IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v182y2022ics0040162522003523.html
   My bibliography  Save this article

A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management

Author

Listed:
  • Pietronudo, Maria Cristina
  • Croidieu, Grégoire
  • Schiavone, Francesco

Abstract

Given innovation's chaotic nature, organizations struggle to make decisions when managing innovation. Both academics and practitioners hope artificial intelligence can solve this problem and provide a solution to support and rationalize innovation processes. The literature on this topic, however, is fragmented. The goal of this paper is to systematically review the literature to guide future research. We build on the garbage can model, as our findings reveal that the rationalizing influences of AI on innovation management as a decision-making process is varied. Our results reveal four main influences that pave the way for future research: AI augmenting rationality, AI augmenting creativity, AI renewing the organizing of innovation, and AI triggering new challenges. Taken together, these findings suggest AI is not a tool that uniformly optimizes innovation management and decision-making but rather, is best understood as a multifaceted solution, with intended and unintended rationalizing influences, in search of problems to solve.

Suggested Citation

  • Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  • Handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522003523
    DOI: 10.1016/j.techfore.2022.121828
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522003523
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2022.121828?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. 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.
    2. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    3. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    4. 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.
    5. Shahriar Akter & Samuel Fosso Wamba, 2016. "Big data analytics in E-commerce: a systematic review and agenda for future research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 173-194, May.
    6. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    7. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    8. Lynn Wu & Lorin Hitt & Bowen Lou, 2020. "Data Analytics, Innovation, and Firm Productivity," Management Science, INFORMS, vol. 66(5), pages 2017-2039, May.
    9. Fredström, Ashkan & Wincent, Joakim & Sjödin, David & Oghazi, Pejvak & Parida, Vinit, 2021. "Tracking innovation diffusion: AI analysis of large-scale patent data towards an agenda for further research," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    10. Burström, Thommie & Parida, Vinit & Lahti, Tom & Wincent, Joakim, 2021. "AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research," Journal of Business Research, Elsevier, vol. 127(C), pages 85-95.
    11. Alan E. Bayer & John C. Smart & Gerald W. McLaughlin, 1990. "Mapping intellectual structure of a scientific subfield through author cocitations," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 444-452, September.
    12. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    13. Elia, Gianluca & Margherita, Alessandro & Passiante, Giuseppina, 2020. "Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    14. Li, Jing-Ping & Mirza, Nawazish & Rahat, Birjees & Xiong, Deping, 2020. "Machine learning and credit ratings prediction in the age of fourth industrial revolution," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    15. Bandaru, Sunith & Aslam, Tehseen & Ng, Amos H.C. & Deb, Kalyanmoy, 2015. "Generalized higher-level automated innovization with application to inventory management," European Journal of Operational Research, Elsevier, vol. 243(2), pages 480-496.
    16. Xu, Jianguo & Guo, Lixiang & Jiang, Jiang & Ge, Bingfeng & Li, Mengjun, 2019. "A deep learning methodology for automatic extraction and discovery of technical intelligence," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 339-351.
    17. Giada Di Stefano & Margaret Peteraf & Gianmario Verona, 2010. "Dynamic Capabilities Deconstructed. A bibliographic investigation into the origins, development, and future directions of the research domain," Post-Print hal-00668737, HAL.
    18. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    19. Katherine W. McCain, 1990. "Mapping authors in intellectual space: A technical overview," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 433-443, September.
    20. Piotr Tomasz Makowski & Yuya Kajikawa, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Papers 2103.02395, arXiv.org.
    21. Christian Fisch & Joern Block, 2018. "Six tips for your (systematic) literature review in business and management research," Management Review Quarterly, Springer, vol. 68(2), pages 103-106, April.
    22. Raghu Garud & Joel Gehman & Thinley Tharchen, 2018. "Performativity as ongoing journeys : Implications for strategy, entrepreneurship, and innovation," Post-Print hal-02312375, HAL.
    23. Katherine W. McCain, 1986. "Cocited author mapping as a valid representation of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 37(3), pages 111-122, May.
    24. Giuditta De Prato & Montserrat Lopez Cobo & Sofia Samoili & Riccardo Righi & Miguel Vazquez Prada Baillet & Melisande Cardona, 2019. "The AI Techno-Economic Segment Analysis," JRC Research Reports JRC118071, Joint Research Centre.
    25. Katharina Blöcher & Rainer Alt, 2021. "AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 529-551, September.
