dutta & Ashima Sharma Borah, 2018. "A Study on Role of Moderating Variables in Influencing Employees’ Acceptance of Information Technology," Vision, , vol. 22(4), pages 387-394, December.
    • Handle: RePEc:sae:vision:v:22:y:2018:i:4:p:387-394
    DOI: 10.1177/0972262918803467
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0972262918803467
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0972262918803467?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. Borghans, L. & ter Weel, B.J., 2002. "Do older workers have more trouble using a computer than younger workers?," ROA Research Memorandum 1E, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    2. Meyer, Jenny, 2007. "Older Workers and the Adoption of New Technologies," ZEW Discussion Papers 07-050, ZEW - Leibniz Centre for European Economic Research.
    3. Katrin Schleife, 2006. "Computer Use and Employment Status of Older Workers — An Analysis Based on Individual Data," LABOUR, CEIS, vol. 20(2), pages 325-348, June.
    4. Viswanath Venkatesh & Xiaojun Zhang & Tracy A. Sykes, 2011. "“Doctors Do Too Little Technology”: A Longitudinal Field Study of an Electronic Healthcare System Implementation," Information Systems Research, INFORMS, vol. 22(3), pages 523-546, September.
    5. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    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. Hudomiet, Péter & Willis, Robert J., 2022. "Computerization, obsolescence and the length of working life," Labour Economics, Elsevier, vol. 77(C).
    2. Anna De Benedictis & Emanuele Lettieri & Michela Piredda & Raffaella Gualandi & Maddalena De Maria & Daniela Tartaglini, 2021. "Development and psychometric testing of a new measure of the determinants that influence the adoption of WhatsApp in hospitals," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-14, December.
    3. Bertschek Irene & Meyer Jenny, 2009. "Do Older Workers Lower IT-Enabled Productivity?: Firm-Level Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 229(2-3), pages 327-342, April.
    4. Lorenz Graf-Vlachy & Katharina Buhtz & Andreas König, 2018. "Social influence in technology adoption: taking stock and moving forward," Management Review Quarterly, Springer, vol. 68(1), pages 37-76, February.
    5. Lionel P. Robert Jr. & Tracy Ann Sykes, 2017. "Extending the Concept of Control Beliefs: Integrating the Role of Advice Networks," Information Systems Research, INFORMS, vol. 28(1), pages 84-96, March.
    6. Luc Behaghel & Eve Caroli & Muriel Roger, 2014. "Age-biased Technical and Organizational Change, Training and Employment Prospects of Older Workers," Economica, London School of Economics and Political Science, vol. 81(322), pages 368-389, April.
    7. Claudio Vitari & Roxana Ologeanu-Taddei, 2018. "The intention to use an electronic health record and its antecedents among three different categories of clinical staff," Post-Print halshs-01923238, HAL.
    8. Meyer, Jenny, 2008. "The Adoption of New Technologies and the Age Structure of the Workforce," ZEW Discussion Papers 08-045, ZEW - Leibniz Centre for European Economic Research.
    9. Jenny Meyer, 2011. "Workforce age and technology adoption in small and medium-sized service firms," Small Business Economics, Springer, vol. 37(3), pages 305-324, October.
    10. Claudio Vitari & Roxana Ologeanu-Taddei, 2018. "The intention to use an electronic health record and its antecedents among three different categories of clinical staff," Grenoble Ecole de Management (Post-Print) halshs-01923238, HAL.
    11. Ravi Seethamraju & Krishna Sundar Diatha & Shashank Garg, 2018. "Intention to Use a Mobile-Based Information Technology Solution for Tuberculosis Treatment Monitoring – Applying a UTAUT Model," Information Systems Frontiers, Springer, vol. 20(1), pages 163-181, February.
    12. Casas, Pablo & Román, Concepción, 2023. "Early retired or automatized? Evidence from the survey of health, ageing and retirement in Europe," The Journal of the Economics of Ageing, Elsevier, vol. 24(C).
    13. Pilav-Velić Amila & Černe Matej & Trkman Peter & Wong Sut I & Abaz Anela Kadić, 2021. "Digital or Innovative: understanding “Digital Literacy – Practice – Innovative Work Behavior” Chain," South East European Journal of Economics and Business, Sciendo, vol. 16(1), pages 107-119, June.
    14. Saeideh Sharifi fard & Ezhar Tamam & Md Salleh Hj Hassan & Moniza Waheed & Zeinab Zaremohzzabieh, 2016. "Factors affecting Malaysian university students’ purchase intention in social networking sites," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1182612-118, December.
    15. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    16. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    17. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    18. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    19. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    20. Talukder, Md. Shamim & Sorwar, Golam & Bao, Yukun & Ahmed, Jashim Uddin & Palash, Md. Abu Saeed, 2020. "Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach," Technological Forecasting and Social Change, Elsevier, vol. 150(C).

    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:22:y:2018:i:4:p:387-394. 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.