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Xiaohui Ji
Department of Management Engineering, School of Economics & Management, Xidian University, Xi'an 710071, China

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Journal article
Published: 21 December 2019 in International Journal of Environmental Research and Public Health
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With the concept of sustainability gaining popularity, low-carbon tourism has been widely considered. In this paper, a multicriteria group decision making (MCGDM) process based on an uncertain environment is proposed to study the evaluation problem of low-carbon scenic spots (LSSs). In order to minimize the influence of subjective and objective factors, the traditional Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) method is expanded, using the improved best and worst method (IBWM) and Bayes approximation method, based on Dempster-Shafer Theory (B-DST). First, in order to make the evaluation process more professional, a number of evaluation criteria are established as effective systems, followed by the use of triangular intuitionistic fuzzy numbers (TIFNs) to evaluate alternatives of LSSs. Next, according to the evaluation results, the weights of the criteria are determined by the IBWM method, and the weights of the expert panels (Eps) are determined by B-DST. Finally, a weighted averaging algorithm of TIFN is used to integrate the above results to expand the traditional VIKOR and obtain the optimal LSS. The applicability of this method is proven by example calculation. The main conclusions are as follows: tourist facilities and the eco-environment are the two most important factors influencing the choice of LSSs. Meanwhile, the roles of management and participant attitudes in LSS evaluations cannot be ignored.

ACS Style

Aijun Liu; Taoning Liu; Xiaohui Ji; Hui Lu; Feng Li. The Evaluation Method of Low-Carbon Scenic Spots by Combining IBWM with B-DST and VIKOR in Fuzzy Environment. International Journal of Environmental Research and Public Health 2019, 17, 89 .

AMA Style

Aijun Liu, Taoning Liu, Xiaohui Ji, Hui Lu, Feng Li. The Evaluation Method of Low-Carbon Scenic Spots by Combining IBWM with B-DST and VIKOR in Fuzzy Environment. International Journal of Environmental Research and Public Health. 2019; 17 (1):89.

Chicago/Turabian Style

Aijun Liu; Taoning Liu; Xiaohui Ji; Hui Lu; Feng Li. 2019. "The Evaluation Method of Low-Carbon Scenic Spots by Combining IBWM with B-DST and VIKOR in Fuzzy Environment." International Journal of Environmental Research and Public Health 17, no. 1: 89.

Journal article
Published: 25 April 2019 in Journal of Cleaner Production
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As the speed of mobile phone updates continues to accelerate, the self-service mobile phone recycling mode, led by third-party reverse logistics providers (3PRLs), has ushered in an important developmental era. This paper proposes a novel interval-valued Pythagorean hesitant fuzzy best-worst multi-criteria large group decision-making method to research the selection of 3PRLs. To minimize the influence of subjective factors and maximize the mathematical analysis method, some related improvements have been made to the traditional best worst method (BWM). First, in order to make an effective strategic assessment and achieve overall optimization of the organization, evaluators are grouped by the self-organized maps (SOM) method to balance the coordination ability and professional level of different groups. Next, the interval Pythagoras hesitant fuzzy set (IPHFS) is used to evaluate the criteria of 3PRLs selection. Then, according to above evaluation results, the BWM method and deviation model are combined to determine the weights of criteria. Finally, the traditional BWM is extended by ranking functions to determine the optimal 3PRL. The applicability of the proposed method is numerically demonstrated by solving a real case, and the key conclusions are that the technical factor is important to affecting the choice of 3PRLs. At the same time, the quantity and price of recycled components on End of Life (EOL) and used mobile phones also have important impacts on the selection of 3PRLs.

ACS Style

Aijun Liu; Xiaohui Ji; Hui Lu; Haiyang Liu. The selection of 3PRLs on self-service mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making. Journal of Cleaner Production 2019, 230, 734 -750.

AMA Style

Aijun Liu, Xiaohui Ji, Hui Lu, Haiyang Liu. The selection of 3PRLs on self-service mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making. Journal of Cleaner Production. 2019; 230 ():734-750.

