Supply Chain Risk Research Articles

Effectiveness of Risk Management Strategies in Mitigating Supply Chain Disruptions in South Africa

Purpose: The aim of the study was to examine the effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa has proven to be critical in maintaining operational stability and ensuring business continuity. In an environment characterized by frequent economic, political, and environmental challenges, robust risk management strategies have become indispensable for South African businesses. These strategies, including risk assessment, diversification of suppliers, implementation of advanced technologies, and development of contingency plans, have significantly enhanced the resilience of supply chains. By systematically identifying and evaluating potential risks, businesses have been able to proactively address vulnerabilities and reduce the impact of disruptions. The use of advanced technologies, such as predictive analytics, real-time monitoring systems, and blockchain, has further strengthened risk management efforts. These technologies provide valuable insights into supply chain dynamics, enable early detection of potential disruptions, and facilitate rapid response measures. As a result, businesses can maintain smoother operations and minimize downtime during unforeseen events. Unique Contribution to Theory, Practice and Policy: Resilience Theory, Resource-Based View (RBV) & Contingency Theory may be used to anchor future studies on effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa. Encourage the adoption of advanced technologies such as Internet of Things (IoT), artificial intelligence (AI), and blockchain for real-time monitoring and supply chain visibility. Practical implementation of these technologies can enhance early detection of disruptions and facilitate rapid response strategies. Foster closer collaboration with suppliers to co-develop robust contingency plans and risk-sharing mechanisms. Practices such as dual sourcing, supplier diversification, and joint risk assessments can build resilience across the supply chain network. Advocate for policies that incentivize resilience-building practices within supply chains. This could include tax incentives for investments in resilient infrastructure, as well as mandatory reporting on supply chain risk management practices to enhance transparency and accountability.

Leveraging an Uncertainty Methodology to Appraise Risk Factors Threatening Sustainability of Food Supply Chain

By diminishing the risk factors associated with the food supply chain (FSC), we have recourse to strengthen the food supply chain's resilience, decrease food waste, and increase its sustainability. Prioritizing and identifying the risk factors impacting the sustainability of the food supply chain is essential for managing uncertainty and averting unfavorable consequences. This study attempts to identify and rank the most significant risks affecting the sustainability of the food supply chain under an uncertain environment. We use the α-Discounting multi-criteria decision-making (α-D MCDM) method for the main three risk factors: the risks of supply, the risks of demand, and the risks of operations. The primary causes of the challenges in assessing the food supply chain's risk elements include inaccurate assessment data, DMs' subjective preferences, and DMs' differing opinions and thoughts about the criteria. Unfortunately, earlier research fell short of fully resolving these issues. A hybrid three-phase neutrosophic MCDM method is proposed by integrating triangular neutrosophic numbers (TNNs), TNN-AHP, and TNN-CoCoSo to close this gap. In this manner, it may efficiently handle ambiguity. The application of the suggested framework is then explored using the top six food and beverage businesses in the world: Nestle (A1), PepsiCo (A2), Coca-Cola (A3), Danon (A4), Anheuser-Busch InBev SA (A5), and Mondelez International (A6). The results show the sustainability rankings from best to worst, which were established on the groups of decision-makers assessments based on the importance of the risk factors that have to be handled. To gain additional insight into the rationale and resilience of this framework, sensitivity evaluation and comparative analysis have been employed in this study.

Allocating Inventory Risk in Retail Supply Chains: Risk Aversion, Information Asymmetry, and Outside Opportunity

Problem definition: Recent global crises have caused unprecedented economic uncertainty and intensified retailers’ concerns over inventory risks. Mitigating inventory risks and incentivizing retailer orders is critical to managing retail supply chains and restoring their norms after severe impacts. We study the allocation of inventory risk using contracts in a retail supply chain with a risk-neutral manufacturer and a risk-averse retailer. We consider two factors that affect the effectiveness of contracting: (1) asymmetric risk aversion information—retailers’ attitudes are typically diverse and unknown to the manufacturer, and (2) uncertain outside opportunity—retailers typically face a volatile external business environment. Methodology/results: With a game-theoretic model that captures the interaction among risk aversion, information asymmetry, and outside opportunity, we derive the contracting equilibrium under two widely adopted risk allocation schemes—push (i.e., the retailer bears the inventory risk) and pull (i.e., the manufacturer bears the inventory risk) contracts. Contrary to the conventional wisdom that pull contracts are more effective in risk mitigation, we show that push contracts may induce larger expected order quantities and achieve the highest supply chain efficiency due to the interaction of asymmetric risk aversion information and risky outside opportunities. We also find that the manufacturer may obtain higher profits with push contracts when both the heterogeneity in the retailer’s risk attitude and the risk of the outside opportunity are sufficiently high. In addition, when the risk of the outside opportunity is in a medium range, the push contract allows the manufacturer to fully eliminate the information rent and achieve the supply chain’s first-best outcomes. We further evaluate the effects of product profitability and demand uncertainty and generalize the retailer’s risk measure to any coherent risk measure. Managerial implications: Our analysis highlights the importance of modeling asymmetric risk aversion information and risky outside opportunities in analyzing supply chain contracting. When considering these practical factors, allocating more inventory risks to a risk-averse retailer may be better than a risk-neutral manufacturer. Our results provide novel insights into the selection of proper contract types for managing inventory risks in retail supply chains. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0624 .

