Using the theory of motivation, and the theory of planned behavior, this study establishes the “motivation-cognition-behavior” model of green utilization of agricultural waste from the perspective of farmers. In the motivational dimension, eight motivational factors were determined in three sub-dimensions of extrinsic motivation. In the cognitive dimension, three sub-dimensions of subjective norms, behavioral attitude, and perceived behavioral control are also determined. In the behavioral dimension, two sub-dimensions of utilization intention and utilization behavior are specified. Methodologically, a questionnaire on the green utilization of agricultural waste of 704 peasant households in five provinces of Jiangsu, Anhui, Shaanxi, Gansu, and Sichuan was administered. With the help of the structural equation model, the influence path and the internal mechanism was then analyzed. It is shown that: (1) in relation to the “motivational dimension → cognitive dimension,” extrinsic motivation significantly promotes the cultivation of farmers’ subjective norms, in which positive broken windows theory has a positive effect. In contrast, negative broken windows theory has a negative one. In intrinsic motivation, the behavior attitude of farmers is negative. In the response analysis, farmers can realize that their ability, self-efficacy, response efficacy, and response cost all have a positive impact on farmers’ perceived behavioral control. (2) In relation of the “cognitive dimension → behavioral dimension,” behavioral attitude slightly hinders utilization intention, while subjective norms and perceived behavioral control all contribute to a stronger utilization intention; the utilization intention maintains a positive correlation with the utilization behavior.
The selection of an urban rail transit system from the perspective of green and low carbon can not only promote the construction of an urban rail transit system but also have a positive impact on urban green development. Considering the uncertainty caused by different conflict criteria and the fuzziness of decision-making experts’ cognition in the selection process of a rail transit system, this paper proposes a hybrid intuitionistic fuzzy MCGDM framework to determine the priority of a rail transit system. To begin with, the weights of experts are determined based on the improved similarity method. Secondly, the subjective weight and objective weight of the criterion are calculated, respectively, according to the DEMATEL and CRITIC methods, and the comprehensive weight is calculated by the linear integration method. Thirdly, considering the regret degree and risk preference of experts, the COPRAS method based on regret theory is propounded to determine the prioritization of urban rail transit system ranking. Finally, urban rail transit system selection of City N is selected for the case study to illustrate the feasibility and effectiveness of the developed method. The results show that a metro system (P1) is the most suitable urban rail transit system for the construction of city N, followed by a municipal railway system (P7). Sensitivity analysis is conducted to illustrate the stability and robustness of the designed decision framework. Comparative analysis is also utilized to validate the efficacy, feasibility and practicability of the propounded methodology.
Quality function deployment (QFD) is an useful tool to solve Multi-criteria decision making, which can translate customer requirements (CRs) into the technical attributes (TAs) of a product and helps maintain a correct focus on true requirements and minimizes misinterpreting customer needs. In applying quality function deployment, rating technical attributes from input variables is a crucial step in fuzzy environments. In this paper, a new approach is developed, which rates technical attributes by objective penalty function and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) based on weighted Hamming distance under the case of uncertain preference characteristics of decision makers in fuzzy quality function deployment. A pair of nonlinear programming models with constraints and a relevant pair of nonlinear programming models with unconstraints called objective penalty function models are proposed to gain the fuzzy important numbers of technical attributes. Then, this paper compares the fuzzy numbers by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method based on weighted Hamming distance in consideration of the uncertain preference characteristics of decision makers. To end with, the developed method is examined with the numerical examples.
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