Computational Analysis and Visualization of Global Supply Network Risks

Basole, Rahul C.; Bellamy, Marcus A.; Park, Hyun-Woo; Putrevu, Jagannath

doi:10.1109/tii.2016.2549268

Cited by 43 publications

(37 citation statements)

References 48 publications

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“…From the above-stated definitions, it is clear that SCRM is vast in its objectives and have become more complex (Basole et al, 2016). Consensus has been developed that there is no clear definition of SCRM (Musa, 2012;Sodhi et al, 2012;Tang and Musa, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Most of the researchers categories overall supply chain risks into three internal to organization also called organizational factors, external to organization but internal to network also known as industry factors and lastly external risk sources also called environmental factors (Basole et al, 2016;Ellis et al, 2011;Faisal et al, 2006;Jüttner et al, 2003;Lockamy III and McCormack, 2010;Ritchie and Brindley, 2007). Industrial factors are a relationship among supply chain partners and these partners are linked through flow, according to the adopted definition; supply chain has three kinds of flow information flow, material flow, and financial flow.…”

Section: Supply Chain Risksmentioning

confidence: 99%

“…Moreover, most of the researchers use information risk to cover information flow risks but this study argues that information side cover information related risks and miss the relational risk like coordination or etc. to cover all these issues, current study use collaboration side risk and this argument is supported by Basole et al (2016). The aim of this study is to cover supply chain risks that comprise external to organization and internal to supply chain risks.…”

Section: Supply Chain Risksmentioning

confidence: 99%

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The impact of supply chain risks on supply chain performance: Empirical evidence from the manufacturing of Malaysia

al.¹

2019

Int. j. adv. appl. sci.

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Nowadays, competition has shifted from organization to industry level so any disruption can not only disturb organization but also affect the whole industry. Although Malaysia is known from palm oil and rubber manufacturing sector has the highest growth rate (7.1%) and the second contributor to GDP and employer. After extensive literature view, it has found that various disruptions have been reported that not only disrupt Malaysian manufacturing but also a global business but there is no study available the empirically assess these risks. This is an empirical investigation and data was collected through a questionnaire distributed by systemic probability sampling to listed Manufacturing organizations listed in the Federation of Manufacturing Malaysia by emails. Final and purified data was analyzed through Structural Equational Modeling through Smart PLS. Total three types of risks were assessed namely logistic side risks, collaboration side risks, and finance side risks. It has been found that although all three types have a negative impact on supply chain performance only logistic side risks is effecting significantly. This study will help managers to understand how supply chain risks are affecting and what type of risks they should be more aware. Furthermore, various approaches can be proposed for mitigation but there is also a need to verify these approaches for Malaysia.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Supply Chain Risksmentioning

confidence: 99%

Section: Supply Chain Risksmentioning

confidence: 99%

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The impact of supply chain risks on supply chain performance: Empirical evidence from the manufacturing of Malaysia

al.¹

2019

Int. j. adv. appl. sci.

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“…The supply network perspective extends the scope of inquiry by accounting for relationships among a firm's partners and its distant and indirect partners (i.e., partners of the direct partners and beyond). Second, the network-oriented view helps identify and mitigate latent supply chain risks and disruptions (Basole and Bellamy, 2014;Basole et al, 2016b;. First, effectively managing supply networks leads to various operational benefits, including inventory, quality, and cycle time improvements.…”

Section: Structure and Dynamism In Supply Networkmentioning

confidence: 99%

“…The Toyota and Schneider Electric cases epitomize these operational benefits from supply chain management (Dyer and Hatch, 2004;Voxant FD Wire, 2009). Second, the network-oriented view helps identify and mitigate latent supply chain risks and disruptions (Basole and Bellamy, 2014;Basole et al, 2016b;. Supply chain management scholars and practitioners alike have realized the importance of sensing risk factors that emanate far from the focal firm but may cause a systemic failure in operations across its supply chain (Haraguchi and Lall, 2015).…”

Section: Structure and Dynamism In Supply Networkmentioning

confidence: 99%

Structural anatomy and evolution of supply chain alliance networks: A multi‐method approach

Park

Bellamy

Basole

2018

J of Ops Management

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We investigate the evolution of supply chain alliance networks with a focus on the influence of structural, firm‐, and industry‐level mechanisms. While several structural supply chain characteristics have been found to be significant drivers of firm innovation and performance, a dearth of studies exists examining how these characteristics change over time by influencing one another. We develop and empirically test hypotheses on the impact of prior structural configurations and the moderating roles of absorptive capacity and industry growth on the temporal trajectory of supply chain alliance network structures. Adopting a multi‐method approach, we jointly use econometric analyses and simulation experiments to examine our hypotheses from complementary angles. Specifically, we characterize the dynamic relationship between the structural mechanisms on a longitudinal dataset of 2221 unique firms and 13,668 firm‐year observations spanning 25 years. We find empirical support for negative crossover effects between two key structural properties of supply chain alliance networks, a positive moderation of a firm's absorptive capacity, and a negative moderation of industry growth on the structural reinforcement. We conduct corresponding simulation experiments based on a separable temporal exponential random graph model (STERGM) to track the temporal changes in the simulated networks' key measures. The simulation results concur with most of our empirical findings and provide additional insights complementary to our econometric analysis results. By focusing on the mechanism of temporal changes in network structural properties, our study contributes to supply chain management research with a supply network perspective and interfirm alliance network research by broadening its scope into structural dynamism. Our multi‐method approach demonstrates how multiple complementary methodologies can foster a more nuanced understanding of managing supply chain alliance network management.

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Computational Analysis and Visualization of Global Supply Network Risks

Cited by 43 publications

References 48 publications

The impact of supply chain risks on supply chain performance: Empirical evidence from the manufacturing of Malaysia

The impact of supply chain risks on supply chain performance: Empirical evidence from the manufacturing of Malaysia

Structural anatomy and evolution of supply chain alliance networks: A multi‐method approach

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