IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v129y2021icp911-926.html
   My bibliography  Save this article

Artificial intelligence in business: State of the art and future research agenda

Author

Listed:
  • Loureiro, Sandra Maria Correia
  • Guerreiro, João
  • Tussyadiah, Iis

Abstract

This study provides an overview of state-of-the-art research on Artificial Intelligence in the business context and proposes an agenda for future research. First, by analyzing 404 relevant articles collected through Web of Science and Scopus, this article presents the evolution of research on AI in business over time, highlighting seminal works in the field, and the leading publication venues. Next, using a text-mining approach based on Latent Dirichlet Allocation, latent topics were extracted from the literature and comprehensively analyzed. The findings reveal 18 topics classified into four main clusters: societal impact of AI, organizational impact of AI, AI systems, and AI methodologies. This study then presents several main developmental trends and the resulting challenges, including robots and automated systems, Internet-of-Things and AI integration, law, and ethics, among others. Finally, a research agenda is proposed to guide the directions of future AI research in business addressing the identified trends and challenges.

Suggested Citation

  • Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
  • Handle: RePEc:eee:jbrese:v:129:y:2021:i:c:p:911-926
    DOI: 10.1016/j.jbusres.2020.11.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296320307451
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2020.11.001?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. Soltani-Fesaghandis, Gholamreza & Pooya, Alireza, 2018. "Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(7), August.
    2. Maria José Sousa & Daniela Wilks, 2018. "Sustainable Skills for the World of Work in the Digital Age," Systems Research and Behavioral Science, Wiley Blackwell, vol. 35(4), pages 399-405, July.
    3. Majid Shishehgar & Seyed Nasirodin Mirmohammadi & Ahmad Reza Ghapanchi, 2015. "A survey on data mining and knowledge discovery techniques for spatial data," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 19(2), pages 265-276.
    4. Cockshott, Paul & Renaud, Karen, 2016. "Humans, robots and values," Technology in Society, Elsevier, vol. 45(C), pages 19-28.
    5. Marija Jankovic & Julie Stal-Le Cardinal & Jean-Claude Bocquet, 2015. "Context management in collaborative decision making in complex design projects," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 20(4), pages 286-303.
    6. Artur Siurdyban & Charles Møller, 2012. "Towards Intelligent Supply Chains: A Unified Framework for Business Process Design," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 5(1), pages 1-19, January.
    7. Michele Dassisti & Antonio Giovannini, 2012. "Ontologies for interoperating sustainable manufacturing: new opportunities for the automotive sector," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 12(3), pages 273-294.
    8. Marek Z. Reformat & Ronald R. Yager & Nhuan D. To, 2018. "Defining personalized concepts for XBRL using iPAD‐drawn fuzzy sets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 25(2), pages 73-85, April.
    9. Baesens, Bart & Verstraeten, Geert & Van den Poel, Dirk & Egmont-Petersen, Michael & Van Kenhove, Patrick & Vanthienen, Jan, 2004. "Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers," European Journal of Operational Research, Elsevier, vol. 156(2), pages 508-523, July.
    10. Andrew Keisner & Julio Raffo & Sacha Wunsch-Vincent, 2016. "Robotics: Breakthrough Technologies, Innovation, Intellectual Property," Foresight-Russia Форсайт, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 10(2 (eng)), pages 7-27.
    11. Michelle Greenwood, 2007. "Stakeholder Engagement: Beyond the Myth of Corporate Responsibility," Journal of Business Ethics, Springer, vol. 74(4), pages 315-327, September.
    12. Russell W. Belk, 2013. "Extended Self in a Digital World," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(3), pages 477-500.
    13. Macpherson, Allan & Holt, Robin, 2007. "Knowledge, learning and small firm growth: A systematic review of the evidence," Research Policy, Elsevier, vol. 36(2), pages 172-192, March.
    14. de Moor, A., 1998. "Information tools for sustainable development : Enabling distributed human intelligence," Other publications TiSEM 6a78d821-1966-4eb7-b214-3, Tilburg University, School of Economics and Management.
