The rapid growth of the industrial economy has affected the survival of wildlife, and the decline in wildlife resources will in turn have some negative impact on the industrial economy. For the sustainable development of the industrial economy, human beings began to reflect on traditional development thinking and strive to find a development strategy that harmonizes industrial economic development and resource protection, and wildlife protection gradually attracted people's attention. "Protecting wild animals, maintaining ecological balance, and promoting economic development" has become a hot topic in the new century. Wildlife resources are valuable natural resources and play an important role in the ecosystem, which is related to the well-being and future of human beings. In recent years, China has made great progress in wildlife protection, while protecting and expanding wildlife habitats, introducing relevant laws and regulations, and other measures which have been implemented recently. However, there are still shortcomings in the protection of wildlife in China. Over-utilization, habitat loss and degradation, environmental pollution, climate change, weak legal awareness, and indiscriminate hunting all pose serious threats to wildlife in China. In this regard, this paper summarizes the main problems and barriers to wildlife resource conservation and utilization in China. Based on the analytic hierarchy process (AHP), the main technology factors influencing wildlife resource conservation and utilization in China are identified. Finally, the future research development direction of wildlife conservation is discussed based on the critical factors. This can provide some guidance for developing wildlife resource conservation and utilization for a sustainable ecosystem in China.
As supply chains, logistics, and transportation activities continue to play a significant role in China's economic and social developments, concerns around energy consumption and carbon emissions are becoming increasingly prevalent. In light of sustainable development goals and the trend toward sustainable or green transportation, there is a need to minimize the environmental impact of these activities. To address this need, the government of China has made efforts to promote low-carbon transportation systems. This study aims to assess the development of low-carbon transportation systems in a case study in China using a hybrid approach based on the Criteria Importance Through Intercriteria Correlation (CRITIC), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and deep learning features. The proposed method provides an accurate quantitative assessment of low-carbon transportation development levels, identifies the key influencing factors, and sorts out the inner connection among the factors. The CRITIC weight matrix is used to obtain the weight ratio, reducing the subjective color of the DEMATEL method. The weighting results are then corrected using an artificial neural network to make the weighting more accurate and objective. To validate our hybrid method, a numerical example in China is applied, and sensitivity analysis is conducted to show the impact of our main parameters and analyze the efficiency of our hybrid method. Overall, the proposed approach offers a novel method for assessing low-carbon transportation development and identifying key factors in China. The results of this study can be used to inform policy and decision-making to promote sustainable transportation systems in China and beyond.
One of the major challenges of the supply chain managers is to select the best suppliers among all possible ones for their business. Although the research on the supplier selection with regards to green, sustainability or resiliency criteria has been contributed by many papers, simultaneous consideration of these criteria in a fuzzy environment is rarely studied. Hence, this study proposes a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem for a real case study of palm oil industry in Malaysia. Firstly, the resilient-based sustainable criteria are localized for the suppliers' performance evaluation in palm oil industry of Malaysia. Accordingly, 30 criteria in three different aspects (i.e. general, sustainable and resilient) are determined by statistical tests. Moreover, a hyper-hybrid model with the use of FDEMATEL (fuzzy decision-making trial and evaluation laboratory), FBWM (fuzzy best worst method), FANP (fuzzy analytical network process) and FIS (fuzzy inference system), simultaneously is developed to employ their merits in an efficient way. In this framework, regarding the outset, the relationships among the criteria/sub-criteria are obtained by FDEMATEL method. Then, initial weights of the criteria/sub-criteria are measured by FBWM method. Next, the final weights of criteria/sub-criteria considering the interrelationships are calculated by FANP. Finally, the performance of the suppliers is evaluated by FIS method. To show the applicability of this hybrid decision-making framework, an industrial case of palm oil in Malaysia is presented. The findings indicate the high performance of the proposed framework in this concept and identify the most important criteria including the cost in general aspects, resource consumption as the most crucial sustainable criterion and agility as the most important resilient criterion.
The recent advances in sustainable supply chain management are integrated with Industry 4.0 concepts. This study develops a new integrated model to consider the sustainability and Industry 4.0 criteria for the supplier selection management. The proposed approach consists of the fuzzy best worst method (FBWM) and the two-stage fuzzy inference system (FIS) to assess the selection of suppliers. Firstly, this study determines a comprehensive list of Industry 4.0 and sustainability criteria along with their definitions. Then, the importance weight of each criterion is computed by the FBWM. Subsequently, a two-stage FIS is devoted to nominate the suppliers' performance with regard to the sustainability and Industry 4.0 criteria. To show the applicability of our integrated model, a case study for a textile company in Iran is provided. Finally, some sensitivity analyses are done to assess the efficiency of the proposed integrated approach. One finding is to establish a decision-making framework to evaluate suppliers separately, rather than relatively in a fuzzy environment using Industry 4.0 and sustainability criteria.