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As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding the external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The results indicate that compatibility, relative advantage, complexity, managerial support, government involvement, and vendor partnership are significantly related to AI adoption. Managerial capability impacts other organizational capabilities and innovation attributes of AI, but it is indirectly related to AI adoption. Market uncertainty and competitive pressure are not significantly related to AI adoption, but all the external environment factors positively influence managerial capability. The study provides support for firms' decision-making and resource allocation regarding AI adoption. In addition, based on the resource-based view (RBV), this article conducts study 2 which explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from telecom companies in China. The results indicate that at the firm level, the customer value and operational expenses are significantly related to sustainable growth. Also, at the industry level, industry investment significant impacts sustainable growth. Study 2 provides insights for practitioners the way to keep sustainable growth.

With increasing downstream carbon emissions, the implementation of a personal carbon trading scheme is urgently required. In order to facilitate the progress, government departments are supposed to adopt a motivating or punitive policy to make guidance for downstream carbon emissions reduction. This study determined and verified the evolutionarily stable strategies (ESSs) of government departments and individuals whose carbon emissions exceeded the initial carbon allowance (CEEICA individuals) by using the evolutionary game and numerical simulation methods, respectively. The findings show that the ESS of government departments is always a punitive policy during the variation of strategies of CEEICA individuals. The ESS of CEEICA individuals is an active plan when the added cost (the difference between emissions reduction cost and trading earning) is less than the carbon tax ; otherwise, it is a passive plan. Furthermore, the rate of convergence can be significantly influenced by the probabilistic distances between initial strategies and the ESSs. On the basis of these findings, this study suggested implementing a &ldquo ; punishment first, motivation-supplemented&rdquo ; policy, and developing a stable operational mechanism for a personal carbon trading market.

At present, China is in a critical period of transition from labor-intensive industries to capital- and technology-intensive industries. Accordingly, the increasing labor force mobility among Chinese cities has promoted competition over production factors among regions, having a significant impact on local governments&rsquo ; fiscal expenditure structure. A theoretical analysis shows that the competition of livelihood public good expenditures is playing an increasingly important role in the factor flow competition. Different labor forces&rsquo ; demand for different public goods and local governments&rsquo ; demand for different labor forces affect the structural preference of local government fiscal expenditures. Based on panel data on Chinese prefecture-level cities in 2010&ndash ; 2016, this paper empirically tests the impact of different labor mobilities on the structure of local government fiscal expenditures, finding that current decision making on labor mobility is increasingly sensitive to the supply of livelihood public goods, and strengthening labor mobility has reversed the expenditure bias historically caused by the government&rsquo ; s simple capital competition. After dividing the mobile labor force based on whether the labor is settled in the current year, the two labor force types&rsquo ; demand for different livelihood public goods was found to be different. To attract different labor inflows, local governments should promote an increase in relevant livelihood public good expenditures, showing a strategic fiscal expenditure structural bias. Specifically, with increasing new added general labor mobility, local goverments will increase the proportion of fiscal expenditures on education and medical care, combined with the increase of newly added registered labor mobility, which will correspondingly increase the proportion of environmental protection expenditures.

The active promotion of carbon abatement to mitigate global climate change and protect the environment and public health has become the international consensus. The carbon capability is a key index for measuring the potential reduction of the carbon emissions by urban residents, and thus encouraging residents to exhibit normal and autonomous low-carbon behavior has become an important issue. In this study, based on grounded theory, data from in-depth interviews were encoded at three levels to identify the multi-layer factors that drive the carbon capability of urban residents, and we constructed a theoretical model for policy intervention. The results showed that individual factors, organizational factors, social factors, and social demographic variables were the main variables that affected the carbon capability, and utility experience perception was the main intermediary variable that affected the carbon capability. There was an obvious gap between utility experience perception and carbon capability. Low carbon selection cost was an internal situational variable that regulated the relationship between these factors, and the policy situation and technical situation were external situational variables. There were two-way effects on the carbon capability and utility experience perception. Thus, we explored these driving factors and the role of the carbon capability model. The results of this study may facilitate targeted policy thinking and the development of an implementation path for government in order to formulate effective guiding policies to enhance the carbon capability of urban residents.

Research Highlights: Stumpage price is the most important factor affecting the value of forests. Therefore, an understanding of the factors affecting stumpage prices and trends is critical for effective forest management. Background and Objectives: Chinese fir is the most important fast-growing timber species in China, it is also the tree species with the largest trading volume in the stumpage markets of Southern China. The aim of this study was to analyze the determinants and trends of stumpage prices for Chinese fir timber forests. Materials and Methods: Data on 928 sales of Chinese fir timber forests transacted between 2007 and 2016 were gathered from the stumpage markets in Southern China. We analyzed the relationship between stumpage prices and sales characteristics using the hedonic price method (HPM) and measured the stumpage price index with a dummy time hedonic index. Results: (1) The double logarithmic form of the HPM yielded a more accurate estimate than the semi logarithmic form. The R2ad values in the nine annual prediction models were all above 80%. Stock volume made the greatest contribution to stumpage price, followed by stand age. Stand area had no significant impact on the stumpage price. (2) Stumpage prices of Chinese fir timber forests fluctuated greatly, especially in 2010 and 2015 when the sequential price indexes were 180.01% and 74.95%, respectively. Taking 2007 as the baseline, we calculated the base price index in 2016 to be 197%, with an average annual growth rate of 7.82%. (3) The stumpage market was associated with a higher degree of risk than the timber market. Conclusions: Our findings provide valuable inputs that can guide and facilitate the Chinese government&rsquo ; s efforts to optimize resource allocation and standardize the stumpage market.

Background: Occupational safety and health issues are closely associated with the wellbeing and survival of every worker and family, as well as of society as a whole. It is a type of typical public issue and requires cooperative governance among different governing subjects. Methods: According to the questionnaire investigation on 2179 subjects with different identities, the research explored the willingness to pay (WTP) for occupational safety and health and the degree of attention, with different identities, through the difference analysis and descriptive statistical analysis. The research studied the relationship between public attention and WTP through the methods of cross-analysis, correlation analysis, and regression analysis. Results: (1) The public show a disregard attitude to occupational safety and health. (2) The public expect the government to fund and solve occupational safety and health problems rather than for themselves to pay directly. (3) Over 50% of questionnaire respondents defined occupational safety and health problems as being classified into two categories, namely, &ldquo ; no attention&mdash ; government payment&rdquo ; or &ldquo ; no attention&mdash ; refusal of individual payment&rdquo ; according to the analysis. (4) The level of attention paid to occupational safety and health can significantly predict the individual income WTP, item WTP, subject WTP, and event WTP. Conclusions: This research aimed to outline the implications for the governance of occupational safety and health.