Resilience Strategies in Sustainable Supply Chain Management: Bibliometric Analysis and Future Research Directions

The emergence of the volatile, uncertainty, complexity, and ambiguity (VUCA) has adversely affected the supply chain network's resilience. The risks and difficulties presented by the VUCA environment can harm an organisation's performance. The project stakeholders are highly encouraged to prioritise sustainability, adaptability, and resilience while considering the constantly changing, volatile, and uncertain climate. Thus, Sustainable Supply Chain Management (SSCM) is a strategic response to the challenges the VUCA environment poses. Contracting firms can expand their capacity to mitigate risks, negotiate volatility, and generate long-term value for all stakeholders by integrating sustainability concepts into supply chain operations. However, SSCM become problematic because of diverse global supply chain disruptions and sustainable demands. Understanding the trends in this topic is crucial to discovering the pattern of resilience strategies in sustainable supply chains. The current literature is reviewed in this study, focusing on studies conducted between 2006 and 2024. The Scopus database and the VOS viewer software were used to arrange a systematic literature review and provide an overview of this field. One hundred fifty-nine (159) publications on resilience, risk management and SSCM were identified and written by hundred and nine (109) authors from forty-four (44) countries. The top number of publications was from Iran, with thirty-eight (38), followed by the United States, with twenty-six (26). The most frequently used keywords are sustainability, supply chain management, supply chains, and sustainable development, reflecting the current significant research direction. Standard bibliometric indicators were utilised in this study, and data analysis was done using VOSviewer, Microsoft Excel, and Harzing's Publish and Perish software. The core input of this study is analysing available information to address resilience issues in mitigating risk in the sustainable supply chain. To build a more sustainable system, it offers suggestions for more research in these areas that scholars may pursue and that project stakeholders could implement in their organisations.

Effect of Supply Chain Risk Management Practices on Organizational Performance in Yemeni Pharmaceutical Companies

Effect of Supply Chain Risk Management Practices on Organizational Performance in Yemeni Pharmaceutical Companies

Measuring dynamic supply chain risks for the offshoring decision in the post‐COVID‐19 era: A longitudinal study

AbstractIn times of prolonged economic doldrums across the globe, multinational firms (MNFs) offshoring blunders can undermine their competitiveness in the marketplace. To help the MNF formulate a more resilient offshoring strategy and identify the most desirable offshoring destination, this article aims to identify dynamic risk factors that significantly hinder the efficiency of offshoring and then measure specific offshoring risks over time using two different versions of data envelopment analysis (DEA) models and Malmquist productivity index (MPI). After assessing the degree of risk resiliency of the offshoring host countries over extended periods and then conducting Tobit regression analysis to identify key factors that significantly influence offshoring risks, we found that the host country's logistics efficiency (i.e., logistics performance index [LPI]) and domestic market size were critical indicators of offshoring success in that country. Since low‐cost sourcing countries (LCCs) tend to have relatively low LPIs and smaller domestic market sizes, they are not attractive offshoring destinations. This finding defies conventional wisdom. This article is one of the first longitudinal studies to assess the comprehensive risk resilience of 87 different offshoring destinations (countries) during multiple periods (6‐year span).

