This paper analyses wherever top executives were born and wherever they attended university to reveal regional groupings of the executives that form company culture and strategy in China and the mechanisms by which they affect corporate performance. It was found that the personal histories of top executives affect their decision-making orientation, and, in turn, company culture. The personal histories of executives and intra-regional, intra-provincial and intra-city links of corporate headquarters were obvious factors for executive selection. Distances were higher, and percentages of intra-regional links were lower for higher profit and growth companies. This shows that more competitive companies are more likely to hire executives who have lived in different regions or institutions in their lifetimes and university educations. The study concludes that Chinese firms’ key choices are influenced, in part, by external geographic factors way more advanced than the self-operation of individual enterprises.

Since the proposal of the low-carbon economy plan, all countries have deeply realized that the economic model of high energy and high emission poses a threat to human life. Therefore, in order to enable the economy to have a longer-term development and comply with international low-carbon policies, enterprises need to speed up the transformation from a high-carbon to a low-carbon economy. Unfortunately, due to the massive volume of data, developing a low-carbon economic enterprise management model might be challenging, and there is no way to get more precise forecast data. This study tackles the challenge of developing a low-carbon enterprise management mode based on the grey digital paradigm, with the aim of finding solutions to these issues. This paper adopts the method of grey digital model, analyzes the strategy of the enterprise to build the model, and makes a comparative experiment on the accuracy and performance of the model in this paper. The results show that the values of MAPE, MSE and MAE of the model in this paper are the lowest. And the r^2 of the model in this paper is also the highest. The MAPE value of the model in this paper is 0.275, the MSE is 0.001, and the MAE is 0.003. These three indicators are much lower than other models, indicating that the model has high prediction accuracy. r² is 0.9997, which is much higher than other models, indicating that the performance of this model is superior. With the support of this model, the efficiency of building an enterprise model has been effectively improved. As a result, developing an enterprise management model for the low-carbon economy based on the gray numerical model can offer businesses new perspectives into how to quicken the shift to the low-carbon economy.

Entrepreneurial motivation has been one psychological factor that determines the success of MSMEs as it interacts with external factors. However, this has been scarcely studied in relation to women and the success of MSMEs. This study aims to analyze the effects of motivation and external factors on the success of women running MSMEs in the province of Jambi, Indonesia. A survey research methodology through the distribution of questionnaires on the motivation scale and the success of the MSMEs scale that were constructed by the authors was applied. The rating scale of the questionnaires was rated on a five-point Likert scale. A total of 325 women running MSMEs in Jambi City were given and returned the questionnaires. The results showed that motivation, which is comprised of self-confidence, risk-taking, results-orientedness, intelligence, and skills, has a significant effect on the success of MSMEs. Meanwhile, the success of MSMEs is significantly more affected by time and length of effort than loans or funds due to the decreasing trend of demand for goods and services.