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Aiming at the financing mode selection problem of a closed‑loop supply chain consisting of a retailer, a recycler, and a capital constrainted manufacturer, the revenue functions of the manufacturer, retailer, recycler, and closed ‐ loop supply chain are constructed when the capital constrained manufacturer can get financing from the retailer (internal financing) or the bank (external financing), respectively, and based on the Stackelberg game, the optimal pricing and return rate strategies under two financing modes are given. On this basis, by comparing the optimal decisions and revenue of the recycler, retailer, manufacturer, and closed ‐ loop supply chain under different financing modes, the financing mode selection strategies are given from different perspectives. The research results show that under certain conditions, the retailer providing financing services are beneficial for the manufacturer, retailer, recycler and closed ‐ loop supply chain. [ABSTRACT FROM AUTHOR]

Considering that travel agencies will pay attention to the demand information and electronic word-of-mouth(e-WOM)development trend of each alternative hotel when choosing partners, a method for hotel partner selection is proposed based on both information. First, the directed and weighted graph is constructed, in which the weight of the node is determined based on the demand information. Further, a time weight correction coefficient that considers the horizontal and vertical development trends of the alternatives’ e-WOM information is proposed to calculate the weight of each stage, and the TOWGA operator is used to calculate the attribute performance of each alternative hotel. By comparing the e-WOM attribute performance, the directed edge and its weight are determined. Then, the algorithm for calculating the ranking value of the alternative hotels is given based on PageRank. Finally, an example is used to verify the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the development of e-commerce, online reviews have been regarded as important data resources for enterprises to analyze the competitiveness of their products. Product feature dimensions that consumers pay most attention to were extracted from review texts. The sentiment analysis of review texts was performed based on the sentiment lexicon method to obtain the feature-sentiment score pairs. The opportunity scores of feature dimensions were calculated by the importance degree and satisfaction degree, and an opportunity landscape diagram was drawn to analyze the competitiveness of the target product itself. Feature dimension satisfaction degree was calculated to compare the competitive advantages and disadvantages between the target product and its competitive products. Competitiveness improvement strategies of the target product were given by considering the competitiveness analysis results from two perspectives comprehensively. The online reviews provided by Zol.com.cn were used to conduct experiments to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Ｂａｓｅｄ ｏｎ ａ ｃｌｏｓｅｄ￣ｌｏｏｐ ｓｕｐｐｌｙ ｃｈａｉｎ ｗｉｔｈ ｒｅｃｙｃｌｅｒ ｃａｐｉｔａｌ ｃｏｎｓｔｒａｉｎｔｓꎬ ｔｈｅ ｐｒｉｃｉｎｇ ａｎｄ ｒｅｃｙｃｌｉｎｇ ｄｅｃｉｓｉｏｎ ｏｆ ｃｌｏｓｅｄ￣ｌｏｏｐ ｓｕｐｐｌｙ ｃｈａｉｎｓ ｉｓ ｓｔｕｄｉｅｄ ｃｏｎｓｉｄｅｒｉｎｇ ｐａｒｔｉｃｉｐａｔｏｒｓ’ ｒｉｓｋ ａｔｔｉｔｕｄｅｓ ｆａｃｅｄ ｗｉｔｈ ｓｔｏｃｈａｓｔｉｃ ｄｅｍａｎｄｓ. Ｔｈｅ ｒｉｓｋ ａｔｔｉｔｕｄｅｓ ｏｆ ｐａｒｔｉｃｉｐａｔｏｒｓ ａｒｅ ｄｅｓｃｒｉｂｅｄ ｂａｓｅｄ ｏｎ ｍｅａｎ￣ ｖａｒｉａｎｃｅ. Ｔｈｅ ｏｐｔｉｍａｌ ｗｈｏｌｅｓａｌｅ ｐｒｉｃｅꎬ ｒｅｔａｉｌ ｐｒｉｃｅ ａｎｄ ｒｅｃｙｃｌｉｎｇ ｒａｔｅ ｉｎ ｃｅｎｔｒａｌｉｚｅｄ ａｎｄ ｄｅｃｅｎｔｒａｌｉｚｅｄ ｄｅｃｉｓｉｏｎｓ ａｒｅ ｄｅｔｅｒｍｉｎｅｄ ｒｅｓｐｅｃｔｉｖｅｌｙ. Ｔｈｅｎ ｔｈｅ ｉｍｐａｃｔｓ ｏｆ ｒｉｓｋ ａｔｔｉｔｕｄｅｓ ｏｆ ｐａｒｔｉｃｉｐａｔｏｒｓꎬ ｌｏａｎ ｉｎｔｅｒｅｓｔ ｒａｔｅｓ ａｎｄ ｄｅｍａｎｄ ｕｎｃｅｒｔａｉｎｔｙ ｏｎ ｔｈｅ ｏｐｔｉｍａｌ ｓｔｒａｔｅｇｉｅｓ ａｎｄ ｔｈｅ ｕｔｉｌｉｔｙ ｏｆ ｍｅｍｂｅｒｓ ａｎｄ ｃｌｏｓｅｄ￣ｌｏｏｐ ｓｕｐｐｌｙ ｃｈａｉｎｓ ａｒｅ ａｎａｌｙｚｅｄ. Ｔｈｅ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ ｔｈｅ ｒｅｃｙｃｌｅｒｓ ｏｆ ｒｉｓｋ ｎｅｕｔｒａｌｉｔｙ ｉｓ ｂｅｎｅｆｉｃｉａｌ ｔｏ ａｌｌ ｐａｒｔｉｃｉｐａｔｏｒｓꎬ ｗｈｉｌｅ ｔｈｅ ｒｅｔａｉｌｅｒｓ ａｎｄ ｍａｎｕｆａｃｔｕｒｅｒｓ ｏｆ ｒｉｓｋ ｎｅｕｔｒａｌｉｔｙ ａｒｅ ｏｎｌｙ ｂｅｎｅｆｉｃｉａｌ ｔｏ ｔｈｅｍｓｅｌｖｅｓ. Ｔｈｅ ｉｎｃｒｅａｓｅ ｏｆ ｌｏａｎ ｉｎｔｅｒｅｓｔ ｒａｔｅｓ ｗｉｌｌ ｒｅｄｕｃｅ ｔｈｅ ｕｔｉｌｉｔｙ ｏｆ ｐａｒｔｉｃｉｐａｔｏｒｓꎬ ｗｈｉｌｅ ｌｏｗｅｒ ｄｅｍａｎｄ ｕｎｃｅｒｔａｉｎｔｙ ｉｓ ｂｅｎｅｆｉｃｉａｌ ｔｏ ｔｈｅ ｒｅｔａｉｌｅｒｓꎬ ｒｅｃｙｃｌｅｒｓ ａｎｄ ｃｌｏｓｅｄ￣ ｌｏｏｐ ｓｕｐｐｌｙ ｃｈａｉｎｓ ｉｎ ｄｅｃｅｎｔｒａｌｉｚｅｄ ｄｅｃｉｓｉｏｎｓ. [ABSTRACT FROM AUTHOR]

