Traditional Supply Chain Research Articles

The Role of AI and ML in Revolutionizing Supply Chain Management

Artificial intelligence and machine learning are being implemented by a constantly growing number of companies to develop a more efficient supply chain. The immense volume of data that companies are producing and sourcing along the supply chain can now be analyzed in real time, enabling better decision-making processes. This paper will explore how the utilization of these technologies is revolutionizing supply chain management. Two specific areas, demand forecasting, and inventory management, will be explored in greater depth. The paper will then highlight the current trends and challenges of AI and ML in supply chain management and offer concluding remarks. Supply chain management is a complex system that connects multiple companies and encompasses the flow of goods, services, information, and finances. To cope with its complexity, more and more companies are turning to technologies like artificial intelligence (AI) and machine learning (ML) to gain a competitive edge. ML is a branch of AI that consists of systems and algorithms that can learn from data to improve decision-making. The number of companies that claim to be using ML has grown by more than 300% since 2015, with the overall AI market considered to be worth around $2 trillion. In the supply chain industry, companies are using ML to optimize delivery routes and times, predict delays and detect variances in quality at an early stage. The use of AI technologies can optimize and execute supply chain tasks promptly, making it more capable than traditional supply chain setups.

AGRI-FOOD SUPPLY CHAIN HOLISTIC DESIGN: TOMATO PRODUCT APPLICATION

Geleneksel tarım-gıda tedarik zincirlerinde ürüne değer katmayan birden fazla aşama olup ürünlerin kalitesini ve fiyatını olumsuz yönde etkilemektedir. Ayrıca tarım-gıda ürünlerindeki enflasyon Tüketici Fiyat Endeksini de doğrudan etkilediğinden zincir üzerinde yapılacak iyileştirmelerin nihai tüketiciye katkısı yüksek olacaktır. Bu çalışma kapsamında tarım-gıda tedarik zincirinde değer yaratmayan katmanların olmadığı ve bütünleşik bir yaklaşımla iş birliğine dayalı bir metodoloji geliştirilmiştir. İlk aşamada ilgili paydaşlar sisteme kabulü ve operasyon süreçleri için Analitik Hiyerarşi Süreci (Analytic Hierarchy Process-AHP) yöntemi ile ayrı ayrı değerlendirilmiştir. Daha sonra Ortaklaşa Planlama, Tahmin ve İkmal (Collaborative Planning, Forecasting and Replenishment- CPFR) yaklaşımı çerçevesinde; doğrusal programlama yöntemiyle en uygun tedarik zincirleri belirlenerek kapasite dengelemesi yapılmıştır. Çalışmanın son kısmında ise metodoloji kapsamında kullanılan yöntemlerin doğrulanmasını gerçekleştirmek üzere domates ürünü üzerine bir uygulama AIMMS modelleme paketi üzerinde analiz edilmiş̧, elde edilen bulgular ve sonuçlar verilmiştir.

Akıllı ve Sürdürülebilir Tedarik Zinciri Yönetiminin Hazırlık ve Olgunluk Düzeyinin Değerlendirilmesi için Geometrik Ortalamaya Dayalı Yeni Bir Model Önerisi

Recently, companies have added smart and sustainable paradigms to their supply chain strategies as a result of globalization and increased global competition, increasing technological growth rate, diversity in customer demands, and increasing complexity in supply chain processes. Real-time information sharing among supply chain players and the effective coordination of each step of the chain are critical for efficient supply chain management. This is made possible by the transition from the traditional supply chain to the digital supply chain. The Fourth Industrial Revolution, also known as Industry 4.0, was coined for the first time in Germany in 2011. It is an innovative paradigm with the goal of intensely integrating technologies, such as information technologies, the Internet of Things, artificial intelligence, cloud computing technology, autonomous vehicles, robotic systems, sensor and automation networks, and virtual and augmented reality into production processes. However, for many companies, the adaptation of Industry 4.0 and the subsequent maturity period may present unexpected challenges. One of the most difficult challenges in establishing smart factories and implementing digital transformation is that Industry 4.0 competencies cannot be effectively applied to all operations simultaneously. In this context, quantitative measurement and evaluation of firms’ maturity levels following Industry 4.0 preparation and adaptation is critical for senior management. The goal of this study is to propose a model for measuring the maturity level of digital supply chains while considering smart and sustainable dimensions. We determined the extent to which each Industry 4.0 tool was compatible with the sustainability dimensions in the numerical example where the model was applied. For example, although additive manufacturing and augmented reality receive high scores in the economic dimension of sustainability, they receive lower scores in the environmental and social dimensions. Similarly, although horizontal and vertical systems integration has high levels of maturity in all three sustainability dimensions, artificial intelligence has an exceptionally low level of maturity.

