Application of catastrophe progression method on hybrid multiple attribute decision-making problems based on regret theory

In order to effectively solve the decision-making problems with the diversity of evaluation information, the dynamics of research objects, the limitations of subjective authorization, and the irrational behavior of decision-makers, this paper extends catastrophe progression method to solve hybrid multiple attribute decision-making problems based on regret theory. Firstly, some basic theories are introduced. Secondly, the original catastrophe progression method is extended by using the regret theory, which is employed to solve the multiple attribute decision-making problems with hybrid evaluation information. Finally, a real-life case study of selecting a fresh cold chain logistics service provider is used to verify the practicality and effectiveness of the proposed method, and a comparative analysis with the TOPSIS method and the sensitivity of the regret avoidance coefficient is analyzed in this article.

Applying catastrophe progression method to evaluate the service quality of cold chain logistics

Logistics service quality (LSQ) is one of the key influential factors in the success of an ecommerce business. In view of the complexity of the topic, this paper proposes a novel model for fresh ecommerce cold chain LSQ evaluation based on the catastrophe progression method. In the proposed methodology, first an index system for evaluating the fresh ecommerce cold chain LSQ is established from the perspective of service recipients. Then, the comprehensive weight of each evaluation index is determined using a combination weighting approach based on maximizing deviations and fuzzy set theory. The priority weights and the ranking of the indices are determined using the catastrophe progression method. Finally, the model is applied in a case study of two representative enterprises. The study demonstrates the validity and practical applicability of the proposed model. Also, based on the evaluation results and findings, some improvement suggestions are made for improving the cold chain LSQ of similar kinds of fresh ecommerce companies.

Regionalization of Green Building Development in China: A Comprehensive Evaluation Model Based on the Catastrophe Progression Method

As an effective measure to reduce energy and material consumption, green building has drawn much attention all over the world. Under the background of ecological city construction, the development speed of green building is extremely high in China. However, it is unclear about the overview of regional green building development. This study puts forward an evaluation model to scientifically measure the regional development of green building. The rough set theory and the catastrophe progression method optimized by entropy method are utilized in the model. A case study is conducted to clarify the application of the evaluation model, and the spatial distribution of regional green building development in 2015 is shown in the end. The result shows that the evaluation model is scientific and applicable. The spatial distribution of green building development in China was uneven. Green building development concentrated on the Beijing-Tianjin-Hebei area, Jiangsu-Zhejiang-Shanghai Area, Guangdong and Chongqing. Tibet was almost the bottom in every aspect, but it performed the best in economic efficiency. This study not only contributes to the research area of green building development, but also helps to promote green buildings in practice.