Traditional Supply Chain Research Articles

Risk-based allocation of COVID-19 personal protective equipment under supply shortages

The COVID-19 outbreak put healthcare systems across the globe under immense pressure to meet the unprecedented demand for critical supplies and personal protective equipment (PPE). The traditional cost-effective supply chain paradigm failed to respond to the increased demand, putting healthcare workers (HCW) at a much higher infection risk relative to the general population. Recognizing PPE shortages and high infection risk for HCWs, the World Health Organization (WHO) recommends allocations based on ethical principles. In this paper, we model the infection risk for HCWs as a function of usage and use it as the basis for distribution planning that balances government procurement decisions, hospitals’ PPE usage policies, and WHO ethical allocation guidelines. We propose an infection risk model that integrates PPE allocation decisions with disease progression estimates to quantify infection risk among HCWs. The proposed risk function is used to derive closed-form allocation decisions under WHO ethical guidelines in both deterministic and stochastic settings. The modelling is then extended to dynamic distribution planning. Although nonlinear, we reformulate the resulting model to make it solvable using off-the-shelf software. The risk function successfully accounts for virus prevalence in space and in time and leads to allocations that are sensitive to the differences between regions. Comparative analysis shows that the allocation policies lead to significantly different levels of infection risk, especially under high virus prevalence. The best-outcome allocation policy that aims to minimize the total infected cases outperforms other policies under this objective and that of minimizing the maximum number of infections per period.

Addressing Proficiency Gaps in Future Skills Between Employers and Learners Through Data Visualization.

The pandemic has principally changed the way the construction industry operates. It has caused a profound shift in how we conduct our work, with a large-scale take-up of remote working and changes in our digital approach. The way we work is changing. All these impacts challenge the traditional supply chain and working practices of the construction industry negatively, resulting in price escalations, additional costs, loss of revenue, payment delays and increase in disputes and claims. This study aimed to assess the skill proficiency of learners and narrow the employers' and young engineers' perspectives on what are the future skills requirements in the construction industry in the world of digitalization. This study, which comprised two surveys entitled "Future Skills-What does the future look like for young engineers?" (for employers) and "WLA Survey in "Future Skills"-The Proficiency Analyses of Young Engineers-to-be" (for learners), was a part of the Workplace Learning and Assessment (WLA) Engagement Series for students. This research attempts to map skill proficiency of learners (or young engineers-to-be) with the future skill requirements of the employers and to make recommendations on the construction-related institutional arrangements. A quantitative approach by using online surveys as the main data collection tool was adopted. A sample of 20 WLA-participating employers and 23 WLA-participating students in construction companies was generated. In December 2021, the project team initiated two surveys to explore the expectation for the future workforce in the construction industry. Interview results covering various construction-related disciplines, including civil engineering, building studies, surveying and building technology, were analysed and illustrated using Microsoft Power BI. Content analysis with data visualizations was used to identify major themes. This study has shown that employers and students have different perceptions of skills and attributes as critical competencies for a successful workforce. On a positive note, there was a high level of satisfaction for both employers and learners in "Training Structure" and "Training and Development". This study highlighted that students did not have the appropriate level of knowledge as expected by their employers in key subject areas of the construction industry. Employers expressed a clear expectation for the roles and responsibilities of young engineers in their organizations. Areas of practice such as building information modelling (BIM), "Problem Solving", and "Presentation Skills" were highlighted as critical for the future. The competency of youngsters in achieving targeted vision and goals as well as the competency in striving for continual improvement was identified as highly relevant for the future. There was potential for young engineers to play a more active role in their organizations and to repackage their technical skill and interpersonal skill sets for anticipated future roles. The choice of the quantitative research design approach was guided by the need to capture numerical data in the construction industry of Hong Kong for the purpose of illuminating differences in perspectives among participants about future skills for WLA implementation in vocational and professional education and training (VPET). This study can help to investigate the skill proficiency gaps that employers will be looking for and how WLA can bring maximized benefits to students and companies. Based on the results, the students can be better informed about the workplace settings and be prepared for the upcoming industrial attachment or apprenticeship programme with WLA. Feedback provided by the companies can help support students' transition into the world of work. On the other hand, by understanding learners' self-perception, this adaptation made by the companies could result in what looks to be part of a longer-term change in how we work, particularly with a move to increased use of hybrid working. The statistical models with data visualization based on Power BI can also lead to the experimentation and inference that inform the institution's strategy.

