IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i7p1942-d528443.html
   My bibliography  Save this article

Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland

Author

Listed:
  • Justyna Łapińska

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Iwona Escher

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Joanna Górka

    (Department of Econometrics and Statistics, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Agata Sudolska

    (Department of Enterprise Management, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Paweł Brzustewicz

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

Abstract

The use of artificial intelligence (AI) in companies is advancing rapidly. Consequently, multidisciplinary research on AI in business has developed dramatically during the last decade, moving from the focus on technological objectives towards an interest in human users’ perspective. In this article, we investigate the notion of employees’ trust in AI at the workplace (in the company), following a human-centered approach that considers AI integration in business from the employees’ perspective, taking into account the elements that facilitate human trust in AI. While employees’ trust in AI at the workplace seems critical, so far, few studies have systematically investigated its determinants. Therefore, this study is an attempt to fill the existing research gap. The research objective of the article is to examine links between employees’ trust in AI in the company and three other latent variables (general trust in technology, intra-organizational trust, and individual competence trust). A quantitative study conducted on a sample of 428 employees from companies of the energy and chemical industries in Poland allowed the hypotheses to be verified. The hypotheses were tested using structural equation modeling (SEM). The results indicate the existence of a positive relationship between general trust in technology and employees’ trust in AI in the company as well as between intra-organizational trust and employees’ trust in AI in the company in the surveyed firms.

Suggested Citation

  • Justyna Łapińska & Iwona Escher & Joanna Górka & Agata Sudolska & Paweł Brzustewicz, 2021. "Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland," Energies, MDPI, vol. 14(7), pages 1-20, April.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1942-:d:528443
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/7/1942/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/7/1942/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rajendra Akerkar, 2019. "Artificial Intelligence for Business," SpringerBriefs in Business, Springer, number 978-3-319-97436-1, October.
    2. Thibaut Th'eate & S'ebastien Mathieu & Damien Ernst, 2020. "An Artificial Intelligence Solution for Electricity Procurement in Forward Markets," Papers 2006.05784, arXiv.org, revised Dec 2020.
    3. Elzbieta Janton-Drozdowska & Maria Majewska, 2015. "Social capital as a key driver of productivity growth of the economy: across-countries comparison," Working Papers 132/2015, Institute of Economic Research, revised May 2015.
    4. Aleksander Jakimowicz & Daniel Rzeczkowski, 2019. "Do barriers to innovation impact changes in innovation activities of firms during business cycle? The effect of the Polish green island," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(4), pages 631-676, December.
    5. Dasheng Lee & Fu-Po Tsai, 2020. "Air Conditioning Energy Saving from Cloud-Based Artificial Intelligence: Case Study of a Split-Type Air Conditioner," Energies, MDPI, vol. 13(8), pages 1-25, April.
    6. Kraus, Mathias & Feuerriegel, Stefan & Oztekin, Asil, 2020. "Deep learning in business analytics and operations research: Models, applications and managerial implications," European Journal of Operational Research, Elsevier, vol. 281(3), pages 628-641.
    7. Thibaut Théate & Sébastien Mathieu & Damien Ernst, 2020. "An Artificial Intelligence Solution for Electricity Procurement in Forward Markets," Energies, MDPI, vol. 13(23), pages 1-17, December.
    8. Miltiadis D. Lytras & Anna Visvizi, 2021. "Artificial Intelligence and Cognitive Computing: Methods, Technologies, Systems, Applications and Policy Making," Sustainability, MDPI, vol. 13(7), pages 1-3, March.
    9. Maranda McBride & Lemuria Carter & Celestine Ntuen, 2012. "The impact of personality on nurses' bias towards automated decision aid acceptance," International Journal of Information Systems and Change Management, Inderscience Enterprises Ltd, vol. 6(2), pages 132-146.
    10. Elzbieta Roszko-Wojtowicz & Maria M. Grzelak & Iwona Laskowska, 2019. "The impact of research and development activity on the TFP level in manufacturing in Poland," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(4), pages 711-737, December.
    11. Jaromir Vrbka & Elvira Nica & Ivana Podhorska, 2019. "The application of Kohonen networks for identification of leaders in the trade sector in Czechia," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(4), pages 739-761, December.
    12. Arkadiusz Kijek & Anna Matras-Bolibok, 2020. "Technological convergence across European regions," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 15(2), pages 295-313, June.
    13. Yevhen Krykavskyy & Olena Pokhylchenko & Nataliya Hayvanovych, 2019. "Supply chain development drivers in industry 4.0 in Ukrainian enterprises," Oeconomia Copernicana, Institute of Economic Research, vol. 10(2), pages 273-290, June.
    14. Fotis Kitsios & Maria Kamariotou, 2021. "Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    15. Rizwan Raheem Ahmed & Giedrius Romeika & Raimonda Kauliene & Justas Streimikis & Rimantas Dapkus, 2020. "ES-QUAL model and customer satisfaction in online banking: evidence from multivariate analysis techniques," Oeconomia Copernicana, Institute of Economic Research, vol. 11(1), pages 59-93, March.
    16. Kwok Tai Chui & Miltiadis D. Lytras & Anna Visvizi, 2018. "Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption," Energies, MDPI, vol. 11(11), pages 1-20, October.
    17. Zeki Murat Çınar & Abubakar Abdussalam Nuhu & Qasim Zeeshan & Orhan Korhan & Mohammed Asmael & Babak Safaei, 2020. "Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0," Sustainability, MDPI, vol. 12(19), pages 1-42, October.
    18. Kurt T. Dirks & Donald L. Ferrin, 2001. "The Role of Trust in Organizational Settings," Organization Science, INFORMS, vol. 12(4), pages 450-467, August.
    19. Irina Kolupaieva & Svitlana Pustovhar & Oleg Suprun & Olena Shevchenko, 2019. "Diagnostics of systemic risk impact on the enterprise capacity for financial risk neutralization: the case of Ukrainian metallurgical enterprises," Oeconomia Copernicana, Institute of Economic Research, vol. 10(3), pages 471-491, September.
    20. Elzbieta Janton-Drozdowska & Maria Majewska, 2015. "Social Capital As A Key Driver Of Productivity Growth Of The Economy: Across-Countries Comparison," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 10(4), pages 61-83, December.
    21. Daniel Z. Levin & Rob Cross, 2004. "The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer," Management Science, INFORMS, vol. 50(11), pages 1477-1490, November.
    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. Kądzielawski Grzegorz, 2023. "The state of development of artificial intelligence in polish industry: opinions of employees," International Journal of Contemporary Management, Sciendo, vol. 59(1), pages 12-25, March.
    2. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.

