This research was conducted on industrial agriculture in Indonesia. Risk analysis was carried out based on previous research. One source of risk was obtained, namely raw materials that did not meet specifications, which was then proposed to be mitigated by evaluating supplier performance. This activity involves a lot of data, requiring efficient and effective data storage and access. The level in the simulation layout includes analysing system needs, using problem diagrams, compiling activity diagrams, deciding subprocesses, and filtering information. The analysis is carried out by comparing the use of supply chains with Blockchain and without Blockchain, which is then obtained to determine whether there is an increase. A sequentially stored data scenario describes a situation when the transaction process is in progress and is stored sequentially according to the process that occurs. Storing data in groups explains a problem when a transaction has been completed and stored in groups with similar data, making it easier to track specific data. In this regard, a simulation will be carried out using a website, namely a blockchain demo. The design stage starts with identifying system requirements, creating use case diagrams, compiling activity diagrams, determining subprocesses, and selecting information. The simulation results obtained will be analysed to determine the feasibility of Blockchain as a means of supporting risk mitigation related to data using aspects, including security, trust, traceability, sustainability, and costs.

In Italy, the wine supply chain is a cornerstone of the national agri-food system and a driving force for the entire economy. The aim of this study is to map the profile of Italian wine companies through the analysis of multiple case studies. The study focuses specifically on companies in the Marche region, investigating their features and supply chain, with a specific focus on product and system certification adopted, marketing policies implemented, and the businesses\' relationship with institutions. A total of 18 companies participated in the study. The primary data for the research was collected through semi-structured interviews lasting 1 h, based on an interview protocol. The results show that the supply chain for the wine sector is configured to be short, even when cooperatives act as an aggregator. The small size and limited financial resources make it particularly difficult to promote the wine outside its reference context, and there is a lack of a network strategy at the local level. Many companies consider organic certification a disadvantage since it tends to homologate production to the large wine industries, making the product\'s naturalness, typicality, and craftsmanship disappear.

Over the past 2 years, the COVID-19 pandemic has placed enormous pressure on the health care industry. There has been an increase in demand and, at the same time, a shortage of supplies. This has shown that supply chain management in the health care industry cannot be taken for granted. Furthermore, the health care industry is also facing other major challenges, such as the current labor market shortage. In the literature, the Internet of Things (IoT) is highlighted as an effective tool to build a more resilient and efficient supply chain that can manage these challenges. Although using IoT in supply chain management has been extensively examined in other types of supply chains, its use in the health care supply chain has largely been overlooked. Given that the health care supply chain, compared to others, is more complex and is under growing pressure, a more in-depth understanding of the opportunities brought by IoT is necessary.
This study aims to address this research gap by identifying and ranking the drivers of and barriers to implementing IoT in the health care supply chain.
We conducted a 2-stage study. In the first, exploratory stage, a total of 12 semistructured interviews were conducted to identify drivers and barriers. In the second, confirmatory stage, a total of 26 health care supply chain professionals were asked in a survey to rank the drivers and barriers.
The results show that there are multiple financial, operational, strategy-related, and supply chain-related drivers for implementing IoT. Similarly, there are various financial, strategy-related, supply chain-related, technology-related, and user-related barriers. The findings also show that supply chain-related drivers (eg, increased transparency, traceability, and collaboration with suppliers) are the strongest drivers, while financial barriers (eg, high implementation costs and difficulties in building a business case) are the biggest barriers to overcome.
The findings of this study add to the limited literature regarding IoT in the health care supply chain by empirically identifying the most important drivers and barriers to IoT implementation. The ranking of drivers and barriers provides guidance for practitioners and health care provider leaders intending to implement IoT in the health care supply chain.