Supply chain risks and geographical supplier distribution strategy

AbstractThis study empirically examines the impact of supply chain risks on the corporate strategy of the geographical distribution of suppliers, by employing text analysis to procure firm‐level supply chain risk data. The findings indicate that, as supply chain risks intensify, firms are inclined to opt for geographically closer suppliers. Heterogeneity studies suggest that the effect of supply chain risks on the selection of geographically proximate suppliers is more pronounced within firms characterised by intense competition, low supplier concentration, low switching costs and in non‐state‐owned enterprises. Further analysis identifies that the supply chain risks, which drive strategies for firms to utilise a geographically proximate supplier distribution, stem from various sources. Each of these sources varies in its impact on a firm's strategies. Tests of economic consequences reveal that, in scenarios of heightened supply chain risks, firms' strategic geographic adjustments in supplier selection can favourably impact their supply chain management efficiency and operational risk.

Food Safety Risk Analysis of Songkem Duck Using Failure Mode and Effect Analysis (FMEA) Method

Food safety is an essential aspect of human health. Food processed without paying attention to food safety regulations can harm consumer health. This research aims to 1) identify activities with food safety risks, 2) determine the sequence of food safety risks that will be followed up, and 3) determine appropriate food safety risk mitigation. This research uses the Failure Mode and Effect Analysis (FMEA) method and fishbone diagrams. A case study was conducted on the Songkem pak Soleh Bangkalan duck supply chain. The research results show that activities that pose a food safety risk include receiving raw materials, storing raw material stocks, using raw materials and BTP, sanitizing production facilities, and storing finished products. The priority order of food safety risks in the Songkem duck supply chain is based on the FMEA method: storage of finished products, sanitation of production facilities, and storage of raw material stocks. Risk mitigation can be done to prevent food safety risks in storing raw material stocks and storing finished products, namely by controlling water activity (aw) and acidity factor (pH); and controlling the room's atmosphere. Meanwhile, to prevent risks due to sanitation hygiene, namely holding training to increase awareness of the importance of sanitation hygiene for restaurant employees monitoring and maintaining sanitation hygiene in the production environment.

Risk Transmission in Low-Carbon Supply Chains Considering Corporate Risk Aversion

In order to study the impact of risk aversion characteristics of enterprises on supply chain risk transmission, the risk aversion utility function is introduced, and the risk elasticity coefficient is used to construct a supplier-dominated low-carbon supply chain risk transmission model. Simulation analysis is conducted to investigate the transmission of emission reduction and revenue risks caused by internal and external contingent risk factors. The study reveals that under conditions of market demand uncertainty, the risk transmission effect is unaffected by the risk aversion characteristics of members in the low-carbon supply chain. While the risk-aversion characteristics of suppliers can decrease their own profit risk, they have a negative effect on the profit risk of manufacturers and the emission reduction risk of supply chain nodes. There exists a critical threshold for the impact of the risk-aversion degree of suppliers on their own emission reduction risk transmission effect. When this threshold is exceeded, the emission reduction risk decreases with increasing risk aversion intensity of suppliers, and vice versa. The risk aversion characteristics of manufacturers can weaken the negative effect of supplier risk aversion on the fluctuation risk of manufacturer profits, but they exacerbate the emission reduction risk transmission effect of manufacturers under asymmetric information influence. The findings have important theoretical and practical implications for supply chain risk management.

BearingFM: Towards a foundation model for bearing fault diagnosis by domain knowledge and contrastive learning

Monitoring bearing failures in production equipment can effectively prevent finished product quality issues and unplanned factory downtime, thereby reducing supply chain uncertainties and risk. Therefore, monitoring bearing failures in production equipment is important for improving supply chain sustainability. Due to the generalization limitations of neural network models, specific models must be trained for specific tasks. However, in real industrial scenarios, there is a severe lack of labeled samples, making it difficult to deploy fault diagnosis models across massive amounts of equipment in workshops. In order to solve the above issue, this paper proposes a cloud-edge-end collaborative semi-supervised learning framework, which provides multi-level computing power and data support for building a foundation model. A data augmentation method based on the bearing fault mechanism is proposed, which effectively preserves the inherent essential characteristics in vibration signals by normalizing frequency and adding noise in specific frequency bands. A novel contrastive learning model is designed, which narrows the distances between positive samples and widens the distances between negative samples in the high-dimensional space through cross comparisons in the time dimension and knowledge dimension, thereby extracting the most essential characteristics from the unlabeled signals. Multiple sets of experiments conducted on four datasets demonstrate that the proposed approach achieves an approximately 98% fault classification accuracy with only 1.2% labeled samples.

