Promoting green packaging production represents a crucial strategy for the packaging industry in its pursuit of sustainable development. This study constructs a three-party evolutionary game model involving suppliers, manufacturers, and brands to examine their strategic decision-making under various scenarios. Simulation and analysis yield three principal findings. First, the system initially begins at (0,0,0) and may transition to a manufacturer-dominated intermediate state—either (1,1,0) or (0,1,1)—before gradually stabilizing at the equilibrium point (1,1,1). Second, supply chain decision-making is influenced by both internal and external factors. Internal factors include penalty mechanisms, carbon trading allocation, and cooperative concessions, whereas external factors comprise consumer preferences for traceability and the environmental attributes of packaging. Specifically, suppliers are primarily driven by internal factors, manufacturers are predominantly influenced by external factors, and brands are impacted by a combination of both. Third, serving as the central node in the supply chain, manufacturers enable upstream and downstream integration through traceable production, refine cooperative concession mechanisms to enhance brand participation, and harness market signals to promote green transformation and co-production among suppliers. Therefore, the effective management of the green packaging supply chain necessitates the establishment and ongoing refinement of a tripartite active cooperation mechanism. Additionally, cultivating consumer preferences for traceability is essential for advancing the long-term sustainable development of the supply chain.

Batch dispersion problem (BDP) restricts batch traceability in large-scale discrete production and negatively impacts batch recall costs. However, previous research has ignored the complexity of the BDP in their analyses. This paper investigates the BDP under the composed bill of materials (BOM) and develops a mathematical model for the BDP with the goal of minimizing the total batch dispersion by utilizing the batch dispersion as a measure of the degree of dispersed usage of part batches. BDP-GAVNS, a hybrid genetic algorithm with variable neighborhood search, is devised for the BDP based on the demonstration that the BDP is an NPC problem. In BDP-GAVNS, memory banks were introduced to increase the diversity of individuals performing crossover operations. Additionally, the encoding method and infeasible solution repair program are designed according to the characteristics of BDP. Numerical experiments validate the viability and effectiveness of BDP-GAVNS in solving BDP. They demonstrate that (1) the optimal combination occurs when the ratio of individuals produced by the three types of population initialization methods, namely global selection (GS), local selection (LS), and random selection (RS), to the population takes values of 0.30, 0.10, and 0.60, respectively; (2) The memory bank enriches the source of individuals required for crossover operations and improves the performance of crossover operations; and (3) The BDP-GAVNS is more effective than the other five heuristic algorithms including genetic algorithms in seeking the optimal solution of BDP.

This study aims to provide implications for the application of the halal logistics traceability model to food commodities in Indonesia and to be able to recommend alternative policy scenarios for the government. The system dynamic approach is used to model the traceability of halal logistics for food commodities in Indonesia. The urgency of this research is that it will contribute to improving the quality of halal logistics which has implications for the halal industry in Indonesia. This research also has implications for food quality and safety which helps food security in Indonesia, the relationship between Halal Certification and Traceability on SMEs Performance, analyzing the relationship between Halal food supply chain management and Halal Certification and Traceability. This research method is a quantitative survey, research data obtained by distributing online questionnaires to 390 food SME owners who have implemented the Halal Assurance Management System. Data analysis used a structural equation model (SEM) with SmartPLS 3.0 software. The stages of data analysis are validity, reliability and significance tests. The sampling technique used is non-probability sampling. The questionnaire used in this study uses a Google form which will be distributed to respondents. This questionnaire measurement method uses a Likert scale of 5, namely Strongly Disagree (STS), (2) Disagree Answers (TS), (3) Neutral Answers (N), (4) Agree Answers (S), Strongly Agree (SS). The independent variable used in this research is halal supply chain management. The dependent variables used in this study are halal certification and traceability and SMEs Performance. The results of this study indicate that Halal food supply chain management has a positive and significant effect on the performance of SMEs, Halal Certification and Traceability have a positive and significant effect on SMEs Performance, Halal Certification and Traceability have a positive and significant effect on Halal food supply chain management.

Blockchain technology is revolutionizing all sectors of industries including the healthcare one. Blockchain technology applications have been realized in healthcare as they have the potential to revolutionize healthcare systems. Integrating blockchain into the design of supply chain design leads to decentralizing the management of the supply chain, and, in turn, improves workflow efficiency and reduces the various security threats. Therefore, this study aimed at examining the impact of integrating blockchain technology, into supply chain practices, on supply chain transparency and resilience. By adopting the organizational information processing theory, this study developed a research model that explored the impact of blockchain technology features including data quality, smart contracts, and traceability on supply chain resilience and transparency. Furthermore, this study examined the effect of supply chain transparency on supply chain resilience. The data was collected, from healthcare industry personnel, in Jordan, using an electronic survey. In total, 215 participants responded to the questionnaire. RStudio- 2022.07.1 was used to conduct the data analysis. Results revealed that data quality significantly and positively affects supply chain transparency and resilience. In addition to that, results indicated that while smart contracts are positively related to supply chain transparency, they do not affect supply chain resilience. Also, traceability was found to be positively related supply chain transparency and resilience. Finally, it was found that blockchain-driven supply chain transparency positively impacts blockchain-driven supply chain resilience. The results imply that integrating blockchain technology into the supply chain can enhance both supply chain transparency and resilience, and, in turn, provide the supply chain the capability of recovering to its original state should it encounter disruptive events. The outcomes of this study can help supply chain managers and other stakeholders to develop strategies and tactics to best utilize blockchain technology to enhance blockchain-driven supply chain transparency and resilience.