Abstract
In today’s data-driven business environment, the ethical management of knowledge and data utilization for decision-making in supply chain management has become increasingly vital. This study explores how artificial ethics principles can guide businesses in managing knowledge ethically and enable data-driven decision-making in supply chain management. The study specifically looks into two key areas: establishing moral standards for handling data and knowledge throughout the supply chain and incorporating artificial ethics principles into data analytics systems to support fairness and impartiality. The study follows a semi-systematic review approach. The findings show the importance of ethical considerations and their contributions to knowledge management and data-driven decision-making in supply chain management. By integrating artificial ethics principles, organizations can uphold ethical values such as accountability, fairness, and transparency in their decision-making procedures. Moreover, integrating these principles into data analytics systems ensures unbiased and equitable decision-making. This study emphasizes the value of integrating ethics into supply chain operations and provides advice for businesses looking to use data ethically and efficiently.
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References
Akkermans, H.A.: Responsible supply chain management: the role of transparency and trustworthiness. J. Bus. Ethics (2016)
Alreshidi, E.: Smart sustainable agriculture (SSA) solution underpinned by internet of things (IoT) and artificial intelligence (AI). arXiv preprint (2019)
Badii, A.C.: Ethical considerations for intelligent agents in supply chain management. J. Bus. Ethics (2016)
Baker-Brunnbauer, J.: Management perspective of ethics in artificial intelligence. AI Ethics 1(2), 173–181 (2021)
Berkowitz, E.N., Williams, C.K.: The strategic use of knowledge management. J. Knowl. Manag. 3(4), 303–313 (1999)
Bosch, R., et al.: A case study of Volkswagen unethical practice in diesel emission scandal. Int. J. Sci. Res. Publ. 6(9), 225–229 (2016)
Badaracco, J.L.: The discipline of building character. Harv. Bus. Rev. 76(2), 115–124 (1998)
Bechtsis, D., Tsolakis, N., Iakovou, E.V.: Data-driven secure, resilient and sustainable supply chains: gaps, opportunities, and a new generalised data sharing and data monetisation framework. Int. J. Prod. Res. 4397–4417 (2022)
Buolamwini, J., Gebru, T.: Gender shades: intersectional accuracy disparities in commercial gender classification. In: Proceedings of the 1st Conference on Fairness, Accountability, and Transparency, pp. 77–91 (2018)
Belhadi, A., Kamble, S., Fosso Wamba, S., Queiroz, M.M.: Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework. Int. J. Prod. Res. 60(14), 4487–4507 (2022)
Brendel, A.B., Mirbabaie, M., Lembcke, T.B., Hofeditz, L.: Ethical management of artificial intelligence. Sustainability 1974 (2021)
Basile, L.J., Carbonara, N., Pellegrino, R., Panniello, U.: Business intelligence in the healthcare industry: the utilization of a data-driven approach to support clinical decision making. Technovation 120, 102482 (2023). https://doi.org/10.1016/j.technovation.2022.102482
Chen, H., Themistocleous, M., Chiu, K.: Approaches to supply chain integration followed by SMEs: an exploratory case study. In: Proceedings of Tenth American Conference on Information Systems (AMCIS), New York, USA, pp. 2610–2620 (2004)
Connelly, L.M.: Inclusion and exclusion criteria. Medsurg Nurs. 29(2) (2020)
Cunningham, E.: Artificial intelligence-based decision-making algorithms, sustainable organizational performance, and automated production systems in big data-driven smart urban economy. J. Self-Governance Manag. Econ. 31–41 (2021)
Du, Y.L.: Sustainable Supply Chain Management in the Sharing Economy: A Resource-Based View Perspective. Resources, Conservation and Recycling (2016)
Davenport, T.H.: Process Innovation: Reengineering Work through Information Technology. Harvard Business Press (2013)
Freeman, R.E.: Strategic management: a stakeholder approach. Pitman (1984)
Gava, O., Bartolini, F., Venturi, F., Brunori, G., Pardossi, A.: Improving policy evidence base for agricultural sustainability and food security: a content analysis of life cycle assessment research. Sustainability 1033 (2020)
Hussain, M., et al.: Blockchain-based IoT devices in supply chain management: a systematic literature review. Sustainability (2021)
Johnson, M., Brown, K., Davis, L.: Implementing AI-driven demand forecasting in Company B: a case study. Int. J. Logist. Supply Chain Manag. 15(2), 87–100 (2020)
Jobin, A., Ienca, M., Vayena, E.: The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1(9), 389–399 (2019)
Johnson, D.S., Sihi, D., Muzellec, L.: Implementing big data analytics in marketing departments: Mixing organic and administered approaches to increase data-driven decision making. Informatics 66 (2021)
Johnson, P.F., Leauby, B.A., Klassen, R.D.: The data-driven decision-making model: a data-driven approach to student success. J. Student Affairs Res. Pract. 53(1), 55–68 (2016)