The supply chain and its development concept of fresh mulberry fruit in Thailand: Observations in Nan Province, the largest production area

Abstract Nan province, the biggest cultivation area of fresh mulberry fruit in Thailand is located in four districts: Chaloem Phra Kiat, Bor Klua, Tha Wang Pha, and Wiang Sa. The production yield of mulberry is about 848.6 kg/acre/year; however, it is mostly sold as frozen product. The Queen Sirikit Department of Sericulture intends to develop a new marketing channel for fresh mulberry fruit. The present study was to explore the current situation of mulberry fruit supply chain management in Nan province and to propose a new supply chain model for fresh mulberry. To gather information about supply chain management, the supply chain operation reference (SCOR) model was utilized to investigate four members of the mulberry supply chains, including growers, primary middlemen, secondary middlemen, and customers. The SCOR model possibly identifies critical points in the current supply chain and five obstacles in the distribution of fresh mulberries that are improperly handled, affecting market channels and product quality due to a lack of suitable knowledge and technology for postharvest handling. Active packaging technology of fresh mulberries from a previous study was introduced to design a new supply chain model, and it was found that this technology could extend the product’s shelf life and preserve its freshness. Although the cost of the active packaging technology leads to a much higher cost on the newly developed supply chain compared to that of the traditional supply chain, the developed model could enhance new market channels, including selling prices, and provide growers with more benefits than the traditional supply chain.

An analysis on the role of blockchain-based platforms in agricultural supply chains

The traditional agricultural supply chain (ASC) has been overwhelmed by several challenges, including financing risk, counterparty risk, and lack of consumer trust. Platforms based on blockchain technology combined with Internet-of-Things technology have emerged to address these challenges by improving supply chain visibility, guaranteeing the execution of contracts, and increasing the authenticity of products’ provenance information in the ASC. This study analyzes how the adoption of a blockchain-based platform can affect the decisions of ASC participants and identifies how the platform creates value for the supply chain by addressing these three challenges. We consider a two-level supply chain featuring a typical cooperative and a buyer and establish stylized game models with and without the blockchain-based platform. By comparing equilibrium outcomes with and without the blockchain-based platform, we show that the involvement of the blockchain-based platform can lead to increased production quantity and total surplus of the supply chain. This can also motivate more sustainability/green investment to produce greener products. Interestingly, we show that the value of the blockchain-based platform decreases in the credibility of the business environment in which the supply chain operates. Furthermore, the buyer will always benefit from the established blockchain-based platform, whereas the cooperative can benefit in most cases but could be worse off under certain conditions. The adoption and operational costs could outweigh the benefits caused by the addition of the blockchain-based platform.

A System Dynamic Model of Closed-Loop Supply Chain considering Recovery Strengthening and Product Differentiation

Considering the strengthening effect of recovery on demand and the product differentiation, a multifactor closed-loop supply chain (CLSC) system dynamics (SDs) model is established and is simulated using the Vensim software. Based on the simulation data, influences of factors of “policy effect,” “recovery delay time,” “recovery strengthening,” and “recovery channel competitions” on the CLSC are analyzed. The results demonstrate that the order amplification and inventory amplification are all better than those of the traditional supply chain. Demands for remanufactured products and new products both reach the stable states in the later period. In addition, the variance analysis indicates that all the factors have a significant effect on the order and inventory amplifications in CLSC. Finally, some managerial implications are put forward.

