IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i17p9366-d629331.html
   My bibliography  Save this article

New Technologies in the Workplace: Can Personal and Organizational Variables Affect the Employees’ Intention to Use a Work-Stress Management App?

Author

Listed:
  • Giulia Paganin

    (Department of Psychology, University of Milan-Bicocca, 20126 Milano, Italy
    Bicocca Center for Applied Psychology, Department of Psychology, University of Milan-Bicocca, 20126 Milano, Italy)

  • Silvia Simbula

    (Department of Psychology, University of Milan-Bicocca, 20126 Milano, Italy
    Bicocca Center for Applied Psychology, Department of Psychology, University of Milan-Bicocca, 20126 Milano, Italy)

Abstract

Organizations are interested in finding new and more effective ways to promote the well-being of their workers, to help their workers manage work-related stress. New technologies (e.g., smartphones) are cheaper, allow more workers to be reached, and guarantee their anonymity. However, not all employees agree on the use of new technological interventions for the promotion of well-being. Consequently, organizations need to investigate technological acceptance before introducing these tools. By considering the technology acceptance model (TAM) framework, we investigate both the influence of workers’ perceived usefulness and ease of use on their intentions to use apps that help them managing work stress. Moreover, we contribute to the extension of this model by considering both personal (i.e., self-efficacy, personal innovativeness) and organizational (i.e., organizational support for innovation) variables. Our research involved 251 participants who completed an online self-report questionnaire. The results confirm the central hypothesis of the TAM and the influence of other variables that could influence acceptance of new technologies, such as apps that help manage work stress, and the intentions to use them. These results could help organizations ensure technological acceptance and usage by their workers, increasing the effectiveness of new technologies and interventions to promote well-being.

Suggested Citation

  • Giulia Paganin & Silvia Simbula, 2021. "New Technologies in the Workplace: Can Personal and Organizational Variables Affect the Employees’ Intention to Use a Work-Stress Management App?," IJERPH, MDPI, vol. 18(17), pages 1-17, September.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:17:p:9366-:d:629331
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/17/9366/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/17/9366/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Natarajan, Thamaraiselvan & Balasubramanian, Senthil Arasu & Kasilingam, Dharun Lingam, 2018. "The moderating role of device type and age of users on the intention to use mobile shopping applications," Technology in Society, Elsevier, vol. 53(C), pages 79-90.
    2. Ritu Agarwal & Jayesh Prasad, 1998. "A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology," Information Systems Research, INFORMS, vol. 9(2), pages 204-215, June.
    3. Jan-Emmanuel De Neve & Ed Diener & Louis Tay & Cody Xuereb, 2013. "The Objective Benefits of Subjective Well-Being," CEP Discussion Papers dp1236, Centre for Economic Performance, LSE.
    4. Justina Naujokaitiene & Margarita Tereseviciene & Vilma Zydziunaite, 2015. "Organizational Support for Employee Engagement in Technology-Enhanced Learning," SAGE Open, , vol. 5(4), pages 21582440156, October.
    5. Bernadette Szajna, 1996. "Empirical Evaluation of the Revised Technology Acceptance Model," Management Science, INFORMS, vol. 42(1), pages 85-92, January.
    6. Daniel A.J. Collins & Samuel B. Harvey & Isobel Lavender & Nicholas Glozier & Helen Christensen & Mark Deady, 2020. "A Pilot Evaluation of a Smartphone Application for Workplace Depression," IJERPH, MDPI, vol. 17(18), pages 1-14, September.
    7. Manis, Kerry T. & Choi, Danny, 2019. "The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware," Journal of Business Research, Elsevier, vol. 100(C), pages 503-513.
    8. Hiba Alhassany & Faisal Faisal, 2018. "Factors influencing the internet banking adoption decision in North Cyprus: an evidence from the partial least square approach of the structural equation modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-21, December.
    9. 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.
    10. Kunsoon Park & Narang Park & Wookjae Heo, 2018. "Factors Influencing Intranet Acceptance in Restaurant Industry: Use of Technology Acceptance Model," International Business Research, Canadian Center of Science and Education, vol. 11(10), pages 1-9, October.
    11. Marco De Angelis & Davide Giusino & Karina Nielsen & Emmanuel Aboagye & Marit Christensen & Siw Tone Innstrand & Greta Mazzetti & Machteld van den Heuvel & Roy B.L. Sijbom & Vince Pelzer & Rita Chiesa, 2020. "H-WORK Project: Multilevel Interventions to Promote Mental Health in SMEs and Public Workplaces," IJERPH, MDPI, vol. 17(21), pages 1-23, October.
    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. Nikola Soukupová, 2022. "Stress Management in Small and Medium-sized Enterprises," Economics Working Papers 2022-05, University of South Bohemia in Ceske Budejovice, Faculty of Economics.

