IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v144y2022icp31-49.html
   My bibliography  Save this article

AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework

Author

Listed:
  • Chowdhury, Soumyadeb
  • Budhwar, Pawan
  • Dey, Prasanta Kumar
  • Joel-Edgar, Sian
  • Abadie, Amelie

Abstract

The extant literature has outlined the significance of collaborative intelligence stemming from effective partnership between artificial intelligence (AI) systems and human workers to achieve organisationally valued outcomes. However, there is paucity of research insights on the factors influencing AI-human partnership and its impact on business performance. To bridge this knowledge gap, this paper draws on the knowledge-based view, (KBV) socio-technical systems (STS) and organisational socialisation framework (OSF) to develop and validate a novel theoretical model examining the relationships between knowledge sharing, employees’ AI skills, trust, and role clarity in a collaborative working environment to enhance business performance. A primary survey-based research method was used to capture responses from 164 employees in the UK creative industries, and further analysed by employing Structural Equation Modelling technique. Our findings will provide managers and the AI community with primary evidence and strategies that will help to develop collaborative intelligence capabilities within the organisations.

Suggested Citation

  • Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    • Handle: RePEc:eee:jbrese:v:144:y:2022:i:c:p:31-49
    DOI: 10.1016/j.jbusres.2022.01.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296322000819
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2022.01.069?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mikalef, Patrick & Pateli, Adamantia, 2017. "Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA," Journal of Business Research, Elsevier, vol. 70(C), pages 1-16.
    2. Horváth, Dóra & Szabó, Roland Zs., 2019. "Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities?," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 119-132.
    3. Kaplan, Andreas & Haenlein, Michael, 2020. "Rulers of the world, unite! The challenges and opportunities of artificial intelligence," Business Horizons, Elsevier, vol. 63(1), pages 37-50.
    4. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    5. Lin, Hsing-Er & Hsu, I-Chieh & Hsu, Audrey Wenhsin & Chung, Hsi-Mei, 2020. "Creating competitive advantages: Interactions between ambidextrous diversification strategy and contextual factors from a dynamic capability perspective," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    6. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    7. Fosso Wamba, Samuel & Queiroz, Maciel M. & Trinchera, Laura, 2020. "Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 229(C).
    8. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    9. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    10. Jan Jöhnk & Malte Weißert & Katrin Wyrtki, 2021. "Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 5-20, February.
    11. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    12. Prasanta Kumar Dey & Chrisovaladis Malesios & Debashree De & Pawan Budhwar & Soumyadeb Chowdhury & Walid Cheffi, 2020. "Circular economy to enhance sustainability of small and medium‐sized enterprises," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2145-2169, September.
    13. Ferreira, Jorge & Coelho, Arnaldo & Moutinho, Luiz, 2020. "Dynamic capabilities, creativity and innovation capability and their impact on competitive advantage and firm performance: The moderating role of entrepreneurial orientation," Technovation, Elsevier, vol. 92.
    14. Shah, Naimatullah & Irani, Zahir & Sharif, Amir M., 2017. "Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors," Journal of Business Research, Elsevier, vol. 70(C), pages 366-378.
    15. Brougham, David & Haar, Jarrod, 2018. "Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace," Journal of Management & Organization, Cambridge University Press, vol. 24(2), pages 239-257, March.
    16. Desouza, Kevin & Evaristo, Roberto, 2003. "Global Knowledge Management Strategies," European Management Journal, Elsevier, vol. 21(1), pages 62-67, February.
    17. Hirokazu Shirado & Nicholas A. Christakis, 2017. "Locally noisy autonomous agents improve global human coordination in network experiments," Nature, Nature, vol. 545(7654), pages 370-374, May.
    18. Lai-Wan Wong & Garry Wei-Han Tan & Voon-Hsien Lee & Keng-Boon Ooi & Amrik Sohal, 2020. "Unearthing the determinants of Blockchain adoption in supply chain management," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2100-2123, April.
    19. Ruta Dadeliene & Stanislav Dadelo & Natalija Pozniak & Leonidas Sakalauskas, 2020. "Analysis of top kayakers’ training-intensity distribution and physiological adaptation based on structural modelling," Annals of Operations Research, Springer, vol. 289(2), pages 195-210, June.