STOCHASTIC MODELING OF STRATEGIC SUPPLY CHAIN DESIGN

Supply chain risk management plays a critical role in the any business or industry environments, and it enables a good coordination of the input and outputs parameters that may affect the smooth processes development such as a manufacturing process for example. However, the supply chain risk management is often prone to the impact of various uncertainties associated with supply chain disruptions caused by meteorological, pandemic, resources shortage, etc. Therefore, one way to quantify these uncertainties are the stochastic modeling approaches of supply chain management. The stochastic modeling is a powerful tool that can predict with certain probability the events that may occur within the supply chain such as that associated with manufacturing processes. In the present research a stochastic model, based on probability theory, is developed and proposed for the analysis of supply chain risk management, for manufacturing processes. Therefore, the studies are performed to investigate the impact of the number of manufacturing processes on the supply chain proper evolution. The current study shows that the increase of the number of the manufacturing processes results in an increase of uncertainty in the supply chain management and thus, it increases the probability of supply chain disruption occurrences, within the supply chain. Therefore, it is recommended that a supply chain should contain a minimum number of manufacturing process, if the delivery time and final product allows.

Supply Chain Risk Mitigation: Modeling an Approach for Greater Visibility in Moroccan Automotive Industry

Supply Chain Risk Mitigation: Modeling an Approach for Greater Visibility in Moroccan Automotive Industry

Cybersecurity in supply chains: Addressing emerging threats with strategic measures

This review paper explores the evolving landscape of cybersecurity threats within supply chains, highlighting strategic measures necessary to mitigate these risks. As supply chains integrate more deeply with digital technologies and global networks, they become more vulnerable to sophisticated cyber attacks that can severely disrupt operational integrity and security. This paper synthesizes existing literature to outline the major cybersecurity challenges faced by supply chains, examining case studies and best practices from various industries. Our findings underscore the prevalent threats such as ransomware, phishing, and insider attacks, which exploit the complex interdependencies and digital interfaces in supply chains. The review identifies effective strategic responses, including the integration of comprehensive cybersecurity frameworks, enhanced inter-organizational cooperation, and the implementation of real-time threat detection systems. Conclusively, the paper advocates for a holistic and proactive approach to cybersecurity, emphasizing continuous improvement and adaptive strategies to protect against the dynamic nature of cyber threats in supply chain contexts. Keywords: Cybersecurity, Supply Chain Management, Risk Assessment, Continuous Monitoring, Incident Response, Blockchain Technology, Artificial Intelligence (AI), Collaboration and Information Sharing, Cyber Threats, Emerging Technologies.

The U.S. National Cybersecurity Strategy: A Vehicle with an International Journey

The U.S. National Cybersecurity Strategy is focused on the five pillars of defending critical infrastructure: detect, disrupt, and dismantle threat actors; improve market resilience and security; invest in future resilience; and create international partnerships with shared goals. The National Cybersecurity Strategy Implementation Plan is focused on critical infrastructure supporting energy, financial, healthcare, information technology, and manufacturing sectors. In the U.S. alone, the SolarWinds supply chain attack affected nine federal agencies and about 100 companies. Ransomware attacks such as the Colonial Pipelines, the largest U.S. oil pipeline, disrupted supplies of gasoline and fuel to the U.S. East Coast and the JBS USA as the largest meat processor ransomware attack affecting one-fifth of the nation’s meat supply. The U.S. National Cybersecurity Strategy as a response to the U.S.’s critical infrastructure concerns led to the creation of two core cybersecurity documents which were crafted jointly with several other allies. Cybersecurity and Infrastructure Security Agency (CISA) crafted the Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software with joint agreement with National Security Agency (NSA), the Federal Bureau of Investigation (FBI), and 15 international government agencies to give international vendors a roadmap of the expected cybersecurity hygiene required from their products. (CISA, 2023a; Car & De Luca, 2022) Building on the Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software, CISA, FBI and NSA met with cybersecurity organizations from Australia, Canada, New Zealand, and United Kingdom and jointly created The Case for Memory Safe Roadmaps: Why Both C-Suite Executives and Technical Experts Need to Take Memory Safe Coding Seriously as a core issue identified in the earlier guidance. (CISA, 2023c). These led by the U.S. helped initiate an international cybersecurity norm insisting international software manufacturers demonstrate product security and transparency. They showed how a global community can rally to solve cybersecurity challenges that have existed for decades. This led to twenty of the largest international software vendors creating the Minimum Viable Secure Product (MSVP) Working Group to address the requirements levied by these documents; CISA has joined this working group to help shape procurement, contractual controls, self-assessment, and system development lifecycle (SDLC) with these vendors. (CISA, 2024d; MSVP, n.d.) This research argues that the U.S. National Security Council (NSC) should leverage the talent pool of CISA, National Institute of Standards and Technology (NIST), Department of Defense (DoD), FBI, and NSA to improve detection, information sharing, security standards, and implementation for not only the U.S.’s government and commercial sectors, but also helps our allies and partners. The DoD and Office of the Director of National Intelligence (ODNI) have made great strides in improving security by integrating improvements with Zero Trust Architecture (ZTA), Supply Chain Risk Management (SCRM), Software Supply Chain Security, Cybersecurity Safety Review Board (CSRB), Cybersecurity Incident & Vulnerability Response Playbooks, and DoD National Security Systems (NSS) standards. The NSC should coordinate through CISA to develop a collaborative effort to not only benefit the U.S. critical infrastructure but also help our allies and partners.

