Consumer Perceived Corporate Social Responsibility Authenticity (CPCSRA) belongs to the field of micro Corporate Social Responsibility (CSR) research. In general, understanding the formation mechanism of CPCSRA could make it better able to play its role in several ways. Firstly, most previous studies do not empirically consider a key factor, i.e., the consumer perceived senior managers’ involvement. We add this key factor into the independent variables of our formation mechanism. Secondly, most previous empirical research studies the relevant factors of consumer perceived CSR commitment as a whole. We study these relevant factors separately instead. Thirdly, we simultaneously choose the consumer perceived strategy-driven motive and consumer perceived value-driven motive as the mediating variables of our formation mechanism. Based on the above innovations, we comprehensively and systematically study the formation mechanism of CPCSRA. We use structural equation modeling to study the formation mechanism. For the convenience of data collection, our data are all from Chinese consumers. The study results show that three independent variables can directly affect CPCSRA. The three independent variables are consumer perceived level of invested resources, consumer perceived CSR efforts matching company and consumer perceived senior managers’ involvement. Consumer perceived senior managers’ involvement has the greatest effect. The two variables consumer perceived strategy-driven motive and consumer perceived value-driven motive play partial mediating effects on the relationship between independent variables and CPCSRA. Based on our empirical research, we put forward some feasible suggestions for company managers to increase company sustainability in market competition by promoting the formation of CPCSRA.
China has always been a major agricultural country, and the issues of agriculture, rural areas and farmers have always been fundamental issues of China’s reform and development. First of all, most previous studies did not combine agricultural development with rural economic development to consider the rural development status. Through the network-slack-based measure (SBM) model, agricultural development and rural economic development are taken as the first stage and the second stage, respectively, to determine the overall efficiency of rural development. Secondly, most previous studies directly selected a number of agricultural materials as inputs to evaluate agricultural production efficiency, and did not consider the impact of a variety of agricultural materials comprehensively. We use the entropy method to calculate a comprehensive index including a variety of agricultural materials. Third, most previous studies did not take into account the harmful effects of agricultural production on the environment. We take carbon emissions and agricultural non-point source pollution (ANPSP) as undesirable outputs into the model, and consider the impact of agricultural production on the ecological environment comprehensively. On the basis of the above innovation, we adopt the two-stage SBM-undesirable model to comprehensively and systematically study the efficiency of rural development in China. Furthermore, the gap of rural development efficiency is determined by sigma convergence and a convergence test. All the data are from the National Bureau of Statistics of China. The results show that the development level of China’s rural agricultural eco-efficiency is significantly higher than that of rural economic development, and the low efficiency of the whole rural development is mainly affected by the low efficiency of rural economic development. The distribution of efficiency value shows that the eastern region is the best, and the development level of the remaining three regions is very low. The regional development gap is large, and this gap still exists for a long period of time. Nevertheless, the efficiency of rural development has improved year by year. Based on empirical analysis, we put forward some feasible suggestions to provide reference for policymakers in formulating rural development policies, narrowing the regional gap and rural sustainable development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.