The 531 New Deal has gradually transitioned the photovoltaic market policy from industrial policy to competition policy. This paper considers the two policy orientations of the photovoltaic supply chain: industrial policy and competition policy. Based on differential game theory, the profit models of photovoltaic supply chain entities under the two policy orientations are constructed, and the optimal solutions of each model are solved. The research finds that policy guidance factors affect the strategic choices of photovoltaic supply chain entities; Compared to industrial policies, competition policy orientation can increase the profits of various entities in the photovoltaic supply chain to varying degrees.

Blockchain technology has attracted widespread attention due to its advantages of decentralization, as well as non-tampering, transparency, and traceability of information. Fourth-party logistics systems that do not use blockchain incur transaction costs and service quality losses due to the inability to fully control the delivery process, whereas the use of blockchain eliminates the transaction costs and quality losses, but the use of blockchain needs implementation and marginal use costs. To study the conditions for the use of blockchain technology, consider the fourth-party logistics system does not use and uses blockchain technology, and the equilibrium strategies in the two cases are compared. Numerical experiments show that there exists a certain range of blockchain costs which leads to a Pareto improvement in profits for both fourth-party logistics and third-party logistics and an improvement in the quality of logistics services when using blockchain.

Nowadays, online social networks play a crucial role in shaping human communication in various life activities. Social Network Analysis (SNA) provides valuable insights for businesses, authorities, and platform owners. One of the challenging tasks in SNA is detecting sequential change points in observed events in social networks when the parameters of statistical distribution of post-change networks are unknown. This challenging problem is particularly prominent in various real-world network systems, especially when the events in the networks can be modeled through a Hawkes process. Identifying change points in the stream of social network data, where the underlying statistical properties undergo significant changes, necessitates the development of adaptive online algorithms. Additionally, in cases where the use of maximum likelihood estimators is impractical or when no exact recursive function for likelihood is available, addressing this issue becomes more complex. This paper proposes likelihood estimators using online convex optimization methods, incorporating the adaptive moment estimation (ADAM) algorithm. The proposed method is seamlessly integrated into the sequential anomaly detection procedure for events in social networks. Experimental results on monitoring time between events demonstrate lower Expected Delay Detection (EDD), indicating the superiority of the proposed algorithm in both synthetic and real-world datasets such as Facebook and contact networks of individuals causing disease transmission. The proposed robust solution provides an efficient practical tool in situations where traditional methods face limitations in swift detection with high accuracy.

Robust supply chain network design that considers supply resiliency, plays vital role in supply chain risk management in dealing with various operational and disruption risks. This study developed a novel three-stage decision approach to consider two echelons robust and resilient supply chain networks. We present a mixed-integer non-linear programming model with two objective functions. The objectives are maximization of SCN profit and maximization of resiliency, where robustness, agility, leanness, flexibility, and integrity can be defined as the five resiliency criteria. Fuzzy Simultaneous Evaluation of Criteria and Alternatives (FSECA) and Simple Multi-Attribute Rating technique (SMART) have been used to obtain the supplier resiliency and weighted importance of resilience criteria. Then, a robust optimization model is built based on uncertainty parameters considering supplier resiliency. A Non-dominated Sorting Genetic Algorithm (NSGAII) and Multi Objective Particle Swarm optimization (MOPSO) were used to solve the robust model on a large scale. parameters calibrated by the Taguchi method and five metrics of performance evaluation were considered to compare the meta-heuristic algorithms. We demonstrate the proposed NSGAII algorithm over a competing method based on five performance metrics. The research findings reveal the optimal level of robust supply chain networks based on algorithm performance and Taguchi analyses. Moreover, the results indicate that when profit increases, resilience can increase simultaneously.

To meet consumer replacement needs, the free replacement extended warranty (FREW) is born and becomes popular in the extended warranty (EW) market. In this context, firms need to consider whether to introduce the FREW. Given the limited resources of the firms and cannibalism caused by the FREW, firms need to decide how to introduce the FREW. To address these issues, we construct theoretical models and obtain some managerial insights. We find that the optimal introduction strategy is related to the development cost and the expansion effect on the product market. Moreover, the optimal bundling strategy is affected by the unit maintenance cost and the cost discount caused by the FREW. Only when the benefit of the FREW is great enough, is bundling always better. An interesting result is that the price of the bundled EW is higher than the sum of the EWs’ prices when selling EWs separately.

