Supply Chain Performance Research Articles

Analisis Risiko Pendistribusian Barang pada PT Pos Indonesia dengan Metode SCOR (Studi Kasus: Kantor Pos Pusat Bandung)

This research was conducted on a case study of a postal and logistics service company involving the Indonesian Post Office entity, courier services, and postal officers. The problems faced are risks during the distribution of goods from customers that cause delays in distribution. Evaluation of the delivery system is needed to maintain customer satisfaction. The study's overarching goal is to map out ways to reduce supply chain risks by identifying potential threats and quantifying their severity throughout product delivery via the Bandung Central Post Office. Companies may use the Supply Chain Operations Reference (SCOR) technique and a House of Risk (HoR) to assess failures and predict them in the supply chain. This study provides a framework for identifying possible risks throughout the supply chain. Direct observation and review of the literature were the methods used to gather data.

Theoretical foundations and practical implementation of supply chain optimization a metal fabrication business model

In the dynamic landscape of modern business, effective management of supply chains stands as a cornerstone of organizational success and competitive edge. This study investigates the theoretical principles and practical implementations of optimization models aimed at refining supply chain operations in the metal fabrication business, giving the maximum profit. It begins with a comprehensive survey of optimization theory, encompassing linear programming, integer programming, and stochastic optimization. It proceeds to their application in addressing diverse challenges encountered in supply chain management. The discussion includes deterministic models, such as those optimizing facility location under capacity constraints and transportation logistics, alongside stochastic models designed to manage uncertainties inherent in demand forecasting and inventory control. Advanced methodologies like metaheuristic algorithms and multi-objective optimization techniques are examined for their capacity to navigate the intricate and often conflicting objectives within supply chain networks. Through comprehensive theoretical analysis and a study of the supply chain model developed for the metal fabrication business, this paper contributes to advancing knowledge in mechanical engineering and supply chain management, offering insights pertinent to practitioners and researchers alike. Ultimately, it emphasizes the critical role of optimization models in optimizing efficiency, reducing costs, improving profit margin, reducing CO2 emission, and enhancing competitiveness in modern supply chain operations.

On the use of machine learning in supply chain management: a systematic review

Abstract Machine learning (ML) has evolved into a crucial tool in supply chain management, effectively addressing the complexities associated with decision-making by leveraging available data. The utilization of ML has markedly surged in recent years, extending its influence across various supply chain operations, ranging from procurement to product distribution. In this paper, based on a systematic search, we provide a comprehensive literature review of the research dealing with the use of ML in supply chain management. We present the major contributions to the literature by classifying them into five classes using the five processes of the supply chain operations reference framework. We demonstrate that the applications of ML in supply chain management have significantly increased in both trend and diversity over recent years, with substantial expansion since 2019. The review also reveals that demand forecasting has attracted most of the applications followed by inventory management and transportation. The paper enables to identify the research gaps in the literature and provides some avenues for further research.

Examining the factors influencing sustainability performance in the UK food industry

ABSTRACT This research examines the role of organisational culture (OC) and supply chain integration (SCI) in improving sustainable supply chain performance (SSCP) in the food manufacturing industry in the UK. A competing value framework (CVF) was used to categorise OC into developmental, group, rational and hierarchical cultures. Qualitative interviews with 11 senior managers in the UK food industry were conducted and manually analysed. We found that three competing values in developmental, group and hierarchical cultures are effective in implementing and achieving higher SSCP. The values inherent in these cultures also trigger internal and external integration through which the firms acquire sustainability ideas, knowledge, training and skills from customers and suppliers to improve SSCP. We also found that within the context of sustainability, internal integration is critical to a successful external integration. The study contributes immensely to sustainability literature by highlighting the actual OC values relevant to achieving higher SSCP and establishing SCI’s mediating role. The study further assesses how SCI is established and formed by firms on the verge of achieving higher SSCP. Managers are advised to adopt blended competing values (developmental, group and hierarchical culture) and strengthen and heighten systemic SCI to implement sustainability practices, improve SSCP as well as overcome sustainability challenges.