    26. Ming-Hui Huang & Roland T. Rust, 2021. "A strategic framework for artificial intelligence in marketing," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 30-50, January.
    27. Giada Di Stefano & Margaret Peteraf & Gianmario Verona, 2010. "Dynamic capabilities deconstructed -super-‡ : a bibliographic investigation into the origins, development, and future directions of the research domain," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(4), pages 1187-1204, August.
    28. E.C.M. Noyons & H.F. Moed & M. Luwel, 1999. "Combining mapping and citation analysis for evaluative bibliometric purposes: A bibliometric study," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(2), pages 115-131.
    29. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    30. Jin, Byoungho Ellie & Shin, Daeun Chloe, 2020. "Changing the game to compete: Innovations in the fashion retail industry from the disruptive business model," Business Horizons, Elsevier, vol. 63(3), pages 301-311.
    31. Kenneth Arrow, 1962. "Economic Welfare and the Allocation of Resources for Invention," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 609-626, National Bureau of Economic Research, Inc.
    32. Kakatkar, Chinmay & Bilgram, Volker & Füller, Johann, 2020. "Innovation analytics: Leveraging artificial intelligence in the innovation process," Business Horizons, Elsevier, vol. 63(2), pages 171-181.
    33. Raphaël Maucuer & Alexandre Renaud, 2019. "Business Model Research: A Bibliometric Analysis of Origins and Trends," Post-Print hal-01918188, HAL.
    34. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    35. Naomi Haefner & Philipp Morf, 2021. "AI for Decision-Making in Connected Business," Springer Books, in: Oliver Gassmann & Fabrizio Ferrandina (ed.), Connected Business, pages 215-231, Springer.
    36. Lynn Wu & Bowen Lou & Lorin Hitt, 2019. "Data Analytics Supports Decentralized Innovation," Management Science, INFORMS, vol. 65(10), pages 4863-4877, October.
    37. Sascha Kraus & Matthias Breier & Sonia Dasí-Rodríguez, 2020. "The art of crafting a systematic literature review in entrepreneurship research," International Entrepreneurship and Management Journal, Springer, vol. 16(3), pages 1023-1042, September.
    38. José M. Merigó & Christian A. Cancino & Freddy Coronado & David Urbano, 2016. "Academic research in innovation: a country analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 559-593, August.
    39. Yu-Ting Cheng & Andrew H. Van de Ven, 1996. "Learning the Innovation Journey: Order out of Chaos?," Organization Science, INFORMS, vol. 7(6), pages 593-614, December.
    40. Sarin, Shikhar & Haon, Christophe & Belkhouja, Mustapha & Mas-Tur, Alicia & Roig-Tierno, Norat & Sego, Trina & Porter, Alan & Merigó, José M. & Carley, Stephen, 2020. "Uncovering the knowledge flows and intellectual structures of research in Technological Forecasting and Social Change: A journey through history," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    41. Wright, Scott A. & Schultz, Ainslie E., 2018. "The rising tide of artificial intelligence and business automation: Developing an ethical framework," Business Horizons, Elsevier, vol. 61(6), pages 823-832.
    42. Ganter, Alois & Hecker, Achim, 2013. "Deciphering antecedents of organizational innovation," Journal of Business Research, Elsevier, vol. 66(5), pages 575-584.
    43. Lee, Changhun & Lim, Chiehyeon, 2021. "From technological development to social advance: A review of Industry 4.0 through machine learning," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    44. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    45. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    46. Maghrabie, Hesham F. & Beauregard, Yvan & Schiffauerova, Andrea, 2019. "Grey-based Multi-Criteria Decision Analysis approach: Addressing uncertainty at complex decision problems," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 366-379.
    47. Lee, In & Shin, Yong Jae, 2020. "Machine learning for enterprises: Applications, algorithm selection, and challenges," Business Horizons, Elsevier, vol. 63(2), pages 157-170.
    48. Peter W Glynn & Henrich R Greve & Hayagreeva Rao, 2020. "Relining the garbage can of organizational decision-making: modeling the arrival of problems and solutions as queues," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(1), pages 125-142.
    49. Elliot Noma, 1984. "Co‐citation analysis and the invisible college," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 35(1), pages 29-33, January.
    50. Greg Fisher, 2012. "Effectuation, Causation, and Bricolage: A Behavioral Comparison of Emerging Theories in Entrepreneurship Research," Entrepreneurship Theory and Practice, , vol. 36(5), pages 1019-1051, September.
    51. 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.
    52. de Alcantara, Douglas Pedro & Martens, Mauro Luiz, 2019. "Technology Roadmapping (TRM): a systematic review of the literature focusing on models," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 127-138.
    53. Sjödin, David & Parida, Vinit & Kohtamäki, Marko & Wincent, Joakim, 2020. "An agile co-creation process for digital servitization: A micro-service innovation approach," Journal of Business Research, Elsevier, vol. 112(C), pages 478-491.
    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. Maria Elisabete Ramos & Ana Azevedo & Deolinda Meira & Mariana Curado Malta, 2022. "Cooperatives and the Use of Artificial Intelligence: A Critical View," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    2. Abderahman Rejeb & Andrea Appolloni, 2022. "The Nexus of Industry 4.0 and Circular Procurement: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 14(23), pages 1-21, November.

