Suchergebnisse

Social credit management is a global issue, has become an important aspect of the economic development of various countries. In the process of social transformation in modern China, the social credit management system has undergone three stages of evolution: from scratch to existence, from existence to reality, and from reality to refinement. Based on the review of the transformation of market order and the construction of social credit system in China, this paper makes a systematic analysis of its main content and internal logic. From the perspective of Huntington's "political decline" and other Chinese and foreign theories, this paper discusses the relationship between the three main bodies of social credit construction - market, society, government and market order respectively, in an attempt to provide inspiration and ideas for the construction of China's future social credit system.

AbstractFirms expand vertical boundaries by obtaining ownership of relevant resources. There are three means by which firms can achieve this goal: internal development, mergers and acquisitions (M&As), and equity joint ventures. From transaction cost theory and resource‐based view, this study analyzed how resource characteristics, environmental conditions, and firms' capabilities influence their governance choices by studying 30 cases involving architectural, engineering, and construction firms and employing a fuzzy‐set qualitative comparative analysis method. The findings reveal that all the antecedents jointly influenced firms' governance choices; however, they did so in a way that led to the firms' rejection as opposed to the implementation of one strategy. Firms avoided choosing internal development to circumvent high internal transaction costs or expand into new business rapidly. Firms excluded M&As when the similarity between new and existing resources was high to avoid resource redundancy. When market uncertainty was high, they did so to avoid investment risks. Moreover, when high external transaction costs were evident due to interactions and interdependency between firms and their partners, firms tended to choose a more integrated strategy and excluded equity joint ventures. The research indicates that firms' relational capabilities help them reduce external transaction costs and identify strategies with the lowest efficiency.

Machine learning has become one of the important methods to process big data. It has made a breakthrough in the limitations of traditional statistical models dealing with high-dimensional data. The current study is to introduce and discuss about how machine learning method can be implemented in high-dimensional education data and help with increasing the model efficacy in dealing with high-dimensional education data. A demonstration of the implementation with an empirical data set is also provided.

Due to the COVID-19 pandemic, citizens of the United Kingdom were required to stay at home for many months in 2020. In the weeks before and months following lockdown, including when it was not being enforced, citizens were advised to stay at home where possible. As a result, in a megacity such as London, where long-distance commuting is common, spatial and temporal changes to patterns of water demand are inevitable. This, in turn, may change where people's waste is treated and ultimately impact the in-river quality of effluent receiving waters. To assess large scale impacts, such as COVID-19, at the city scale, an integrated modelling approach that captures everything between households and rivers is needed. A framework to achieve this is presented in this study and used to explore changes in water use and the associated impacts on wastewater treatment and in-river quality as a result of government and societal responses to COVID-19. Our modelling results revealed significant changes to household water consumption under a range of impact scenarios, however, they only showed significant impacts on pollutant concentrations in household wastewater in central London. Pollutant concentrations in rivers simulated by the model were most sensitive in the tributaries of the River Thames, highlighting the vulnerability of smaller rivers and the important role that they play in diluting pollution. Modelled ammonia and phosphates were found to be the pollutants that rivers were most sensitive to because their main source in urban rivers is domestic wastewater that was significantly altered during the imposed mobility restrictions. A model evaluation showed that we can accurately validate individual model components (i.e., water demand generator) and emphasised need for continuous water quality measurements. Ultimatly, the work provides a basis for further developments of water systems integration approaches to project changes under never-before seen scenarios.