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Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

Di Vaio, Assunta, Palladino, Rosa, Hassan, Rohail, Escobar, Octavio·2020·Journal of Business Research
DOI 10.1016/j.jbusres.2020.08.019
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Abstract

Abstract This paper investigates the literary corpus on the role of Artificial Intelligence (AI) in the construction of sustainable business models (SBMs). It provides a quantitative overview of the academic literature that constitutes the field. The paper discusses the relationships between AI and rapid developments in machine learning and sustainable development (SD). Specifically, the aim is to understand whether this branch of computer science can influence production and consumption patterns to achieve sustainable resource management according to Sustainable Development Goals (SDGs) outlined in the UN 2030 Agenda. Moreover, the paper aims to highlight the role of Knowledge Management Systems (KMS) in the cultural drift toward the spread of AI for SBMs. Despite the importance of the topic, there is no comprehensive review of the AI and SBM literature in light of SDGs. Based on a database containing 73 publications in English with publication dates from 1990 to 2019, a bibliometric analysis is conducted. The findings show that the innovation challenge involves ethical, social, economic, and legal aspects. Thus, considering that the development potential of AI is linked to the UN 2030 Agenda for SD, especially to SDG#12, our results also outline the framework of the existing literature on AI and SDGs, especially SDG#12, including AI’s association with the cultural drift (CD) in the SBMs. The paper highlights the key contributions, which are: i) a comprehensive review of the key underlying relationship between AI and SBMs, offering a holistic view as needed, ii) identifying a research gap regarding KMS through AI, and iii) the implications of AI concerning SDG#12. Academic and managerial implications are also discussed regarding KMS in the SBMs, where the AI can represent the vehicle to meet the SDGs allowing for the identification of the cultural change required by enterprises to achieve sustainable goals. Thus, business companies, academic research practitioners, and state policy should focus on the further development of the use of AI in SBMs.

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Research works printed but not linked: 89

  1. Allayannis, 2001, The use of foreign currency derivatives and firm market value, The Review of Financial Studies, 14, 243, 10.1093/rfs/14.1.243 · DOI · Paper page
  2. Arinze, 1997, Combining and selecting forecasting models using rule based induction, Computers & Operations Research, 24, 423, 10.1016/S0305-0548(96)00062-7 · doi:10.1016/s0305-0548(96)00062-7
  3. Babu, 2018, An integrated approach to evaluating sustainability in supply chains using evolutionary game theory, Computers & Operations Research, 89, 269, 10.1016/j.cor.2017.01.008 · DOI
  4. Bansal, 2002, The corporate challenges of sustainable development, Academy of Management Perspectives, 16, 122, 10.5465/ame.2002.7173572 · DOI · Paper page
  5. Barro, 2019, People and machines: Partners in innovation, MIT Sloan Management Review, 60, 22
  6. Baskerville, 2006, The theoretical foundations of knowledge management, Knowledge Management Research & Practice, 4, 83, 10.1057/palgrave.kmrp.8500090 · DOI · Paper page
  7. Brenner, 2018, Transformative sustainable business models in the light of the digital imperative—A global business economics perspective, Sustainability, 10, 4428, 10.3390/su10124428 · DOI · Paper page
  8. Brenner, S. N., & Cochran, P. (1991). The stakeholder theory of the firm: Implications for business and society theory and research. In Proceedings of the international association for business and society,(Vol. 2, pp. 897-933). https://doi.org/10.5840/iabsproc1991235. · DOI · Paper page
  9. Brynjolfsson, 2017, The business of artificial intelligence, Harvard Business Review, 1
  10. Buzko, 2016, Artificial Intelligence technologies in human resource development, Computer Modelling and New Technologies, 20, 26
  11. Chelliah, 2017, Will artificial intelligence usurp white collar jobs?, Human Resource Management International Digest, 25, 1, 10.1108/HRMID-11-2016-0152 · DOI