In order to assist tourists to select hotels through tourism websites, a method for selecting desirable hotels is proposed based on features information and online ratings information of alternative hotels provided by tourism websites. Firstly, the directed and weighted graph of alternative hotels is constructed, in which hotel features are weighted objectively by the maximum deviation method based on hotel features information and then the node weights of directed weighted graph are determined by the simple weighting method. The directed edge and its weight are determined by comparing the online ratings information of node hotels. Then, the algorithm for calculating the sorting value of alternative hotels is given based on the principle of PageRank algorithm. Finally, in order to verify the effectiveness and feasibility of the proposed method, a case study on desirable hotel selection is proposed based on the information of hotel features and online ratings from the Booking, com website. [ABSTRACT FROM AUTHOR]

In order to support consumers’ purchasing decision， a product purchasing recommendation ranking method based on multi-attribute online ratings information was proposed. First， the online rating information on each product attribute was transformed into the probability distributions of attribute rating scales， and the cumulative distribution functions of online evaluation results to each product attribute were obtained. Then， the weighted cumulative distribution functions decision matrix was constructed， and the weighted cumulative distribution vectors of the ideal and anti-ideal products were determined based on the decision matrix. Furthermore， the distances between the weighted cumulative distribution vectors of each alternative product and the ideal/anti-ideal product were calculated， and the closeness coefficient of each alternative product was obtained. According to the closeness coefficient， the recommendation ranking results of alternative products were determined. Finally， an example to support consumers’ car purchasing decision was used to illustrate the feasibility and validity of the proposed method. [ABSTRACT FROM AUTHOR]

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With respect to the emergency response problem with uncertain scenario predictions, a beforehandongoing two-stage decision making method is proposed considering that the prevention actions adopted beforehand will affect the effects of response actions when the emergency is ongoing. In the method, by calculating the utility of each response action, the most desirable response action concerning each prevention action and each scenario is determined. Then, based on the idea of regret theory, the excessive response matrix and insufficient response matrix for pairwise comparisons of prevention actions are constructed,and then an overall anticipated regret matrix is built for selection the desirable prevention action. Further, the global delight value, global regret value and ranking value of each prevention action is calculated according to the overall anticipated regret matrix. Moreover, the ranking of the prevention actions can be determined, and the desirable prevention action and the response action corresponding to each emergency scenario can be obtained. Finally, a case study is given to illustrate the use of the proposed method. [ABSTRACT FROM AUTHOR]