To achieve SDGs (sustainable development goals) and carbon neutrality goals, the Chinese government have been adopting the cap-and-trade regulation to curb carbon emissions. With this background, members in the supply chain should properly arrange their carbon reduction and marketing decisions to acquire optimal profits, especially when the favorable event may happen, which tends to elevate goodwill and the market demand. However, the event may not be of their benefit when the cap-and-trade regulation is conducted, since the increase in market demand is always associated with an increase in carbon emissions. Hence, questions arise about how the members adjust their carbon reduction and marketing decisions while envisioning the favorable event under the cap-and-trade regulation. Given the fact that the event occurs randomly during the planning period, we use the Markov random process to depict the event and use differential game methodology to dynamically study this issue. After solving and analyzing the model, we acquire the following conclusions: (1) the occurrence of the favorable event splits the whole planning period into two regimes and the supply chain members should make optimal decisions in each regime to maximize the overall profits. (2) The potential favorable event will elevate the marketing and carbon reduction efforts, as well as the goodwill level before the event. (3) If the unit emissions value is relatively low, the favorable event will help to decrease the emissions quantity. However, if the unit emissions value is relatively large, then the favorable event will help to increase the emissions quantity.

This paper presents a new mathematical model of the green closed-loop supply chain network (GCLSCN) during the COVID-19 pandemic. The suggested model can explain the trade-offs between environmental (minimizing CO2 emissions) and economic (minimizing total costs) aspects during the COVID-19 outbreak. Considering the guidelines for hygiene during the outbreak helps us design a new sustainable hygiene supply chain (SC). This model is sensitive to the cost structure. The cost includes two parts: the normal cost without considering the coronavirus pandemic and the cost with considering coronavirus. The economic novelty aspect of this paper is the hygiene costs. It includes disinfection and sanitizer costs, personal protective equipment (PPE) costs, COVID-19 tests, education, medicines, vaccines, and vaccination costs. This paper presents a multi-objective mixed-integer programming (MOMIP) problem for designing a GCLSCN during the pandemic. The optimization procedure uses the scalarization approach, namely the weighted sum method (WSM). The computational optimization process is conducted through Lingo software. Due to the recency of the COVID-19 pandemic, there are still many research gaps. Our contributions to this research are as follows: (i) designed a model of the green supply chain (GSC) and showed the better trade-offs between economic and environmental aspects during the COVID-19 pandemic and lockdowns, (ii) designed the hygiene supply chain, (iii) proposed the new indicators of economic aspects during the COVID-19 outbreak, and (iv) have found the positive (reducing CO2 emissions) and negative (increase in costs) impacts of COVID-19 and lockdowns. Therefore, this study designed a new hygiene model to fill this gap for the COVID-19 condition disaster. The findings of the proposed network illustrate the SC has become greener during the COVID-19 pandemic. The total cost of the network was increased during the COVID-19 pandemic, but the lockdowns had direct positive effects on emissions and air quality.

Sustainable supply chain management (SSCM) has received extensive attention by academia and industries recently. However, there are increasing yet still scarce studies measuring the social sustainability performance of supply chain and discussing the interrelationship between social and economic sustainability. Further, the measurement does not fully utilize key performance indicators (KPIs) attributing to the lack of understanding of precise quantitative gauge of the supply chain social sustainable performance. To bridge this gap, this study analyses the social and economic sustainability performance in terms of demand planning, innovation, manufacturing, finance, sales and customer relationship, distribution and delivery and compliance. A framework is proposed to locate key metrics to evaluate the social sustainable supply chain (SSC) performance. A hybrid fuzzy-AHP-DEMATEL-VIKOR method is designed to investigate the social sustainability of supply chain. Data analysis and a case study are given to validate and support the feasibility and potency of the proposed approach. The robustness of our proposed model is executed via sensitivity analysis. From the proposed framework, demand planning and distribution and delivery are found to be the most critical criteria in economic and social dimension, respectively.