    20. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).
    21. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    22. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    23. Upadhyay, Parijat & Kumar, Anup, 2020. "The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance," International Journal of Information Management, Elsevier, vol. 52(C).
    24. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    25. Ciechanowski, Leon & Jemielniak, Dariusz & Gloor, Peter A., 2020. "TUTORIAL: AI research without coding: The art of fighting without fighting: Data science for qualitative researchers," Journal of Business Research, Elsevier, vol. 117(C), pages 322-330.
    26. Bag, Surajit & Pretorius, Jan Ham Christiaan & Gupta, Shivam & Dwivedi, Yogesh K., 2021. "Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    27. Chowdhury, Md Maruf H. & Quaddus, Mohammed, 2017. "Supply chain resilience: Conceptualization and scale development using dynamic capability theory," International Journal of Production Economics, Elsevier, vol. 188(C), pages 185-204.
    28. Bernadette Szajna, 1996. "Empirical Evaluation of the Revised Technology Acceptance Model," Management Science, INFORMS, vol. 42(1), pages 85-92, January.
    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. Sergi, Bruno S. & Ključnikov, Aleksandr & Popkova, Elena G. & Bogoviz, Aleksei V. & Lobova, Svetlana V., 2022. "Creative abilities and digital competencies to transitioning to Business 4.0," Journal of Business Research, Elsevier, vol. 153(C), pages 401-411.
    2. Zhao, Jingyou & Hu, Enhua & Han, Mingyan & Jiang, Keshen & Shan, Hongmei, 2023. "That honey, my arsenic: The influence of advanced technologies on service employees’ organizational deviance," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    3. Chen, Pengyu & Chu, Zhongzhu & Zhao, Miao, 2024. "The Road to corporate sustainability: The importance of artificial intelligence," Technology in Society, Elsevier, vol. 76(C).
    4. Yu, Yubing & Xu, Jiawei & Zhang, Justin Z. & Liu, Yulong (David) & Kamal, Muhammad Mustafa & Cao, Yanhong, 2024. "Unleashing the power of AI in manufacturing: Enhancing resilience and performance through cognitive insights, process automation, and cognitive engagement," International Journal of Production Economics, Elsevier, vol. 270(C).
    5. Muhammad Zafar Yaqub & Abdullah Alsabban, 2023. "Industry-4.0-Enabled Digital Transformation: Prospects, Instruments, Challenges, and Implications for Business Strategies," Sustainability, MDPI, vol. 15(11), pages 1-33, May.
    6. Maggie Wang, Yazhu & Matook, Sabine & Dennis, Alan R., 2024. "Unintended consequences of humanoid service robots: A case study of public service organizations," Journal of Business Research, Elsevier, vol. 174(C).
    7. Chakraborty, Debarun & Polisetty, Aruna & G, Sowmya & Rana, Nripendra P. & Khorana, Sangeeta, 2024. "Unlocking the potential of AI: Enhancing consumer engagement in the beauty and cosmetic product purchases," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    8. Ion Popa & Marian Mihai Cioc & Andreea Breazu & Catalina Florentina Popa, 2024. "Identifying Sufficient and Necessary Competencies in the Effective Use of Artificial Intelligence Technologies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 1-33, February.
    9. Haefner, Naomi & Parida, Vinit & Gassmann, Oliver & Wincent, Joakim, 2023. "Implementing and scaling artificial intelligence: A review, framework, and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    10. Pattanayak, Sirsha & Ramkumar, M. & Goswami, Mohit & Rana, Nripendra P., 2024. "Blockchain technology and supply chain performance: The role of trust and relational capabilities," International Journal of Production Economics, Elsevier, vol. 271(C).
    11. Lea Kocjancic & Sergej Gricar, 2023. "Usage of AI in Sustainable Knowledge Management and Innovation Processes; Data Analytics in the Electricity Sector," FinTech, MDPI, vol. 2(4), pages 1-19, November.
    12. Xin Zhang & Felix Nutakor & Michael Kaku Minlah & Jinke Li, 2023. "Can Digital Transformation Drive Green Transformation in Manufacturing Companies?—Based on Socio-Technical Systems Theory Perspective," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    13. Yang, Fucheng & Luo, Chunyang & Pan, Lu, 2024. "Do digitalization and intellectual capital drive sustainable open innovation of natural resources sector? Evidence from China," Resources Policy, Elsevier, vol. 88(C).
    14. Berman, Alexander & de Fine Licht, Karl & Carlsson, Vanja, 2024. "Trustworthy AI in the public sector: An empirical analysis of a Swedish labor market decision-support system," Technology in Society, Elsevier, vol. 76(C).
    15. Duarte Alonso, Abel & Vu, Oanh Thi Kim & Nguyen, Trung Q. & McClelland, Robert & Nguyen, Ngan M. & Huynh, Hoa Thi Ngoc & Tran, Thanh Duc, 2024. "Industry 4.0 involvement and knowledge management across industries: A qualitative investigation from an emerging economy," Journal of Business Research, Elsevier, vol. 174(C).

