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With the strengthening of environmental awareness, the government pays much more attention to environmental protection and thus implements carbon trading schemes to promote the reduction of global carbon dioxide emissions. The carbon Generalized System of Preferences (GSP) is an incentive mechanism for citizens to value their energy conservation and carbon reduction. Individual travel needs to rely on various means of transportation, resulting in energy consumption. Carbon tax or subsidy can only be carried out after carbon GSP accurately measures individual carbon emissions. The big data acquired from the smart cards of passengers’ travels provide the possibility for carbon emission accounting of individual travel. This research proposes a carbon emission measurement of individual travel. Through establishing the network model of the Nanjing metro with a complex method, the shortest path of the passengers’ travels is obtained. Combined with the origination–destination (OD) records of the smart cards, the total distance of the passengers’ travels is obtained. By selecting the operation table to estimate the carbon emissions generated by the daily operation of the subway system, the carbon emissions per kilometer or per time of passenger travel are finally obtained. With the accurate tracking of carbon emissions for individual travel, the government may establish a comprehensive monitoring system so as to establish a carbon tax and carbon supplement mechanism for citizens.
Wei Yu; Tao Wang; Yujie Xiao; Jun Chen; Xingchen Yan. A Carbon Emission Measurement Method for Individual Travel Based on Transportation Big Data: The Case of Nanjing Metro. International Journal of Environmental Research and Public Health 2020, 17, 5957 .
AMA StyleWei Yu, Tao Wang, Yujie Xiao, Jun Chen, Xingchen Yan. A Carbon Emission Measurement Method for Individual Travel Based on Transportation Big Data: The Case of Nanjing Metro. International Journal of Environmental Research and Public Health. 2020; 17 (16):5957.
Chicago/Turabian StyleWei Yu; Tao Wang; Yujie Xiao; Jun Chen; Xingchen Yan. 2020. "A Carbon Emission Measurement Method for Individual Travel Based on Transportation Big Data: The Case of Nanjing Metro." International Journal of Environmental Research and Public Health 17, no. 16: 5957.
Based on the original text information, this paper converts the users' theme preferences and text sentiment features into attention information and combines different forms with the LSTM (Long Short-Term Memory) model to predict the personality characteristics of social network users. Finally, the experimental results of multiple groups’ show that the Attention-based LSTM model proposed in the paper can achieve better results than the currently popular methods in the recognition of user personality traits and that the model has good generalization ability.
Jinghua Zhao; Dalin Zeng; Yujie Xiao; Liping Che; Mengjiao Wang. User personality prediction based on topic preference and sentiment analysis using LSTM model. Pattern Recognition Letters 2020, 138, 397 -402.
AMA StyleJinghua Zhao, Dalin Zeng, Yujie Xiao, Liping Che, Mengjiao Wang. User personality prediction based on topic preference and sentiment analysis using LSTM model. Pattern Recognition Letters. 2020; 138 ():397-402.
Chicago/Turabian StyleJinghua Zhao; Dalin Zeng; Yujie Xiao; Liping Che; Mengjiao Wang. 2020. "User personality prediction based on topic preference and sentiment analysis using LSTM model." Pattern Recognition Letters 138, no. : 397-402.
Purpose The purpose of this paper is to examine the impact of carbon permit allocation rules (grandfathering mechanism and benchmarking mechanism) on incentive contracts provided by the retailer to encourage the manufacturer to invest more in reducing carbon emissions. Design/methodology/approach The authors consider a two-echelon supply chain in which the retailer offers three contracts (wholesale price contract, cost-sharing contract and revenue-sharing contract) to the manufacturer. Based on the two carbon permit allocation rules, i.e. grandfathering mechanism and benchmarking mechanism, six scenarios are examined. The optimal price and carbon emission reduction decisions and members’ equilibrium profits under six scenarios are analyzed and compared. Findings The results suggest that the revenue-sharing contract can more effectively stimulate the manufacturer to reduce carbon emissions compared to the cost-sharing contract. The cost-sharing contract can help to achieve the highest environmental performance, whereas the implementation of revenue-sharing contract can attain the highest social welfare. The benchmarking mechanism is more effective for the government to prompt the manufacturer to produce low-carbon products than the grandfathering mechanism. Although a loose carbon policy can expand the total emissions, it can improve the social welfare. Practical implications These results can provide operational insights for the retailer in how to use incentive contract to encourage the manufacturer to curb carbon emissions and offer managerial insights for the government to make policy decisions on carbon permit allocation rules. Originality/value This paper contributes to the literature regarding to firm’s carbon emissions reduction decisions under cap-and-trade policy and highlights the importance of carbon permit allocation methods in curbing carbon emissions.