  12. Chen, 2014, Business concepts of systemic service innovations in e-Healthcare, Technovation, 34, 513, 10.1016/j.technovation.2014.03.002 · DOI
  13. Cui, 2004, Implementing neural networks for decision support in direct marketing, International Journal of Market Research, 46, 235, 10.1177/147078530404600204 · DOI
  14. de Pádua Pieroni, M., McAloone, T., & Pigosso, D. (2019). Business model innovation for circular economy: integrating literature and practice into a conceptual process model. InProceedings of the design society: international conference on engineering design(Vol. 1, No. 1, pp. 2517-2526). Cambridge University Press. https://doi.org/10.1017/dsi.2019.258. · DOI
  15. Dada, 2018, A model of entrepreneurial autonomy in franchised outlets: A systematic review of the empirical evidence, International Journal of Management Reviews, 20, 206, 10.1111/ijmr.12123 · DOI
  16. de Paula Arruda Filho, 2017, The agenda 2030 for responsible management education: An applied methodology, The International Journal of Management Education, 15, 183, 10.1016/j.ijme.2017.02.010 · doi:10.1016/j.ijme.2017.02.010
  17. de Sousa Jabbour, 2019, Circular economy business models and operations management, Journal of Cleaner Production, 235, 1525, 10.1016/j.jclepro.2019.06.349 · DOI · Paper page
  18. Danese, 2018, A systematic literature review on recent lean research: State-of-the-art and future directions, International Journal of Management Reviews, 20, 579, 10.1111/ijmr.12156 · DOI · Paper page
  19. Demil, 2010, Business model evolution: In search of dynamic consistency, Long Range Planning, 43, 227, 10.1016/j.lrp.2010.02.004 · DOI · Paper page
  20. Ding, 2019, Modeling price volatility based on a genetic programming approach, British Journal of Management, 30, 328, 10.1111/1467-8551.12359 · DOI
  21. Dirican, 2015, The impacts of robotics, artificial intelligence on business and economics, Procedia-Social and Behavioral Sciences, 195, 564, 10.1016/j.sbspro.2015.06.134 · DOI · Paper page
  22. Fish, 1995, Artificial neural networks: A new methodology for industrial market segmentation, Industrial Marketing Management, 24, 431, 10.1016/0019-8501(95)00033-7 · DOI
  23. Foss, 2017, Fifteen years of research on business model innovation: How far have we come, and where should we go?, Journal of Management, 43, 200, 10.1177/0149206316675927 · DOI · Paper page
  24. Garbuio, 2019, Artificial intelligence as a growth engine for health care startups: Emerging business models, California Management Review, 61, 59, 10.1177/0008125618811931 · DOI · Paper page
  25. Govindan, 2019, Designing a sustainable supply chain network integrated with vehicle routing: A comparison of hybrid swarm intelligence metaheuristics, Computers & Operations Research, 110, 220, 10.1016/j.cor.2018.11.013 · DOI
  26. Hajli, 2018, The impact of new ICT technologies and its applications on health service development and management, Technological Forecasting and Social Change, 126, 1, 10.1016/j.techfore.2017.09.015 · doi:10.1016/j.techfore.2017.09.015
  27. Haseeb, 2019, Industry 4.0: A solution towards technology challenges of sustainable business performance, Social Sciences, 8, 154, 10.3390/socsci8050154 · DOI · Paper page
  28. Hicks, 2011, Coverage and overlap of the new social sciences and humanities journal lists, Journal of the American Society for Information Science and Technology, 62, 284, 10.1002/asi.21458 · DOI
  29. Hlupic, 2002, Towards an integrated approach to knowledge management:‘hard’, ‘soft’ and ‘abstract’ issues, Knowledge and Process Management, 9, 90, 10.1002/kpm.134 · DOI · Paper page
  30. Hoeschl, H. C., & Barcellos, V. (2006). Artificial intelligence and knowledge management. InIFIP international conference on artificial intelligence in theory and practice(pp. 11–19). Springer, Boston, MA. https://doi.org/10.1007/978-0-387-34747-9_2. · DOI
  31. Hsieh, 2009, Applying an expert system into constructing customer’s value expansion and prediction model based on AI techniques in leisure industry, Expert Systems with Applications, 36, 2864, 10.1016/j.eswa.2008.01.058 · DOI
  32. Hughes, 2019, Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda, International Journal of Information Management, 49, 114, 10.1016/j.ijinfomgt.2019.02.005 · DOI · Paper page
  33. Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. InProceedings of the international conference on electronic business(pp. 106–114). https://aisel.aisnet.org/iceb2018/.
