IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v116y2020icp68-74.html
   My bibliography  Save this article

Robot will take your job: Innovation for an era of artificial intelligence

Author

Listed:
  • Rampersad, Giselle

Abstract

Fear is growing that robots and artificial intelligence will replace many occupations. To remain relevant in this changing career landscape, the worker of the future is expected to be innovative, able to spot opportunities transform industries and provide creative solutions to meet global challenges. To develop such capabilities, work integrated learning (WIL) has emerged as an important approach. The purpose of this study is to investigate the key factors driving innovation among WIL students. Unlike prior studies that have been predominantly qualitative or based on one single snapshot, this quantitative, longitudinal study measures student capabilities before and after participation in a WIL placement at a business. It then undertakes confirmatory factor analysis to compare pre- and post-placement capabilities. The study found that critical thinking, problem solving, communication and teamwork have significant impacts on the development of innovation: vital in the era of artificial intelligence.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jbrese:v:116:y:2020:i:c:p:68-74
    DOI: 10.1016/j.jbusres.2020.05.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296320303118
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2020.05.019?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Montag-Smit, Tamara & Maertz, Carl P., 2017. "Searching outside the box in creative problem solving: The role of creative thinking skills and domain knowledge," Journal of Business Research, Elsevier, vol. 81(C), pages 1-10.
    2. Xie, Xuemei & Wang, Hongwei, 2020. "How can open innovation ecosystem modes push product innovation forward? An fsQCA analysis," Journal of Business Research, Elsevier, vol. 108(C), pages 29-41.
    3. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    4. Giselle Rampersad, 2014. "Perceptions of Creativity in University–Industry Partnerships: A Pedagogical Approach," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1-22.
    5. Castaño, María Soledad & Méndez, María Teresa & Galindo, Miguel Ángel, 2016. "The effect of public policies on entrepreneurial activity and economic growth," Journal of Business Research, Elsevier, vol. 69(11), pages 5280-5285.
    6. Lazzeretti, Luciana & Capone, Francesco, 2016. "How proximity matters in innovation networks dynamics along the cluster evolution. A study of the high technology applied to cultural goods," Journal of Business Research, Elsevier, vol. 69(12), pages 5855-5865.
    7. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    8. Jenson, Ian & Leith, Peat & Doyle, Richard & West, Jonathan & Miles, Morgan P., 2016. "Innovation system problems: Causal configurations of innovation failure," Journal of Business Research, Elsevier, vol. 69(11), pages 5408-5412.
    9. Nitika Garg, 2019. "Misery wants control: The roles of helplessness and choice in the sadness–consumption relationship," Australian Journal of Management, Australian School of Business, vol. 44(3), pages 407-424, August.
    10. Sousa, Maria José & Rocha, Álvaro, 2019. "Skills for disruptive digital business," Journal of Business Research, Elsevier, vol. 94(C), pages 257-263.
    11. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    12. Jenson, Ian & Leith, Peat & Doyle, Richard & West, Jonathan & Miles, Morgan P., 2016. "The root cause of innovation system problems: Formative measures and causal configurations," Journal of Business Research, Elsevier, vol. 69(11), pages 5292-5298.
    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. Francesco Badia & Fabio Donato, 2022. "Opportunities and risks in using big data to support management control systems: A multiple case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(3), pages 39-63.
    2. Sun, Pengfei & Yuan, Chunhui & Li, Xiaolong & Di, Jia, 2024. "Big data analytics, firm risk and corporate policies: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
    3. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    4. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2025. "Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems," Journal of Intelligent Manufacturing, Springer, vol. 36(1), pages 61-93, January.
    5. Sidney Anderson, 2024. "Expanding data literacy to include data preparation: building a sound marketing analytics foundation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 227-234, June.
    6. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    7. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    8. Sabeen Hussain Bhatti & Wan Mohd Hirwani Wan Hussain & Jabran Khan & Shahbaz Sultan & Alberto Ferraris, 2024. "Exploring data-driven innovation: What’s missing in the relationship between big data analytics capabilities and supply chain innovation?," Annals of Operations Research, Springer, vol. 333(2), pages 799-824, February.
    9. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
    10. Baogui Xin & Yue Liu & Lei Xie, 2024. "Data capital investment strategy in competing supply chains," Annals of Operations Research, Springer, vol. 336(3), pages 1707-1740, May.
    11. Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Traditional Marketing Analytics, Big Data Analytics, Big Data System Quality and the Success of New Product Development," OSF Preprints 9auec, Center for Open Science.
    12. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    13. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    14. 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.
    15. Karabag, Solmaz Filiz, 2019. "Factors impacting firm failure and technological development: A study of three emerging-economy firms," Journal of Business Research, Elsevier, vol. 98(C), pages 462-474.
    16. Tino T. Herden & Steffen Bunzel, 2018. "Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study," Logistics, MDPI, vol. 2(2), pages 1-20, May.
    17. 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).
    18. Erkan Bayraktar & Ekrem Tatoglu & Arafat Salih Aydiner & Dursun Delen, 2024. "Business Analytics Adoption and Technological Intensity: An Efficiency Analysis," Information Systems Frontiers, Springer, vol. 26(4), pages 1509-1526, August.
    19. Rajesh Chidananda Reddy & Biplab Bhattacharjee & Debasisha Mishra & Anandadeep Mandal, 2022. "A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy," Information Systems and e-Business Management, Springer, vol. 20(1), pages 223-255, March.
    20. Ashrafi, Amir & Zareravasan, Ahad, 2022. "An ambidextrous approach on the business analytics-competitive advantage relationship: Exploring the moderating role of business analytics strategy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:eee:jbrese:v:116:y:2020:i:c:p:68-74. 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.