Qinqin Li; Yujie Xiao; Yuzhuo Qiu; Xiaoling Xu; Caichun Chai. Impact of carbon permit allocation rules on incentive contracts for carbon emission reduction. Kybernetes 2018, 49, 1143 -1167.
AMA StyleQinqin Li, Yujie Xiao, Yuzhuo Qiu, Xiaoling Xu, Caichun Chai. Impact of carbon permit allocation rules on incentive contracts for carbon emission reduction. Kybernetes. 2018; 49 (4):1143-1167.
Chicago/Turabian StyleQinqin Li; Yujie Xiao; Yuzhuo Qiu; Xiaoling Xu; Caichun Chai. 2018. "Impact of carbon permit allocation rules on incentive contracts for carbon emission reduction." Kybernetes 49, no. 4: 1143-1167.
With the intensification of global warming and the levy of energy tax, more industries are paying attention to energy saving and reduction of carbon footprint. For the food industry, energy cost in the supply chain of perishable food is quite high because of cold-chain transport and storage. Therefore, the efficacies of cold chain management and inventory control are the key factors that increase the efficiency of food supply chain and make it more ecological. This research analyzes the degradation process of perishable food and determines the optimal temperature of the cold chain as well as the optimal price to maximize the channel profit. We prove that there is an optimal price with a certain temperature and develop an efficient search algorithm to find the optimal temperature. We also perform sensitivity analyses to test which parameters affect the channel profit significantly. Numerical experiments are conducted to illustrate the proposed models.
Shuai Yang; Yujie Xiao; Yan Zheng; Yan Liu. The Green Supply Chain Design and Marketing Strategy for Perishable Food Based on Temperature Control. Sustainability 2017, 9, 1511 .
AMA StyleShuai Yang, Yujie Xiao, Yan Zheng, Yan Liu. The Green Supply Chain Design and Marketing Strategy for Perishable Food Based on Temperature Control. Sustainability. 2017; 9 (9):1511.
Chicago/Turabian StyleShuai Yang; Yujie Xiao; Yan Zheng; Yan Liu. 2017. "The Green Supply Chain Design and Marketing Strategy for Perishable Food Based on Temperature Control." Sustainability 9, no. 9: 1511.
It has been a challenging task to manage perishable food supply chains because of the perishable product’s short lifetime, the possible spoilage of the product due to its deterioration nature, and the retail demand uncertainty. All of these factors can lead to a significant amount of shortage of food items and a substantial retail loss. The recent development of tracing and tracking technologies, which facilitate effective monitoring of the inventory level and product quality continuously, can greatly improve the performance of food supply chain and reduce spoilage waste. Motivated by this recent technological advancement, our research aims to investigate the joint decision of pricing strategy, shelf space allocation, and replenishment policy in a single-item food supply chain setting, where our goal is to maximize the retailer’s total expected profit subject to stochastic retail demand. We prove the existence of optimality for the design of the perishable food supply chain. We then extend the single-item supply chain problem to a multi-item setting and propose an easy-to-implement searching algorithm to produce the optimal allocation of shelf space among these items for practical implementation. Finally, we provide numerical examples to demonstrate the effectiveness of our solution.
Shuai Yang; Yujie Xiao; Yong-Hong Kuo. The Supply Chain Design for Perishable Food with Stochastic Demand. Sustainability 2017, 9, 1195 .
AMA StyleShuai Yang, Yujie Xiao, Yong-Hong Kuo. The Supply Chain Design for Perishable Food with Stochastic Demand. Sustainability. 2017; 9 (7):1195.
Chicago/Turabian StyleShuai Yang; Yujie Xiao; Yong-Hong Kuo. 2017. "The Supply Chain Design for Perishable Food with Stochastic Demand." Sustainability 9, no. 7: 1195.
