IDEAS home Printed from https://ideas.repec.org/a/now/fnttom/0200000100.html

AI and Business Models: The Good, The Bad and The Ugly

Author

Listed:
  • Sena, Vania
  • Nocker, Manuela

Abstract

Over the last five years, several scholars from a range of disciplines have started to analyse how Artificial Intelligence (AI) affects businesses outcomes. This research effort has produced many predictions on the expected impact of automation on labour demand and equilibrium employment. However, most of the expected results are dependent on how businesses change their behaviour due to adopting AI. We argue that, as AI diffuses across the economy, changing behaviour is a necessary outcome for incumbents: the argument is that the diffusion of AI across an industry generates the conditions for a process of value migration from incumbents to new entrants (Helper et al. 2018); in these cases, the only mechanism available to incumbents to offset the negative impact of the migration process is by changing the architecture of their business, i.e., the business model. However, companies can choose from several AI-driven business models; their preference for one model is driven by many industry-level factors such as technical standards, the structure of the technology industry and the presence of an ethical framework for the use of AI. This monologue summarises the existing literature on business model innovation and AI; it then analyses the industry-level factors that may shape the business-level preference for specific business models. Finally, the monologue offers some suggestions for future research in the area.

Suggested Citation

  • Sena, Vania & Nocker, Manuela, 2021. "AI and Business Models: The Good, The Bad and The Ugly," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 14(4), pages 324-397, May.
  • Handle: RePEc:now:fnttom:0200000100
    DOI: 10.1561/0200000100
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1561/0200000100
    Download Restriction: no

    File URL: https://libkey.io/10.1561/0200000100?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
    ---><---

    References listed on IDEAS

    as
    1. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1091-1117.
    2. Christoph Zott & Raphael Amit, 2008. "The fit between product market strategy and business model: implications for firm performance," Strategic Management Journal, Wiley Blackwell, vol. 29(1), pages 1-26, January.
    3. Christoph Zott & Raphael Amit, 2007. "Business Model Design and the Performance of Entrepreneurial Firms," Organization Science, INFORMS, vol. 18(2), pages 181-199, April.
    4. Feng Zhu & Marco Iansiti, 2012. "Entry into platform‐based markets," Strategic Management Journal, Wiley Blackwell, vol. 33(1), pages 88-106, 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. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).

    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. Täuscher, Karl & Laudien, Sven M., 2018. "Understanding platform business models: A mixed methods study of marketplaces," European Management Journal, Elsevier, vol. 36(3), pages 319-329.
    2. Haftor, Darek M. & Costa Climent, Ricardo & Lundström, Jenny Eriksson, 2021. "How machine learning activates data network effects in business models: Theory advancement through an industrial case of promoting ecological sustainability," Journal of Business Research, Elsevier, vol. 131(C), pages 196-205.
    3. Thomas Clauss & Peter Harengel & Marianne Hock, 2019. "The perception of value of platform-based business models in the sharing economy: determining the drivers of user loyalty," Review of Managerial Science, Springer, vol. 13(3), pages 605-634, June.
    4. Shi Yin & Yuanyuan Yu & Nan Zhang, 2024. "The Effect of Digital Green Strategic Orientation On Digital Green Innovation Performance: From the Perspective of Digital Green Business Model Innovation," SAGE Open, , vol. 14(2), pages 21582440241, June.
    5. Linlin Zheng & Yashi Dong & Jineng Chen & Yuyi Li & Wenzhuo Li & Miaolian Su, 2022. "Impact of Crisis on Sustainable Business Model Innovation—The Role of Technology Innovation," Sustainability, MDPI, vol. 14(18), pages 1-28, September.
    6. Cinzia Battistella & Gianluca Murgia & Fabio Nonino, 2021. "Free-driven web-based business models," Electronic Commerce Research, Springer, vol. 21(2), pages 445-486, June.
    7. Meena Madhavan & Mohammed Ali Sharafuddin & Thanapong Chaichana, 2022. "Impact of Business Model Innovation on Sustainable Performance of Processed Marine Food Product SMEs in Thailand—A PLS-SEM Approach," Sustainability, MDPI, vol. 14(15), pages 1-33, August.
    8. Wüstenhagen, Rolf & Menichetti, Emanuela, 2012. "Strategic choices for renewable energy investment: Conceptual framework and opportunities for further research," Energy Policy, Elsevier, vol. 40(C), pages 1-10.
    9. Wissal Affes & Habib Affes, 2022. "Business Model and Firm Performance in Tunisian Firms: a Mediated Moderation Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(4), pages 2822-2839, December.
    10. Chengde Zheng & Xiaofeng Yu & Qiming Jin, 2017. "How user relationships affect user perceived value propositions of enterprises on social commerce platforms," Information Systems Frontiers, Springer, vol. 19(6), pages 1261-1271, December.
    11. Esben Rahbek Gjerdrum Pedersen & Wencke Gwozdz & Kerli Kant Hvass, 2018. "Exploring the Relationship Between Business Model Innovation, Corporate Sustainability, and Organisational Values within the Fashion Industry," Journal of Business Ethics, Springer, vol. 149(2), pages 267-284, May.
    12. Raphaël Maucuer & Alexandre Renaud & Sébastien Ronteau & Laurent Muzellec, 2022. "What can we learn from marketers? A bibliometric analysis of the marketing literature on business model research," Post-Print hal-03718522, HAL.
    13. Breunig, Karl Joachim & Kvålshaugen, Ragnhild & Hydle, Katja Maria, 2014. "Knowing your boundaries: Integration opportunities in international professional service firms," Journal of World Business, Elsevier, vol. 49(4), pages 502-511.
    14. Shuting Chen & Dengke Yu, 2024. "What Drives Business Model Innovation? Exploring the Role of Knowledge Management Capability in Chinese Top-Ranking Innovative Enterprises," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 6390-6424, June.
    15. Xuerong Li & Han Qiao & Shouyang Wang, 2017. "Exploring evolution and emerging trends in business model study: a co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 869-887, May.
    16. Gian Luca Casali & Mirko Perano & Andrea Moretta Tartaglione & Roxanne Zolin, 2018. "How Business Idea Fit Affects Sustainability and Creates Opportunities for Value Co-Creation in Nascent Firms," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
    17. Barneto, Pascal & Ouvrard, Stéphane, 2015. "Is the firm's business model related to segment reporting?," Research in International Business and Finance, Elsevier, vol. 35(C), pages 122-137.
    18. Dehkordi, Rashid & Ahokangas, Petri & Evers, Natasha & Sorvisto, Mika, 2024. "Business model design for Electric Commercial Vehicles (ECVs): An ecosystemic perspective," Energy Policy, Elsevier, vol. 186(C).
    19. Zhang, Yimeng & Ma, Xinyu & Pang, Jianing & Xing, Hailong & Wang, Jian, 2023. "The impact of digital transformation of manufacturing on corporate performance — The mediating effect of business model innovation and the moderating effect of innovation capability," Research in International Business and Finance, Elsevier, vol. 64(C).
    20. Xiu‐e Zhang & Yijing Li & Xinyu Teng, 2025. "How does green entrepreneurial orientation improve enterprises' sustainable performance? Evidence from agricultural sector in China," Business Ethics, the Environment & Responsibility, John Wiley & Sons, Ltd., vol. 34(4), pages 1255-1277, October.

    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:now:fnttom:0200000100. 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: Lucy Wiseman (email available below). General contact details of provider: http://www.nowpublishers.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.