A Blockchain-Based System for Agri-Food Supply Chain Traceability Management

Ensuring high quality and safety of food products has become a key factor on one hand to protect and improve consumers health and, on the other one, to gain market share. For this reason, much effort in the last year has been devoted to the development of integrated and innovative Agriculture and Food (Agri-Food) supply chains management systems, which should be responsible, in addition to track and store orders and deliveries, to guarantee transparency and traceability of the food production and transformation process. In this paper, differently from traditional supply chains which are based on centralized systems, we propose a fully distributed approach, based on blockchain technology, to define a supply chain management system able to provide quality, integrity and traceability of the entire supply chain process. The proposed framework is based on the Hyperledger Fabric technology, which is a permissioned blockchain system: a prototype has been developed and, by using some use cases, we show the effectiveness of the approach.

Analysis of Logistics 4.0 service quality and its sustainability enabler scenarios in emerging economy

The main purpose of this study is to identify the Logistics 4.0 service quality (L4.0SQ) criteria and to investigate the effectiveness of emerging technologies as sustainability and value-creating enablers on improving the quality of logistics services. In this regard, first, according to the literature review and using the opinion of industrial and academic experts, the criteria for measuring the logistics 4.0 services quality were classified into two groups: Competitive Lever and Social Value Creator. So that nine criteria were in the Competitive Lever group and five criteria were in the Social Value Creator group. Then, using the Group Grey BWM method, the importance of each of the extracted criteria was determined. In the next step, based on the selected criteria, the impact of each of the sustainability enablers on the logistics 4.0 services quality in the form of different scenarios using Improved Grey Relational Analysis (IGRA) was investigated. The findings show that among the sustainability enablers studied, artificial intelligence (S8), advanced robotics (S4), blockchain (S7) and additive manufacturing (S3) as the most important enablers in the Logistics 4.0 service quality. The results of this study provide a good guide for companies and managers to measure and improve the quality of logistics 4.0 services quality to address the challenges of traditional supply chain and logistics. It also enables companies to create more flexibility and agility in their processes to respond more quickly to customers and market needs.

Innovating the supply chain in health-related crises: some evidence from ISINNOVA case

PurposeAdditive manufacturing (AM) technologies, also known as three-dimensional printing (3DP), is a technological breakthrough that have the potential to disrupt the traditional operations of supply chains. They open the way to a supply chains innovation that can significantly benefit hospitals and health-related organizations in dealing with crises or unexpected events in a faster and more flexible way. In this study the authors identify the boundary of this potential support.Design/methodology/approachThe authors adopt a case study approach to understand the dynamics behind a well-known best practice to identify the main opportunities and the main pitfalls that AM may pose to health-related organizations wanting to leverage them.FindingsThe case highlights that it is possible to increase hospital flexibility using AM and that by leveraging the Internet it is possible to spread the benefits faster than what it would be normally possible using traditional supply chain processes. At the same time the case highlights that leveraging these technologies needs buy-in from all the relevant stakeholders.Originality/valueThe paper is one of the first, to the best of the authors' knowledge, to highlight the main opportunities and difficulties of implementing 3DP technologies in hospital supply chain management.

Redesigning traditional linear supply chains into circular supply chains–A study into its challenges

Transitioning to a Circular Economy (CE) is considered the most promising way to achieve economic and environmental sustainability. However, companies and governments are faced with challenges in redesigning existing linear supply chains (SCs) into circular supply chains (CSCs). Although previous research has tried to identify challenges in the implementation of CE in their own specific contexts, the literature lacks a systematic identification and validation of challenges to transition to circular supply chain management (CSCM). This study identifies the key barriers to the redesign of SCs into CSCs in the global manufacturing sector and develops a broad classification to facilitate their mitigation. An extensive review of the state-of-the-art literature on CSCM identified a list of 20 barriers plaguing manufacturing firms and impeding the transition of their linear SCs into CSCs. The barriers were analysed through 200 responses received from experts in the fields of CE and supply chain management using a questionnaire-based survey. The findings of the study suggest significant restraints towards CSCs implementation owing to the lack of incentives and policies, and product complexity. Moreover, the study of the broadly classified barriers such as standardisation and legal barriers, and financial and economic barriers indicate substantial similarities between the results and findings of the extant literature thereby implying significant alignment between the industry and the academia regarding the subject. This work is useful in formulating strategies to redesign CSCs, and helps researchers and practitioners to understand the challenges in implementing CSCs.

