Global Supply Chain Network Research Articles

Global reverse supply chain design for solid waste recycling under uncertainties and carbon emission constraint

The emergence of concerns over environmental protection, resource conservation as well as the development of logistics operations and manufacturing technology has led several countries to implement formal collection and recycling systems of solid waste. Such recycling system has the benefits of reducing environmental pollution, boosting the economy by creating new jobs, and generating income from trading the recyclable materials. This leads to the formation of a global reverse supply chain (GRSC) of solid waste. In this paper, we investigate the design of such a GRSC with a special emphasis on three aspects; (1) uncertainty of waste collection levels, (2) associated carbon emissions, and (3) challenges posed by the supply chain’s global aspect, particularly the maritime transportation costs and currency exchange rates. To the best of our knowledge, this paper is the first attempt to integrate the three above-mentioned important aspects in the design of a GRSC. We have used mixed integer-linear programming method along with robust optimization to develop the model which is validated using a sample case study of e-waste management. Our results show that using a robust model by taking the complex interactions characterizing global reverse supply chain networks into account, we can create a better GRSC. The effect of uncertainties and carbon constraints on decisions to reduce costs and emissions are also shown.

The robustest clusters in the input\u2013output networks: global hbox {CO}_2 emission clusters

Finding environmentally significant clusters in global supply-chain networks of goods and services has been investigated by Kagawa et al. (Soc Netw 35(3):423–438, 2013a; Econ Syst Res 25(3):265–286, 2013b; Glob Environ Chang, 2015), using the popular clustering method of nonnegative matrix factorization, which actually yields sensitive cluster assignments. Due to this sensitivity issue, there is a danger of overfitting of the results. In order to confirm the robustness of the obtained clusters, which in fact have strong implications for international climate change mitigation, especially for the US-induced Chinese clusters, we design a simulation-based experiment. Empirical findings of the proposed approach are compared with those of Kagawa et al. (Glob Environ Chang, 2015). The environmental implications are reported as well.

Networked liabilities: Transnational authority in a world of transnational business

The proliferation of production networks and cross-border contracting is frequently cited as empowering globally active corporations to skirt, and shape, national regulations. While scholars often focus on the political gains from these new forms of business organization, we shift the conversation to the potential political costs of global firm reorganization. The spread of corporate subsidiaries and global supply-chain networks leave firms vulnerable to a host of jurisdictional claims, and by targeting a domestically rooted affiliate, states can bring the global practices of the multinational corporation in line with their interests. In other words, states can take advantage of the transnationalization of the firm to transnationalize their authority beyond traditional jurisdictional boundaries. We label this process “networked liabilities.” Specifically, the combination of a firm’s sunk costs and the country’s jurisdictional substitutability determines the ability of governments to exert demands on multinational corporations. A key contribution of the article is to better specify the relationship between mobility and authority and to illustrate that networked liabilities can further empower a variety of states beyond traditional economic powers like the US or the European Union. We further highlight when firms may curtail the authority of great powers. The growing reach of the regulatory state domestically, coupled with the transnationalization of the firm, creates an increasing number of tools for certain governments to engage in economic statecraft beyond their borders. Our findings, then, contribute to debates on business–government relations in a globalized world, the changing nature of political risk, and the deterritorialization of state authority.

Impact of application factors of the AEO program on its performance

Purpose In a changing trade landscape, global trade transaction relies on a global supply-chain network. Customs clearance to cross borders is critical to enhancing the competitiveness of both importers and exporters. As such, each country has adopted an authorized economic operator (AEO) program to promote the security of both imported and exported cargo as well as expedite freight movements. The purpose of this paper is to discover the factors which should be taken into account to utilize an AEO program, and to look at the causal relations between these factors. Design/methodology/approach This study conducted a survey on 201 AEO programs in Korea. With partial least squares, the structure model is tested using the coefficient value of the determination of the dependent variable, explained by the sign and scale of the path coefficient, statistical significance, and leading variable. Moreover, this study performed bootstrap re-sampling to verify all paths and significance. Findings It was found that AEO external pressure, training capacity, and sustainability are shown to have a significant impact on AEO performance. Furthermore, for the group with a high level of AEO application, training capacity and AEO sustainability are shown to have a greater effect on AEO performance. For the group with a low level of AEO application, internal regulation is shown to have a bigger impact on AEO performance. Originality/value This study sets itself apart from previous ones in that it examines AEO application for trade security and facilitation with regard to customs, which would affect global supply-chain management.