Leveraging blockchain for sustainable supply chain management: A data privacy and security perspective

This review examines how blockchain technology can be leveraged to enhance data privacy and security in sustainable supply chain management (SSCM). As global supply chains become increasingly complex and the demand for sustainability grows, ensuring data privacy and security has become a critical concern. Traditional supply chain systems often face challenges such as data breaches, lack of transparency, and difficulty in tracing products and materials. Blockchain technology, with its decentralized, immutable, and transparent architecture, offers a promising solution to these challenges. Blockchain can enhance data security by ensuring that data is tamper-proof, traceable, and encrypted, thus protecting sensitive information across the supply chain. It provides transparency while allowing permissioned access, ensuring that stakeholders can verify data without exposing confidential information. Furthermore, privacy-preserving technologies such as zero-knowledge proofs and homomorphic encryption allow verification of data without compromising its security. Smart contracts enable automated compliance with regulatory frameworks like GDPR, reducing the risk of human error and improving operational efficiency. The integration of blockchain in SSCM can improve traceability, transparency, and accountability, thereby promoting environmental and social sustainability. By tracking the origin and journey of goods, blockchain helps verify ethical sourcing practices and reduce carbon footprints. However, the technology also presents challenges, including scalability, integration with legacy systems, and cost considerations. Through case studies in industries such as food, textiles, and renewable energy, this review highlights the practical applications and benefits of blockchain for SSCM. It concludes that blockchain has the potential to revolutionize supply chain operations, but careful consideration must be given to overcoming its technical and financial barriers to widespread adoption.

Assessment of supply chain efficiency through a sustainable supply chain management strategy in the textile sector

The textile industry processes fiber into yarn or fabric. Problems often faced by textile companies are delays in raw materials, which result in the production and distribution of fabrics not reaching the target, so consumers are unsatisfied and switch to competing companies. In addition, solid waste from the production process is still disposed of, potentially polluting the environment. This study uses the Green Supply Chain Operation Reference (Green SCOR) approach to evaluate the performance of green supply chain management (GSCM) in textile companies located in Yogyakarta. The findings of this study could significantly impact the textile industry as they provide a comprehensive evaluation of GSCM performance. Twenty-two performance indicators have been validated using the Item-Content Validity Index (I-CVI) method and weighted using the Analytical Hierarchy Process (AHP) method. Based on the calculation results, the GSCM performance value is 60.208. Improvement recommendations are given for three indicators that need to be prioritized based on Importance Performance Analysis (IPA) matrix mapping and the actual condition of the company. Improvements can be made by using the Vacuum Flash Evaporation method so that recycled PVA can be reused, using natural materials or alternative auxiliary materials that are more environmentally friendly, increasing cooperation with companies engaged in processing weaving waste or textile waste appropriately and effectively, checking the concentration of starch solution not only when changing construction but every beam change, and forming a checklist form that is filled in for monitoring after machine settings and preparation of the production process.

How Does Supply Network Structure Influence Firms’ Financial Performance During Disruption?

In a post pandemic world, supply chain mapping has become a key concern for almost any supply chain operation. A single focal supply chain network might have hundreds of suppliers including those that supply both goods and services. These increase exponentially as one traces the network downstream. Using a pair of networks from the auto industry (Ford and General Motors) as a basis for the analysis, we apply a data mining technique to filter for significant supply chain relationships in each of these networks over the period spanning 2018–2022. We then examine the structural metrics for each of these networks and compare these measures with applicable financial measures to elucidate how supply chain network structure affects financial performance. Our regression analyses reveal that supplier network structures significantly affect customers’ market value. Specifically, Tobin’s Q is negatively related to the number of suppliers they source from and the importance of the customer (e.g., Ford) to its suppliers, but it is positively associated with the tightness of supplier customer connection and the density of the network.

Sustainability performance assessment of sago industry supply chain using a multi-criteria adaptive fuzzy inference model

Background Sustainable supply chains are more competitive than conventional supply chains. Supply chain sustainability performance needs to be carried out to determine sustainability under current conditions and to design appropriate strategies to increase sustainability. This study aims to design a sustainability performance assessment model for the sago agro-industry supply chain and identify critical indicators for sustainability improvement. Methods The Fuzzy Inference System (FIS) evaluates sustainability on three levels: economic, social, and environmental. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is then used to aggregate the overall sustainability performance. The cosine amplitude method (CAM) was used to analyze key indicators. This study assessed the sustainability performance on industrial- and small-medium-scale sago agro-industry. Results The results show that the supply chain sustainability performance on the industrial scale is 44.25, while it is 48.81 for the small-medium scale with the same status, almost sustainable. Key indicators for improving sago agro-industry supply chain sustainability performance include profit distribution among supply chain actors, institutional support for supply chains, waste utilization (reuse & recycle), and the availability of waste management facilities. The implication of this research for managers regards assessing the current status of sustainability performance and key indicators as a reference for formulating sustainability strategies and practices. Implication The sago agro-industry sustainability performance evaluation methodology uses industry-relevant metrics to assess supply chain sustainability, promoting collaboration among stakeholders and assisting in the creation of sustainable strategies. Conclusions The results of the study will enable supply chain actors to understand the key indicators for improving sustainability performance in the sago agro-industry supply chain, especially in Meranti Islands Regency, Riau Province. The proposed model can be applied to other agro-industries by adjusting the indicators used and assessing data availability and suitability for the research object.