Chicago/Turabian Style

Aijun Liu; Xiaohui Ji; Hui Lu; Haiyang Liu. 2019. "The selection of 3PRLs on self-service mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making." Journal of Cleaner Production 230, no. : 734-750.

Journal article
Published: 15 October 2018 in Journal of Cleaner Production
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Sharing bicycle has attracted the most sharply increased attention throughout the world in recent years. Its rapid development has increased transportation convenience. However, abandoned bicycles have caused a waste of resources and environmental damage. Additionally, the negative effects will exceed the positive impact that sharing bicycle creates if these abandoned bicycles are handled improperly. This paper proposes a two-stage method to study the recycling of abandoned bicycles, including the selection of the third-party logistics suppliers (3PLs) and the recycling network design. In the first stage, interval type-2 fuzzy sets (IT2FSs) and Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) are used to select the 3PLs. The dynamic time series, individual regrets, and group efficiency are all taken into account. In the second stage, From the perspective of maximizing overall benefits, a mathematical model considering the purchase cost of raw materials, transportation costs, recovery costs, and environmental benefits is established to design a recycling network.Finally, the applicability of the proposed method is numerically demonstrated by solving a real case, and key conclusions are that the recycling mode with the participation of the 3PLs in sharing bicycle system is the most reasonable and feasible. However, in this mode, the selection criteria of the 3PLs are different from other industries, which need to be given enough attention by the sharing bicycle operators. Additionally, in the recycling network design, considering the maximum overall interests of the three parties, the factory, the 3PLs, and the operators, must coincide with the social philosophy of sustainable development. The results are of great guiding significance to the recycling of sharing bicycles.

ACS Style

Aijun Liu; Xiaohui Ji; Lei Xu; Hui Lu. Research on the recycling of sharing bikes based on time dynamics series, individual regrets and group efficiency. Journal of Cleaner Production 2018, 208, 666 -687.

AMA Style

Aijun Liu, Xiaohui Ji, Lei Xu, Hui Lu. Research on the recycling of sharing bikes based on time dynamics series, individual regrets and group efficiency. Journal of Cleaner Production. 2018; 208 ():666-687.

Chicago/Turabian Style

Aijun Liu; Xiaohui Ji; Lei Xu; Hui Lu. 2018. "Research on the recycling of sharing bikes based on time dynamics series, individual regrets and group efficiency." Journal of Cleaner Production 208, no. : 666-687.

Journal article
Published: 09 July 2018 in International Journal of Environmental Research and Public Health
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Low-carbon product design is an important way to reduce greenhouse gas emission. Customer collaborative product innovation (CCPI) has become a new worldwide product design trend. Based on this popularity, we introduced CCPI into the low-carbon product design process. An essential step for implementing low carbon CCPI is to clarify key low carbon requirements of customers. This study tested a novel method for perceiving key requirements of customer collaboration low-carbon product design based on fuzzy grey relational analysis and genetic algorithm. Firstly, the study considered consumer heterogeneity, allowing different types of customers to evaluate low carbon requirements in appropriate formats that reflected their degrees of uncertainty. Then, a nonlinear optimization model was proposed to establish the information aggregation factor of customers based on the genetic algorithm. The weight of customers was obtained simultaneously. Next, the key low carbon requirements of customer were identified. Finally, the effectiveness of the proposed method was illustrated with a case related to a low carbon liquid crystal display.

ACS Style

Aijun Liu; Qiuyun Zhu; Xiaohui Ji; Hui Lu; Sang-Bing Tsai; Jiangtao Wang; Biru Liang. Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design. International Journal of Environmental Research and Public Health 2018, 15, 1446 .

AMA Style

Aijun Liu, Qiuyun Zhu, Xiaohui Ji, Hui Lu, Sang-Bing Tsai, Jiangtao Wang, Biru Liang. Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design. International Journal of Environmental Research and Public Health. 2018; 15 (7):1446.

Chicago/Turabian Style

Aijun Liu; Qiuyun Zhu; Xiaohui Ji; Hui Lu; Sang-Bing Tsai; Jiangtao Wang; Biru Liang. 2018. "Novel Method for Perceiving Key Requirements of Customer Collaboration Low-Carbon Product Design." International Journal of Environmental Research and Public Health 15, no. 7: 1446.

