Characteristics Of Supply Chain Research Articles

Food safety risk assessment in Vietnam - Current situation and way forward

Risk assessment is an important scientific step in risk-based food safety (FS) management that has been applied in many countries. In Vietnam, despite being regulated by law, risk assessment activities have not been widely implemented due to inadequate attention and limited resources, which reduces its roles in FS management. Several challenges of FS risk assessment in Vietnam are related to institutional organizations, data management, human resources, and the characteristics of the food supply chain. This article aims to review the progress of risk assessment activities in Vietnam. Different risk assessments have been conducted for various chemical hazards such as pesticides, mycotoxins, preservatives, heavy metals, and environmental residuals, whereas fewer risk assessments have been implemented for microbial hazards, which were mainly focused on common food poisoning pathogens, like Salmonella, Staphylococcus aureus, and E. coli. This article also analyzes risk assessment models from countries and regions such as China, Japan, the United States, Europe, and ASEAN in order to identify the issues and challenges in Vietnam. Based on the review and analysis, we recommend that Vietnam take action to implement risk assessment activities as a tool for effective FS management.

Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry

China's automotive industry, the world's largest producer and consumer, has reached a crucial stage in its transition from rapid expansion to high-quality and low-carbon development. Considering the decarbonization of the whole automotive industry, in addition to reducing the CO2 emissions from fuel supply and exhaust pipes, which account for 65–80 % of the total value chain CO2 emissions, the automotive industry should also accelerate the decarbonization of raw materials, which contribute to 18–22 % of these CO2 emissions. Many automotive manufacturers are collaborating with steel producers on green steel initiatives due to the high CO2 emissions from steel production, the integrated nature of the steel supply chain, and the need for early planning in low-carbon steel production routes transformation. To clarify the carbon emission characteristic of the automotive steel supply chain, this research establishes a mathematical method for calculating cradle-to-gate carbon footprint of automotive steel product based on BF (Blast furnace)-BOF (Basic oxygen furnace), Scrap-EAF (Electric arc furnace), and DRI (Direct reduced iron)-EAF steel production routes. The cradle-to-gate carbon footprints of BF-BOF, Scrap-EAF, and DRI-EAF steel production routes are 1711.84 kgCO2/t-sp (steel product), 916.39 kgCO2/t-sp, and 2738.53 kgCO2/t-sp. A projection of CO2 emissions in automotive steel supply chain from 2020 to 2060 has been investigated, taking into account production structure adjustment, scrap recycling, and low-carbon electricity adoption, as well as the demand for automotive steel products. Projections from 2020 to 2060 indicate that the CO2 emission intensity of the automotive steel supply chain will decrease by 28.25 % by 2030 and 93.99 % by 2060, with total emissions dropping by 28.47 % and 96.92 %, respectively. This research identifies effective decarbonization measures in the automotive steel supply chain, including internal and end-of-life (EOL) steel scrap recycling, which offer significant CO2 emissions reduction without increased costs, demonstrating high cost-effectiveness. In a word, this research provides a technical framework and data foundation for decarbonizing the automotive steel supply chain.

Research on Topology Optimization of Building Digital Supply Chain Based on Genetic Neural Network

In order to maximize the benefit of building supply chain, the topology optimization method of building digital supply chain based on genetic neural network is studied. According to the overall structural characteristics of the building digital supply chain, customer demand data, supplier sales data, manufacturer production management data, and environmental policy exception data are collected to form a building digital supply chain data set. As input data, a building digital supply chain demand prediction model based on improved genetic LSTM neural network is constructed. Capture the needs of the building digital supply chain; according to the demand of suppliers, manufacturers and customers in building digital supply chain, a nonlinear 0–1 mixed integer programming model based on the newsboy model is established. According to the various information provided by the supplier, the ant colony algorithm is used to calculate the optimal supplier. After all suppliers are identified, the topology of the digital supply chain is constructed. So far, the optimization of the supply chain has been completed. The experimental data show that this method can accurately predict the demand of construction projects, the maximum error is less than 1.5%, and can obtain the best supplier selection results. Compared with before optimization, the profit of the structural digital supply chain after topology optimization increases the most.