    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. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    2. Haenlein, Michael & Kaplan, Andreas, 2021. "Artificial intelligence and robotics: Shaking up the business world and society at large," Journal of Business Research, Elsevier, vol. 124(C), pages 405-407.
    3. David Mortimore, 2024. "Moving beyond human-centric organizational designs," Journal of Organization Design, Springer;Organizational Design Community, vol. 13(2), pages 65-75, June.
    4. Soumyadeb Chowdhury & Oscar Rodriguez-Espindola & Prasanta Dey & Pawan Budhwar, 2023. "Blockchain technology adoption for managing risks in operations and supply chain management: evidence from the UK," Annals of Operations Research, Springer, vol. 327(1), pages 539-574, August.
    5. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    6. Kirti Nayal & Rakesh D. Raut & Balkrishna E. Narkhede & Pragati Priyadarshinee & Gajanan B. Panchal & Vidyadhar V. Gedam, 2023. "Antecedents for blockchain technology-enabled sustainable agriculture supply chain," Annals of Operations Research, Springer, vol. 327(1), pages 293-337, August.
    7. Chaudhuri, Atanu & Subramanian, Nachiappan & Dora, Manoj, 2022. "Circular economy and digital capabilities of SMEs for providing value to customers: Combined resource-based view and ambidexterity perspective," Journal of Business Research, Elsevier, vol. 142(C), pages 32-44.
    8. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    9. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    10. Samuel Ogbeibu & Charbel Jose Chiappetta Jabbour & James Gaskin & Abdelhak Senadjki & Mathew Hughes, 2021. "Leveraging STARA competencies and green creativity to boost green organisational innovative evidence: A praxis for sustainable development," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2421-2440, July.
    11. Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Rodríguez-Espíndola, Oscar & Parkes, Geoff & Tuyet, Nguyen Thi Anh & Long, Dang Duc & Ha, Tran Phuong, 2022. "Impact of Organisational Factors on the Circular Economy Practices and Sustainable Performance of Small and Medium-sized Enterprises in Vietnam," Journal of Business Research, Elsevier, vol. 147(C), pages 362-378.
    12. Athota, Vidya S. & Pereira, Vijay & Hasan, Zahid & Vaz, Daicy & Laker, Benjamin & Reppas, Dimitrios, 2023. "Overcoming financial planners’ cognitive biases through digitalization: A qualitative study," Journal of Business Research, Elsevier, vol. 154(C).
    13. Abadie, Amelie & Roux, Mélanie & Chowdhury, Soumyadeb & Dey, Prasanta, 2023. "Interlinking organisational resources, AI adoption and omnichannel integration quality in Ghana’s healthcare supply chain," Journal of Business Research, Elsevier, vol. 162(C).
    14. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," Sustainability Nexus Forum, Springer, vol. 29(3), pages 217-230, December.
    15. Wang, Lei & Zhou, Yahong & Chiao, Benjamin, 2023. "Robots and firm innovation: Evidence from Chinese manufacturing," Journal of Business Research, Elsevier, vol. 162(C).
    16. Shin-Cheng Yeh & Ai-Wei Wu & Hui-Ching Yu & Homer C. Wu & Yi-Ping Kuo & Pei-Xuan Chen, 2021. "Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-34, August.
    17. Zhao, Nanyang & Hong, Jiangtao & Lau, Kwok Hung, 2023. "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International Journal of Production Economics, Elsevier, vol. 259(C).
    18. Wong, David T.W. & Ngai, Eric W.T., 2023. "The impact of advanced manufacturing technology, sensing and analytics capabilities, and planning comprehensiveness on sustained competitive advantage: The moderating role of environmental uncertainty," International Journal of Production Economics, Elsevier, vol. 265(C).
    19. Justy, Théo & Pellegrin-Boucher, Estelle & Lescop, Denis & Granata, Julien & Gupta, Shivam, 2023. "On the edge of Big Data: Drivers and barriers to data analytics adoption in SMEs," Technovation, Elsevier, vol. 127(C).
    20. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(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:eee:jbrese:v:144:y:2022:i:c:p:31-49. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.