Supply chain resilience in the construction industry: a bibliometric review on operations management practices from Industry 4.0 to Industry 5.0

PurposeThe purpose of this research was to conduct a comprehensive bibliometric analysis to explore supply chain resilience and operations management practices in the construction industry, with a particular focus on the transition from Industry 4.0 to Industry 5.0. The study addressed a significant gap in the literature regarding the impact of these advanced technologies on the construction sector’s ability to anticipate, respond to and recover from disruptions.Design/methodology/approachThe methodology employed a bibliometric analysis using the Scopus database to identify key trends, influential publications and emerging research areas using keywords such as “supply chain”, “operations management”, “Industry 4.0”, “Industry 5.0” and “construction”. This approach allowed for a quantitative evaluation of existing literature, offering insights into the intellectual structure of the field.FindingsThe findings revealed that while Industry 4.0 technologies, such as IoT and AI, have enhanced the construction industry’s supply chain visibility and efficiency, the shift towards the Industry 5.0 paradigm introduces a human-centric approach that further strengthens resilience through collaboration and sustainability.Practical implicationsThe study’s practical implications suggest to both industry and academia that embracing Industry 5.0 principles could significantly enhance the construction industry’s resilience, enabling it to withstand disruptions better and maintain project quality, timelines, and budgets in an increasingly complex global environment.Originality/valueThis research examines the shift from Industry 4.0 to Industry 5.0 within construction supply chains, offering a novel perspective on integrating these technologies.

Triple-A supply chains: unveiling the mediating power of collaboration and innovation on operational performance

Triple-A (agile, adaptable, and aligned) Supply Chain (SC) has been analyzed as a source of competitive advantage, but the influence of mediating variables in this relationship remains underexplored. This research seeks to advance the Triple-A SC framework by considering and testing the mediating effects of SC collaboration and innovation levels on the Triple-A SC–operational performance (efficiency and responsiveness) relationship. The research model was tested with PLS-SEM using a sample of 277 Spanish manufacturing firms with a minimum of 50 employees from 14 different sectors. The results show that SC collaboration and innovation levels significantly mediate relationships between Triple-A SC and operational performance. Additionally, collaboration level plays a more important role in responsiveness than efficiency, while innovation level has similar effects on both performance dimensions. This work contributes to knowledge on the impact of Triple-A SC on operational performance and alerts managers to the need to strengthen their levels of collaboration with SC partners and innovation over their main competitors.

A Comprehensive Approach for Selecting Third-Party Logistics Providers

The finest third-party logistics (3PL) supplier is a vital decision for businesses trying to streamline their supply chain operations. In order to free up time for businesses to concentrate on their core skills, third-party logistics providers offer a variety of services, such as distribution management, warehousing, and transportation. However, selecting the best 3PL supplier necessitates a rigorous assessment of variables including sector expertise, technical prowess, service quality, scalability, and cost-effectiveness. This introduction discusses the significance of choosing the best 3PL supplier and emphasizes important factors to take into account when making a choice. It is essential since there is a chance that third-party logistics (3PL) provider selection study may boost the supply chain's effectiveness and competitiveness. Firms may make selections that are tailored to their unique requirements by recognizing and assessing the elements that affect the choosing process. Proper 3PL selection may boost market response, save costs, expand the capacity of operations, and improve customer happiness. As a result, research in this field helps to create best practices and strategies that enhance supply chain management and promote entrepreneurship. A multi-criteria decision-making approach called The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank and choose the best option from a list of options. To determine how closely each alternative resembles the ideal answer, TOPSIS takes into account both positive and negative features. Based on the greatest distance from the inverse idealistic and the lowest distance to the positive ideal, the outcome score is calculated. This approach facilitates decision-making processes in a variety of contexts, such as project prioritization, supplier selection, and investment appraisal. Alternative parameters taken as 3PL-1, 3PL-2, 3PL-3, 3PL-4, 3PL-5. Evaluation parameters taken as Delivery Service (%), Quality of the Customer Experience (Quos), Coverage of the EU Territories (%), Flexibility, and Cost (EUR/km). From the result it is seen that 3PL-2 secures the first rank which is acquired by the TOPSIS method. To secure the first place on the table consistency will be the key factor which was maintained by 3PL-2