Supply chain risk management (SCRM) process: an analysis in the aerospace industry

PurposeThe study analysed the aerospace industry, a traditionally important sector for the topic of risk management, from three complementary perspectives: the supply chain risks present in the sector, the mitigation strategies adopted to face them, and the characteristics (dimensions) observed in the SCRM process of aerospace companies.Design/methodology/approachThe research employed a quali–quantitative method: a survey was carried out, followed by interviews with professionals from companies belonging to different tiers of aerospace supply chains. Interviews helped to interpret the survey data and understand in more detail risk management in aerospace companies.FindingsThe study presents a panorama of the aerospace industry in terms of risk management. The sector’s turbulent environment is described as well as the strategies to prevent, minimise or postpone the impact of supply chain risks. In particular, ten dimensions that have been identified in the SCRM process of aerospace firms are discussed. These characteristics influence the objectives of this process and are related to resources, roles and responsibilities, incentives, development of competences and skills, scope (internal and external) and approaches to integrate decisions and actions in the context of the supply chain.Originality/valueArticles that address the SCRM process usually focus on the process steps, whereas this study investigated dimensions that transcend these steps but whose discussion in the literature is still fragmented. It also analysed a reference sector for the topic from a broader perspective than others available in the literature (supply chain risks, mitigation strategies and characteristics of the SCRM process). Supply chain members with relationships with each other were investigated, a desirable approach for SCRM but still under-explored. The study also answers calls for industry-specific studies and research on emerging countries.

Do Supply Chain Characteristics Influence a Rival Firm's Responses to a Focal Firm's Product Preannouncements? A Competitive Dynamics Perspective

ABSTRACTThis study investigates how supply chain characteristics influence a rival firm's response to a focal firm's product preannouncements from a competitive dynamics perspective. Indeed, many firms recognize that it is critical to leverage their supply chains to gain a competitive advantage. We propose that common suppliers enhance a rival firm's awareness of the focal firm's credibility, reducing competitive responses. In addition, a rival firm's strong supplier inventory performance will motivate rivals to respond more aggressively, while the rival's supply–chain partnerships enhance its capability to react to the focal firm. Using panel data from S&P 1500 firms between 2007 and 2015, our findings provide support for our hypotheses, illustrating that supply chain characteristics can significantly influence a rival firm's responses to the focal firm's preannouncements. This research contributes to the competitive dynamics and supply chain management literature by highlighting the strategic role of supply chain characteristics in interfirm competition, offering practical insights for managers on leveraging supply chain resources to effectively navigate competitive threats.

Virtual warehousing through digitalized inventory and on-demand manufacturing: A case study

Novel digital on-demand manufacturing technologies provide a significant opportunity to support development of virtual warehousing and in turn improve supply chain performance. However, the implementation of virtual warehouse comes with a set of challenges, especially where the objective is to virtually warehouse standard or legacy parts that have been developed and verified initially for conventional (non-digital) manufacturing. In this paper, we explore the key elements required for successful implementation of a virtual warehouse for legacy parts based on a combination of part digitalization, on-demand manufacturing, and part validation. Our proposed framework for adoption of virtual warehouse includes development of a digital inventory which includes supply chain and manufacturability data, identification, and selection of suitable parts for on-demand manufacturing, selection of on-demand manufacturing technology, fit-for-purpose validation of the parts. Our framework is exemplified through a case study, and we conclude that the building of an effective virtual warehouse requires several enablers, including availability of digital data about technical and supply chain characteristics of parts, but also a suitable part identification tool. This part identification tool needs to be flexible to include comparison with reference parts already produced by different on-demand manufacturing technologies.

How to configure the supply chain to stimulate firm innovation performance?

Supply chain characteristics are an important driving force for innovation at the focal firm. Previous research has separately examined the impact of structural, relational, and capability dimensions of the supply chain on firm innovation. Relying on the structure-relationship-capability framework, this study explores the configurational impact of geographical distance, business concentration, and partner innovation of both the supplier-base and the customer-base on firm innovation. Necessary causality analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) are employed. Based on a dataset of 123 Chinese listed firms in high-tech manufacturing sectors, we provide novel insights on the antecedent configurations of the partner characteristics in both ends of supply chains for facilitating firm innovation. Our findings indicate that there are no necessary conditions for high firm innovation performance. We identify three distinct paths - namely, innovation-driven, customer-dominated, and relationship-driven configurations - that consistently lead to high firm innovation performance. From a configurational perspective, this research contributes to the innovation and supply chain literature and provides practical implications for managers to facilitate firm innovation.

