Published: May 28, 2024
Language: Английский
Journal of Purchasing and Supply Management, Journal Year: 2024, Volume and Issue: 30(1), P. 100896 - 100896
Published: Jan. 1, 2024
Artificial intelligence and machine learning are key technologies for purchasing organizations worldwide their usage is still in a nascent stage. This systematic review offers an overview of the state-of-the-art literature practice, where 46 works meeting inclusion criteria were interactively classified 11 use case clusters. The work follows content analysis approach material evaluation was empirically enriched with 20 interviews to assess cluster's business value ease implementation through triangulation. first area operations supply chain management utilizing Computer Classification System as de facto standard computer science clarity terminology these emerging technologies. In matching search interview results, mismatch found between reviewed expert's assessments. For instance, cluster cost deserves higher research attention well supplier sustainability. Moreover, there seems be gap operational area, which many believe considered due data availability. insights may guide researchers executives better understand dynamic capabilities needed successfully steer organization transformation toward procurement 4.0.
Language: Английский
Citations
19
Journal of Purchasing and Supply Management, Journal Year: 2025, Volume and Issue: unknown, P. 100993 - 100993
Published: Feb. 1, 2025
Language: Английский
Citations
2
Logistics, Journal Year: 2023, Volume and Issue: 7(3), P. 63 - 63
Published: Sept. 13, 2023
Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like Internet Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting comprehensive review 111 papers sourced from Scopus database. These are classified seven sub-themes encompassing I4.0 or (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, AI. Results: investigation reveals that technologies, particularly e-procurement have garnered substantial attention. Such offer diverse value propositions, streamlined supplier evaluation, lead time reduction, cost optimization, enhanced data security. Conclusion: paper underscores pivotal trends insights for evolution Procurement 4.0, illuminating path toward more efficient management.
Language: Английский
Citations
37
Journal of Purchasing and Supply Management, Journal Year: 2024, Volume and Issue: 30(1), P. 100908 - 100908
Published: Jan. 1, 2024
Language: Английский
Citations
13
Journal of the Knowledge Economy, Journal Year: 2024, Volume and Issue: unknown
Published: June 13, 2024
Language: Английский
Citations
13
Production Planning & Control, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23
Published: Jan. 11, 2024
This study presents a comprehensive investigation into the AI supply chain journey, combining systematic literature review (SLR) and empirical interviews with experts. The objective is to identify analyze key enablers constraints influencing in pre-development, deployment, post-development stages. research integrates data Technology-Organization-Environment (TOE) framework, revealing interactions between technological, organizational, environmental factors. thematic analysis uncovers six axial themes for pre-development stage one theme deployment stages respectively, providing valuable insights factors successful integration. Moreover, industry-specific are unveiled Airline, Agri-food, Retail, Logistics sectors, emphasizing importance of contextual tailored strategies. contributes existing knowledge by offering practical implications integration chains, highlighting significance managing industry heterogeneity. By identifying understanding constraints, this provides deeper faced during different chains. makes substantial contribution current socio-technical discourse on journey chains deriving eight propositions that offer insights. These delve addressing transforming them achieving enhanced performance. guidance both academic researchers professionals, equipping actionable strategies navigate complexities intricacies integrating technologies chain. embracing these propositions, stakeholders can effectively harness power optimize various aspects chain, leading improved efficiency, agility, competitiveness. Ultimately, advancing offers solutions drive real-world environments.
Language: Английский
Citations
11
International Journal of Production Economics, Journal Year: 2024, Volume and Issue: 274, P. 109289 - 109289
Published: May 31, 2024
Language: Английский
Citations
10
Computers in Industry, Journal Year: 2024, Volume and Issue: 162, P. 104132 - 104132
Published: Aug. 12, 2024
This article presents a systematic literature review (SLR) of empirical studies concerning Artificial Intelligence (AI) in the field Supply Chain Management (SCM). Over past decade, technologies belonging to AI have developed rapidly, reaching sufficient level maturity catalyze transformative changes business and society. Within SCM community, there are high expectations about disruptive impacts on current practices. However, this is not first instance where has sparked excitement, often falling short hype. It thus important examine both opportunities challenges emerging from its actual implementation. Our analysis clarifies technological approaches application areas, while expounding research themes around four key categories: data system requirements, technology deployment processes, (inter)organizational integration, performance implications. We also present contextual factors identified literature. lays solid foundation for future SCM. By exclusively considering contributions, our minimizes buzz underscores relevant intersecting AI, organizations, supply chains (SCs). effort meant consolidate existing insights managerial audience.
Language: Английский
Citations
10
Journal of Intelligent Manufacturing, Journal Year: 2023, Volume and Issue: unknown
Published: Nov. 13, 2023
Abstract Scientific research on emerging technologies underscored the advantages of their implementation within production systems, with a particular focus artificial intelligence (AI). In particular, integration AI other cutting-edge is relevant topic which can potentially lead to huge impacts in terms business performance. Yet, literature subject, although rich, still fragmented, limited specific cases and applications, but lacking comprehensive classification framework. Therefore, using systematic review, this study provides an overview how combination could improve market organisational performance functions processes. By classifying case studies real-world applications into taxonomies, considers indicator, co-occurrence ratio, highlighting most significant combinations between technologies, also specifying contexts they are used. The shows that strongly interconnected suggesting agenda promising systems contexts, providing benefits opportunities for companies.
Language: Английский
Citations
20
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Jan. 24, 2024
Abstract This research study provides a comprehensive analysis of academic publications that examine the significant impact artificial intelligence (AI) on strengthening resilience and sustainability supply chains. Using data-driven methodology Web Science platform, we carefully identify evaluate important themes, issues, developments related to AI applications in various chain settings. The synthesis present is based compilation 28 articles published from 2020 2023. These cover subjects such as transparency, optimizing last-mile delivery, multiagent systems, generative AI, influence micro, small, medium enterprises (MSMEs) findings not only illuminate level subject but also provide insight into developing patterns uncharted areas. Our offers overview how influencing current future state management. It gives vital insights for researchers, practitioners, decision-makers who are involved this dynamic ever-changing field.
Language: Английский
Citations
5