BLOCKCHAIN READY MANUFACTURING SUPPLY CHAIN USING DISTRIBUTED LEDGER

The blockchain technology as a foundation for distributed ledgers offers an innovative platform for a new decentralized and transparent transaction mechanism in industries and businesses. The inherited characteristics of this technology enhance trust through transparency and traceability within any transaction of data, goods, and financial resources. Despite initial doubts about this technology, recently governments and large corporations have investigated to adopt and improve this technology in various domains of applications, from finance, social and legal industries to design, manufacturing and supply chain networks. In this article, the authors review the current status of this technology and some of its applications. The potential benefit of such technology in manufacturing supply chain is then discussed in this article and a vision for the future blockchain ready manufacturing supply chain is proposed. Manufacturing of cardboard boxes are used as an example to demonstrate how such technology can be used in a global supply chain network. Finally, the requirements and challenges to adopt this technology in the future manufacturing systems are discussed.

A facility location model for global closed-loop supply chain network design

Forward and reverse supply chains form a closed-loop supply chain. In this paper, a mathematical model is proposed for a closed-loop supply chain network by considering global factors, including exchange rates and customs duties. The model is a multi-objective mixed-integer linear programming model under uncertain demand. A solution approach based on fuzzy programming is developed for solving the optimization problem. The model is then applied in a network, which is located in Southwestern Ontario, Canada. A sensitivity analysis is provided to validate the model. This model considers global factors, multi-objectives, and uncertainty simultaneously in a closed-loop supply chain network.

Multienterprise supply chain: Simulation and optimization

The advancements in connectivity among the entities belonging to industrial supply chain have given rise to more complex, global supply chain networks. These networks are often constituted of entities that belong to multiple such networks. Interactions among the entities in such networks are also influenced by whether they belong to the same enterprise or different ones. This work takes into consideration the effect of such interactions. The entities belonging to different enterprises are assumed to interact through auctions. An agent based simulation model that incorporates such auctions is used to represent multienterprise supply chain networks. The dynamics of the supply chain affected by the auction mechanism are investigated. Also a derivative free optimization methodology is proposed to find the optimal warehouse capacities for the minimization of total cost. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3392–3403, 2016

OM Forum—Benchmarking Global Production Sourcing Decisions: Where and Why Firms Offshore and Reshore

Problem definition: Manufacturing firms are undergoing restructuring defined by a collection of adjustments and decisions, which affect the source and destination of manufactured products throughout the firm’s global supply chain network. We report on a comprehensive picture of manufacturing sourcing on a global basis. Academic/practical relevance: With dynamic changes in global economic, political, and technological conditions, the design of global supply chain strategies has become critically important for executives and has great potential for operations management research. Methodology: Our work is based on a global field study conducted in 2014 and 2015 among leading manufacturers from a wide range of industries. The data set has the distinguishing feature of reflecting actual decisions that the firms made recently (during the last three years). Results: Companies are currently restructuring their global production footprints. The majority of firms engage in offshoring. Reshoring does occur but seldom for corrective reasons. China remains the most attractive site for production sourcing, followed by Eastern Europe and Southern Asia. Manufacturing continues to decline in the developed economies of Japan and Western Europe. We observe that while North America may be at the cusp of a manufacturing renaissance, such a change is not just because of reshoring by domestic firms. Labor cost no longer dominates manufacturing location decisions; rather, firms decide based on complex trade-offs among a variety of factors. Finally, firms localize production in developed economies and use developing economies as production hubs. Managerial implications: Our goal in this paper is to inform both managerial policy decisions and the academic research agenda by developing insights on managerial practices that concern production sourcing and on the factors that drive such decisions. We develop hypotheses concerning how firms make these strategy decisions, and we discuss implications for analytical and empirical research.