Scheduling in an uncertain environment remains a meaningful yet challenging direction of research. In this paper, we consider a new scheduling setting from practical complex business applications, where resources (e.g., raw materials) used for processing jobs arrive randomly, due to reasons such as unstable transportation service caused by extreme weather conditions, unreliable suppliers, unpredictable industrial actions, etc. Further, jobs must be processed one by one and preemption is not allowed. The processing times of jobs are not known but their distribution. We incorporate these factors into a stochastic single-machine scheduling model and examine two different common types of objectives: minimizing total expected weighted completion time and minimizing total expected weighted squared completion time. We derive and prove a natural and intuitive optimal policy for the model with the first objective. Besides, we find that, under some mild conditions, the well-known policy in stochastic scheduling, WSEPT (weighted shortest expected processing time), still holds optimal for achieving either of objectives. The numerical example further supports and illustrates our results, which provide decision-makers insights into tricky uncertain scheduling problems.
Lianmin Zhang; Yizhong Lin; Yujie Xiao; Xiaopeng Zhang. Stochastic single-machine scheduling with random resource arrival times. International Journal of Machine Learning and Cybernetics 2017, 9, 1101 -1107.
AMA StyleLianmin Zhang, Yizhong Lin, Yujie Xiao, Xiaopeng Zhang. Stochastic single-machine scheduling with random resource arrival times. International Journal of Machine Learning and Cybernetics. 2017; 9 (7):1101-1107.
Chicago/Turabian StyleLianmin Zhang; Yizhong Lin; Yujie Xiao; Xiaopeng Zhang. 2017. "Stochastic single-machine scheduling with random resource arrival times." International Journal of Machine Learning and Cybernetics 9, no. 7: 1101-1107.
Managing perishable food in a retail store is quite difficult because of the product’s short lifetime and deterioration. Many elements, such as price, shelf space allocation, and quality, which can affect the consumption rate, should be taken into account when the perishable food retail chain is designed. The modern tracking technologies provide good opportunities to improve the management of the perishable food retail chain. In this research, we develop a mathematical model for a single-item retail chain and determine the pricing strategy, shelf space allocation, and order quantity to maximize the retailer’s total profit with the application of tracking technologies. Then the single-item retail chain is extended into a multi-item one with a shelf space capacity and a simple algorithm is developed to find the optimal allocation of shelf space among these items. Finally, numerical experiments and real-life examples are conducted to illustrate the proposed models.
Yujie Xiao; Shuai Yang. The Retail Chain Design for Perishable Food: The Case of Price Strategy and Shelf Space Allocation. Sustainability 2016, 9, 12 .
AMA StyleYujie Xiao, Shuai Yang. The Retail Chain Design for Perishable Food: The Case of Price Strategy and Shelf Space Allocation. Sustainability. 2016; 9 (1):12.
Chicago/Turabian StyleYujie Xiao; Shuai Yang. 2016. "The Retail Chain Design for Perishable Food: The Case of Price Strategy and Shelf Space Allocation." Sustainability 9, no. 1: 12.
In this paper, we consider a two-echelon sustainable supply chain with price-sensitive demand. The government taxes the carbon footprint of each item caused by producing, transporting, and consuming the products. Both the supplier and retailer can exert efforts to reduce the carbon footprint. In a non-cooperative setting, the government only taxes the supplier, so that the retailer has no incentive to exert any effort to reduce the carbon footprint and the supplier merely decides on the selling price to maximize its own profit. We develop a centralized supply chain and show that there is an optimal solution to maximize the channel profit. Since the centralized policy may not be always not practical, we propose a tax-sharing contract, where both parties profit from the carbon footprint reduction. This problem is modeled as the Stackelberg game and Nash game. The results show that the leader has more power than the follower, which results in more profit. The Stackelberg game provides boundaries for both parties’ profits in the Nash game. Although the tax-sharing contract does not result in full cooperation, its efficiency is still much higher than that of the non-cooperative case. The results are illustrated with some numerical experiments.
Yujie Xiao; Shuai Yang; Lianmin Zhang; Yong-Hong Kuo. Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts. Sustainability 2016, 8, 716 .
AMA StyleYujie Xiao, Shuai Yang, Lianmin Zhang, Yong-Hong Kuo. Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts. Sustainability. 2016; 8 (8):716.
Chicago/Turabian StyleYujie Xiao; Shuai Yang; Lianmin Zhang; Yong-Hong Kuo. 2016. "Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts." Sustainability 8, no. 8: 716.