Sourcing efficacy – The role of supportive intelligence - Aleksandar Erceg; Santhosh Joseph (Ekonomski Vjesnik)
Purpose: Globalization has increased the importance of sourcing and procurement strategies and factbased negotiation (FBN). Technological advances such as machine learning (ML) and artificial intelligence (AI) and their integration in FBN are significant transformative steps. The paper explores ML and AI’s role in improving FBN processes that traditionally rely on data-driven perceptions. Methodology: The research used in the paper used a multi-method approach with quantitative and qualitative elements. This research design was chosen to explore the complexity of integrating AI and ML in FBN and to obtain the impact this integration has on sourcing processes in different industries. The research results are based on a survey of 210 participants and 33 in-depth interviews. Results: The research showed that companies use FBN and see it as a beneficial approach to increasing negotiation efficacy. AI and ML integration in FBN significantly improves the negotiation process since it provides predictive modeling and real-time data analysis. Conclusion: The paper’s results align with current scientific studies highlighting the opportunities and barriers to AI and ML integration in negotiation processes. Companies must prioritize planning, education and organizational alignment for further development and optimization of these tools. With this, it is possible to fully realize the possibilities that integrating AI and ML into FBN can bring to the transformation of sourcing processes and the company’s competitiveness.