How public environmental appeals affect the collaborative governance in pollution and carbon reduction: Evidence from spatial effects across Chinese cities.

China has always adhered to the strategy of sustainable development. It is prevalent the public want a good living environment, which requires local governments and businesses to enhance their environmental governance capabilities. Using the panel data from Chinese cities from 2012 to 2019 and econometrics models, we examine the impact mechanisms of public environmental appeals (PEA) on efficiency of collaborative governance in pollution reduction and carbon mitigation (GPC). Results indicate that there is a positive spatial clustering of GPC across cities, with high-high clustering is notably concentrated in the southern regions of China and low-low clustering is prevalent in the northern regions. Spatial econometrics model results reveal that the stronger PEA, the higher GPC. The result of mechanism analysis shows the mediation of environmentally friendly technological innovation is crucial. Subsequent inquiry uncovers that the digital economy positively moderates the impact of PEA on GPC. The Belt and Road policy region exhibits heightened sensitivity to PEA, thereby enhancing the positive impact of PEA on GPC.

How digital transformation facilitate synergy for pollution and carbon reduction: Evidence from China.

Frontier studies have neglected the impact of digital transformation (DT) on the synergy for pollution and carbon reduction (SPCR) from the perspective of micro enterprises. This paper explores the SPCR effect of DT, as well as its mechanism at micro-firm level. The study found that: (1) DT significantly facilitates corporate SPCR. For every 10% increase in the level of DT, the ranking of SPCR will rise by about 2.3 places. This effect is more obvious in high-tech firms and non-heavy polluters, firms in the eastern region in China, and non-SOE. (2) DT creates innovation-driven and structure-optimizing effects, which enhance the corporate green innovation ability, optimize the business structure and capital allocation structure of enterprises, and then drive the SPCR. (3) External public environmental concerns (PEC) and internal corporate ESG governance act as "accelerators" promoting the SPCR effect of DT. Based on these, policy implications are made to accelerate the pace of corporate DT, give full play to the first-mover advantage, and break the "pollution (carbon) lock-in" with a view to providing theoretical references for the listed enterprises' digitalized governance of SPCR, as well as the governmental departments' formulation of relevant guiding policies, and striving to achieve the high-quality development goal.

How exports affect green technology innovation in small- and medium-sized enterprises? Evidence from Chinese companies listed on the growth enterprise market.

Using matched data from China Stock Market and Accounting Research (CSMAR) and Wind databases, this paper explores the impact of exports on the green technology innovation (GTI) of small- and medium-sized enterprises (SMEs). The mechanisms are analyzed through a two-way fixed effects model. First, exports contribute significantly to GTI of SMEs. Second, exports mainly contribute to GTI of SMEs by attracting government subsidies and increasing firms' environmental awareness. Third, from the perspective of heterogeneity, exports significantly positively impact GTI of SMEs especially in medium- and low-technology industries and in eastern China. The impact of exports on GTI is also examined by replacing core variables, modifying the sample for robustness testing, and utilizing both urban river density and distance from the center of the city to the nearest port as instrumental variables for endogeneity test. With the continuous development of international import and export trade, enterprises increase GTI research and development by attracting government subsidies, improving the quality of disclosed information, and increasing environmental awareness.

National innovative city and green technology progress: empirical evidence from China.

In this paper, a quasi-natural experiment of national innovative city pilot policy (NICPP) is carried out to investigate the impact of the NICPP on green technology innovation (GTI) and its intrinsic mechanism with the method of difference-in-differences. It is found that the NICPP significantly enhances GTI, and there is a certain lag and persistence in this effect. Heterogeneity analysis shows that the higher the administrative level and the more the geographical advantages of NICPP, the more obvious the driving effect of GTI. The mechanism test shows that the NICPP has an effect on the GTI through three channels: innovation factor input, agglomeration effect of science and technology talent, and entrepreneurial vitality empowerment. The findings of this study provide policy insights for further optimizing the construction of innovative cities and then promoting GTI development, ultimately realizing green dynamics transformation and high-quality development of China's economy.

Faultline configurations affecting the entrepreneurial team performance of new generation of returning migrant workers in China: An empirical study based on fuzzy-set qualitative comparative analysis.

As the impact of faultlines is still without a consensus, to figure out how faultlines will hurt or promote the entrepreneurial performance can help the new generation of Chinese migrant workers to start their businesses successfully under the Rural Revitalization Strategy. This study addressed a fuzzy-set qualitative comparative analysis (fsQCA) based on 32 returning entrepreneurial teams from a complexity perspective. We firstly introduced three faultline categories for migrant workers and selected five of the faultlines with high factor loads in each category for further analysis. Then a scale was developed to measure the team performance. By conducting fsQCA, four types of faultline configurations were found: (1) background-experience actuation; (2) guidance-balance lacking; (3) role-cognition conflict; and (4) information-decision polarization. The "background-experience actuation" type will promote the entrepreneurial performance while the other types will hurt the performance. Theoretically, breaking through the limitations of traditional regressions in previous studies, fsQCA is used to explore the complex interactions and integrated effects among different categories of faultlines, demonstrates that the unstable impact is just a one-sided representation of the overall effect, and fills the general faultline theory with Chinese specific scenario and small-sized entrepreneurship. Practically, several implications are proposed to optimize the heterogeneity of the returning migrant workers' entrepreneurial teams and increase their performances, such as constructing the "balance" and "guidance" mechanism, enriching the background diversity of the members and solving the information-decision faultlines into individual diversity, etc., which can also be utilized by migrant worker entrepreneurs in other developing areas in the world.

A Hybrid Algorithm of Ant Colony and Benders Decomposition for Large-Scale Mixed Integer Linear Programming.

The mixed integer linear programming (MILP) has been widely applied in many fields such as supply chain management and robot control, while how to develop a more efficient algorithm to solve large-scale MILP is still in discussion. This study addresses a hybrid algorithm of the ant colony and Benders decomposition to improve the efficiency. We firstly introduce the design of our algorithm, in which the Benders algorithm decomposes the MILP into a master problem and a slack problem, the ant colony algorithm generates initial solutions for the master problem, and heuristic rules obtain feasible solutions for the slack problem. Then, the computational experiments are carried out to verify efficiency, with a benchmark test and some medium-large scale examples. Compared with other algorithms like CPLEX, GUROBI, and traditional ACA, our algorithm shows a better performance with a 0.3%-4.0% optimality gap, as well as a significant decrease of 54.3% and 33.6% on average in the CPU time and iterations, respectively. Our contribution is to provide a low-workload, time-saving, and high-accuracy hybrid algorithm to solve MILP problems with a large amount of variables, which can be widely used in more commercial solvers and promote the utilization of the artificial intelligence.