Kroll, J.A., et al.: Accountable algorithms. Univ. Pa. Law Rev. 165(3), 633–705 (2017)
Keele, S.: Guidelines for performing systematic literature reviews in software engineering (2007)
Lee, M.H.: An ethical decision-making framework for supply chain management. Sustainability (2017)
Mishra, S.B., Alok, S.: Handbook of research methodology (2022)
Nolan, C., et al.: The Volkswagen emissions scandal: a case study in corporate misbehaviour. J. Manag. Policy Pract. 18(1), 44–56 (2017)
Nasim, S.F., Ali, M.R., Kulsoom, U.: Artificial intelligence incidents & ethics a narrative review. Int. J. Technol. Innov. Manag. (2022)
Nitsche, A.-M.N., Matthias, C.L.: Technological and Organisational Readiness in the Age of Data-Driven Decision Making: A Manufacturing Perspective. Leeds Beckett Repository (2020)
Nonaka, I., Takeuchi, H.: The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press (1995)
Peppoloni, S., Di Capua, G.: Geoethics as global ethics to face grand challenges for humanity. Geological Society, London, Special Publications, 13–29 (2021)
Pournader, M., Ghaderi, H., Hassanzadegan, A., Fahimnia, B.: Artificial intelligence applications in supply chain management. Int. J. Prod. Econ. 241, 108250 (2021)
Patino, C.M., Ferreira, J.C.: Inclusion and exclusion criteria in research studies: definitions and why they matter. J. Bras. Pneumol. 44, 84 (2018)
Rajagopal, P.R.: Fuzzy logic-based approach for managing ethical issues in supply chain management. J. Bus. Ethics (2017)
Rong, P., Liu, S.: The impact of the ethical CEO on top management team’s creativity from the perspective of knowledge management: the moderating role of psychological distance. Curr. Psychol. 1–15 (2022)
Ribeiro, M.T., Singh, S., Guestrin, C.: “Why should I trust you?”: explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135–1144 (2016)
Rest, J.R.: Moral development: advances in research and theory. Praeger (1986)
Saghiri, S.: A hybrid model for green supply chain management under uncertainty. J. Clean. Prod. (2016)
Scheibe, K.P., Mukandwal, P.S., Grawe, S.J.: The effect of transactive memory systems on supply chain network collaboration. Int. J. Phys. Distrib. Logist. Manag. (2020)
Smith, J., Adams, R., Johnson, M.: AI-based demand forecasting models in supply chain management: a case study of Company A. J. Supply Chain Manag. 25(3), 123–135 (2019)
Seif El-Nasr, M., Kleinman, E.: Data-driven game development: ethical considerations. In: Proceedings of the 15th International Conference on the Foundations of Digital Games, pp. 1–10 (2020)
Singh, R.: An overview of artificial intelligence and its application in supply chain management. Int. J. Emerg. Technol. Adv. Eng. (2016)
Sleep, S., Gala, P.: Removing silos to enable data-driven decisions: the importance of marketing and IT knowledge, cooperation, and information quality. J. Bus. Res. (2022)
Soratana, K., Landis, A.E., Jing, F., Suto, H.: Supply Chain Management of Tourism Towards Sustainability. Springer, Cham (2020)
Themistocleous, M., Irani, Z., Love, P.E.D.: Evaluating the integration of supply chain information systems: a case study. Eur. J. Oper. Res. 159(2), 393–405 (2004)
Themistocleous, M., Cunha, P., Tabakis, E., Papadaki, M.: Towards cross-border CBDC interoperability: insights from a multivocal literature review. J. Enterprise Inf. Manag. 36(5), 1296–1318 (2023). https://doi.org/10.1108/JEIM-11-2022-0411
Tseng, M.L., Ha, H.M., Tran, T.P., Bui, T.D., Chen, C.C., Lin, C.W.: Building a data-driven circular supply chain hierarchical structure: resource recovery implementation drives circular business strategy. Bus. Strateg. Environ. 31(5), 2082–2106 (2022)
Tseng, M.-L., Tran, T.P.: Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: a data driven analysis. J. Ind. Prod. Eng. 581–598 (2021)
Tseng, M.L., Ha, H.M., Tran, T.P.T., Bui, T.D., Chen, C.C., Lin, C.W.: Building a data-driven circular supply chain hierarchical structure: Resource recovery implementation drives circular business strategy. Bus. Strategy Environ. 31, 2082–2106 (2022)
Tsolakis, N., Iakovou, E.: Data-driven secure, resilient and sustainable supply chains: gaps, opportunities, and a new generalised data sharing and data monetisation framework. Int. J. Prod. Res. 60, 4397–4417 (2021)
Wang, X., Chen, X., Tian, F.: An economic analysis of the 2008 milk scandal in China. J. Public Econ. 95(11–12), 1253–1262 (2011)
Zekhnini, K., Cherrafi, A., Bouhaddou, I., Benghabrit, Y., Garza-Reyes, J.A.: Supply chain management 4.0: a literature review and research framework. Benchmarking Int. J. 465–501 (2020)
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Alhaili, S., Mir, F. (2024). The Role of Artificial Ethics Principles in Managing Knowledge and Enabling Data-Driven Decision Making in Supply Chain Management. In: Papadaki, M., Themistocleous, M., Al Marri, K., Al Zarouni, M. (eds) Information Systems. EMCIS 2023. Lecture Notes in Business Information Processing, vol 501. Springer, Cham. https://doi.org/10.1007/978-3-031-56478-9_19
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