Journal article
Published: 09 July 2018 in Sustainability
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The selection of fresh product suppliers is a multi-criteria decision making (MCDM) problem with great significant and application value. This requires trade-offs between multiple criteria to prove its ambiguity and uncertainty. Therefore, a novel two-stage fuzzy integrated MCDM method to select suitable suppliers is employed. In the first stage, two collective relationship matrixes are constructed by quality function development (QFD), and relationships among customer requirements (CRs), company strategies (CSs) as well as selection criteria are considered separately in the two matrixes. Subjective criteria weights are obtained by fuzzy best-worst method (BWM) appropriately. In the second stage, the objective criteria weights are obtained using Shannon’s entropy method, and the fuzzy multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) is applied to rank suppliers. Finally, an application case is applied to prove the feasibility of the proposed method. These conclusions can help companies improve their CSs and increase their market competitiveness.

ACS Style

Aijun Liu; Yaxuan Xiao; Xiaohui Ji; Kai Wang; Sang-Bing Tsai; Hui Lu; Jinshi Cheng; Xinjun Lai; Jiangtao Wang. A Novel Two-Stage Integrated Model for Supplier Selection of Green Fresh Product. Sustainability 2018, 10, 2371 .

AMA Style

Aijun Liu, Yaxuan Xiao, Xiaohui Ji, Kai Wang, Sang-Bing Tsai, Hui Lu, Jinshi Cheng, Xinjun Lai, Jiangtao Wang. A Novel Two-Stage Integrated Model for Supplier Selection of Green Fresh Product. Sustainability. 2018; 10 (7):2371.

Chicago/Turabian Style

Aijun Liu; Yaxuan Xiao; Xiaohui Ji; Kai Wang; Sang-Bing Tsai; Hui Lu; Jinshi Cheng; Xinjun Lai; Jiangtao Wang. 2018. "A Novel Two-Stage Integrated Model for Supplier Selection of Green Fresh Product." Sustainability 10, no. 7: 2371.

Journal article
Published: 27 June 2018 in Sustainability
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Sharing express boxes is an effective disposal method for obsolete express packages. Its appearance also represents an unstoppable trend in the development of green logistics. This paper takes the sharing express box as research object and conducts two-stage research. In the first stage, the collaborative consumption theory and calculus are used to analyze the economic benefits that sharing express boxes bring to operators, that is, to demonstrate the feasibility of this business model from an economic perspective. In the second stage, the design of the overlay network is studied from the management science perspective. Firstly, an optimal coverage model is established considering the characteristics of the sharing express box, and cleaning costs, relocation costs, etc. are all integrated into the model. Secondly, the genetic algorithm is used to solve the model. A numerical example is described to illustrate the feasibility of the proposed method. In addition, sensitivity analysis investigates the effect of hub coverage change on the results. Finally, the theoretical guidance gained from this paper can be beneficial to the sustainable development of sharing express boxes.

ACS Style

Aijun Liu; Xiaohui Ji; Sang-Bing Tsai; Hui Lu; Gang Du; Feng Li; Guodong Li; Jiangtao Wang. An Empirical Study on the Innovation Sharing Express Box: Collaborative Consumption and the Overlay Network Design. Sustainability 2018, 10, 2201 .

AMA Style

Aijun Liu, Xiaohui Ji, Sang-Bing Tsai, Hui Lu, Gang Du, Feng Li, Guodong Li, Jiangtao Wang. An Empirical Study on the Innovation Sharing Express Box: Collaborative Consumption and the Overlay Network Design. Sustainability. 2018; 10 (7):2201.

Chicago/Turabian Style

Aijun Liu; Xiaohui Ji; Sang-Bing Tsai; Hui Lu; Gang Du; Feng Li; Guodong Li; Jiangtao Wang. 2018. "An Empirical Study on the Innovation Sharing Express Box: Collaborative Consumption and the Overlay Network Design." Sustainability 10, no. 7: 2201.