Due to an increasing number of issues such as climate change, sustainable development has become an important theme worldwide. Sustainable development is inseparable from technological innovation. Only by making technological breakthroughs can we ensure the overall integration of economic development and environmental protection. Here, based on China’s inter-provincial panel data from 2006 to 2019, we examine the relationship between green technological innovation and carbon dioxide (CO2) emissions in 30 provinces (excluding Hong Kong, Macao, Taiwan, and Tibet) and sub-regions (eastern, central, and western China) in China using a space panel econometric model based on the STIRPAT equation. Additionally, we use geographic information analysis methods to analyze the spatial pattern and evolution characteristics of CO2 emissions. Our major finding is that, from the perspective of the whole country, green technology innovation has a negative correlation with carbon emissions, but the effect is not obvious. In addition, from the regional sample, green technology innovation in the eastern and central regions can effectively reduce carbon emissions, while in the western region, green technology innovation can promote carbon emissions in the province. At the same time, the research results show a strong spatial spillover effect of inter-provincial carbon dioxide emissions, and the progress of green technology in neighboring provinces has a negative impact on carbon emissions in their own provinces. Therefore, cross-province policies and actions for reducing carbon emissions are necessary. Additionally, our results show that carbon-emission driving factors, such as economic development, industrial structure, energy consumption structure, and population, have a significant positive effect on carbon dioxide emissions. Based on the above research results, we put forward corresponding policy recommendations.
The performance evaluation is one of the most important organizational management strategies used to guide the sales behavior of sales staff. However, it should be work process-oriented or sales result-oriented has become a dilemma for the management when evaluating employees' performance. Therefore, comprehensively evaluating the work process and sales results has become a challenge when it comes to salespeople performance appraisal. To solve this dilemma, this research builds a salesperson performance evaluation model which considering both of work efficiency and effectiveness, based on the decision tree model. Specifically, we use the Data Envelopment Analysis (DEA) model to quantify the work efficiency of salespeople and measure the work effectiveness by amount of sales. Moreover, this research proposes an advanced integrated DEA model by integrating the self-evaluation DEA models, peer-evaluation DEA models, and Gini impurity, which is identified to be more stable compared with the current DEA model. Finally, a case study of a Chinese liquor company is introduced to illustrate the applicability and feasibility of the salesperson performance evaluation model. The proposed model is applied to evaluate the performance of the salespeople, and a set of comprehensive and objective sales performance evaluation results are obtained. The estimated results can provide feasible sales management suggestions for the company in diagnosing work problems of salespeople.
The industrial division of labor and geographical concentration is the key factor to affect and determine the industrial layout and industrial optimization of China. Collecting 2014 Chinese industries in the provincial spatial data distribution, to study China's industrial geography concentration and the degree of regional specialization, and for the Chinese optimization of industrial layout and promote industrial development to provide policy recommendations.
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