Designing a sustainable closed-loop supply chain network considering lateral resupply and backup suppliers using fuzzy inference system.

Sustainability is key factor for transforming traditional supply chain networks into modern ones. This study, for the first time, considers the impacts of the backup suppliers and lateral transshipment/resupply simultaneously on designing a Sustainable Closed-Loop Supply Chain Network (SCLSCN) to decrease the shortage that may occur during the transmission of produced goods in the network. In this manner, the fuzzy multi-objective mixed-integer linear programming model is proposed to design an efficient SCLSCN resiliently. Moreover, the concept of circular economy has been studied in this paper to reduce environmental effects. This study aims to optimize total and environmental costs, including energy consumption and pollution emissions, while increasing job opportunities. A demand uncertainty component is considered to represent reality more closely. Due to the importance of demand, this parameter is estimated using the Fuzzy Inference System (FIS) as an input into the proposed mathematical model. Then, the fuzzy robust optimization approach is applied in a fuzzy set’s environment. The model is tackled by a Multi-Choice Goal Programming Approach with Utility Function (MCGP-UF) to be solved in a timely manner, and the equivalent auxiliary crisp model is employed to convert the multi-objective function to a single objective. The proposed model is tested on the case study of the tire industry in terms of costs, environmental impacts, and social effects. The result confirmed that considering the concept of lateral resupply and backup supplier could considerably decrease the total costs and reduce shortages on the designed SCLSCN. Finally, sensitivity analysis on some crucial parameters is conducted, and future research directions are discussed.

Customer Prioritization Integrated Supply Chain Optimization Model with Outsourcing Strategies.

Pre-COVID-19, most of the supply chains functioned with more capacity than demand. However, COVID-19 changed traditional supply chains' dynamics, resulting in more demand than their production capacity. This article presents a multiobjective and multiperiod supply chain network design along with customer prioritization, keeping in view price discounts and outsourcing strategies to deal with the situation when demand exceeds the production capacity. Initially, a multiperiod, multiobjective supply chain network is designed that incorporates prices discounts, customer prioritization, and outsourcing strategies. The main objectives are profit and prioritization maximization and time minimization. The introduction of the prioritization objective function having customer ranking as a parameter and considering less capacity than demand and outsourcing differentiates this model from the literature. A four-valued neutrosophic multiobjective optimization method is introduced to solve the model developed. To validate the model, a case study of the supply chain of a surgical mask is presented as the real-life application of research. The research findings are useful for the managers to make price discounts and preferred customer prioritization decisions under uncertainty and imbalance between supply and demand. In future, the logic in the proposed model can be used to create web application for optimal decision-making in supply chains.

The Impact of Blockchain Technology and The Internet of Things on the Agile and Sustainable Supply Chain

In addition to being a revolutionary technology for all industries, the Internet of Things; has also shown its potential in processes such as supply chain. With the advancement of technology and the emergence of the new era, the challenges of the traditional supply chain that follows a path from top to bottom (suppliers of raw materials to final consumers) are revealed. Also, due to environmental issues and the increasing speed of the changes in the needs of customers in various industries, including the retail industry, which has undergone many changes with the emergence of innovation, the entire path of the supply chain requires the implementation of strategies such as agile and green supply chains and achieving smartness. Therefore, emerging technologies such as The Internet of Things play a significant role in the agility and greenness of the entire retail supply chain. The presence of blockchain technology with decentralized data archiving in supply chain processes based on the Internet of Things guarantees the security of big data and helps in optimal data performance. This helps the agility of supply chain processes. In this chapter, dimensions, components, and key indicators effective in the implementation of an agile smart supply chain based on transformative technologies are examined.

