In the context of economic globalization, innovation has become a major drive for the sustainable development of enterprises, which emphasizes the importance of studying the influencing factors of enterprise innovation output. The purpose of this study is to clarify the influence mechanism of different indicators on enterprise innovation output, and then provide relevant suggestions for improving enterprise innovation ability. This paper takes 562 enterprises in Chaoyang Sub-park and Fengtai Sub-park of Zhongguancun in Beijing within the time span between 2015 and 2016 as the research objects, and constructs a comprehensive indicator system of influencing factors for enterprise innovation output from the perspective of enterprise co-opetition relationship, factor input and environmental factors. A quantitative model of innovation output and influencing factors was built and then solved, via spike-and-slab sparse function and stepwise regression, aiming at analyzing the influence of different indicators on enterprise innovation output. In addition, this paper also classifies enterprises according to their innovation level and explores the influence of indicators on different types of enterprises. The innovation of this study lies in the modeling of competition and cooperation between enterprises and the establishment of a relatively comprehensive indicator system of influencing factors for enterprise innovation output. The results show that the degree of technological collaboration between enterprises, the level of financing and the degree of capital and labor input in innovation activities have significant positive effects on enterprise innovation output. On the contrary, product and service competition, as well as capital competition, tends to have a negative impact, which urges enterprises to pay heed to the intensity of competition faced by products and services as well as the diversity of financing sources and investment targets to reduce the negative impacts. In addition, enterprises with different levels of innovation should take customized measures in terms of factor input and co-opetition relationships, in that some indicators such as network structure indicators negatively influence the innovation output of enterprises with lower levels of innovation, but has positive impacts on those with higher levels of innovation.

The large increase in the number of tourists brings challenges to the tourist carrying capacity of tourist destinations. By constructing a tourism carrying capacity indicator system and a coupling coordination model, we calculate and compare the development of tourism carrying capacity and the coupling coordination between all first-class indicators of tourism carrying capacity for provinces and cities in China. We find that the tourism carrying capacity and the coupling coordination between all first-class indicators of tourism carrying capacity for provinces and cities in China both showed an upward trend from 2008 to 2017, but the development was not balanced. In coastal provinces, their development level was high although lately showing a downward trend. In the provinces of the northwest China, their development level is low, and their development speed is relatively slow. The provinces and cities in the middle reaches of the Yangtze River and the southwest China recorded the fastest growth rate. In addition, we found that the development of tourism carrying capacity is closely related to coupling coordination between all first-class indicators of tourism carrying capacity.