Principles of Economic Externality Dynamics Economic Dynamics and the Standard Model (V)

The present paper discusses the importance of economic externality and the economic phenomena involved. Section 1 draws on the framework of weak force theory in physics, we propose a new approach of dynamic analysis for economic externality. From a mesoscopic (intermediate scale) perspective, no distinction is made between the macro-demand and individual micro-buyers nor between the macro-supply and individual micro-sellers. Section 2 applies the isospin modeling method to construct two economic isospin models. One is between the achieving impulse and the fear-of-failure impulse, under the effect of economic externality. The other is between the market behavior and market residues, namely, market aftertaste. Section 3 discusses the microstructural properties of the market, including Dirac's equation and the market, Dirac γmatrix notation, and the chirality and spin structure of market components. Section 4 discusses the helical structural characteristics of supply chains, including CPT theorems, Penrose zigzag helical processes, and several modeling directions of economic externality and buyer-seller interactions (weak interactions). Section 5 discusses the economic externality and the electroweak model, including extensive externality, externality mediations with Weinberg rotations, and economic analysis using lepton weak currents, including the analysis of lepton neutral weak currents. Finally, Section 6 provides a general discussion on the standard model of economic dynamics.

Facility Location Problem: Modeling Joint Disruptions Using Subordination

We study the facility location problem with disruptions where the objective is to choose a set of locations that minimizes the sum of expected servicing and setup costs. Disruptions can affect multiple locations simultaneously and are caused by multiple factors like geography, supply chain characteristics, politics, and ownership. Accounting for the various factors when modeling disruptions is challenging due to a large number of required parameters, the lack of calibration methodologies, the sparsity of disruption data, and the number of scenarios to be considered in the optimization. Because of these reasons, existing models neglect dependence or prespecify the dependence structures. Using partially subordinated Markov chains, we present a comprehensive approach that starts from disruption data, models dependencies, calibrates the disruption model, and optimizes location choices. We construct a metric and a calibration algorithm that learns from the data the strength of dependence, the number of necessary factors (subordinators), and the locations each subordinator affects. We prove that our calibration approach yields consistent estimates of the model parameters. Then, we introduce a variant of the standard approach to the underlying optimization problem, which leverages partially subordinated Markov chains to solve it quickly and precisely. Finally, we demonstrate the efficacy of our approach using twelve different disruption data sets. Our calibrated parameters are robust, and our optimization algorithm performs better than the simulation-based algorithm. The solutions from our model for disruptions have lower costs than those from other disruption models. Our approach allows for better modeling of disruptions from historical data and can be adapted to other problems in logistics, like the hub location, capacitated facility location, and so on., with joint disruptions. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0103 .

Identification of Key Risk Nodes and Invulnerability Analysis of Construction Supply Chain Networks

The construction supply chain confronts interruption risks that raise significant concerns regarding industry safety and stability. Consequently, exploring risk management strategies from both enterprise and supply chain network perspectives is crucial. This study employs complex network theory and the cascade failure model to propose a methodology tailored to the unique characteristics of the construction supply chain, facilitating the identification of key risk nodes and the conduct of invulnerability analyses. By evaluating the importance of construction enterprise nodes and their risk propagation ability during cascade failures, this method enables the comprehensive identification of key risk node enterprises within the construction supply chain network. Furthermore, this study examines and discusses strategies for enhancing network invulnerability by taking into account node capacity, load, and resilience. Empirical results indicate that the key nodes and risk nodes in the construction supply chain network are mainly located upstream and downstream, displaying specific distribution patterns. In addition to core enterprises, key risk nodes comprise some strong suppliers at the intermediary and lower tiers of the supply chain. Adjustments to node enterprise parameters like capacity, load, and resilience have diverse impacts on the invulnerability of the construction supply chain network. This study clarifies the distribution patterns of key risk nodes within the construction supply chain network and the variations in network invulnerability under particular conditions, providing valuable insights for risk management decision-making.

Life after use: circular supply chains for second-life of electric vehicle batteries

Despite the increasing interest in second-life of electric vehicle batteries, the characteristics of supply chains to support such products are yet to be developed. The purpose of this paper is to investigate the key supply chain characteristics required to effectively accommodate circular models for second-life electric vehicle batteries. Through a longitudinal case study, we map possible application areas and customer segments, necessary key activities, and potential actors that might emerge in future supply chains for these products. The findings are discussed in relation to product-oriented, use-oriented, and result-oriented circular models. The suggested circular models and their comparisons provide insights into how different supply chain dimensions are configured for different circular business models, and the advantages, disadvantages, and prerequisites associated by each model.