A Systematic Literature Review of Strategic Partnership in Sustainable Supply Chain - Indian Aerospace Industries

The sustainable supply chain is an integration of mainly environmental and social aspects to the traditional supply chain for an organization’s economic performance over a long period and creating a competitive advantage. Supply chain collaboration or strategic partnership is important in the supply chain network, which can result in effective sustainable supply chain in all three dimensions of environmental, social, and economic aspects of an organization. In the present study, an attempt has been made to develop a conceptual framework in understanding the role of supplier strategic partnership and collaboration in creating a sustainable supply chain in Indian aerospace industries. This framework has been developed by considering the concepts and research gaps identified by several researchers in the relevant research articles on sustainability, sustainable supply chain management, green supply chain management, supplier collaboration, or strategic partnership. This framework is developed focusing on goal 9 of the 17 sustainable development goals namely Industry, Innovation, and Infrastructure.

Determinants of Market Channel Choices by Vegetable Farmers in Sri Lanka

Purpose: The traditional vegetable supply chain in Sri Lanka is that the majority of farmers are small-scale farmers who have not had the ability or capacity to meet the final customer directly. As a result, more than 90% of the supply and distribution of vegetables is managed by a limited number of private intermediaries. It causes to distribute low profitability for producers and higher prices for consumers. The main aim of the study is to investigate factors that concurrently underpin Sri Lankan vegetable farmers' decision-making and influence their market channel choice.
 Methods: Drawing on the prior studies socio-economic, institutional, and marketing factors were selected. The primary data was collected from 150 vegetable farmers in Central province through a structured questionnaire. The cross-tabulation and ordinal regression analysis were utilized to identify the significant factors.
 Findings: The cross-tabulation analysis results indicated that there are significant differences in the farmers’ market channel choices in relation to various socio-economic, institutional, and marketing factors. The ordinal regression analysis revealed that socio-economic factors like age, gender, education level, number of family members; institutional factors such as distance to the nearest marketplace, access to market information, farm size; and marketing factors like price offer, network build significantly affect the market channel choices of the farmers.
 Implications: This study is useful to identify relationships between these variables and marketing channel choices can be further researched and these relationships can be utilized to enhance the knowledge and practices of farmers about selecting effective market channels.
 Originality: The study makes a unique and substantive contribution to the knowledge of vegetable farmers' decision-making about market channel choice in Sri Lanka and theoretically contributes to the role of socio-economic, institutional, and marketing aspects in predicting potential market choices.

Credit Risk Early Warning of Small and Medium-Sized Enterprises Based on Blockchain Trusted Data

Small and medium-sized enterprises (SMEs) are now growing rapidly and playing an important role in the development of the national economy. As the economy grows, the contradiction between the credit risk of SMEs and the credit risk early warning mechanism of traditional supply chain financing has become increasingly important. In response to the issues of a single source of business information, the high investment cost of the existing early risk early warning mechanism, etc., from a commercial bank credit risk management perspective, this paper proposes to build an SMEs credit risk early warning system based on reliable blockchain data. The reliability of the data obtained is assessed utilising a hierarchical analysis and a vague overall judgement method. The results show that the use of blockchain technology can enhance the credibility and accuracy of the data, which provides a data guarantee for more rapid risk alert.

Multiauthority Attribute-Based Access Control for Supply Chain Information Sharing in Blockchain