Macrogenomics-Based Analysis of the Effects of Intercropped Soybean Photosynthetic Characteristics and Nitrogen-Assimilating Enzyme Activities on Yield at Different Nitrogen Levels.

Currently, China's soybean self-sufficiency rate is only 15%, highlighting the soybean crisis and the supply chain risks that pose a major threat to China's food security. Thus, it has become imperative to step up efforts to boost soybean production capacity while promoting the green and sustainable development of regional farmland ecosystems. In this context, the present study comprehensively investigated the effects of intercropping and nitrogen application rate on soybean yield, as well as the changes in gradients generated by different levels of nitrogen application. Based on six consecutive years of maize-soybean intercropping planting patterns, the inter-root soils of soybeans were collected at the flowering stage and evaluated for soil nitrogen content, nitrogen-assimilating enzyme activities, and microbial community composition of soybean, which were correlated with yield, to clarify the main pathways and modes of intercropping effects. The N2 level (80 kg·ha-1) was favourable for higher yield. In comparison to monocropping, the intercropping reduced yield by 9.65-13.01%, photosynthetic characteristics by 1.33-7.31%, and plant nitrogen-assimilating enzyme activities by 8.08-32.01% at the same level of N application. Likewise, soil urease and catalase activities were reduced by 9.22 and 1.80%, while soil nitrogen content declined by an average of 6.38%. Gemmatimonas and Bradyrhizobium enrichment significantly increased soil nitrogen content, photosynthetic characteristics, and soybean yield, while it was reduced by Candidatus_Udaeobacter and Candidatus_Solibacte enrichment. The results of this study provide a theoretical basis for further optimising maize-soybean intercropping, which is crucial for enhancing the agricultural production structure and improving the overall soybean production capacity.

Prediction-based decomposition optimisation for multi-portfolio supply chain resilience strategies under disruption risks

ABSTRACT This paper focuses on the design of supply chain (SC) risk mitigation and recovery strategies during long-term disruptions caused by the COVID-19 outbreak, which affect both suppliers and plants. Consequently, concurrent disruptions in supply and production are observed, which vary in duration and result in time-varying reductions in supply and production capacity. To cope with long-term disruptions, a modified multi-portfolio approach that integrates simulation and predictions is proposed to develop efficient mitigation and recovery plans. This approach involves selecting primary and recovery supply and production portfolios concurrently. To achieve this objective, time-dependent mixed integer programming (MIP) models that incorporate preparedness and recovery measures are developed to optimise SC operations. A prediction-based decomposition optimisation method is proposed to solve MIP problems and coordinate supply and production portfolios under disruptions and uncertainties. Furthermore, a heuristic approach is established to provide a comprehensive solution process. Finally, computational experiments and comparative analysis are conducted on a real-life case study. The results demonstrate that the proposed modelling and optimisation methods can effectively address disruptions and improve SC resilience. In addition, the developed models and approaches have the potential to serve as decision-making tools in SC management during disruptions.

DEA-driven risk management framework for oil supply chains

This paper develops a comprehensive risk management framework to optimise the Nigerian oil supply chain risk mitigation strategies. Given the complexities of the oil supply chain, this framework aids researchers and decision-makers in navigating innovative risk management approaches and considering the implementation of associated challenges. Data Envelopment Analysis (DEA) is initially employed to prioritise risk factors, and based on obtained results, optimal response strategies are determined. The study's findings reveal that criminality and terrorist attacks are the paramount Nigerian oil supply chain risk factors. Additionally, the research identifies practical mitigation strategies, such as risk transfer, safety planning, alternative energy carriers, improved energy efficiency, emergency rescue plans, expected shortages, and diplomatic relations. This research contributes valuable insights to both academia and industry, fostering a deeper understanding of risk dynamics in the Nigerian oil sector. The framework presented offers a powerful approach to risk management, providing a foundation for informed decision-making and strategic planning in the ever-evolving landscape of supply chain dynamics.