    15. A Collins & L Thomas, 2012. "Comparing reinforcement learning approaches for solving game theoretic models: a dynamic airline pricing game example," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(8), pages 1165-1173, August.
    16. Alexander Rodriguez‐Melo & S. Afshin Mansouri, 2011. "Stakeholder Engagement: Defining Strategic Advantage for Sustainable Construction," Business Strategy and the Environment, Wiley Blackwell, vol. 20(8), pages 539-552, December.
    17. Lanndon A. Ocampo & Gabrielle Khryss M. Abad & Karen Grace L. Cabusas & Maria Lizandra A. Padon & Nicole C. Sevilla, 2018. "Recent approaches to supplier selection: a review of literature within 2006-2016," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 12(1/2), pages 22-68.
    18. Dohnal, Mirko & Doubravsky, Karel, 2016. "Equationless and equation-based trend models of prohibitively complex technological and related forecasts," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 297-304.
    19. Byung Joon Park & Jin Seop Han, 2016. "Efficient decision support for detecting content polluters on social networks: an approach based on automatic knowledge acquisition from behavioral patterns," Information Technology and Management, Springer, vol. 17(1), pages 95-105, March.
    20. Schmidt, Gunter, 1998. "Case-based reasoning for production scheduling," International Journal of Production Economics, Elsevier, vol. 56(1), pages 537-546, September.
    21. Hede, Shantesh & Nunes, Manuel Jose Lopes & Ferreira, Paula Fernanda Varandas & Rocha, Luis Alexandre, 2013. "Incorporating sustainability in decision-making for medical device development," Technology in Society, Elsevier, vol. 35(4), pages 276-293.
    22. Jiøí Mazurek, 2013. "Discovering Knowledge With The Rough Set Approach," Polish Journal of Management Studies, Czestochowa Technical University, Department of Management, vol. 7(1), pages 245-254, June.
    23. Chan, Felix T. S. & Jiang, Bing & Tang, Nelson K. H., 2000. "The development of intelligent decision support tools to aid the design of flexible manufacturing systems," International Journal of Production Economics, Elsevier, vol. 65(1), pages 73-84, April.
    24. Rumpala, Yannick, 2012. "Artificial intelligences and political organization: An exploration based on the science fiction work of Iain M. Banks," Technology in Society, Elsevier, vol. 34(1), pages 23-32.
    25. Capatina, Alexandru & Kachour, Maher & Lichy, Jessica & Micu, Adrian & Micu, Angela-Eliza & Codignola, Federica, 2020. "Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    26. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    27. 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.
    28. Raymond Kosala, 2017. "Predicting the likelihood of dividend payment from Indonesian public companies with data mining methods," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 26(2), pages 139-150.
    29. 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.
    30. Krabuanrat, K. & Phelps, R., 1998. "Heuristics and rationality in strategic decision making: An exploratory study," Journal of Business Research, Elsevier, vol. 41(1), pages 83-93, January.
    31. Moro, Sérgio & Rita, Paulo & Cortez, Paulo, 2017. "A text mining approach to analyzing Annals literature," Annals of Tourism Research, Elsevier, vol. 66(C), pages 208-210.
    32. João Guerreiro & Paulo Rita & Duarte Trigueiros, 2016. "A Text Mining-Based Review of Cause-Related Marketing Literature," Journal of Business Ethics, Springer, vol. 139(1), pages 111-128, November.
    33. Christina Fang & Steven Orla Kimbrough & Stefano Pace & Annapurna Valluri & Zhiqiang Zheng, 2002. "On Adaptive Emergence of Trust Behavior in the Game of Stag Hunt," Group Decision and Negotiation, Springer, vol. 11(6), pages 449-467, November.
    34. David B. Paradice & James F. Courtney, 1989. "Organizational Knowledge Management," Information Resources Management Journal (IRMJ), IGI Global, vol. 2(3), pages 1-14, July.
    35. S Robinson & T Alifantis & J S Edwards & J Ladbrook & A Waller, 2005. "Knowledge-based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 912-921, August.
    36. V. Kumar & Ashutosh Dixit & Rajshekar (Raj) G. Javalgi & Mayukh Dass, 2016. "Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing," Journal of the Academy of Marketing Science, Springer, vol. 44(1), pages 24-45, January.
