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The contribution of good governance to development has been extensively examined; however, the effects of good governance on innovation, a critical factor for achieving sustainable development in the volatility, uncertainty, complexity and ambiguity environment, have received limited attention. This study examines the effects of good governance on innovation and its channel mechanisms. Thus, using a two-way fixed effects regression model, we analyse data from a sample of 112 economies worldwide over the period 2011–2021. We determine that good governance, measured using the worldwide governance indicators, has positive effects on innovation. Moreover, based on the shaping effect of good governance on the external environment, we identify that economic freedom serves as a channel mechanism through which good governance impacts innovation. Furthermore, we observe that compared with advanced economies, the positive effects of good governance on innovation are more significant in samples of emerging markets and developing economies. These findings underscore the mechanisms through which good governance impacts innovation, drawing attention to the shaping effect of good governance on the external environment and offering empirical evidence for economies to enhance economic freedom and promote innovation. • Examining the effects of good governance on innovation • Good governance has a shaping effect on the external environment. • Economic freedom is a channel mechanism for good governance to impact innovation. • The findings of this paper support the scepticism towards the Popper hypothesis. [ABSTRACT FROM AUTHOR]

The relationship between environmental, social, and governance (ESG) and corporate financial performance (CFP) has received much attention. Previous studies have mainly focused on the net effects of ESG on CFP, i.e., emphasizing the individual impact of the overall ESG level or each ESG pillar on CFP. However, there is a complex causal relationship between ESG and CFP, and different combinations of ESG pillars may have a differential impact on CFP. Based on configuration theory, this paper aims to analyze how the different configurations of the ESG pillars impact CFP using the longitudinal fuzzy set qualitative comparative analysis (fsQCA) approach. Using a sample of listed new energy companies in China from 2016 to 2020, we identified two configurations that generate high CFP and four that generate low CFP. The social pillar is a determinant in generating high CFP outcomes, and it has shown stability in its configuration across time. The study will contribute to guiding new energy companies to strengthen their corporate social responsibility practices and expand the application of the fsQCA in longitudinal datasets. [ABSTRACT FROM AUTHOR]

• The GTFP growth is calculated using a three-stage DEA dynamic analysis model. • An asymmetric spatial weighting matrix is constructed. • The temporal-spatial evolution of GTFP growth in China's coastal cities is explored. • The relevant policy implications are provided. Coastal cities are the strategic core areas of China's economic growth. Measuring and understanding green total factor productivity (GTFP) growth in coastal cities is an essential prerequisite for achieving high-quality development (HQD). This paper aims to measure the accurate GTFP growth of China's coastal cities and grasp its temporal-spatial evolution. First, a three-stage dynamic analysis model is constructed to calculate the accurate GTFP growth with the effects of external environmental factors and random errors eliminated. In the context of the "3060" double carbon target, carbon reduction poses a challenge to the HQD of the coastal cities. To measure GTFP growth under the carbon emission constraints, carbon emissions are considered as one of the undesired outputs. On this basis, the temporal-spatial evolution of the GTFP index and its spatial effects are further explored using kernel density estimation and spatial Markov chains. The empirical results show that: (i) The adjusted GTFP index after eliminating the effects of environmental factors and random errors is significantly different from the original results. The GTFP index of coastal cities is underestimated without eliminating the effects of environmental factors and random errors. (ii) There are significant differences in the regional distribution of GTFP growth in coastal cities, with cities with faster GTFP growth gathering production factors from adjacent cities and causing a siphon effect. Finally, policy recommendations related to these findings are given. [ABSTRACT FROM AUTHOR]

In recent years, the Chinese government attaches great importance to the development of a high-quality marine economy. The Ministry of Natural Resources issued the opinions on promoting the high-quality development of the marine economy, which pointed out that technology innovation should play a leading role in the high-quality development of the marine economy. In this paper, we use a comprehensive weight model including the entropy method and the best-worst method (BWM) to measure the level of marine technology innovation in China's coastal regions from 2006 to 2016. Then, we use the threshold regression model to examine the role of marine technology innovation in the high-quality development of the marine economy. The results show that there is a nonlinear relationship between marine technology innovation and high-quality development of the marine economy. Furthermore, we find that when the level of marine technology innovation exceeds a certain threshold, its promotion effect of the high-quality development of the marine economy gradually weakens. Finally, we analyze the reasons for the above findings and discuss the corresponding policy suggestions. • A comprehensive weight model is used to calculate the marine technology innovation index in China's coastal regions. • The SBM-Undesirable model and SuperSBM-Undesirable model are used to calculate the growth of the GTFP of the marine economy. • The growth of GTFP of the marine economy is used to represent the high-quality development level of the marine economy. • The nonlinear relationship between marine technology innovation and the growth of GTFP of the marine economy is examined. [ABSTRACT FROM AUTHOR]

