Marcus A. Bellamy

Network analysis of supply chain systems: A systematic review and future research

Supply chains are continuously evolving and adapting systems driven by complex socio-technical interfirm interactions. Traditional engineering and operations management modeling approaches have primarily focused on technical issues and are not well suited to effectively capture the many complex structural and behavioral aspects of supply chain systems (SCSs). There is growing recognition by the supply chain community of the significant benefits a network analytic lens can provide to understand, design, and manage SCSs. We systematically review and analyze the relevant literature and, drawing on a multi-disciplinary theoretical foundation, develop an integrative framework. Our framework identifies three distinct, but interdependent themes that characterize the study of SCSs: SCS network structure (i.e. system architecture), SCS network dynamics (i.e. system behavior), and SCS network strategy (i.e. system policy and control). We elaborate on these themes, review key findings, identify the current limitations and knowledge gaps, and discuss the fundamental benefits derived from adopting an integrated SCSs perspective. We conclude with future research directions for network analysis in SCS design and management, in particular, and complex enterprise systems in general.

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

Understanding and managing supply chain risks is a critical functional competency for todays global enterprises. A lack of this competency can have significant negative outcomes, including costly production and delivery delays, loss of future sales, and a tarnished corporate image. The ability to identify and mitigate risks, however, is complicated as supply chains are becoming increasingly global, complex, and interconnected. Drawing on the complex systems and epidemiology literature, and using a computational modeling and network analysis approach, we examine the impact of global supply network structure on risk diffusion and supply network health and demonstrate the importance of supply network visibility. Our results show a significant association between network structure and both risk diffusion and supply network health. In particular, our results indicate that small-world supply network topologies consistently outperform supply networks with scale-free characteristics. Theoretically, our study contributes to our understanding of risk management and supply networks as complex networked systems using a computational approach. Managerially, our study illustrates how decision makers can benefit from a network analytic approach to develop a more holistic understanding of system-wide risk diffusion and to guide network governance policies for more favorable health level outcomes. The article concludes by highlighting the main findings and discussing possibilities of future research directions.

Visual analysis of supply network risks

In todays complex, global supply networks it has become increasingly challenging to identify, evaluate, and mitigate risks of disruption. Traditional supply chain practices have primarily focused on dyadic risk management, rarely considering risks in the sub-tier supply network. However, this approach severely limits a decision makers ability to understand the highly interconnected nature of systemic risks and develop corresponding mitigation strategies. Grounded in theories of supply chains as complex systems, network analysis, and risk management, we demonstrate the importance of visual decision support for supply network risk assessment. We empirically illustrate our approach with supply network visualization examples from the electronics industry. We conclude the study with implications for the design and implementation of visual supply network decision support systems and future research opportunities. A visual network analytic approach allows mapping of flow, information, and risk.Subtier risk is prevalent in electronics industry and distributions differ by tier.The study provides macroscopic view of supply network risk issues across multiple tiers.Multiple visual depictions reveal distribution of risk levels across supply network.Integrating depictions enables timely identification of dependencies and risks.

Visualization of Innovation in Global Supply Chain Networks

This methodological note identifies and describes a data-driven visualization approach to study innovations in supply chain networks (ISCN). We demonstrate its value and applicability with illustrative examples to pertinent structure-related ISCN research questions in the global electronics industry. Our visualization approach can be used to reveal and understand important clusters, patterns, trends, and outliers of ISCN not necessarily identified with traditional methods. The broader aim of this note is to demonstrate the complementary value of emerging visual analytic approaches in managerial decision-making contexts and describe how actionable insights can be achieved.

Global supply network health: Analysis and visualization

The health of a global supply network GSN plays an important role in the effective and timely delivery of complex products and services. Decision makers are in need of a holistic approach inclusive of several aspects affecting GSN performance, moving beyond traditional approaches that limit GSN analysis to a singular aspect, such as operational or financial performance. We argue that GSN health consists of four key aspects: operational, financial, collaboration, and strategic health. Using a network analytic approach, we propose a methodology to assess and visualize GSN health. We illustrate our methodology using a field study in the aerospace industry. Our contributions are multifold. Theoretically, we contribute to our understanding of GSNs as multimodal networks consisting of both technical and social relationships. From a managerial perspective, we provide a GSN health assessment and visualization framework that enables decision makers to identify risks, determine potential paths of their diffusion, and devise appropriate mitigation strategies.

Computational Analysis and Visualization of Global Supply Network Risks

Management of supply network risks is a critical competency for todays global enterprises. Current practices and tools, however, have limited capabilities and do not allow for systemic exploration of alternate risk strategies. We develop a computational model of risk diffusion in global supply networks that is grounded in techniques from complex systems, network analysis, and epidemiological risk modeling. We draw on a unique, curated dataset of firms, their supply networks, and financial risk in the global electronics industry. Specifically, we assess and visualize the impact of network structure on risk diffusion and supply network health, and determine the impact of visibility on reduction and potential mitigation of cascading risks. Our approach enables decision makers to identify risks and determine potential paths of their diffusion. In doing so, we advance our understanding of the design and development of computational risk management tools in a global supply network context.

Challenges and Opportunities for Enterprise Transformation Research

This article summarizes the activity of the First International Workshop on Enterprise Transformation, hosted by the Tennenbaum Institute at the Georgia Institute of Technology in March 2013. The workshop brought together researchers (faculty and students) from a wide range of disciplines (e.g., engineering, management, computing, and social science) and institutions to (1) discuss and define the scholarly challenges and opportunities for enterprise transformation research and (2) facilitate the development of an emerging interdisciplinary academic community. The results of the workshop highlight the particular complexities of conducting enterprise transformation research in an academic context and identify both near- and long-term opportunities for impactful future research.