Supply-chain networks: a complex adaptive systems perspective

By Amit Surana, Soundar Kumara *, Mark T. Greaves, Usha Nandini Raghavan. 2005

615 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/8e900ba5b010eac8d4a7639b85bbb8fcffabcb01

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Citations in the corpus

Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context (2020, background): “Since its introduction in the 1960s, CAS has been used to model social systems of varying size and complexity such as supply-chain networks [19, 103] and individual organizations [10, 24, 93], to health care systems [8, 9, 79, 89] and economic systems [2].”
Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective (2007, background): “…Harrison, & Hayya, 2004; Sawaya, 2006; Pathak, Dilts, & Biswas, 2007), cellular automata (Wolfram, 2002; Mizraji, 2004), dynamical systems theory (Surana et al., 2005), dynamic networks analysis (Carley, forthcoming), and empirical and case-study methods (Varga & Allen, 2006) have been applied…”
The impact of supply chain complexity on manufacturing plant performance (2009, background): “More recently, Surana et al. (2005) and Pathak et al. (2007) have extended the theory-building work that applies complex adaptive system (CAS) concepts to SCM, the former by suggesting analytical frameworks for applying CAS principles in studying the management and performance improvement of supply…”
Applications of agent-based systems in intelligent manufacturing: An updated review (2006, background): “Coexistence of competition and cooperation is a dichotomy governing today's enterprises [134].”
Artificial intelligence in supply chain management: A systematic literature review (2021, positive): “…studies and for different purposes, such as supply chain demand forecasting (Carbon-neau et al., 2008), time-series classification in supply chains (García et al., 2012), supplier selection (Guosheng and Guohong, 2008), and the designing of systems for supply chain networks (Surana et al., 2005).”
Biologicalisation: Biological transformation in manufacturing (2018, background): “This might lead to a better understanding of how complexity occurs, whether it follows any general scientific laws of nature, and how it might be related to simplicity [Surana et al., 2005].”
Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management (2020, neutral): “The implementation of these new organisational principles became possible due to advances in information and manufacturing technology such as multi-agent systems (Swaminathan, Smith, and Sadeh 1998; Fox, Barbuceanu, and Teigen 2000), complex adaptive systems (Choi, Dooley, and Rungtusanatham 2001; S”