Due to the destructive effects of fossil fuels on the environment, using renewable energies has nowadays been suggested. In addition, because of the increased use of solar energy and the prevention the solar cell supply chain (SCSC), this chain is mainly supported by government funding. In this study, we mathematically model both supply-side and demand-side policies for a two-echelon SCSC, considering the competition between domestic and foreign suppliers as well as government intervention under the supply-side subsidy policies to support SCSC members and finance the customers through demand-side subsidy policies. The aim of this paper is to investigate the effects of government intervention under the supply-side and demand-side policies on supporting the members of SCSC and encouraging customers to increase the use of solar panels. In addition, this study explores the best policy for improving and promoting SCSC. In the real world, both supply-side and demand-side policies will help industrial factories, power plants, and households to enhance the use of solar energy for producing electricity. This study has been investigated using one real example, whose results show that the efficiency under the supply-side policy is about 7% more than the efficiency under the demand-side policy. The price under the supply-side policy is roughly 10% less than the price under the demand-side policy. The members\' profit under the supply-side policy is approximately 5% bigger than the one under the demand-side policy. According to real examples, the government\'s utility under the demand-side policy is nearly 1% smaller than the government\'s utility under the supply-side policy. Finally, key findings are considered for the proposed model.

BACKGROUND: Da Vinci surgery is used extensively, but the high costs of the surgical instrument are a serious clinical and management problem.
OBJECTIVE: To reduce the cost of the Da Vinci robotic surgical instrument supply chain.
METHODS: Patients were selected from the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. Control group patients underwent Da Vinci robot-assisted surgery between January 2019 and June 2019 (control group). Patients who were operated with the same robot from July 2019 to December 2019 were selected as the experimental group (SCM group). The cost analysis and comparison were carried out to integrate instrument sets, working hours, workforce expenditure, and direct and indirect expenses.
RESULTS: Compared with the control group, the number of instrument packages was lower (4.5 ± 1.4 vs. 11.5 ± 1.6, P< 0.001) and the personnel\'s awareness of the instruments was higher (92.3 ± 4.2 vs. 83.4 ± 3.7, P< 0.001) in the SCM group. The SCM group showed lower processing time per device (8.1 ± 1.6 vs. 44.2 ± 5.6 min, P< 0.001) and lower costs per surgical instrument (RMB 11.5 ± 2.3 vs. 60.3 ± 10.2, P< 0.001).
CONCLUSIONS: The application of the supply chain management can reduce the costs of robotic surgery, improve work efficiency and decrease the failure rate of instruments.

In today\'s competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization\'s activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies. \"Artificial Intelligence of Things (AIoT)\", which means using the Internet of Things to perform intelligent tasks with the help of artificial intelligence integration, is one of these expected innovations that can turn a complex supply chain into an integrated process. AIoT innovations such as data sensors and RFID (radio detection technology), with the power of artificial intelligence analysis, provide information to implement features such as tracking and instant alerts to improve decision making. Such data can become vital information to help improve operations and tasks. However, the same evolving technology with the presence of the Internet and the huge amount of data can pose many challenges for the supply chain and the factors involved. In this study, by conducting a literature review and interviewing experts active in FMCG industries as an available case study, the most important challenges facing the AIoT-powered supply chain were extracted. By examining these challenges using nonlinear quantitative analysis, the importance of these challenges was examined and their causal relationships were identified. The results showed that cybersecurity and a lack of proper infrastructure are the most important challenges facing the AIoT-based supply chain.

As a polluting industry, the green transformation of coatings is highly concerned by the Chinese government. In order to explore the role of government in the process of green transformation of coating industry, this paper constructs a green governance evolutionary game model of \"government-manufacturing companies-application companies,\" and the complex interaction mechanism among the three parties is studied. Then, the evolutionary game theory is used to analyze the asymptotic stability conditions and evolutionary stability strategies of the equilibrium point of the tripartite game in the three stages of green governance in the coating industry (traditional technology-green transformation-collaborative governance). Finally, the model was verified by numerical simulation, and the influence of the changes of subjective parameters on the evolutionary game was discussed. The results show that (1) the intensity of government governance is related to the frequency of spot checks and punishment coefficients, and the evolution tends to be balanced when the intensity of governance is moderate. (2) The evolutionary trend of the game\'s main players\' strategy selection also depends on the government\'s punishment. There is greater probability of green transition of manufacturing companies under punishment. (3) The green subsidy coefficient and the green degree of the product also have a greater impact on the strategic choice of the game player.