IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxxvy2022i2p509-529.html
   My bibliography  Save this article

The Manager as an Organisation Agent during the Fourth Industrial Revolution

Author

Listed:
  • Anna Rogozinska-Pawelczyk

Abstract

Purpose: This paper, which was inspired by challenges faced by organisations transforming towards the Fourth Industrial Revolution (FIR), explores the role of managers as organisation agents in this process. Design/Methodology/Approach: A qualitative method and an interpretative paradigm are used to analyse the outcomes of semi-structured individual in-depth interviews conducted with a purposively assembled sample of 12 managers. Findings: The analysis determined three main thematic threads describing the roles and attributes that the FIR requires of managers. The first thematic thread concerned the impact of the FIR on the functioning of organisations and their employees. The following roles were further identified: talent manager, development initiator, change visionary, and transparent leader. With regard to attributes, strategic thinking, flexibility, and responsiveness to change, creativity and innovation, an ability to cooperate and inspiringly motivate employees, agility in seizing opportunities created by the FIR and an ability to cope with its challenges were indicated as essential. Originality/Value: Based on the study’s findings, a preliminary model of the FIR as the driver of new roles for managers-agents is proposed. The paper makes an important theoretical and practical contribution to the understanding of the essential role of managers-agents during the FIR. It has been prepared in response to the paucity of studies on this subject. The findings of the study are hoped to help managers to better understand their role during the FIR and to adjust to it.

Suggested Citation

  • Anna Rogozinska-Pawelczyk, 2022. "The Manager as an Organisation Agent during the Fourth Industrial Revolution," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 509-529.
    • Handle: RePEc:ers:journl:v:xxv:y:2022:i:2:p:509-529
    as

    Download full text from publisher

    File URL: https://ersj.eu/journal/2970/download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mojtaba Vaismoradi & Hannele Turunen & Terese Bondas, 2013. "Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study," Nursing & Health Sciences, John Wiley & Sons, vol. 15(3), pages 398-405, September.
    2. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    3. Coyle-Shapiro, Jacqueline A-M. & Shore, Lynn M, 2007. "The employee-organization relationship: where do we go from here?," LSE Research Online Documents on Economics 4887, London School of Economics and Political Science, LSE Library.
    4. McIver, Derrick & Lengnick-Hall, Mark L. & Lengnick-Hall, Cynthia A., 2018. "A strategic approach to workforce analytics: Integrating science and agility," Business Horizons, Elsevier, vol. 61(3), pages 397-407.
    5. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    6. Marco Ardolino & Mario Rapaccini & Nicola Saccani & Paolo Gaiardelli & Giovanni Crespi & Carlo Ruggeri, 2018. "The role of digital technologies for the service transformation of industrial companies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2116-2132, March.
    7. Min Xu & Jeanne M. David & Suk Hi Kim, 2018. "The Fourth Industrial Revolution: Opportunities and Challenges," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(2), pages 90-95, April.
    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. Klaus Jaffe, 2015. "Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus," Papers 1509.04264, arXiv.org, revised Nov 2015.
    2. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    4. Zhang, Hui & Cao, Libin & Zhang, Bing, 2017. "Emissions trading and technology adoption: An adaptive agent-based analysis of thermal power plants in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 23-32.
    5. Liu, Beibei & He, Pan & Zhang, Bing & Bi, Jun, 2012. "Impacts of alternative allowance allocation methods under a cap-and-trade program in power sector," Energy Policy, Elsevier, vol. 47(C), pages 405-415.
    6. Qingxu Huang & Dawn C Parker & Tatiana Filatova & Shipeng Sun, 2014. "A Review of Urban Residential Choice Models Using Agent-Based Modeling," Environment and Planning B, , vol. 41(4), pages 661-689, August.
    7. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    8. Richard Holt & J. Barkley Rosser & David Colander, 2011. "The Complexity Era in Economics," Review of Political Economy, Taylor & Francis Journals, vol. 23(3), pages 357-369.
    9. Fenintsoa Andriamasinoro & Raphael Danino-Perraud, 2021. "Use of artificial intelligence to assess mineral substance criticality in the French market: the example of cobalt," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(1), pages 19-37, April.
    10. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    11. Доможиров Д. А. & Ибрагимов Н. М. & Мельникова Л. В. & Цыплаков А. А., 2017. "Интеграция подхода «затраты – выпуск» в агент-ориентированное моделирование. Часть 1. Методологические основы. Integration of input–output approach into agent-based modeling. Part 1. Methodological pr," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(1), pages 86-99.
    12. repec:zbw:iamodp:109915 is not listed on IDEAS
    13. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Wei Cui & Anthony Brabazon & Michael O'Neill, 2011. "Dynamic trade execution: a grammatical evolution approach," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 2(1/2), pages 4-31.
    15. Gräbner, Claudius, 2016. "From realism to instrumentalism - and back? Methodological implications of changes in the epistemology of economics," MPRA Paper 71933, University Library of Munich, Germany.
    16. Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
    17. Emanuele Ciola & Edoardo Gaffeo & Mauro Gallegati, 2021. "Search for Profits and Business Fluctuations: How Banks' Behaviour Explain Cycles?," Working Papers 450, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    18. Oeffner, Marc, 2008. "Agent–Based Keynesian Macroeconomics - An Evolutionary Model Embedded in an Agent–Based Computer Simulation," MPRA Paper 18199, University Library of Munich, Germany, revised Oct 2009.
    19. Paul De Grauwe, 2012. "Booms and busts: New Keynesian and behavioural explanations," Chapters, in: Robert M. Solow & Jean-Philippe Touffut (ed.), What’s Right with Macroeconomics?, chapter 6, pages 149-180, Edward Elgar Publishing.
    20. repec:spo:wpecon:info:hdl:2441/53r60a8s3kup1vc9l5643ehjk is not listed on IDEAS
    21. de Koning, Koen & Filatova, Tatiana & Bin, Okmyung, 2017. "Bridging the Gap Between Revealed and Stated Preferences in Flood-prone Housing Markets," Ecological Economics, Elsevier, vol. 136(C), pages 1-13.
    22. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).

    More about this item

    Keywords

    Fourth industrial revolution; organizational behaviour; manager as an organisation agent; managers’ roles and attributes.;
    All these keywords.

    JEL classification:

    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    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:ers:journl:v:xxv:y:2022:i:2:p:509-529. 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: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    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.