A Hybrid Optimization Method for Sustainable and Flexible Design of Supply–Production–Distribution Network in the Physical Internet

The resilience and sustainability of supply chains are facing new challenges due to the increasing complexity of supply chains. Compared to traditional supply chain networks, the Physical Internet (PI) has the potential to address sustainable development challenges and build resilient supply chain networks by providing interconnected and open logistics services. However, the interplay between resilience and sustainability has yet to be thoroughly explored in the PI-enabled supply chain literature. This paper aims to investigate the relationship between resilience and sustainability in PI-enabled supply chains. An innovative hybrid approach that combines the resilient-sustainable performance scoring method with mixed-possibilistic programming is proposed to trade-off and analyze the relationship between the two. Applying the concepts of resilience and sustainability to PI-enabled supply chains involves optimizing costs, sustainable performance, and resilience levels simultaneously. This enables coping with unforeseen disruptions from suppliers, plants, and PI hubs. The results of computational experiments have demonstrated that the PI-enabled supply chain exhibits stronger sustainable and resilience performance in dealing with random disruptions compared to traditional supply chains. The fruitful research yielded important management insights and practical implications, thereby contributing to the reinforcement of the literature on PI.

A Novel Risk Control Method of Supply Chain Finance for Commercial Banks with Big Data

Commercial bank supply chain financial business is mainly divided into accounts receivable financing mode, inventory financing mode and advance financing mode. Traditional supply chain financial business of commercial banks in different modes will form different risks, including small and medium-sized enterprise credit risk, the core enterprise credit risk and credit risk of the third-party logistics warehousing company. Under the background of increasingly powerful financial science and technology, we can use more financial technology through big data multidimensional collecting enterprise information, establishing intelligent risk control process, establishing the core enterprise credit evaluation system, preventing the core and small and medium-sized enterprises collusion fraud, preventing the third-party logistics warehousing enterprise credit risk, and reducing the risk of commercial banks supply chain financial business.

Analyzing the critical success factors to implement green supply chain management in the apparel manufacturing industry: Implications for sustainable development goals in the emerging economies

Green supply chain management (GSCM) is an emerging concept of modern supply chain management (SCM) that integrates eco-friendly and ethical environmental concerns with the traditional supply chain by reducing the negative impacts of unsustainable manufacturing practices. Developed countries have already adopted different sustainable SCM practices. However, despite being one of the significant sources of export earnings in emerging economies like Bangladesh, the apparel manufacturing industry is still lagging in the case of GSCM implementation. This study, thereby, utilized an integrated multi-criteria decision-making (MCDM) approach, including gray theory and decision-making trial and evaluation laboratory (DEMATEL) method to identify, prioritize, and examine the relations among the critical success factors (CSFs) to implement GSCM practices in the Bangladeshi apparel manufacturing industry. The study initially identified the CSFs from the literature review. After expert validation, sixteen significant CSFs were finally analyzed by the gray-DEMATEL method. The findings revealed that 'demand from buyers', 'economic and tax benefits', and 'government rules and regulations' are the three most prominent CSFs to implement GSCM practices in the apparel manufacturing industry. The cause-effect relations among the CSFs were later explored, which indicated 'Economic and tax benefits' to be the most influencing and 'Supplier training and cooperation' to be the most influenced CSF. The study insights can potentially guide apparel industry managers in successfully implementing GSCM practices toward achieving long-term sustainability and sustainable development goals (SDGs).

Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

RFID supply chain data deconstruction method based on artificial intelligence technology

Abstract Radio frequency identification (RFID) is a broad rapidly evolving skill in the past few years. It is characterized by non-contact identification, fast read and write speed, small label size, large data storage capacity, and other technical advantages. RFID technology for goods movement has completely changed the traditional supply chain management, greatly improved the operational efficiency of enterprises, and has become an important method for the development of supply chain logistics. This work mainly studies and analyzes the RFID supply chain, introduces the development and application of RFID supply chain sector technology, and discusses the operation of the supply chain in detail. Then, according to the existing RFID supply chain, a RFID supply chain artificial intelligence (AI) based approach to technology is proposed, and the data analysis of RFID supply chain is introduced in detail. In this work, through the research experiment of AI technology RFID supply chain data analysis, the experimental data show that there are several time-consuming links in the supply chain system. The time consumed in the AI RFID system is 9.9, 3.4, 3.5, and 29.9 min, respectively, while each link in the original system takes 13.4, 4.9, 4.9, and 34.9 min. It can be seen from the above data that the amount of time in each system link of the AI RFID supply chain system is less than that of the original supply chain system, which shortens the entire product passing cycle and greatly improves work efficiency.

