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Due to growing concerns for environmental problems and food quality, consumers pay more attention to the carbon emission and freshness of fresh food. The booming e-commerce also accelerates the development of the dual-channel supply chain. In the dual-channel supply chain of fresh food, the carbon emission and freshness of fresh food are becoming important factors affecting consumers’ purchase demand. This paper focuses on the optimal decision of carbon emission reduction and pricing, which is investigated by a Stackelberg game-theoretic approach in three dual-channel supply chain sales models (retailer dual channel, producer dual channel, and mixed dual channel). A two-stage fresh food supply chain system composed of a producer and a retailer is explored. The sensitivity analysis and the comparison of three dual-channel models are carried out. The results show the following: (1) the sales price, carbon emission reduction, market demand, producer’s profit, retailer’s profit, and supply chain’s profit of fresh food under the three dual-channel supply chains show the same change on different levels of consumers’ low-carbon preference coefficient and freshness level, respectively; (2) the optimal decision of carbon emission reduction and pricing, demand, and profit of the three dual-channel models need to be determined according to the value of consumers’ purchasing preferences for the retailer’s offline channel. The paper gives some enlightenment to the decision-making members in the fresh dual-channel supply chain.
Jingci Xie; Jianjian Liu; Xin Huo; Qingchun Meng; Mengyu Chu. Fresh Food Dual-Channel Supply Chain Considering Consumers’ Low-Carbon and Freshness Preferences. Sustainability 2021, 13, 6445 .
AMA StyleJingci Xie, Jianjian Liu, Xin Huo, Qingchun Meng, Mengyu Chu. Fresh Food Dual-Channel Supply Chain Considering Consumers’ Low-Carbon and Freshness Preferences. Sustainability. 2021; 13 (11):6445.
Chicago/Turabian StyleJingci Xie; Jianjian Liu; Xin Huo; Qingchun Meng; Mengyu Chu. 2021. "Fresh Food Dual-Channel Supply Chain Considering Consumers’ Low-Carbon and Freshness Preferences." Sustainability 13, no. 11: 6445.
In recent years, China’s dry ports have entered into a period of rapid development, especially driven by the Belt and Road initiative (BRI). This initiative not only provides valuable opportunities, but also intensifies fierce competition between ports. In order to earn more profits and maintain an advantageous position, dry ports generally tend to rely on seaports to increase competitiveness and attract more goods, and seaports are also willing to cooperate with dry ports to expand their business. As a large coastal province in China, Shandong Province has good maritime resources. Because of the fierce competition among seaports inside and outside Shandong Province, port operators should make good use of the opportunity offered by BRI to make connections with the inland cities through the dry port-seaport logistics network and enhance the competitiveness. In order to take an active part in the process of the BRI, forming a dry port-seaport logistics network is a win-win strategy for Shandong province. The research first analyzes the impact of the Belt and Road initiative on ports of Shandong and its development, then uses complex network theory and TOPSIS method to select dry port candidate cities from BRI’s important transportation nodes. After considering economic benefits, carbon emissions and construction costs, a multi-objective optimization model is established with a construction cost preference coefficient. Then the NSGA-II algorithm is used to solve the realistic problem. The study finds that when the construction cost increases, the transportation cost and carbon emission cost will decrease, which indicates that the dry port-seaport logistics network established under the BRI can reduce the cost of logistics transportation and environmental pollution.
Jingci Xie; Yiran Sun; Xin Huo. Dry Port-Seaport Logistics Network Construction under the Belt and Road Initiative: A Case of Shandong Province in China. Journal of Systems Science and Systems Engineering 2021, 30, 178 -197.
AMA StyleJingci Xie, Yiran Sun, Xin Huo. Dry Port-Seaport Logistics Network Construction under the Belt and Road Initiative: A Case of Shandong Province in China. Journal of Systems Science and Systems Engineering. 2021; 30 (2):178-197.
Chicago/Turabian StyleJingci Xie; Yiran Sun; Xin Huo. 2021. "Dry Port-Seaport Logistics Network Construction under the Belt and Road Initiative: A Case of Shandong Province in China." Journal of Systems Science and Systems Engineering 30, no. 2: 178-197.