The impact of transshipment and staggered deliveries on pharmaceutical supply chain performance

ABSTRACT This paper studies the impact of proactive transshipment and staggered deliveries on the pharmaceutical supply chain performance. Therefore, a mathematical model considering transshipment and staggered deliveries is developed to minimise the total inventory management costs of a pharmaceutical supply chain under uncertain demand. To deal with this problem, a two-stage stochastic model is presented and solved using the sample average approximation. The proposed solution shows an important gain of 5% on average in the total inventory management costs when incorporating transshipment of drugs between hospitals and a gain of 32% on average when considering both transshipment and staggered deliveries.

The impact of industry 5.0 on supply chain performance

The transformative potential of Industry 5.0 (I5.0) to enhance supply chain performance (SCP) has become a compelling focus for numerous supply chain (SC) managers. This research explores the profound impact of I5.0 on SCP, highlighting three key dimensions: Efficiency, Visibility, and Responsiveness. It illuminates the dynamic interplay among these dimensions, demonstrating that improved visibility leads to heightened responsiveness and efficiency. While the enabling technologies of I5.0 hold significant potential for diverse applications, this study zeroes in on seven I5.0 technologies identified as highly impactful within the SC context. A closed-ended questionnaire was employed to collect 105 valid responses from managers, experts, and practitioners who are well-versed in I5.0 within the SC domain. Data analysis was performed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The findings reveal both positive direct and indirect relationships between I5.0 and SCP, emphasizing how I5.0 reshapes performance dynamics and can expedite the adoption of I5.0.

The Impact of Lead Time Variability on Supply Chain Management

Purpose: The impact of lead time variability on supply chain management (SCM) is a critical factor affecting operational efficiency, cost management, and service delivery. This study examines how variations in lead time affect key aspects of supply chain performance, including inventory management, production scheduling, and order fulfillment. Methodology: A mixed-methods approach is adopted, combining quantitative analysis through simulation modeling and qualitative insights derived from case studies of companies in the manufacturing and retail sectors. The simulation model accounts for different levels of lead time variability and its influence on stockouts, excess inventory, and overall supply chain responsiveness. Case studies are used to illustrate real-world challenges and strategies employed by businesses to mitigate the effects of lead time fluctuations. Findings: Findings indicate that higher lead time variability leads to increased inventory costs, stockouts, and delays in product deliveries. Companies that rely heavily on just-in-time (JIT) systems are particularly vulnerable to these fluctuations, whereas firms with flexible inventory strategies or buffer stock perform better in managing variability. Additionally, the study reveals that advanced demand forecasting and more resilient supplier relationships can significantly reduce the negative impact of lead time uncertainty. The analysis also highlights the importance of integrating lead time variability into the broader risk management framework of supply chains. Unique Contribution to Theory, Practice and Policy: Based on these findings, recommendations include implementing more robust demand forecasting systems, optimizing safety stock levels, diversifying suppliers, and using advanced inventory management technologies. Moreover, it is advised that businesses foster stronger communication and collaboration with suppliers to reduce variability and improve lead time predictability. Future research should explore the potential of real-time data and AI-driven supply chain management systems to further mitigate lead time variability's impact on SCM.

How to improve supply chain sustainable performance by resilience practices through dynamic capability view: Evidence from Chinese construction

This study explores the relationship between supply chain resilience (SCR) and sustainable supply chain performance (SSCP) within the context of the Chinese construction industry, a sector known for its complexity and vulnerability to disruptions. Drawing on data from 525 construction companies, the research investigates how SCR directly influences SSCP and examines the mediating role of dynamic capabilities in this relationship. The results highlight those dynamic capabilities, specifically the ability to seize and reconfigure, serve as critical mediators in the resilience-sustainability relationship while sensing does not have a significant mediating effect. This suggests that in highly dynamic environments like China's construction sector, focusing on capturing opportunities and reconfiguring resources is more effective for achieving sustainable outcomes than relying solely on sensing capabilities. This finding contributes to the growing body of knowledge by providing a nuanced understanding of how resilience practices can be leveraged to promote long-term sustainability.