  34. Johannessen, 1999, Aspects of innovation theory based on knowledge-management, International Journal of Information Management, 19, 121, 10.1016/S0268-4012(99)00004-3 · DOI · Paper page
  35. Johnson, 2010, The time has come for business model innovation, Leader to Leader, 2010, 6, 10.1002/ltl.421 · doi:10.1002/ltl.421
  36. Joyce, 2016, The triple layered business model canvas: A tool to design more sustainable business models, Journal of Cleaner Production, 135, 1474, 10.1016/j.jclepro.2016.06.067 · DOI · Paper page
  37. Kahneman, 2016, Noise: How to overcome the high, hidden cost of inconsistent decision making, Harvard Business Review, 94, 38
  38. Kaplan, 2012, If you love something, let it go mobile: Mobile marketing and mobile social media 4x4, Business Horizons, 55, 129, 10.1016/j.bushor.2011.10.009 · DOI · Paper page
  39. Kaplan, 2016, Higher education and the digital revolution: About MOOCs, SPOCs, social media, and the Cookie Monster, Business Horizons, 59, 441, 10.1016/j.bushor.2016.03.008 · DOI · Paper page
  40. Kaplan, 2019, Digital transformation and disruption: On big data, blockchain, artificial intelligence, and other things, Business Horizons, 62, 679, 10.1016/j.bushor.2019.07.001 · DOI
  41. Kauppi, 2018, Sourcing from Africa: A systematic review and a research agenda, International Journal of Management Reviews, 20, 627, 10.1111/ijmr.12158 · DOI
  42. Key, 1999, Toward a new theory of the firm: A critique of stakeholder “theory”, Management Decision, 37, 317, 10.1108/00251749910269366 · DOI · Paper page
  43. Kim, 2019, Predicting corporate financial sustainability using novel business analytics, Sustainability, 11, 64, 10.3390/su11010064 · DOI
  44. Klauck, 1997, Formal business process engineering based on graph grammars, International Journal of Production Economics, 50, 129, 10.1016/S0925-5273(95)00047-X · doi:10.1016/s0925-5273(95)00047-x
  45. Klumpp, 2018, Automation and artificial intelligence in business logistics systems: Human reactions and collaboration requirements, International Journal of Logistics Research and Applications, 21, 224, 10.1080/13675567.2017.1384451 · DOI · Paper page
  46. Kuo, 2018, A systematic review of technologies involving eco-innovation for enterprises moving towards sustainability, Journal of Cleaner Production, 192, 207, 10.1016/j.jclepro.2018.04.212 · DOI · Paper page
  47. Lacher, 1995, A neural network for classifying the financial health of a firm, European Journal of Operational Research, 85, 53, 10.1016/0377-2217(93)E0274-2 · DOI · Paper page
  48. Lenssen, 2013, A value mapping tool for sustainable business modelling, Corporate Governance, 13, 482, 10.1108/CG-06-2013-0078 · DOI · Paper page
  49. Leonidou, 2018, An integrative framework of stakeholder engagement for innovation management and entrepreneurship development, Journal of Business Research
  50. Lewellen, 2006, Financing decisions when managers are risk averse, Journal of Financial Economics, 82, 551, 10.1016/j.jfineco.2005.06.009 · DOI · Paper page
  51. Liao, 2003, Knowledge management technologies and applications—literature review from 1995 to 2002, Expert Systems with Applications, 25, 155, 10.1016/S0957-4174(03)00043-5 · DOI · Paper page
  52. Liu, 2004, Using concept mapping for assessing and promoting relational conceptual change in science, Science Education, 88, 373, 10.1002/sce.10127 · DOI
  53. Maduravoyal, 2018, Artificial Intelligence in Human Resource Management, International Journal of Pure and Applied Mathematics, 119, 1891
  54. Massaro, 2016, On the shoulders of giants: Undertaking a structured literature review in accounting, Accounting, Auditing & Accountability Journal, 29, 767, 10.1108/AAAJ-01-2015-1939 · DOI · Paper page
  55. McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955.AI Magazine,27(4), 12–12. https://doi.org/10.1609/aimag.v27i4.1904. · doi:10.1609/aimag.v27i4.1904
  56. Mikalef, P., Framnes, V. A., Danielsen, F., Krogstie, J., & Olsen, D. (2017). Big data analytics capability: antecedents and business value. InPacific Asia conference on information systems (PACIS). Association For Information Systems. https://aisel.aisnet.org/pacis2017/136.