    37. 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.
    38. Loureiro, Sandra Maria Correia & Guerreiro, João & Eloy, Sara & Langaro, Daniela & Panchapakesan, Padma, 2019. "Understanding the use of Virtual Reality in Marketing: A text mining-based review," Journal of Business Research, Elsevier, vol. 100(C), pages 514-530.
    39. O’Dwyer, Edward & Pan, Indranil & Acha, Salvador & Shah, Nilay, 2019. "Smart energy systems for sustainable smart cities: Current developments, trends and future directions," Applied Energy, Elsevier, vol. 237(C), pages 581-597.
    40. Hakan Er & Adnan Hushmat, 2017. "The application of technical trading rules developed from spot market prices on futures market prices using CAPM," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 7(3), pages 313-353, December.
    41. S. Vasin & L. Gamidullaeva & E. Shkarupeta & I. Palatkin & T. Vasina, 2018. "Emerging Trends and Opportunities for Industry 4.0 Development in Russia," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 63-76.
    42. Andrew Kusiak, 2018. "Smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 508-517, 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. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Christou, Prokopis & Hadjielias, Elias & Simillidou, Aspasia & Kvasova, Olga, 2023. "The use of intelligent automation as a form of digital transformation in tourism: Towards a hybrid experiential offering," Journal of Business Research, Elsevier, vol. 155(PB).
    3. Ully Y. Nafizah & Stephen Roper & Kevin Mole, 2024. "Estimating the innovation benefits of first-mover and second-mover strategies when micro-businesses adopt artificial intelligence and machine learning," Small Business Economics, Springer, vol. 62(1), pages 411-434, January.
    4. Wareham, Jonathan & Pujol Priego, Laia & Romasanta, Angelo Kenneth & Mathiassen, Thomas Wareham & Nordberg, Markus & Tello, Pablo Garcia, 2022. "Systematizing serendipity for big science infrastructures: The ATTRACT project," Technovation, Elsevier, vol. 116(C).
    5. Steve J. Bickley & Ho Fai Chan & Benno Torgler, 2022. "Artificial intelligence in the field of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2055-2084, April.
    6. 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.
    7. Cristian-Mihai Vidu & Florina Pinzaru & Andreea Mitan, 2022. "What managers of SMEs in the CEE region should know about challenges of artificial intelligence’s adoption? – an introductive discussion," Nowoczesne Systemy Zarządzania. Modern Management Systems, Military University of Technology, Faculty of Security, Logistics and Management, Institute of Organization and Management, issue 1, pages 63-76.
    8. Jeon, Yongwoog Andrew, 2022. "Let me transfer you to our AI-based manager: Impact of manager-level job titles assigned to AI-based agents on marketing outcomes," Journal of Business Research, Elsevier, vol. 145(C), pages 892-904.
    9. Alexandru Constantin Ciobanu & Gabriela Meè˜Nièšä‚, 2021. "Ai Ethics In Business €“ A Bibliometric Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 28, pages 169-202, December.
    10. Zhang, Haili & Song, Michael & Wang, Yufan, 2023. "Does AI-infused operations capability enhance or impede the relationship between information technology capability and firm performance?," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    11. Cugno, Monica & Castagnoli, Rebecca & Büchi, Giacomo & Pini, Marco, 2022. "Industry 4.0 and production recovery in the covid era," Technovation, Elsevier, vol. 114(C).
    12. Sandra Maria Correia Loureiro, 2023. "Overview of the brand journey and opportunities for future studies," Italian Journal of Marketing, Springer, vol. 2023(2), pages 179-206, June.
    13. Tarikul Islam & Erhua Zhou, 2024. "Unpacking the Reasons Shaping Employee Acceptance and Attitudes towards AI Assistant Services in the Hotel Industry: A Behavioral Reasoning Perspective," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(5), pages 1-7.
    14. Bosse, Douglas & Thompson, Steven & Ekman, Peter, 2023. "In consilium apparatus: Artificial intelligence, stakeholder reciprocity, and firm performance," Journal of Business Research, Elsevier, vol. 155(PA).
    15. wael AL-khatib, Ayman, 2023. "Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework," Technology in Society, Elsevier, vol. 75(C).