Spraying for the beauty: Pesticide use for visual appearance in apple production

AbstractPesticides are used to reduce yield losses and to enhance the visual quality of products. However, pesticide use raises concerns due to negative health and environmental effects, hence ambitious policy goals for their reduction have been established. Reducing pesticides which mainly focus on visual quality of products could be an efficient strategy to contribute to these goals, without reducing food production. However, the role of “cosmetic” pesticide use is so far not well documented and understood. Here, we quantify cosmetic pesticide use and the influence of supply chain characteristics on their use. We focus on table apple production, where the visual quality of products is a key aspect. Using a sample of 196 apple growers in Switzerland, we find that 23.5%–59.2% of growers use cosmetic pesticides for the apples’ visual appearance. Farms mainly marketing via intermediaries are 23.9‐29.6% more likely to spray cosmetic pesticides for visual purposes compared to farms mainly direct marketing. Our findings highlight the role of supply chains in farmer decision‐making, recommending a decrease in the focus on visual product quality, especially in retail environments, thus minimizing unnecessary and irreversible risks of pesticide exposure by farmers without compromising food security.

Research on the Application of Green Supply Chain Management: Based on SCOR Model

This paper takes Apple Inc. as the research object and explores the green supply chain management issues based on the SCOR model. By combining the SCOR model through the theoretical framework and the characteristics of Apple's supply chain, management practice suggestions are made to reveal Apple's green performance in terms of environment, resources, and social responsibility. The study results show that Apple performs better in green procurement and marketing, but is slightly inferior in green recycling storage, and transportation. This provides valuable ideas for Apple's subsequent industrial sustainable development strategy, as well as lessons and references for other companies and industries, helping to promote the green development of the entire supply chain industry. In the future, it will be a key area to continue in-depth research on promoting and optimizing green supply chain practices in different industries and enterprises of different sizes.

Research on the Resilience Assessment of Cross-border E-commerce Supply Chains under the RCEP Agreement

Under the RCEP (Regional Comprehensive Economic Partnership) agreement, cross-border e-commerce supply chains face the multiple risks that can lead to supply chain disruptions, severely affecting a nation's economic security, trade stability, and international market competitiveness. Enhancing supply chain resilience is a key method to address supply chain disruptions. This study, based on an analysis of the characteristics of cross-border e-commerce supply chains, utilizes Grounded Theory and Social Network Analysis to construct an evaluation indicator system. The resilience indicator system for cross-border e-commerce supply chains under the RCEP agreement developed in this study aids in the efficient and stable development of businesses.

효율적 및 반응적 공급사슬 구성 제조기업의 제3자 물류기업 선정요인의 우선순위와 가중치 분석

Using AHP, it is to clearly analyze that there is a difference in the importance and weight of the selection criteria factors that should be applied first in the selection of a third-party logistics company depending on the characteristics of the product and supply chain from the viewpoint of Korean manufacturing companies. For this purpose, previous studies that presented factors for selecting third-party logistics companies were reviewed. As a method of integrating the presented selection criteria, 4 items of ‘logistics service’, 3 items of ‘logistics information (IT) system’, 4 items of ‘logistics price (cost)’, 5 selection criteria of 3 items of ‘Corporate Reputation’ and 6 items of ‘Capacity and Infrastructure’ and 20 application items were selected. And using these contents, a survey was conducted on manufacturing companies.
 Survey results As a questionnaire that can be used for AHP analysis, 51 companies in the efficient supply chain group and 35 companies in the reactive supply chain group were collected. The priority and weight of the selection criteria and application items were determined by performing pairwise comparisons on Tier II selection criteria and Tier III application factors, and calculating overlapping weights.
 The priority and importance of the Tier II selection criteria and the Tier III application factors were confirmed, and the weights for the selection criteria and application items that should be applied preferentially were calculated by synthesizing them. In the efficient supply chain group, the importance of stability, service price, image, cost reduction, accuracy, financial stability, and compatibility was high. In the reactive supply chain group, the importance of stability, accuracy, image, service price, information capability, compatibility, and incentives was high. Through these research results, by reflecting the characteristics of product manufacturing and supply chain, selection criteria and application items that should be applied first when manufacturers select third-party logistics companies are clearly presented.

EU27 regional trade networks for medical products in fight against Covid-19 pandemic: Quantifying vulnerability and self sufficiency in critical inputs.