Inventory management and information sharing based on blockchain technology

This paper presents a structural framework for blockchain-based supply chains (SCs) and demonstrates how blockchain technology can help realize five crucial changes: common platform, end-to-end information sharing and traceability, real-time update, speedy and efficient asset transfer, and contract automation. The most unique change is that a blockchain-based supply chain operates on a decentralized common platform, in contrast to the tiered structure of a traditional supply chain. Using fundamental analytical models, inventory management and information-sharing benefits from the abovementioned critical changes were quantified. Therefore, the three managerial implications for supply chain resilience are as follows. (1) A blockchain-based SC essentially transforms a multi-tier SC into a one-platform SC, effectively shortening the length of SC tiers and therefore eliminating problems and challenges in multi-tier supply chain management (SCM). (2) A blockchain-based SC can be both time- and cost-efficient. (3) A company on the blockchain platform can reduce the cost and risk/variance associated with its SC partners. These results can substantially contribute to the industry, given that blockchain is in the early stage, thus rendering supply chains smarter and more efficient.

Modelling the barriers of rice supply chain in India using the fuzzy logic approach

PurposeRice is an important grain in Indian scenarios, and the purpose of the research work is to identify the attributes which can be the possible barriers in the traditional rice supply chain network.Design/methodology/approachA multilevel conceptual model is developed based on the literature review, and a field study is conducted by administering a questionnaire from the experts. Fuzzy logic methodology and a ranking score method is applied to identify the rice supply chain performance and the barriers of the traditional rice supply chain network.FindingsThe rice supply chain performance index for the traditional rice supply chain network is obtained, and the performance of the existing rice supply chain is found to be “fair”. The “information flow” is the attribute that can be a critical weak attribute in the traditional rice supply chain network. A proposed model of the blockchain technology-enabled rice supply chain network is developed as a solution for the “information flow” barrier.Research limitations/implicationsThe present research work is focussed on the generalized rice supply chain model of the Indian scenario, and more detailed studies can be carried out based on the regional issues.Originality/valueThe rice supply chain plays an important role in Indian economic development, and hence the current research paper focusses on identifying the barriers and the performance of the existing rice supply chain network.

An overview of the impact of additive manufacturing on supply chain, reshoring, and sustainability

The paper provides an overview of the impact of the integration of additive manufacturing (AM) within the supply chain, the correlation with the reshoring phenomenon, and its effect on environmental sustainability. Implementing AM technologies simplifies the traditional supply chain and significantly reduces costs related to transport and warehousing. Furthermore, it allows for a considerably reduced production of waste. However, the high price of machinery and the lack of current knowledge prevent it from spreading widely.

Moving from the Traditional Practices to the Green Era

As environmental issues have become of prime importance, green supply chain management (GSCM) has become a proactive approach for industries to improve their environmental performance and develop a competitive advantage. GSCM has been widely implemented by different industrial sectors to minimize the environmental impact of their supply chain activities, such as waste generation and pollution. Nowadays, industries are seeking to convert their traditional supply chain management (TSCM) to (GSCM) due to concerns about environmental sustainability and to improve their overall performance, develop a competitive advantage, and gain a brand image. This paper started with an interest in understanding the factors that lead companies to convert their traditional practices to more environmentally friendly activities. Many theories in the literature were employed to explore the topic of GSCM; three theories have been observed to be the vital theoretical pillars within the GSCM literature namely, institutional theory, stakeholder theory, and resource-based view theory. These theories will be discussed in this paper. The aim of reviewing these theories is to understand the transition process from TSCM into GSCM. Additionally, the transition from TSCM to GSCM is associated with tensions that may arise as companies still prioritize the economic goals over the environmental dimensions. This paper will investigate the potential tensions and conflicts GSCM barriers may cause between various stakeholders. Therefore, the goal of this paper is to explore what the pressures are for companies to implement green supply chain management, what drives or prevents companies from adopting GSCM. To accomplish this task, literature is reviewed, focusing on theories, tensions, drivers, and barriers that are related to the field of GSCM.