The forecast of carbon dioxide (CO2) emissions has played a significant role in drawing up energy development policies for individual countries. Since data about CO2 emissions are often limited and do not conform to the usual statistical assumptions, this study attempts to develop a novel multivariate grey prediction model (MGPM) for CO2 emissions. Compared with other MGPMs, the proposed model has several distinctive features. First, both feature selection and residual modification are considered to improve prediction accuracy. For the former, grey relational analysis is used to filter out the irrelevant features that have weaker relevance with CO2 emissions. For the latter, predicted values obtained from the proposed MGPM are further adjusted by establishing a neural-network-based residual model. Prediction accuracies of the proposed MGPM were verified using real CO2 emission cases. Experimental results demonstrated that the proposed MGPM performed well compared with other MGPMs considered.
Yu-Jing Chiu; Yi-Chung Hu; Peng Jiang; Jingci Xie; Yen-Wei Ken. A Multivariate Grey Prediction Model Using Neural Networks with Application to Carbon Dioxide Emissions Forecasting. Mathematical Problems in Engineering 2020, 2020, 1 -10.
AMA StyleYu-Jing Chiu, Yi-Chung Hu, Peng Jiang, Jingci Xie, Yen-Wei Ken. A Multivariate Grey Prediction Model Using Neural Networks with Application to Carbon Dioxide Emissions Forecasting. Mathematical Problems in Engineering. 2020; 2020 ():1-10.
Chicago/Turabian StyleYu-Jing Chiu; Yi-Chung Hu; Peng Jiang; Jingci Xie; Yen-Wei Ken. 2020. "A Multivariate Grey Prediction Model Using Neural Networks with Application to Carbon Dioxide Emissions Forecasting." Mathematical Problems in Engineering 2020, no. : 1-10.
The infectious disease COVID-19 has swept across the world in 2020, and it continues to cause massive losses of life and severe economic problems in all countries. Providing emergency supplies such as protective medical equipment and materials required to secure people’s livelihood is thus currently prioritized by governments. Establishing a reliable emergency logistics system is critical in this regard. This paper used the Delphi method to design a formal decision structure to assess emergency logistics system reliability (ELSR) by obtaining a consensus from a panel of experts. Assessing ELSR is a typical multiple-attribute decision making (MADM) problem, and the related MADM methods are usually on the basis of symmetry principles. A hybrid MADM model, called the Decision Making Trial and Evaluation Laboratory (DEMATEL)-based Analytical Network Process (D-ANP), was developed to identify the critical factors influencing ELSR. An analysis of empirical evidence showed that the emergency logistics command and coordination system and the emergency material supply system play important roles in ELSR, while the emergency logistics transportation and distribution system and the emergency information system are not so important. This conclusion is different from previous research about traditional disaster emergency logistics. Moreover, the cause–effect relationships among the key factors indicated that the system of command and coordination for emergency logistics and the supply system for emergency materials should be improved. Accordingly, effective suggestions for emergency logistics services for epidemic prevention are provided in this paper. The main contributions of this paper are (1) establishing a comprehensive and systematic evaluating index of ELSR for epidemic prevention; (2) employing a kind of structured, namely D-ANP, to identify the critical factors with non-commensurable and conflicting (competing) characteristics; and (3) comparing the differences of reliable criteria between the emergency logistics of epidemic prevention and the traditional disaster emergency logistics.
Peng Jiang; Yixin Wang; Chao Liu; Yi-Chung Hu; Jingci Xie. Evaluating Critical Factors Influencing the Reliability of Emergency Logistics Systems Using Multiple-Attribute Decision Making. Symmetry 2020, 12, 1115 .
AMA StylePeng Jiang, Yixin Wang, Chao Liu, Yi-Chung Hu, Jingci Xie. Evaluating Critical Factors Influencing the Reliability of Emergency Logistics Systems Using Multiple-Attribute Decision Making. Symmetry. 2020; 12 (7):1115.
Chicago/Turabian StylePeng Jiang; Yixin Wang; Chao Liu; Yi-Chung Hu; Jingci Xie. 2020. "Evaluating Critical Factors Influencing the Reliability of Emergency Logistics Systems Using Multiple-Attribute Decision Making." Symmetry 12, no. 7: 1115.