scholarly journals Administrative environmental innovations, supply network structure, and environmental disclosure

2020 ◽  
Vol 66 (7-8) ◽  
pp. 895-932
Author(s):  
Marcus A. Bellamy ◽  
Suvrat Dhanorkar ◽  
Ravi Subramanian
Keyword(s):  
Network Structure ◽  
Supply Network ◽  
Environmental Disclosure

When Ignorance Is Not Bliss: An Empirical Analysis of Subtier Supply Network Structure on Firm Risk

2020 ◽  
Author(s):  
Yixin (Iris) Wang ◽  
Jun Li ◽  
Di (Andrew) Wu ◽  
Ravi Anupindi
Keyword(s):  
Supply Chain ◽  
Network Structure ◽  
Operations Management ◽  
Financial Risk ◽  
Significant Proportion ◽  
Abnormal Returns ◽  
Supply Network ◽  
Tier 2 ◽  
Risk Levels ◽  
Common Structure

Using a multitier mapping of supply-chain relationships constructed from granular global, firm-to-firm supplier–customer linkages data, we quantify the degree of financial risk propagation from the supply network beyond firms’ direct supply-chain connections and isolate structural network properties serving as significant moderators of risk propagation. We first document a baseline fact: a significant proportion of tier-2 suppliers are shared by tier-1 suppliers. We then construct two simple metrics to capture the degree of tier-2 sharing and disentangle its effect from tier-2 suppliers’ own risks. We show that the focal firms’ risk levels are significantly related to the proportion of shared tier-2 suppliers in their supply network, and the effect becomes monotonically stronger as their tier-2 suppliers become more highly shared. Finally, we uncover causal relationships behind these associations using a new source of exogenous, idiosyncratic risk events in an event study setting. We show that, as tier-2 suppliers are impacted by these events, focal firms experience negative abnormal returns, the magnitude of which is significantly larger when the impacted tier-2 suppliers are more heavily shared. Overall, our study uncovers the subtier network structure as an important risk source for the focal firm, with the degree of tier-2 sharing as the main moderator. Our results also provide the microfoundation for a common structure in idiosyncratic risks and suggest the importance of incorporating the effect of subtier supply network structure in the portfolio-optimization process. This paper was accepted by Vishal Gaur, operations management.

scholarly journals Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

Entropy ◽  
2016 ◽  
Vol 18 (10) ◽  
pp. 367 ◽  
Author(s):  
Joshua Rodewald ◽  
John Colombi ◽  
Kyle Oyama ◽  
Alan Johnson
Keyword(s):  
Information Theory ◽  
Network Structure ◽  
Supply Network ◽  
Structure And Dynamics ◽  
Complex Adaptive

How “smart cities” will change supply chain management

2015 ◽  
Vol 20 (3) ◽  
pp. 237-248 ◽  
Author(s):  
Elcio M. Tachizawa ◽  
María J. Alvarez-Gil ◽  
María J. Montes-Sancho
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Network Structure ◽  
Smart Cities ◽  
Supply Network ◽  
Supply Networks ◽  
Chain Management ◽  
Content Type ◽  
Integrative Framework

Purpose – The purpose of this paper is to analyze the impact of smart city initiatives and big data on supply chain management (SCM). More specifically, the connections between smart cities, big data and supply network characteristics (supply network structure and governance mechanisms) are investigated. Design/methodology/approach – An integrative framework is proposed, grounded on a literature review on smart cities, big data and supply networks. Then, the relationships between these constructs are analyzed, using the proposed integrative framework. Findings – Smart cities have different implications to network structure (complexity, density and centralization) and governance mechanisms (formal vs informal). Moreover, this work highlights and discusses the future research directions relating to smart cities and SCM. Research limitations/implications – The relationships between smart cities, big data and supply networks cannot be described simply by using a linear, cause-and-effect framework. Accordingly, an integrative framework that can be used in future empirical studies to analyze smart cities and big data implications on SCM has been proposed. Practical implications – Smart cities and big data alone have limited capacity of improving SCM processes, but combined they can support improvement initiatives. Nevertheless, smart cities and big data can also suppose some novel obstacles to effective SCM. Originality/value – Several studies have analyzed information technology innovation adoption in supply chains, but, to the best of our knowledge, no study has focused on smart cities.

Supply Network Structure and Firm Performance: Evidence From the Electronics Industry

2018 ◽  
Vol 65 (1) ◽  
pp. 141-154 ◽  
Author(s):  
Rahul C. Basole ◽  
Soumen Ghosh ◽  
Manpreet S. Hora
Keyword(s):  
Firm Performance ◽  
Network Structure ◽  
Electronics Industry ◽  
Supply Network

Relating supply network structure to productive efficiency: A multi-stage empirical investigation

2017 ◽  
Vol 259 (2) ◽  
pp. 469-485 ◽  
Author(s):  
Ta-Wei (Daniel) Kao ◽  
N.C. Simpson ◽  
Benjamin B.M. Shao ◽  
Winston T. Lin
Keyword(s):  
Network Structure ◽  
Empirical Investigation ◽  
Productive Efficiency ◽  
Supply Network ◽  
Multi Stage

scholarly journals A supply network governance framework: a case study of the South Australian mining industry

2018 ◽  
Vol 11 (1) ◽  
pp. 55-78 ◽  
Author(s):  
Larissa Statsenko ◽  
Alex Gorod ◽  
Vernon Ireland
Keyword(s):  
Supply Chain ◽  
Conceptual Framework ◽  
Network Structure ◽  
Mining Industry ◽  
Network Governance ◽  
Supply Network ◽  
Supply Networks ◽  
Policy Makers ◽  
Content Type

Purpose The competitiveness of mining regions largely depends on the performance of the regional supply chains that provide services to mining companies. These local supply chains are often highly intertwined and represent a regional supply network for the industry. Individual companies often use supply chain strategies that are sub-optimal to overall supply network performance. To effectively respond to an uncertain business environment, policy-makers and supply chain participants would benefit by a governance framework that would allow to incentivise the formation of supply networks structures enabling effective operations. The purpose of this paper is to offer an empirically grounded conceptual framework based on Complex Adaptive Systems (CASs) governance principles, which links network governance mechanisms with supply network structure and operational performance to incentivise the formation of adaptive and resilient supply networks in the mining industry. Design/methodology/approach A mixed method research design and a case study of the South Australian mining sector were used to collect empirical data. Qualitative interviews and network analysis of the SA mining industry regional supply network structure were conducted. The relationships between network parameters were interpreted using CAS theory. Findings An empirically grounded conceptual framework based on CAS governance principles is developed. The case study revealed that supply chain strategies and governance mechanisms in the SA mining industry have led to the formation of a hierarchical, scale-free structure with insufficient horizontal connectivity which limits the adaptability, responsiveness and resilience of the regional supply network. Research limitations/implications The findings are drawn from a single case study. This limits generalisability of the findings and the proposed framework. Practical implications The proposed framework draws the attention of the policy-makers and supply chain participants towards the need for utilising CAS governance principles to facilitate the formation of adaptive, responsive and resilient regional supply networks in the mining industry. Originality value The proposed conceptual framework is an attempt to parameterise the governance of the regional supply networks in the mining industry.

Supply Network Structure, Visibility, and Risk Diffusion: A Computational Approach

2014 ◽  
Vol 45 (4) ◽  
pp. 753-789 ◽  
Author(s):  
Rahul C. Basole ◽  
Marcus A. Bellamy
Keyword(s):  
Network Structure ◽  
Computational Approach ◽  
Supply Network
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