An exploration into the factors influencing the implementation of big data analytics in sustainable supply chain management

PurposeWith big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).Design/methodology/approachThe factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).FindingsA total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.Research limitations/implicationsThis research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.Practical implicationsThis research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.Social implicationsThe result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.Originality/valueThis research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

Decision-Making Models and Coordination in a Closed-Loop Supply Chain Considering Patent Protection for DfR

With improvement in consumers’ environmental awareness and the level of design for remanufacturing (DfR), the traditional supply chain is gradually changing into a closed-loop supply chain (CLSC). However, a high level of remanufacturing design will increase design costs for manufacturers, while also reducing the cost for remanufacturers. Moreover, manufacturers usually use patent barriers to restrict the development of remanufacturers. The main aims of this study were to explore how manufacturers and remanufacturers can benefit each other, taking into account patent protection and carbon emissions. Firstly, we adopted game theory to establish four decision-making models of the manufacturer and remanufacturer regarding DfR. Secondly, we designed a cost-sharing contract for DfR based on the decentralized decision-making model to coordinate a CLSC. The results of this study showed that under the patent-protected market environment, DfR increased the manufacturer’s profit but did not necessarily promote the remanufacturer’s profit growth. A cost-sharing contract can effectively achieve improvements in the presence of DfR, increase profits for both parties, and improve the economic and environmental benefits of the CLSC.

The Impact of Social Preferences on Supply Chain Performance: An Application of the Game Theory Model

Traditional supply chain literature on contracting only considers agents’ economic motivation. Nowadays, with the development of behavioral economics, social preference theory has been widely used in supply chain research. These social preferences are distinct from economic motivation and will influence agents’ behaviors in the supply chain. Agents will make decisions based on not only self-interests but also the interests of others, reciprocity, and fairness. This paper introduces the relationship and status preferences in the utility function. We aim to analyze the impact of social preference on individual competition intensity in the supply chain. A Stackelberg game model (tacit collusion) is used as the theoretical framework of the choice behavior between competition and cooperation. The theoretical results and numerical simulation analysis show that under some conditions, suppliers and retailers who take the social preference factors into account can realize multiple-stage channel coordination through revenue sharing. Moreover, social preference factors will influence the choice behavior of agents in competition and cooperation. Specifically, the relationship preference promotes close cooperation among enterprises and significantly improves the supply chain and individual performance. Status preference causes fierce competition among enterprises and adversely affects supply chain performance and individual performance, making it more unstable. These findings can provide useful insights for supply chain coordination.

The Importance of Digitalization for the Sustainability of the Food Supply Chain

This paper aims to define the negative impact of various indicators on the sustainability and functioning of the traditional food supply chain (FSC) in the segment of wholesale and retail activities and to propose a set of measures and incentives for the digitalization of its business processes. After a systematic review of the literature, the most common indicators significant for the functioning of the FSC were defined, primarily in the segment of wholesale and retail activities. Empirical research examined the influence of given indicators on the FSC. The obtained results showed that indicators such as poor coordination and transfer of information among FSC participants, food loss, economic performance, transaction costs, external elements, chemical and microbial contamination, and control of raw material, food, and waste flows significantly complicate the sustainability and functioning of the FSC. Based on the obtained results, a set of measures and incentives is proposed that the management of the supply chain should undertake to digitalize business processes, primarily in the segment of wholesale and retail activities. This paper also lists shortcomings of the research and gives guidelines for future research.

Covid-19 Specific Challenges and Solutions in Digital Transformation for the Retail Sector

Digital transformation is characterized by gathering individuals, data, and processes to generate value for online customers and stay competitive in the new consumer marketplace. This has increasingly become common in retail. Digital consumer retailers are experimenting with numerous ways to adapt to new shoppers’ needs, attempting to combine the digital market with the conventional market, and finding various ways to revolutionize the digital transition of modern times. During the ongoing COVID-19 crisis, traditional supply chains for food are challenged in an unprecedented manner. This paper recommends the rapid implementation of digital transformation to identify both immediate and mid-level goals which hold the key to sustainable growth and profit. In this paper, I’ve proposed three main solutions to the challenges mentioned above, which would help satisfy all demands and fulfill the customers’ needs during this Covid-19. Still, it is also required to think that these solutions should give good results for technologically sound people like old generations. Hence, making those solutions user-friendly is the important way to be leveraged by all types of customers to improve their experiences effectively, which would also help grow business.

Design and implementation of the food supply chain traceability system based on the blockchain

Traditional enterprise-level food supply chain traceability systems are notoriously expensive and complex to set up, but there is a solution that can successfully address both of these problems: the food supply chain traceability system. This study, on the other hand, suggests a blockchain-based food supply chain traceability system business system. The paper is concerned with the food supply chain traceability system. The authentication and authorization procedures, traffic scheduling, and settlement monitoring are examples of some of the operations that make use of the blockchain infrastructure. In the meanwhile, the throughput of the system is increased by making improvements to the consensus method. Users of this system can provide customized service needs for food supply chain traceability systems by using this system. The issue of locking up the system in the food supply chain traceability system is successfully solved by the system, which embodies a great deal of application potential inside the food supply chain traceability system.