Information sharing has become an important application in modern supply chain management systems with business technology development. Because traditional supply chain information systems have problems such as easy data tampering, low information transparency, and interaction delays, blockchain has been taken consideration into supply chain information sharing research. Furthermore, blockchain technology is expected to provide decentralized supply chain information sharing solutions to enhance security, availability, and transparency. However, with the in-depth study of the application of blockchain technology in supply chain information sharing, people have found that the data stored publicly in the blockchain are still threatened by privacy leakage. In addition, due to the openness and accessibility of the blockchain, the lack of fine-grained access control is also apparent. In order to improve the security of data, we propose a novel privacy-preserving multiauthority attribute-based access control scheme for secure blockchain-based information sharing in a supply chain. In this scheme, blockchain stores encrypted supply chain information on distributed nodes. Multiple attribute authorities manage different attributes of users to achieve fine-grained access control and flexible authorization. Even if some attribute authorities fail, the user’s private key will not be leaked. In user secret key generation, we adopt an anonymous key generation protocol to realize the secure distribution of user keys by the attribute authorities. Furthermore, in order to meet the protection of communication privacy between blockchain nodes, properties of policy hiding and identity hiding are considered. Finally, we design experiments to analyze the performance of our scheme, including secret key sizes and running time of encryption and decryption.

A technological quality control system for rice supply chain

AbstractRice quality affects social stability, consumer health, and corporate brand benefit. The traditional supply chain traceability management system is centralized, monopolized, asymmetric, and opaque. It is the main factor leading to frequent food safety incidents. This paper proposes a technological quality control system for rice supply chain to protect rice products quality and safety. Firstly, it adopts risk assessment and traceability mechanism to prevent the hazard factors in the production and processing. Then, to prevent spoiled food from endangering the consumers’ health and reduce food waste, it explores a shelf life model of rice products to predict the remaining shelf life of products. Finally, this paper constructs a decentralized traceability management system based on blockchain and IoT, which enables consumers to access the real information of rice products and helps supervisors to monitor the quality of products in the supply chain.

Nexus among blockchain visibility, supply chain integration and supply chain performance in the digital transformation era

PurposeDigital transformation (DT) in the semiconductor industry goes beyond traditional business operations and supply chain management (OSCM) to the digital world. Despite significant developments in recent years, blockchain implementations for OSCM remain relatively underdeveloped in the semiconductor industry. Therefore, this research aims to examine the relationships between blockchain visibility, supply chain integration (SCI) and supply chain performance (SCP) in the era of DT in Malaysia's semiconductor industry to shed light on this emerging area.Design/methodology/approachA convenience sampling of 71 operations and supply chain managers attached to semiconductor manufacturing firms in Malaysia were invited to participate in a survey. In assessing blockchain visibility within the industry, key terms namely business intelligence gathering, information exchange, information technology (IT) and knowledge of asset status, were conceptualised from the literature review. The questionnaires developed to collect data were validated by industry and academic experts.FindingsThe results from the analysis confirmed that SCI mediates the link between blockchain visibility (information exchange, business intelligence gathering and knowledge asset status) and SCP. Likewise, the importance-performance matrix analysis (IPMA) outcomes revealed that IT played a minor role. The results suggested that semiconductor manufacturers should pay less attention to IT since this was identified as having the least priority towards improvement.Practical implicationsThe outcomes from this research enable policymakers to strategise and integrate blockchain technology in the era of DT to ensure sustainable SCM in the semiconductor industry in Malaysia.Originality/valueThe research bridge the knowledge gap by revealing the value that blockchain visibility can facilitate SCP and explore SCI as the prevailing factor and demonstrates how Resource-Based Theory and Network Theory can be applied in this study.

Additive Manufacturing Enabled Supply Chain Management: A Review and Research Directions

The emergence of additive manufacturing (AM) is expected to recon figure the traditional supply chain (SC) with more flexibility and agility, leading to opportunistic collaboration. The purpose of the work is to identify research dimensions based on AM-enabled supply chain management (SCM) taxonomy from the product, information and service flow point of view. This article uses a systematic literature review (SLR) on AM-enabled SCM. The literature from 116 peer-reviewed journal papers over 10 years (2010–2021) was comprehensively reviewed and assessed. The selected articles were characterized using (a) SC processes—upstream, manufacturing and downstream and (b) SC flows—goods and services, information and finance. This work provides a direction to scholars and academicians for identifying important SC implications of AM technology adoption. Practitioners can benefit by understanding several challenges involved in AM technology adoption and its implications on SC processes. This work adds new insights by identifying research dimensions based on AM-enabled SCM taxonomy.