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Taoning Liu
Department of Management Engineering, School of Economics & Management, Xidian University, Xi'an, 710071, China

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Journal article
Published: 10 July 2020 in Journal of Management Science and Engineering
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This study assesses supplier selection at the beginning of project management to establish an evaluation system corresponding to blockchain tracing anti-counterfeiting platforms (BTAP). First, this paper determines 20 evaluation criteria from the four dimensions of platform overview, core technology, application support, and operations management. On this basis, multi-criteria decision making (MCDM) based on customer needs is proposed, which consists of three main steps. First, quality function deployment (QFD) and the best and worst method (BWM) are used to evaluate the four dimensions of the BTAP and specific evaluation criteria from the perspective of customers to obtain the criteria weight. Then, this method uses the extended Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) approach to sort the alternatives. Finally, the improved decision making trial and evaluation laboratory (DEMATEL) method is used to analyse the relationships between the 20 criteria in the four dimensions. The feasibility and effectiveness of this method are verified by an example. According to the sensitivity analysis and comparative analysis, the results show that this method can evaluate blockchain anti-counterfeiting enterprises. The main conclusions are as follows: the core technology is the most important factor influencing the choice of a BTAP project, and the role of application support in evaluation cannot be ignored.

ACS Style

Aijun Liu; Taoning Liu; Jian Mou; Ruiyao Wang. A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management. Journal of Management Science and Engineering 2020, 5, 172 -194.

AMA Style

Aijun Liu, Taoning Liu, Jian Mou, Ruiyao Wang. A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management. Journal of Management Science and Engineering. 2020; 5 (3):172-194.

Chicago/Turabian Style

Aijun Liu; Taoning Liu; Jian Mou; Ruiyao Wang. 2020. "A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management." Journal of Management Science and Engineering 5, no. 3: 172-194.

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: 04 December 2019 in Entropy
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With the continuous development of data mining techniques in the medical field, variance analysis in clinical pathways based on data mining approaches have attracted increasing attention from scholars and decision makers. However, studies on variance analysis and treatment of specific kinds of disease are still relatively scarce. In order to reduce the hazard of postpartum hemorrhage after cesarean section, we conducted a detailed analysis on the relevant risk factors and treatment mechanisms, adopting the integrated Bayesian network and association rule mining approaches. By proposing a Bayesian network model based on regression analysis, we calculated the probability of risk factors determining the key factors that result in postpartum hemorrhage after cesarean section. In addition, we mined a few association rules regarding the treatment of postpartum hemorrhage on the basis of different clinical features. We divided the risk factors into primary and secondary risk factors by realizing the classification of different causes of postpartum hemorrhage after cesarean section and sorted the posterior probability to obtain the key factors in the primary and secondary risk factors: uterine atony and prolonged labor. The rules of clinical features associated with the management of postpartum hemorrhage during cesarean section were obtained. Finally, related strategies were proposed for improving medical service quality and enhancing the rescue efficiency of clinical pathways in China.

ACS Style

Gang Du; Yinan Shi; Aijun Liu; Taoning Liu. Variance Risk Identification and Treatment of Clinical Pathway by Integrated Bayesian Network and Association Rules Mining. Entropy 2019, 21, 1191 .

AMA Style

Gang Du, Yinan Shi, Aijun Liu, Taoning Liu. Variance Risk Identification and Treatment of Clinical Pathway by Integrated Bayesian Network and Association Rules Mining. Entropy. 2019; 21 (12):1191.

Chicago/Turabian Style

Gang Du; Yinan Shi; Aijun Liu; Taoning Liu. 2019. "Variance Risk Identification and Treatment of Clinical Pathway by Integrated Bayesian Network and Association Rules Mining." Entropy 21, no. 12: 1191.