Raising public awareness of the Sustainable Development Goals (SDGs) is a critical prerequisite for their implementation. However, little is known about attitude formation among the public toward SDGs at the national level. We explored this topic in China, a country that has emerged as a leading world economy with strong transformational imperatives to work toward sustainable development. Following Chaiken’s heuristic–systematic model and using data from an online survey with 4128 valid respondents, this study investigated the factors that affect public support for SDGs and explains how individuals form supportive attitudes. Our empirical evidence showed that in China, first, public support is mainly shaped by demographic attributes (gender, age, and educational attainment), value predispositions (e.g., altruistic values and anthropocentric worldviews), and the level of SDG-relevant knowledge. Second, an interaction effect exists between value predispositions and knowledge among the public concerning support for SDGs. Third, the Chinese public views the implementation of SDGs as a part of development policy rather than environmental policy. This study provides empirical findings on the factors that account for public attitudes toward SDGs, outlining some useful implications for designing policy tools that would bolster SDG action.

Building upon the global innovation system (GIS) framework, this paper develops an analytical approach to incorporate data as a foundation-level resource in data-driven innovation systems and to unravel how the interplay of system resources’ spatial characteristics, multi-scalar institutions and actor strategies leads to the emergence of China’s artificial intelligence industry. China’s loose institutional regime significantly facilitates the formation of the market, legitimacy and data, while entrepreneurs and digital platforms are the key actors coupling system resources to China’s innovation system. As data become a critical resource, actors controlling data develop institutional power to shape the formation of the data-driven industry.

Whereas the pivotal role of trust in the adoption of e-government was highlighted in prior research, attention was rarely paid thus far to investigate the role of post-use trust and its impact on citizens’ continuous-use intention of e-government. This study develops a comprehensive model, which consists of antecedents of post-use trust, perceived usefulness, satisfaction, and citizens’ continuous-use intention of e-government, to explain how interactional, government, and environmental factors influence citizens’ post-use trust as well as how post-use trust influences citizens’ continuous-use intention. Using data collected from a survey of 1867 citizen users living in one direct-controlled municipality and four high-population cities in China, this study tests the proposed concept model using structural equation modeling. The results show that trust in government, trust in the internet, service quality, and information quality have positive effects on citizens’ post-use trust. Factors that do not determine a user’s post-use trust are the perception of privacy and security, as well as system quality. Another finding is that citizens’ post-use trust does not directly influence their continuous intention to use e-government. Post-use trust will impact continuous-use intention through whether or not citizens find using e-government useful and satisfying.

For 15 years the China Council for International Cooperation on Environment and Development (CCICED) has given advice to the Chinese government on various aspects of environmental conservation. In 2004, the Council established a Task Force on Environmental Governance, consisting of six international and six Chinese experts. On the basis of a thorough comparative evaluation of the structures, processes and outcomes of the environmental policies in China, the US, Japan and the EU, in November 2006 the Task Force presented its report consisting of 25 major recommendations, which are documented here in a condensed version.