Industry 5.0 challenges for post-pandemic supply chain sustainability in an emerging economy

To ensure business continuity in the post-COVID-19 era, decision-makers should reconfigure their traditional supply chain (SC) networks, assisted by the development and implementation of cutting-edge technologies. Recently, Industry 5.0 (I5.0) has gained increasing attention as a paradigm offering salient features for the creation of resilient and inclusive operations by ensuring long-standing SC sustainability. However, there has been insufficient analysis of the challenges of implementing I5.0 in SCs. Therefore, this study aims to understand the challenges of implementing I5.0 when managing the impact of SC disruptions due to the COVID-19 pandemic in an emerging economy. Both qualitative and quantitative methods were used for this research. First, the challenges to I5.0 implementation were identified through a literature review and experts’ feedback. Those challenges were examined and prioritised using the Best-Worst Method (BWM). Second, the contextual relationships amongst these challenges were analysed using interpretive structural modelling (ISM) with cross-impact matrix multiplication applied to classification (MICMAC) analysis. Findings showed that to adopt I5.0 initiatives successfully in order to manage the post-COVID-19 impact on SC sustainability, the active involvement of senior managers is required in the execution process. Findings also showed that financial support and funding (e.g., tax reduction, short loans, etc.) from investors and the government play a pivotal role in enabling sustainability in SCs. Finally, the challenges were classified using MICMAC analysis to provide valuable insights for managing future disruptions. This study is expected to help managers and decision-makers successfully overcome the challenges of implementing I5.0 in SCs and thus improve SC sustainability.

Green supply chain management, risk-taking, and corporate value—Dual regulation effect based on technological innovation capability and supply chain concentration

With the promotion of carbon-peak and carbon-neutral strategies and the increase in green awareness, green development is gradually gaining attention, and the green supply chain management (GSCM) derived from traditional supply chain management is gradually becoming a path to promote green development. At the same time, enterprise, as an important source of pollution, how to consider social responsibility, such as environmental protection, in the process of ensuring efficiency improvement has become an important issue. To study the impact of green supply chain management on enterprise value and its path of action, this paper examines the impact of green supply chain management on enterprise value, explores the moderating effect of the risk-taking level, and further analyzes the dual moderating effect played by technological innovation capability and supply chain concentration. Based on the micro data of 131 Chinese listed enterprises from 2014 to 2021, a panel-regression model is used to illustrate how green supply chain management affects enterprise value, and the results show that: 1) green supply chain management can promote enterprise value; 2) the level of risk-taking strengthens the promoting effect of green supply chain management on enterprise value enhancement; and 3) the technological innovation capability negatively regulates the moderating effect of risk-taking, while the supply chain concentration positively regulates the moderating effect of risk-taking. The research results of this paper enrich the path of the effect of implementing of green supply chain management on enterprise value enhancement, i.e., the process of green supply chain management to enhance enterprise value is regulated by the level of enterprise risk-taking, while technological innovation capability and supply chain concentration will also regulate the level of enterprise risk-taking and thus promote enterprise value enhancement. This research not only extends the research perspective and enriches the existing research, but also provides a theoretical basis for enterprises to implement green supply chain management to promote value enhancement and improve the level of green supply chain management implementation and the green development of enterprises.

A novel extended Portuguese of Interactive and Multi‐Criteria Decision Making and Archimedean Bonferroni mean operators based on prospect theory to select green supplier with complex q‐rung orthopair fuzzy information

AbstractThe word sustainable or green supply chain refers to the concept of incorporating sustainable environmental procedures into the traditional supply chain. Green supply chain management gives a chance to revise procedures, materials and operational ideas. Choosing the fuzziness of assessing data and the spiritual situations of experts in the decision‐making procedure are two important issues. The main contribution of this analysis is to derive the theory of Archimedean Bonferroni mean operator for complex q‐rung orthopair fuzzy (CQROF) information, called the CQROF Archimedean Bonferroni mean and CQROF weighted Archimedean Bonferroni mean operators which are very valuable, dominant and classical type of aggregation operators used for examining the interrelationship among the finite number of attributes in modern data fusion theory. Inspirational and well‐used properties of the initiated theories are also diagnosed with some special cases. Additionally, the theory of extended TODIM tool using the prospect theory based on CQROF information was discovered, which play an essential and critical role in the environment of fuzzy set theory. Finally, a real life problem by computing a green supply chain management based on the initiated CQROF operators was evaluated and fully illustrating the feasibility and efficiency of the diagnosed work with the help of a comparison between existing and prevailing theories.