With a decentral and global economy, distributed scheduling problems are getting a lot of attention. This paper addresses a distributed flexible job shop scheduling problem (DFJSP) with minimizing makespan, in which three subproblems, namely operations sequencing, factory selection and machine selection must be determined. To solve the DFJSP, a novel mixed-integer linear programming (MILP) model is first developed, which can solve the small-scaled instances to optimality. Since the NP-hard characteristic of DFJSP, a hybrid algorithm (GA-VNS-CP) of genetic algorithm (GA), variable neighborhood search (VNS) and constraint programming (CP). Specifically, the GA-VNS-CP is divided into two stages. The first stage uses the hybrid meta-heuristic algorithms of GA and VNS (GA-VNS), and the VNS is designed to improve the local search ability of GA. In GA-VNS, the encoding only considers the factory selection and the operations sequencing problems, and the machine selection problem is determined by the decoding rule. Because the solution space may be limited by the decoding rule, the second stage uses the CP to extend the solution and further improve the solution. Numerical experiments based on benchmark instances are conducted to evaluate the effectiveness of the MILP model, VNS, CP and GA-VNS-CP. The experimental results show effectiveness of the MILP model, VNS and CP. Moreover, the GA-VNS-CP algorithm has better performance than traditional algorithms and improves 6 current best solutions for benchmark instances

The objective of the study is to assess the impact of circular economy practices on financial performance of construction enterprises in Vietnam. The study conducted a survey in 3 months using a survey resulting in 233 valid surveys representing 233 construction enterprises in Vietnam. Using Smart PLS 4.1 software to analyze data, the results show that circular economy practice positively impacts financial performance of circular economy construction and innovation enterprises that play a mediate role in the relationship between circular economy practice and financial performance. Finally, enterprise size has a role to play in moderating impact of circular economy practices on financial performance of construction enterprises in Vietnam.

Economic growth is mostly dependent on small and medium-sized businesses (SMEs), especially in Bamenda III and similar districts. Examining how an entrepreneurial mindset affects the success of small and medium-sized enterprises (SMEs) in Bamenda III was the primary goal of this research. The study implemented a structured questionnaire and analyzed based on both descriptive and inferential statistics. Results from the ordinary least squares revealed that proactiveness behavior exerted a positive significant effect on SMEs_Performance in Bamenda III. Similarly, risk taking had a coefficient of 0.788, indicating a positive relationship with SMEs_Performance. Competitive aggressiveness had a positive coefficient indicating a positive association with SMEs_Performance, although it was not statistically significant at the conventional significance level. Innovativeness behavior had a positive statistically significant effect on SMEs_Performance. From a policy perspective, enhancing the entrepreneurial skills and mindset of SME owners and employees can foster a greater entrepreneurial orientation, leading to improved business performance.

The objective of the paper is to assess the impact of sustainable supply chain management practices on environmental performance of Vietnamese agricultural enterprises. The study conducted a survey of management leaders of Vietnamese agricultural enterprises. After 3 months, 328 surveys were obtained, after cleaning the data, there were 283 valid surveys for analysis. The results show that sustainable supply chain management practice has a positive impact on environmental performance and environmental regulations are not enough grounds to affirm a moderating role in the relationship between sustainable supply chain management practice and environmental performance of Vietnamese agricultural enterprises. From there, the study makes recommendations for Vietnamese agricultural enterprises.

The importance of green building concepts is emphasized in the current era due to the drastic decline in global climate conditions. However, their development is hindered as they are primarily applied to new buildings, while almost two-thirds of the world's buildings are already constructed. This study aims to improve the efficiency of Green Retrofitting, accelerating the growth of green buildings in Indonesia. It identifies the procurement and permitting processes for Green Retrofitting in high-rise office buildings in Jakarta, along with high-risk activities from these processes. Additionally, it develops a model of the relationship between these high-risk activities and the implementation efficiency of green retrofitting, using a Monte Carlo approach based on the Regulation of the Minister of Public Works and Housing No. 21 of 2021 and the Green Building Council Indonesia. The analysis uses data from 26 expert respondents on green retrofitting procurement and permitting, finding 83 activities with 214 risk indicators influencing green retrofitting efficiency, including 57 high risks. Identifying the most risky activities, the study develops a relationship model and conducts simulation and optimization to improve project time efficiency, ultimately accelerating the growth of green buildings in Indonesia.