Visualization of Innovation in Global Supply Chain Networks

ABSTRACTThis 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.

Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study

A mixed-integer, non-linear model is developed for designing robust global supply chain networks under uncertainty. Six resilience strategies are proposed to mitigate the risk of correlated disruptions. In addition, an efficient parallel Taguchi-based memetic algorithm is developed that incorporates a customized hybrid parallel adaptive large neighborhood search. Fitness landscape analysis is used to determine an effective selection of neighborhood structures, while the upper bound found by Lagrangian relaxation heuristic is used to evaluate quality of solutions and effectiveness of the proposed metaheuristic. The model is solved for a real-life case of a global medical device manufacturer to extract managerial insights.

Predicting Future Inbound Logistics Processes Using Machine Learning

Manufacturing industry is highly affected by trends of globalization and increasing dynamics of product life-cycles which results in global supply chain networks. For inbound logistics, a high variance of parts from different suppliers and locations needs to be delivered to the assembly line. Planning these inbound logistics processes depends on frequently changing information of product development, assembly line planning and purchasing. Currently, a high amount of time is spent for gathering information during planning and existing knowledge from previous planning processes is scarcely used for future planning. Therefore, this paper presents an approach for predictive inbound logistics planning. Using machine learning, generic knowledge of logistics processes can be extracted and used to predict future scenarios.

Global Supply Chain Network Design for Lower Material-based CO2 Emissions and Costs between Developed and Emerging Countries

Global Supply Chain Network Design for Lower Material-based CO2 Emissions and Costs between Developed and Emerging Countries

Systems perspective of the primary aluminum supply chain: Unintended consequences of participant policies

Supply chains have been proposed as complex adaptive systems. This paper looks at the global aluminum supply chain network in those terms. Developments in this industry have included formation of a cartel by bauxite producing countries, emergence of Australia as a leading producer, the collapse of communism in Europe, and the rise of Chinese production in all phases of primary aluminum production. Complex adaptive systems literature is reviewed, and the world aluminum production system described. This includes identification of system elements, their relationships, interactions, and developments. Analysis in terms of how this production system exhibits complex adaptive systemic behavior across the supply chain is provided. The decentralized behavior of the overall primary aluminum system provides understanding of how individual agents, be they multinational firms, individual governments, or cartels are unable to totally control the system in the long run.

Preface to the special feature

The world economy is changing at an increasing pace in the wake of the ongoing digital revolution. Modern information and communication technologies (ICT) strengthen forces of global flows of goods, people, information, and finance. We live in an increasingly interconnected world in which infrastructures composed of different techno-social system layers. Examples include transportation and mobility infrastructures, global supply chain networks, and financial networks. Many studies analyze the socioeconomic systems such as cascading failures and financial stability issues using network theory and agent-based modeling. The financial crises, for instance, triggered many studies about systemic risk caused by contagion effects via the interconnections in the global financial networks. Network analysis provides powerful mathematical tools for analyzing the global circulation of goods, resources, people, money, and information. The accessibility of new data and the advances in theory and modeling are providing an integrated framework that brings us closer to analyzing the behavior of socioeconomic systems from a new perspective. An agent-based approach has also proven useful in many applications. Agent-based modeling provides answers to questions where traditional analysis methods are weak, and it is leading to improved models across wide types of financial risks. This special issue is being launched at a time of ever-increasing connectivity and complexity in socioeconomic networks. The first article in the issue, ‘‘Towards capturing heterogeneity of supply network structures and their temporal transitions: an investigation of supply relationships in the Japanese automobile industry’’ by Tomomi Kito and Steve New, consider connectivity among car manufacturers (OEMs) and auto-parts suppliers in the

Integrating Operational Hedging of Exchange Rate Risk in the Optimal Design of Global Supply Chain Networks

Supply chain network (SCN) design and operation is a strategic and value adding process for all synchronous companies. In the face of globalization, several issues should be contemplated and incorp...