Circular supply chain transformation: leveraging evolving technologies for enhanced performance

ABSTRACT Circular supply chains (CSC) and evolving technologies work together to enhance supply chain performance. To assess this, we examine the integration of technologies, such as Industry 4.0, smart manufacturing, and smart logistics in a CSC setup. The study focuses on two product types: smart and normal (non-smart) products. Smart products feature sensing, connectivity, networking, and monitoring capabilities, while normal products lack these features. Using a multi-objective optimisation technique, we analyse the CSC network to estimate the benefits of evolving technologies. The study aims to maximise profits and minimise carbon emissions across the supply chain. Eleven models are examined based on varying demand percentages of smart and normal products. The gamultiobj algorithm (a variant of NSGA II) is used to generate Pareto frontiers. The findings show that a 2-5% increase in technology adoption costs can boost profits by 15-30% and reduce emissions by 20-30% for smart products.

Dynamics analysis of green supply chain under the conditions of demand uncertainty and blockchain technology

This research investigates the implications of incorporating blockchain technology into the process of making decisions for green supply chains, particularly under conditions of demand uncertainty. A model was formulated to encompass both environmentally friendly products enabled by blockchain technology and those without such enabling technology. The study further explores the optimal method of introducing green input in a duopoly market using game theory. It also examines how consumer uncertainty about green products and acceptance of the technical parameters of blockchain influence this strategy. The findings suggest that increased consumer uncertainty can, in some instances, motivate manufacturers to enhance the eco-friendliness of their products and improve supply chain performance. However, the universal adoption of blockchain does not necessarily ensure better results; on the contrary, it may compromise product sustainability while enhancing supply chain profitability. Moreover, research has indicated that products enabled by blockchain typically have lower prices, thereby offering potential benefits to consumers when acceptance of sustainable energy solutions is high or uncertain. Additionally, this paper analyzes the impact of changes in green supply chain decision-making on system reliability. This involves exploring the relationship between decision parameters and consumer reluctance towards sustainable products and the adoption of blockchain technology. To ensure stable market competition in dynamic complex systems, research shows that feedback control technology can effectively regulate unpredictable behavior.

Optimizing Supply Chain Efficiency Using Cross-Efficiency Analysis and Inverse DEA Models

Our study employs cross-efficiency analysis (CEA) and machine learning techniques to optimize supply chain performance. By integrating inverse DEA models with directional distance functions, we measure operational efficiency across various decision-making units (DMUs), accounting for undesirable outputs such as excess costs and emissions. Our results indicate a 20% improvement in market recognition efficiency and a 15% increase in earnings persistence efficiency after model application. Additionally, machine learning classifiers, including Random Forest and Support Vector Machines, further enhanced predictive accuracy, with Random Forest achieving the lowest mean absolute error of 0.07. These findings underscore the effectiveness of advanced analytical models in improving supply chain resilience and decision-making accuracy, contributing to sustainable operational performance.

How do collaborative systems affect organizational agility and performance in supply chains?

How do collaborative systems affect organizational agility and performance in supply chains?

Marketing-Driven Supply Chain Innovation: A Framework for FMCG SME Sustainability

In an increasingly competitive and sustainability-conscious market, small and medium-sized enterprises (SMEs) in the Fast-Moving Consumer Goods (FMCG) sector face unique challenges in achieving long-term sustainability. This review explores the concept of marketing-driven supply chain innovation as a strategic framework for enhancing SME sustainability. By integrating consumer-centric marketing strategies with supply chain operations, SMEs can align their product offerings, sourcing practices, and logistics with growing consumer demand for environmentally and socially responsible products. The framework outlined in this study includes key components such as sustainable product design, green logistics, ethical sourcing, and the incorporation of circular economy principles. Additionally, technology-driven innovation, such as data analytics and digital platforms, is emphasized as a tool to improve supply chain transparency, reduce waste, and optimize resource utilization. Through these collaborative efforts, SMEs can foster stronger consumer trust, enhance brand loyalty, and build a competitive edge in the market. Despite the potential benefits, the review also discusses the challenges SMEs may face, including limited financial resources, resistance to organizational change, and balancing profitability with sustainability goals. However, by leveraging green financing options, cross-sector partnerships, and phased implementation strategies, SMEs can overcome these barriers. Ultimately, the integration of marketing-driven supply chain innovation is positioned as a critical path for FMCG SMEs to achieve long-term sustainability, profitability, and market competitiveness in an evolving global economy. Keywords: Marketing-Driven, Supply Chain, FMCG SME, Review.