In the context of the booming sharing economy, shared bicycles as an important part of the sharing economy have been studied by many scholars, and these researches mainly focus on the socioeconomic characteristics of users and the system design level of shared bicycles, it is very necessary to study the evaluation method of shared bicycles which is a typical multi-attribute decision- making (MADM) problem. Firstly, the linguistic spherical fuzzy numbers (Lt-SFNs) is proposed to express the public's language evaluation information. Compared with the linguistic intuitionistic fuzzy numbers (LIFNs) and the linguistic q-rung orthopair fuzzy numbers (Lq-ROFNs), Lt-SFNs have a wider information expression range. Then, in order to integrate the language evaluation information, the linguistic spherical fuzzy weighted averaging (Lt-SFSWA) operator is proposed, which can aggregate the group linguistic evaluation information. Further, the MABAC (Multi-Attributive Border Approximation area Comparison) method is extended to the linguistic spherical fuzzy environment and the Lt-SFS-MABAC method is proposed, which can process linguistic evaluation information and select an optimal alternative from a plurality of alternatives. At the same time, the TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method is extended to the linguistic spherical fuzzy environment and the Lt-SFS-TODIM method is proposed. Lastly, we conducted sensitivity analysis and comparative analysis of the Lt-SFS-MABAC method, the Lt-SFS-TODIM method and the Lt-SFSWA method. The results show that the Lt-SFS-MABAC method is sensitive to weights, decision makers can use the Lt-SFS-MABAC method to make a realistic evaluation based on the actual environment. • Define linguistic T-spherical fuzzy numbers (Lt-SFNs) and their operational rules. • Propose Lt-SFSWA operator for Lt-SFNs. • Propose an improved TODIM method and a MABAC method based on Lt-SFNs. • Construct the evaluation index system of Shared Bicycles. • Show the advantages of the proposed method by a real case of Shared Bicycles. [ABSTRACT FROM AUTHOR]

The aim of the paper is to evaluate empirically the main implications of digital technology (DT) on carbon emissions (CE). Our sample focuses on 283 cities of China over the period from 2003 to 2019, and the effect of DT on CE is examined with a threshold spatial effect model. Empirical results show that DT has a negative impact on carbon emissions and the transmission mechanism contains both a direct impact on local region and a spillover effect across regions. There is empirical evidence of a threshold effect in the relationship between DT and CE, with stronger carbon reduction effect for DT values larger than the established threshold. Moreover, CE reduction effect of DT appear to be amplified by the level of marketization. Regions with a higher level of marketization thus show a more significant manifestation of CE reduction effect attributed to DT. Our results provide empirical evidence that DT development may contribute to achieving carbon neutrality at least partially. [ABSTRACT FROM AUTHOR]

• The ecological management capacity of the Yellow River Basin is evaluated. • An Uninorm combination indicator weight model is proposed. • An integrated model based on the MULTIMOORA-Borda method is developed. • Policy recommendations are given to help improve ecological governance. As a river of great strategic significance in China, the ecological governance of the Yellow River is an important issue. As a multi-attribute decision-making (MADM) problem, evaluating the ecological governance of the Yellow River involves many evaluation indexes. To accurately measure the importance of each indicator, this paper applies the best-worst method (BWM) based on linguistic variables to calculate the subjective weights of the indexes. The improved grey relational (IGR) method is proposed to calculate the objective weights. And the two weights are combined using the Uninorm operator to obtain the combination weights of the indexes. To evaluate the problem from multiple perspectives, we apply the MULTIMOORA method to the ecological governance problem. Then we propose the novel Borda method to aggregate the three evaluation results obtained by the MULTIMOORA method and thus construct the MULTIMOORA-Borda method. Based on the above methods, we analyze the evaluation results and provide policy recommendations for ecological governance of the Yellow River Basin. [ABSTRACT FROM AUTHOR]