The Covid-19 pandemic spread fast due to a lack of vaccines and a severe shortage of medical products to treat and combat the disease. Many studies have focused on the characteristics of extant global supply chains and trade networks that are determined by globalization drives for production to low-cost countries and the technological complexity of products with many components distributed globally. This, along with the lockdown of many sectors and national policies that divert exports for domestic use, are reasons for lack of access, especially, in Western countries to these products. Governments adopted policies that aim to mitigate vulnerability to imports of critical medical products that include self-sufficiency measures such as increased domestic production, stockpiling and reduction of exports. However, there is as yet no quantitative way to assess if a country's vulnerability to critical imports has been reduced by such drives for self-sufficiency, when other countries in the trade network follow similar policies. For this we develop a Google PageRank style centrality measure based on the Markose-Giansante eigen-pair method for a specially constructed global bilateral trade network to assess the vulnerability of net importers of critical medical products when they attempt to mitigate it by regional or domestic buffers. We use the network vulnerability centrality measure to quantify the regional self-sufficiency for EU27 countries over 2019-2021 for four Covid-19 critical medical products, viz. facemasks, personal protective equipment, ventilators and hand sanitizers. Despite, growth in value and share of intra-EU regional trade in most of these products by 2021, some countries did not achieve the reduction of vulnerability centrality.

Service-oriented supply chain: what do we know about its risks?

ABSTRACT This study identifies the risks entailed in a service-oriented supply chain. By employing supply chain mapping, contingency, and Risk Breakdown Structure (RBS) theories to elaborate a picture of the current knowledge, we were able to summarise and categorise the various risks into three main levels of cause. Next, these literature-based risks were narrowed down into a specific industry context and were then tested and confirmed using exploratory factor and confirmatory factor analyses to form an industry-oriented RBS for the construction business. The data were collected from 195 firms who participated in a large-scale survey sponsored by the Japanese Government to promote sustainable socio-economic development for the ASEAN region. As a result, seven risk categories related to demand, supply, operations, information, finance, time (delays) and external sources (human-made or natural-related) were identified and will be a valuable reference for researchers and practitioners. Furthermore, the relationship between identified risk and supply chain performance was explored. This paper is the first to introduce the concept and characteristics of a service-oriented supply chain by using a systematic review combined with a bibliometric mapping of the literature and an empirical study to generate both generic and industry-oriented RBSs in a single study.

Digital capabilities to manage agri-food supply chain uncertainties and build supply chain resilience during compounding geopolitical disruptions

PurposeThe agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.Design/methodology/approachThe authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.FindingsDownstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.Originality/valueThis study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

Podsticanje održivog razvoja i inovacija u tekstilnoj industriji kroz upravljanje cirklularnim lancima snabdevanja

This study explores the integration of circular supply chain management (CSCM) principles within the textile industry to drive sustainable innovation. Through a systematic literature review, this paper aims to dissect the components of CSCM that contribute to sustainability, assess the practical outcomes of circular practices in textile companies, and identify the barriers and enablers affecting CSCM adoption. The research questions focus on understanding the characteristics of circular supply chains in the textile sector, the real-world application and outcomes of these principles, the factors influencing the adoption of circular practices, and the implications for sustainability metrics. This review aims to provide a comprehensive overview of how CSCM can foster environmental, economic, and social sustainability in the textile industry, offering insights for businesses, policymakers, and researchers seeking to promote a more sustainable future.

An analysis of pipe spool supply chain in shipbuilding using 2-stage queuing model and discrete event simulation

Pipe spool supply in Korean shipbuilding industry consists of a complex supply chain comprising manufacturing and painting vendors. Major Korean shipyards with the most competitive edge have applied various policies and techniques to control the pipe spool supply chain and prevent production delays related to supply delays in pipe spools. Although research has been done on implementing the policies and techniques, there has been a gap on the theoretical consideration of pipe spool supply chain characteristics using a simulation model. Therefore, this study proposes an analytical method based on queueing model to analyze the characteristics of the pipe spool supply chain and also proposes a simulation model based on discrete event simulation (DES) to verify it. In addition, a numerical experiment using DES for the M/G/1 queuing model is conducted to examine the effect of time variability in the spool supply chain. From the more reliable experimental results, control parameters and management insights to manage the supply chain optimality are proposed and the effectiveness of policies that have been implemented by major shipyards is verified.