    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. Agata Sudolska & Justyna Łapińska, 2020. "Exploring Determinants of Innovation Capability in Manufacturing Companies Operating in Poland," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    2. Renzl, Birgit, 2008. "Trust in management and knowledge sharing: The mediating effects of fear and knowledge documentation," Omega, Elsevier, vol. 36(2), pages 206-220, April.
    3. Harvey, Michael & Reiche, B. Sebastian & Moeller, Miriam, 2011. "Developing effective global relationships through staffing with inpatriate managers: The role of interpersonal trust," Journal of International Management, Elsevier, vol. 17(2), pages 150-161, June.
    4. Shoaib Shafique & Iram Naz, 2023. "A Mediating and Moderating Analysis of the Relationship Between Team Emotional Intelligence and Team Performance," SAGE Open, , vol. 13(1), pages 21582440231, February.
    5. Michal Bernard Pietrzak, 2016. "The Problem of the Inclusion of Spatial Dependence Within the TOPSIS Method," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 12(3), pages 69-86.
    6. Levine, Emma E. & Schweitzer, Maurice E., 2015. "Prosocial lies: When deception breeds trust," Organizational Behavior and Human Decision Processes, Elsevier, vol. 126(C), pages 88-106.
    7. Jakub Horak & Tomas Krulicky & Zuzana Rowland & Veronika Machova, 2020. "Creating a Comprehensive Method for the Evaluation of a Company," Sustainability, MDPI, vol. 12(21), pages 1-23, November.
    8. Dariusz Fatula, 2018. "Selected micro- and macroeconomic conditions of wages, income and labor productivity in Poland and other European Union countries," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(1), March.
    9. Adam P. Balcerzak & Michal Bernard Pietrzak, 2016. "Dynamic Panel Analysis of Influence of Quality of Human Capital on Total Factor Productivity in Old European Union Countries," Working Papers 19/2016, Institute of Economic Research, revised May 2016.
    10. Narda R. Quigley & Paul E. Tesluk & Edwin A. Locke & Kathryn M. Bartol, 2007. "A Multilevel Investigation of the Motivational Mechanisms Underlying Knowledge Sharing and Performance," Organization Science, INFORMS, vol. 18(1), pages 71-88, February.
    11. Mateusz Borkowski, 2023. "Social Capital and Economic Development: PLS-SEM Model," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 11-27.
    12. Fatima, Johra Kayeser & Di Mascio, Rita, 2018. "Reversing the dependency-trust relationship in B2C services," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 1-10.
    13. Ebers, Mark & Maurer, Indre, 2014. "Connections count: How relational embeddedness and relational empowerment foster absorptive capacity," Research Policy, Elsevier, vol. 43(2), pages 318-332.
    14. Michal Bernard Pietrzak & Adam P. Balcerzak, 2016. "Quality of Human Capital and Total Factor Productivity in New European Union Members States," Working Papers 23/2016, Institute of Economic Research, revised May 2016.
    15. Magdalena Kludacz-Alessandri & Małgorzata Cygańska, 2021. "Corporate Social Responsibility and Financial Performance among Energy Sector Companies," Energies, MDPI, vol. 14(19), pages 1-16, September.
    16. Kamil Decyk, 2021. "Service Sector Productivity in the European Union Member States," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 185-202.
    17. Nault, Kelly A. & Sezer, Ovul & Klein, Nadav, 2023. "It’s the journey, not just the destination: Conveying interpersonal warmth in written introductions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 177(C).
    18. M. Max Evans & Ilja Frissen & Anthony K. P. Wensley, 2018. "Organisational Information and Knowledge Sharing: Uncovering Mediating Effects of Perceived Trustworthiness Using the PROCESS Approach," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-29, March.
    19. M. Kamil Kozan & Levent Akdeniz, 2014. "Role of Strong versus Weak Networks in Small Business Growth in an Emerging Economy," Administrative Sciences, MDPI, vol. 4(1), pages 1-16, February.
    20. Gareth D. Leeves, 2014. "Increasing returns to education and the impact on social capital," Education Economics, Taylor & Francis Journals, vol. 22(5), pages 449-470, October.

    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:jeners:v:14:y:2021:i:7:p:1942-:d:528443. 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.