Leveraging supply chain networks for sustainability beyond corporate boundaries: Explorative structural network analysis

Laari, Sini; Wetzel, Philipp; Töyli, Juuso; Solakivi, Tomi

doi:10.1016/j.jclepro.2022.134475

Cited by 10 publications

(5 citation statements)

References 98 publications

(197 reference statements)

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“…This unforeseen event and its repercussions on supply networks at a global level heightened the need for tools that can provide a precise visualization of networks, actors, and the nature of the ties between them [9,13]. Concepts derived from diverse fields of knowledge, such as SNA, have gained traction in terms of application in the area of SCM [10,17,[19][20][21][22][23]. Furthermore, new developments have emerged from the application of SNA in SCM, including directed and non-directed networks [24] and the concept of semi-directedness [25].…”

Section: Social Network Analysis In Supply Chain Managementmentioning

confidence: 99%

“…Refs. [15,20] calculate the metric degree assortativity, which measures the extent to which companies associate with similar companies in the network, that is, the preference for a network's node to link to others that have some similarity. Moreover, Cai and other researchers [15] also devised two new metrics to identify outbreaks of disease and contamination: MSC-Maximum Spread Capacity-and MIC-Maximum Infection Chain.…”

Section: Descriptive Analysismentioning

confidence: 99%

“…This not only addresses structural aspects but also associates SNA with various topics, as explored by Wichmann and Kaufmann [13], indicating that the use of SNA in SCM goes beyond being just an analytical tool. Most of the studies reviewed applied SNA in the context of manufacturing, especially in the automotive sector [10,17,[20][21][22]42].…”

Section: Qualitative Analysis 421 Areas Of Applicationmentioning

confidence: 99%

Section: Qualitative Analysis 421 Areas Of Applicationmentioning

confidence: 99%

“…In addition, focusing on the automotive sector, Laari, Wetzel, Töyli, and Solakivi [20] explored how network characteristics and nodes can influence sustainability and concluded that the most sustainable companies are not necessarily the ones closest to customers but rather the most central ones. Therefore, according to [20], supply chain managers must map their suppliers and consider network configuration. Regarding network configuration, Le, Oláh, and Pakurár [21] analyze a supply chain composed of 60 assemblers and 210 suppliers and point out that only a few manufacturers predominantly control the exchange of information.…”

Section: Qualitative Analysis 421 Areas Of Applicationmentioning

confidence: 99%

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Social Network Analysis: Applications and New Metrics for Supply Chain Management—A Literature Review

Bento,

Cruz,

Fernandes

et al. 2024

Logistics

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Background: Supply chains, characterized by complexity and sensitivity, require continuous mapping to address challenges, particularly disruptions like the COVID-19 pandemic. In this context, Social Network Analysis (SNA) has proven valuable in analyzing how actors in a network connect and create interdependencies. However, some studies suggest that the SNA literature needs to embrace new fields of application and develop innovative metrics. Methods: The aim of this study is to clarify the role and contribution of SNA when characterizing and understanding the challenges of contemporary supply chains. A literature review was conducted to achieve this. Results: The results reveal that SNA has been applied in a wide variety of areas (e.g., manufacturing and construction sectors), with an emerging application in the tertiary sector. Furthermore, the findings demonstrate that metrics related to the network and to nodes have been used repeatedly, highlighting the need for new supply-chain-related metrics, such as the novel concept of semi-directedness. Conclusions: Despite the versatility of SNA, some aspects may limit its application to supply chain management, including shortcomings in data acquisition and the fact that SNA only allows for the visualization of network configurations, thus preventing the capture of nuances that characterize the relationships between the actors involved.

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