    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. 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).
    2. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    3. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Raphaël Maucuer & Alexandre Renaud, 2019. "Business Model Research: A Bibliometric Analysis of Origins and Trends," Post-Print hal-01918188, HAL.
    5. Carolina Navarro-Lopez & Salvador Linares-Mustaros & Carles Mulet-Forteza, 2022. "“The Statistical Analysis of Compositional Data†by John Aitchison (1986): A Bibliometric Overview," SAGE Open, , vol. 12(2), pages 21582440221, April.
    6. Singh, Shiwangi & Dhir, Sanjay & Das, V. Mukunda & Sharma, Anuj, 2020. "Bibliometric overview of the Technological Forecasting and Social Change journal: Analysis from 1970 to 2018," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    7. Francesco Paolo Appio & Fabrizio Cesaroni & Alberto Minin, 2014. "Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 623-661, October.
    8. Black, J. Stewart & van Esch, Patrick, 2020. "AI-enabled recruiting: What is it and how should a manager use it?," Business Horizons, Elsevier, vol. 63(2), pages 215-226.
    9. Dennys Eduardo Rossetto & Roberto Carlos Bernardes & Felipe Mendes Borini & Cristiane Chaves Gattaz, 2018. "Structure and evolution of innovation research in the last 60 years: review and future trends in the field of business through the citations and co-citations analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1329-1363, June.
    10. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Romero-Castro, Noelia María & Pérez-Pico, Ada María, 2020. "Innovation, entrepreneurship and knowledge in the business scientific field: Mapping the research front," Journal of Business Research, Elsevier, vol. 115(C), pages 475-485.
    11. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    12. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    13. Araz Zirar, 2023. "Can artificial intelligence’s limitations drive innovative work behaviour?," Review of Managerial Science, Springer, vol. 17(6), pages 2005-2034, August.
    14. Dzikowski, Piotr, 2018. "A bibliometric analysis of born global firms," Journal of Business Research, Elsevier, vol. 85(C), pages 281-294.
    15. Johnson, Prince Chacko & Laurell, Christofer & Ots, Mart & Sandström, Christian, 2022. "Digital innovation and the effects of artificial intelligence on firms’ research and development – Automation or augmentation, exploration or exploitation?," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    16. Markus Gmür, 2003. "Co-citation analysis and the search for invisible colleges: A methodological evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(1), pages 27-57, January.
    17. Gorupec Natalia & Tiberius Victor & Brehmer Nataliia & Kraus Sascha, 2022. "Tackling uncertain future scenarios with real options: A review and research framework," The Irish Journal of Management, Sciendo, vol. 41(1), pages 69-88, July.
    18. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(3), pages 217-230, December.
    19. Hugo Baier-Fuentes & José M. Merigó & José Ernesto Amorós & Magaly Gaviria-Marín, 2019. "International entrepreneurship: a bibliometric overview," International Entrepreneurship and Management Journal, Springer, vol. 15(2), pages 385-429, June.
    20. Mas-Tur, Alicia & Roig-Tierno, Norat & Sarin, Shikhar & Haon, Christophe & Sego, Trina & Belkhouja, Mustapha & Porter, Alan & Merigó, José M., 2021. "Co-citation, bibliographic coupling and leading authors, institutions and countries in the 50 years of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 165(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:tefoso:v:182:y:2022:i:c:s0040162522003523. 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.sciencedirect.com/science/journal/00401625 .

    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.