CO2 emission clusters within global supply chain networks: Implications for climate change mitigation

Production and consumption of goods and services are interlinked through complex global supply-chain networks; so are the greenhouse gas emissions associated with them. Using a model that represents global supply-chain networks, we identified supply-chain clusters with high CO2 emissions within more than 300 million individual supply chains. We distinguished 4756 significant CO2 clusters and found that in 2008, global supply-chain networks associated with U.S. transport equipment and construction demand included relatively large CO2 clusters in China, accounting for 17% and 10%, respectively, of the U.S. CO2 footprint. Of added importance is the fact that these two clusters in China had annual growth rates of 42% and 58%, respectively, during the period 1995–2008. Our results show the importance for climate policy of monitoring these CO2 clusters that dominate CO2 emissions in global supply chains, and they offer insights on where climate policy can be effectively directed.

A Robust Competitive Global Supply Chain Network Design under Disruption: The Case of Medical Device Industry

In this study, an optimization model is proposed to design a Global Supply Chain (GSC) for a medical device manufacturer under disruption in the presence of pre-existing competitors and price inelasticity of demand. Therefore, static competition between the distributors’ facilities to more efficiently gain a further share in market of Economic Cooperation Organization trade agreement (ECOTA) is considered. This competition condition is affected by disruption occurrence. The aim of the proposed model is to maximize the expected net after-tax profit of GSC under disruption and normal situation at the same time. To effectively deal with disruption, some practical strategies are adopted in the design of GSC network. The uncertainty of the business environment is modeled using the robust optimization technique based on the concept of uncertainty budget. To tackle the proposed Mixed-Integer Nonlinear Programming (MINLP) model, a hybrid Taguchi-based Memetic Algorithm (MA) with an adaptive population size is developed that incorporates a customized Adaptive Large Neighborhood Search (ALNS) as its local search heuristic. A fitness landscape analysis is used to improve the systematic procedure of neighborhood selection in the proposed ALNS. A numerical example and computational results illustrate the efficiency of the proposed model and algorithm in dealing with global disruptions under uncertainty and competition pressure.

Disentangling diversification in supply chain networks

We propose a model for the quantification of business disruption risk in a global supply chain network. To calculate the loss distribution induced by supply chain disruptions for a focal firm, we apply a bottom-up modeling approach. On the firm level, we model production disruptions of various hazard events in reduced form. We incorporate the network structure explicitly and define the loss propagation between the firms. Via Monte Carlo simulation, we analyze the effects of different model specifications and network structures on the loss distribution of the focal firm. We show that diversification effects can lead to counterintuitive results when we consider the network structure and the correlations of hazard events. Our methodology and findings enable more informed and transparent decisions for supply chain design.

Modeling and Balancing for Costs and CO2 Emissions in Global Supply Chain Network among Asian Countries

The amount of CO2 emissions in production and logistics has been increasing in not only developed countries but also emerging countries, especially Asian countries such as Malaysia and China which have been achieved remarkable economic growth. For global warming, these emerging countries also play an important role to reduce the CO2 volumes, therefore, it has been more important to design a low-carbon supply chain including the Asian countries by balancing not only costs but also the CO2 volumes. This study models and designs a global supply chain network including these Asian countries for balancing the costs and the CO2 volumes in production and logistics. The research defines a mixed integer programming (MIP) problem to satisfy not only the demand of the market for finished products but also the reduction ratio of the environmental impact by determining the supplier and factory location between developed and emerging countries.

Multi Criteria Simulation Model for Lead Times, Costs and CO2 Emissions in a Low-carbon Supply Chain Network

Recently founded manufacturing companies have been increasing overseas production in order to decrease local production cost, especially in East and Southeast Asian countries such as China and Malaysia, and a global supply chain network is now being constructed not only in developed but also in emerging countries. Furthermore, in order to prevent global warming, a low-carbon supply chain has been required to reduce CO2 emissions in materials/parts production. However, the overseas production essentially brings a longer logistics lead time, and emerging countries are more sensitive in considering uncertainties such as fluctuating lead time. Therefore, the low-carbon supply chain should be constructed and evaluated by multi criteria for the lead time, costs and CO2 Emissions. This study models a low-carbon supply chain network between Malaysia, China and Japan on a discrete event simulation, evaluates multi criteria decisions for the lead times, costs and CO2 emissions, and analyzes the effect of the fluctuating lead time.