  57. Miller, S. M. (2018). AI: AI: Augmentation, more so than automation. (2018). Asian Management Insights, 5(1), 1-20. https://ink.library.smu.edu.sg/ami/83.
  58. Min, 2010, Artificial intelligence in supply chain management: Theory and applications, International Journal of Logistics: Research and Applications, 13, 13, 10.1080/13675560902736537 · DOI · Paper page
  59. Morris, 2005, The entrepreneur’s business model: Toward a unified perspective, Journal of Business Research, 58, 726, 10.1016/j.jbusres.2003.11.001 · DOI · Paper page
  60. Nemati, 2002, Knowledge warehouse: An architectural integration of knowledge management, decision support, artificial intelligence and data warehousing, Decision Support Systems, 33, 143, 10.1016/S0167-9236(01)00141-5 · DOI · Paper page
  61. Nilsson, 2016, Policy: Map the interactions between sustainable development goals, Nature, 534, 320, 10.1038/534320a · DOI · Paper page
  62. Nilsson, N. J. (1983). Artificial intelligence prepares for 2001.AI Magazine,4(4), 7-7. https://doi.org/10.1609/aimag.v4i4.411. · DOI
  63. Nofal, 2018, Biology and management: A review, critique, and research agenda, Journal of Management, 44, 7, 10.1177/0149206317720723 · DOI
  64. Nosratabadi, 2019, Sustainable business models: A review, Sustainability, 11, 1663, 10.3390/su11061663 · DOI · Paper page
  65. Okoli, C., & Schabram, K. (2010). A guide to conducting a systematic literature review of information systems research. http://sprouts.aisnet.org/10-26 / Accessed 05 March 2020. · DOI · Paper page
  66. Omoteso, 2012, The application of artificial intelligence in auditing: Looking back to the future, Expert Systems with Applications, 39, 8490, 10.1016/j.eswa.2012.01.098 · DOI · Paper page
  67. Orriols-Puig, 2013, Unsupervised KDD to creatively support managers’ decision making with fuzzy association rules: A distribution channel application, Industrial Marketing Management, 42, 532, 10.1016/j.indmarman.2013.03.005 · doi:10.1016/j.indmarman.2013.03.005
  68. Osterwalder, 2005, Clarifying business models: Origins, present, and future of the concept, Communications of the Association for Information Systems, 16, 1
  69. Rashman, 2009, Organisational learning and knowledge in public service organisations: A systematic review, International Journal of Management Reviews, 11, 463, 10.1111/j.1468-2370.2009.00257.x · DOI · Paper page
  70. Sachs, 2019, Six transformations to achieve the sustainable development goals, Nature Sustainability, 2, 805, 10.1038/s41893-019-0352-9 · DOI · Paper page
  71. Schaltegger, 2016, Business models for sustainability: Origins, present research, and future avenues, Organization & Environment, 29, 3, 10.1177/1086026615599806 · DOI · Paper page
  72. Schneider, 2019, Me or information technology? Adoption of artificial intelligence in the delegation of personal strategic decisions, Managerial and Decision Economics, 40, 223, 10.1002/mde.2982 · DOI · Paper page
  73. Schneider, 2019, Rethinking drug design in the artificial intelligence era, Nature Reviews Drug Discovery, 1–12
  74. Stormer, 2003, Making the shift: Moving from” ethics pays” to an inter-systems model of business, Journal of Business Ethics, 44, 279, 10.1023/A:1023600820194 · DOI