    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. Ivonne Angelica Castiblanco Jimenez & Laura Cristina Cepeda García & Maria Grazia Violante & Federica Marcolin & Enrico Vezzetti, 2020. "Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications," Future Internet, MDPI, vol. 13(1), pages 1-21, December.
    2. Xin Xu & Viswanath Venkatesh & Kar Yan Tam & Se-Joon Hong, 2010. "Model of Migration and Use of Platforms: Role of Hierarchy, Current Generation, and Complementarities in Consumer Settings," Management Science, INFORMS, vol. 56(8), pages 1304-1323, August.
    3. Gao, Tao (Tony) & Rohm, Andrew J. & Sultan, Fareena & Pagani, Margherita, 2013. "Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance," Journal of Business Research, Elsevier, vol. 66(12), pages 2536-2544.
    4. Kasilingam, Dharun Lingam, 2020. "Understanding the attitude and intention to use smartphone chatbots for shopping," Technology in Society, Elsevier, vol. 62(C).
    5. Shivraj Kanungo & Vikas Jain, 2008. "Modeling email use: a case of email system transition," System Dynamics Review, System Dynamics Society, vol. 24(3), pages 299-319, September.
    6. Christopher R. Plouffe & John S. Hulland & Mark Vandenbosch, 2001. "Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions—Understanding Merchant Adoption of a Smart Card-Based Payment System," Information Systems Research, INFORMS, vol. 12(2), pages 208-222, June.
    7. Yuan Li & Jiaqi Liang & Jingxiong Huang & Mengsheng Yang & Runyan Li & Huanxia Bai, 2022. "Would You Accept Virtual Tourism? The Impact of COVID-19 Risk Perception on Technology Acceptance from a Comparative Perspective," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    8. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    9. Cristopher Siegfried Kopplin, 2021. "Two heads are better than one: matchmaking tools in coworking spaces," Review of Managerial Science, Springer, vol. 15(4), pages 1045-1069, May.
    10. Cliff R. Kikawa & Charity Kiconco & Moses Agaba & Dimas Ntirampeba & Amos Ssematimba & Billy M. Kalema, 2022. "Social Media Marketing for Small and Medium Enterprise Performance in Uganda: A Structural Equation Model," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    11. Lim, Joon Soo & Zhang, Jun, 2022. "Adoption of AI-driven personalization in digital news platforms: An integrative model of technology acceptance and perceived contingency," Technology in Society, Elsevier, vol. 69(C).
    12. Riffat Ara Zannat Tama & Md Mahmudul Hoque & Ying Liu & Mohammad Jahangir Alam & Mark Yu, 2023. "An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh," Agriculture, MDPI, vol. 13(2), pages 1-22, February.
    13. Kostas Zafiropoulos & Ioannis Karavasilis & Vasiliki Vrana, 2012. "Assessing the Adoption of e-Government Services by Teachers in Greece," Future Internet, MDPI, vol. 4(2), pages 1-17, May.
    14. Nistor, Cristian, 2013. "A conceptual model for the use of social media in companies," MPRA Paper 44224, University Library of Munich, Germany.
    15. Francisco Rejón-Guardia & Juán Sánchez-Fernández & Francisco Muñoz-Leiva, 2011. "Motivational Factors that influence the Acceptance of Microblogging Social Networks: The µBAM Model," FEG Working Paper Series 06/11, Faculty of Economics and Business (University of Granada).
    16. Wei Wang & Shoujian Zhang & Yikun Su & Xinyang Deng, 2019. "An Empirical Analysis of the Factors Affecting the Adoption and Diffusion of GBTS in the Construction Market," Sustainability, MDPI, vol. 11(6), pages 1-24, March.
    17. Xuechao Sui & Xianhui Geng, 2021. "Continuous usage intention to e-transaction cards in wholesale markets of agriproducts: empirical evidence from China," Future Business Journal, Springer, vol. 7(1), pages 1-13, December.
    18. Raphael Warren Jankeeparsad & Dev Tewari, 2018. "End-User Adoption of Bitcoin in South Africa," Journal of Economics and Behavioral Studies, AMH International, vol. 10(5), pages 230-243.
    19. Amit Shankar & Biplab Datta, 2018. "Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective," Global Business Review, International Management Institute, vol. 19(3_suppl), pages 72-89, June.
    20. Md. Alamgir Hossain & Ruhul Amin & Abdullah Al Masud & Md. Imran Hossain & Mohammad Awal Hossen & Mohammad Kamal Hossain, 2023. "What Drives People’s Behavioral Intention Toward Telemedicine? An Emerging Economy Perspective," SAGE Open, , vol. 13(3), pages 21582440231, July.

    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:gam:jijerp:v:18:y:2021:i:17:p:9366-:d:629331. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.