    16. Luis Moreno-Izquierdo & Adrián Más-Ferrando & Marta Suárez-Tostado & Ana B. Ramón-Rodríguez, 2022. "Reinvención del turismo en clave de inteligencia artificial. Buscando un modelo sostenible y competitivo para el siglo XXI," Fedea Economy Notes 2022-19, FEDEA.
    17. Gustavo A. Cruz-Martínez & Alejandro Vega-Muñoz & Guido Salazar-Sepúlveda & Pablo Toledo-Aceituno, 2024. "Analysis of Studies on Digital Strategy: Bibliometric Research of Three Decades," Sustainability, MDPI, vol. 16(20), pages 1-20, October.
    18. Zahoor, Nadia & Donbesuur, Francis & Christofi, Michael & Miri, Domnan, 2022. "Technological innovation and employee psychological well-being: The moderating role of employee learning orientation and perceived organizational support," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    19. Chen, Qian & Gong, Yeming & Lu, Yaobin & Tang, Jing, 2022. "Classifying and measuring the service quality of AI chatbot in frontline service," Journal of Business Research, Elsevier, vol. 145(C), pages 552-568.
    20. Abdelhamid Zaidi & Samuel-Soma M. Ajibade & Majd Musa & Festus Victor Bekun, 2023. "New Insights into the Research Landscape on the Application of Artificial Intelligence in Sustainable Smart Cities: A Bibliometric Mapping and Network Analysis Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 287-299, July.
    21. Pathak, Kanishka & Prakash, Gyan, 2023. "Exploring the role of augmented reality in purchase intention: Through flow and immersive experience," Technological Forecasting and Social Change, Elsevier, vol. 196(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. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
    2. Lee, Kuo-Wei & Li, Chia-Ying, 2023. "It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    3. Jana Holthöwer & Jenny Doorn, 2023. "Robots do not judge: service robots can alleviate embarrassment in service encounters," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 767-784, July.
    4. 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).
    5. Peng, Leiqing & Luo, Mengting & Guo, Yulang, 2023. "Deposit AI as the “invisible hand†to make the resale easier: A moderated mediation model," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Araz Zirar, 2023. "Can artificial intelligence’s limitations drive innovative work behaviour?," Review of Managerial Science, Springer, vol. 17(6), pages 2005-2034, August.
    7. Zirar, Araz & Ali, Syed Imran & Islam, Nazrul, 2023. "Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda," Technovation, Elsevier, vol. 124(C).
    8. Zeba, Gordana & Dabić, Marina & Čičak, Mirjana & Daim, Tugrul & Yalcin, Haydar, 2021. "Technology mining: Artificial intelligence in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    9. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    10. Alabed, Amani & Javornik, Ana & Gregory-Smith, Diana, 2022. "AI anthropomorphism and its effect on users' self-congruence and self–AI integration: A theoretical framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    11. Maria Vasilska, 2021. "Characteristics of Strategic Subcontracting Relations of Industrial SMEs," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 7, ejes_v7_i.
    12. Stornelli, Aldo & Ozcan, Sercan & Simms, Christopher, 2021. "Advanced manufacturing technology adoption and innovation: A systematic literature review on barriers, enablers, and innovation types," Research Policy, Elsevier, vol. 50(6).
    13. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    14. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    15. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    16. Sagarika Mishra & Michael T. Ewing & Holly B. Cooper, 2022. "Artificial intelligence focus and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1176-1197, November.
    17. Navid Bahmani & Amit Bhatnagar & Dinesh Gauri, 2022. "Hey, Alexa! What attributes of Skills affect firm value?," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1219-1235, November.
    18. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.
    19. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    20. Kinkel, Steffen & Capestro, Mauro & Di Maria, Eleonora & Bettiol, Marco, 2023. "Artificial intelligence and relocation of production activities: An empirical cross-national study," International Journal of Production Economics, Elsevier, vol. 261(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:129:y:2021:i:c:p:911-926. 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.