HCSRL: hyperledger composer system for reducing logistics losses in the pharmaceutical product supply chain using a blockchain-based approach

Blockchain technology uses a secure and decentralised framework for transaction management and data sharing within supply chains. This is particularly crucial in the pharmaceutical industry, where product authenticity and traceability are paramount. Blockchain plays a pivotal role in preventing product loss and counterfeiting, while simultaneously enhancing transparency and efficiency throughout the supply chain. The research introduces a step-by-step approach to implementing a proof-of-concept (PoC) for Supply Chain Risk Management (SCRM) through blockchain technology. This PoC involves simulating a supply chain process to assess feasibility and measure key performance indicators. Engaging stakeholders and gathering feedback is integral to refining the blockchain-based SCRM system. The study rigorously evaluates the performance of the SCRM blockchain across various test scenarios, featuring differing numbers of organizations and clients. Multiple fabric networks are employed to assess the system’s scalability and performance under diverse conditions. The results of these comprehensive tests inform practical deployment decisions and highlight areas for potential optimization and further development. So this research provides valuable insights into the application of blockchain in pharmaceutical supply chains, offering a roadmap for implementation and improving supply chain security, efficiency, and transparency.

Managing logistics risks in pharmaceutical supply chain: a 4PL perspective

Supply chain risks and vulnerabilities have been growing recently due to the global, interconnected, and complex networks. The Pharmaceutical Supply Chain (PSC), as a critical national asset, requires increased attention to mitigate the severe consequences of global events. With various risks impacting both the firm’s performance and the lives of patients, effective risk management is paramount for the PSC. This empirical study focuses on the UK-based Fourth-Party Logistics (4PL) provider, which manages pharmaceutical manufacturers’ logistics operations. The 4PL provider’s past experiences with unexpected risky events have influenced its performance. This study aims to explore inherent logistics risks, evaluate them, and recommend mitigation strategies. An integrated approach considering probability, impact and manageability parameters is proposed for risk assessment. In identifying 11 risks from the 4PL perspective, structured interviews are used to gather risk information. The probability of risk occurrence, severity of impact, and manageability are quantified. The delivery delay should be given priority in the follow-up risk management process, while counterfeiting has the least priority. Finally, three resilience strategies named improving flexibility, redundancy, and creating a risk culture are proposed for the 4PL case company. The study offers multiple theoretical and managerial implications based on its findings.

Analisis Risiko Rantai Pasok Material dalam Pelaksanaan Proyek Konstruksi Gedung Di Aceh

The material supply chain is a material distribution flow that varies from various sources or suppliers, until the material arrives at the project site. This study aimed to analyze material supply chain risk factors that arise in the implementation of building construction projects in Aceh Province, as well as identify solutions to prevent material supply chain risk factors that arise in the implementation of building construction projects in Aceh Province. The methods developed in this research are validity test, reliability test, quantitative descriptive, and multiple regression analysis through SPSS software version 25. From the validity test results obtained, the value of Rcount ≥ Rtable. This shows that the validity test performed on all questions is valid. Furthermore, the results of the reliability test obtained the average value of each variable of 0.708, then the reliability test was said to be reliable. Because the value of a variable is said to be reliable (reliable) if Cronbach Alpha value exceeds 0.6. Then from the results of the descriptive analysis, there are indicators that are often questioned as risk factors, namely the delay of the main contractor in paying subcontractors (X2.8) with a mean value of 3.39. This shows that the majority of respondents stated that X2.8 has a high influence on the occurrence of material supply chains in the implementation of construction projects. From the results of the correlation analysis, the R value of 0.382 (low/weak), then the two variables have a unidirectional relationship. This means that if the value of the X variable is high, then the value of the Y variable will also be high or if it means that all X variables are related to material supply chain risk, and the regression model obtained is: Ŷ=7.408+0.096X1-0.006.X2+ 0.132X3+0.112X4. From the results of the coefficient of determination, the value of R2 = 14.6%, which means that the risk of the material supply chain is influenced by supply factors, control factors, demand factors, process factors, amounting to 14.6%, the remaining 85.4% is influenced by other factors variables which are not included in this study.