  75. Strandhagen, 2017, Logistics 4.0 and emerging sustainable business models, Advances in Manufacturing, 5, 359, 10.1007/s40436-017-0198-1 · DOI · Paper page
  76. Stubbs, 2008, Conceptualising a “sustainability business model”, Organization & Environment, 21, 103, 10.1177/1086026608318042 · DOI · Paper page
  77. Teece, 2010, Business models, business strategy and innovation, Long Range Planning, 43, 172, 10.1016/j.lrp.2009.07.003 · DOI · Paper page
  78. Thomas, 2001, The knowledge management puzzle: Human and social factors in knowledge management, IBM Systems Journal, 40, 863, 10.1147/sj.404.0863 · DOI · Paper page
  79. Tranfield, 2003, Towards a methodology for developing evidence-informed management knowledge by means of systematic review, British Journal of Management, 14, 207, 10.1111/1467-8551.00375 · DOI · Paper page
  80. Tsui, 2000, The role of artificial intelligence in knowledge management, Knowledge Based Systems, 13, 235, 10.1016/S0950-7051(00)00093-9 · DOI · Paper page
  81. Tuan, 2019, Applying a mindfulness-based reliability strategy to the Internet of Things in healthcare–A business model in the Vietnamese market, Technological Forecasting and Social Change, 140, 54, 10.1016/j.techfore.2018.10.024 · DOI
  82. Venkatraman, 1990, Environment-strategy coalignment: An empirical test of its performance implications, Strategic Management Journal, 11, 1, 10.1002/smj.4250110102 · DOI · Paper page
  83. Vinuesa, 2020, The role of artificial intelligence in achieving the Sustainable Development Goals, Nature Communications, 11, 1, 10.1038/s41467-019-14108-y · DOI · Paper page
  84. Wang, 2014, Entrepreneurial learning: Past research and future challenges, International Journal of Management Reviews, 16, 24, 10.1111/ijmr.12007 · DOI · Paper page
  85. Witell, 2016, Defining service innovation: A review and synthesis, Journal of Business Research, 69, 2863, 10.1016/j.jbusres.2015.12.055 · DOI · Paper page
  86. Wright, 2018, The rising tide of artificial intelligence and business automation: Developing an ethical framework, Business Horizons, 61, 823, 10.1016/j.bushor.2018.07.001 · DOI · Paper page
  87. Yoo, 2018, A decision-making model for adopting a cloud computing system, Sustainability, 10, 2952, 10.3390/su10082952 · DOI
  88. Žigienė, 2019, Artificial intelligence based commercial risk management framework for SMEs, Sustainability, 11, 4501, 10.3390/su11164501 · DOI
  89. Zilahy, 2016, Sustainable business models-what do management theories say?, Vezetéstudomány-Budapest Management Review, 47, 62, 10.14267/VEZTUD.2016.10.06 · DOI

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Metadata

Authors
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O.
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2020-12
Volume
121
Pages
283-314
ISSN
0148-2963 (ISSN-L)
DOI
10.1016/j.jbusres.2020.08.019
OpenAlex
W3085940513
Cited by
1,096
References
23
FWCI
13.84
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)
Funders
Università degli Studi di Napoli Parthenope

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Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2020.08.019

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