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From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges

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From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges. / Silvestre, Bruno S.; Gong, Yu; Bessant, John et al.
In: International Journal of Operations and Production Management, Vol. 43, No. 8, 08.08.2023, p. 1177-1194.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Silvestre, BS, Gong, Y, Bessant, J & Blome, C 2023, 'From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges', International Journal of Operations and Production Management, vol. 43, no. 8, pp. 1177-1194. https://doi.org/10.1108/IJOPM-04-2023-0318

APA

Silvestre, B. S., Gong, Y., Bessant, J., & Blome, C. (2023). From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges. International Journal of Operations and Production Management, 43(8), 1177-1194. https://doi.org/10.1108/IJOPM-04-2023-0318

Vancouver

Silvestre BS, Gong Y, Bessant J, Blome C. From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges. International Journal of Operations and Production Management. 2023 Aug 8;43(8):1177-1194. Epub 2023 Jul 31. doi: 10.1108/IJOPM-04-2023-0318

Author

Silvestre, Bruno S. ; Gong, Yu ; Bessant, John et al. / From supply chain learning to the learning supply chain : drivers, processes, complexity, trade-offs and challenges. In: International Journal of Operations and Production Management. 2023 ; Vol. 43, No. 8. pp. 1177-1194.

Bibtex

@article{78b5d85ad1c54504bc90c1eb7b3bd4c3,
title = "From supply chain learning to the learning supply chain: drivers, processes, complexity, trade-offs and challenges",
abstract = "Purpose: The view that supply chain learning (SCL) has become a fundamental capability that supply chains must employ to innovate and improve their financial, technological, operational, environmental and social performance is widely accepted. However, the SCL phenomenon is still understudied and not fully understood by scholars, decision-makers and government representatives. This article aims to make sense of the existing literature and to identify important research directions that require further attention. Design/methodology/approach: This article reviews the diversity of SCL in the literature, proposes a typology of such a phenomenon, provides an overview of key articles in the literature and identifies a series of recommendations for the future development of the field. Findings: This article combines two fundamental dimensions from the literature (i.e. SCL driver and SCL network) to produce a typology of four types of SCL: Captive, Consortium, Selective and Distributed. Practical implications: The typology proposed here offers an important framework for supply chain decision-makers to rely on when implementing SCL initiatives. The implications of each type of SCL offer a robust rationale for decision-makers to adopt the most appropriate type of SCL or combinations of SCL types, given each situation. In addition, the typology supports policy-makers in further understanding the SCL phenomenon and creating effective innovation, economic development and sustainability policies through supply chains. Originality/value: This article offers a novel typology that the authors hope will help scholars to advance the field of SCL in order to understand this important phenomenon. There is no good/bad/better/worse SCL type in the proposed typology, but the critical element for the success of SCL efforts is the level of fit between the type of SCL, the type of knowledge to be created and diffused, and the outcome supply chains aim to achieve with that learning effort. In addition, the authors coin the construct of “the learning supply chain”, which refers to a supply chain that learns constantly by employing all four types of SCL simultaneously.",
keywords = "Driver, Focal company driven learning, Supplier driven learning, Supply chain learning, Supply chain learning network, Typology, “The learning supply chain”",
author = "Silvestre, {Bruno S.} and Yu Gong and John Bessant and Constantin Blome",
year = "2023",
month = aug,
day = "8",
doi = "10.1108/IJOPM-04-2023-0318",
language = "English",
volume = "43",
pages = "1177--1194",
journal = "International Journal of Operations and Production Management",
issn = "0144-3577",
publisher = "Emerald Group Publishing Ltd.",
number = "8",

}

RIS

TY - JOUR

T1 - From supply chain learning to the learning supply chain

T2 - drivers, processes, complexity, trade-offs and challenges

AU - Silvestre, Bruno S.

AU - Gong, Yu

AU - Bessant, John

AU - Blome, Constantin

PY - 2023/8/8

Y1 - 2023/8/8

N2 - Purpose: The view that supply chain learning (SCL) has become a fundamental capability that supply chains must employ to innovate and improve their financial, technological, operational, environmental and social performance is widely accepted. However, the SCL phenomenon is still understudied and not fully understood by scholars, decision-makers and government representatives. This article aims to make sense of the existing literature and to identify important research directions that require further attention. Design/methodology/approach: This article reviews the diversity of SCL in the literature, proposes a typology of such a phenomenon, provides an overview of key articles in the literature and identifies a series of recommendations for the future development of the field. Findings: This article combines two fundamental dimensions from the literature (i.e. SCL driver and SCL network) to produce a typology of four types of SCL: Captive, Consortium, Selective and Distributed. Practical implications: The typology proposed here offers an important framework for supply chain decision-makers to rely on when implementing SCL initiatives. The implications of each type of SCL offer a robust rationale for decision-makers to adopt the most appropriate type of SCL or combinations of SCL types, given each situation. In addition, the typology supports policy-makers in further understanding the SCL phenomenon and creating effective innovation, economic development and sustainability policies through supply chains. Originality/value: This article offers a novel typology that the authors hope will help scholars to advance the field of SCL in order to understand this important phenomenon. There is no good/bad/better/worse SCL type in the proposed typology, but the critical element for the success of SCL efforts is the level of fit between the type of SCL, the type of knowledge to be created and diffused, and the outcome supply chains aim to achieve with that learning effort. In addition, the authors coin the construct of “the learning supply chain”, which refers to a supply chain that learns constantly by employing all four types of SCL simultaneously.

AB - Purpose: The view that supply chain learning (SCL) has become a fundamental capability that supply chains must employ to innovate and improve their financial, technological, operational, environmental and social performance is widely accepted. However, the SCL phenomenon is still understudied and not fully understood by scholars, decision-makers and government representatives. This article aims to make sense of the existing literature and to identify important research directions that require further attention. Design/methodology/approach: This article reviews the diversity of SCL in the literature, proposes a typology of such a phenomenon, provides an overview of key articles in the literature and identifies a series of recommendations for the future development of the field. Findings: This article combines two fundamental dimensions from the literature (i.e. SCL driver and SCL network) to produce a typology of four types of SCL: Captive, Consortium, Selective and Distributed. Practical implications: The typology proposed here offers an important framework for supply chain decision-makers to rely on when implementing SCL initiatives. The implications of each type of SCL offer a robust rationale for decision-makers to adopt the most appropriate type of SCL or combinations of SCL types, given each situation. In addition, the typology supports policy-makers in further understanding the SCL phenomenon and creating effective innovation, economic development and sustainability policies through supply chains. Originality/value: This article offers a novel typology that the authors hope will help scholars to advance the field of SCL in order to understand this important phenomenon. There is no good/bad/better/worse SCL type in the proposed typology, but the critical element for the success of SCL efforts is the level of fit between the type of SCL, the type of knowledge to be created and diffused, and the outcome supply chains aim to achieve with that learning effort. In addition, the authors coin the construct of “the learning supply chain”, which refers to a supply chain that learns constantly by employing all four types of SCL simultaneously.

KW - Driver

KW - Focal company driven learning

KW - Supplier driven learning

KW - Supply chain learning

KW - Supply chain learning network

KW - Typology

KW - “The learning supply chain”

U2 - 10.1108/IJOPM-04-2023-0318

DO - 10.1108/IJOPM-04-2023-0318

M3 - Journal article

AN - SCOPUS:85175111312

VL - 43

SP - 1177

EP - 1194

JO - International Journal of Operations and Production Management

JF - International Journal of Operations and Production Management

SN - 0144-3577

IS - 8

ER -