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The sustainability of mariculture depends on adopting green technologies, which can mitigate the negative impacts on the environment and ensure long-term viability. However, existing studies do not comprehensively understand the characteristics and regional differences of green technology progress (GTP) in mariculture. According to data from ten coastal regions from 2008 to 2020, this study adopts the Epsilon-Based Measure (EBM)-Malmquist model to measure the GTP of mariculture, uses the Dagum Gini coefficient to analyze the spatial differences of GTP, and uses convergence models to explore the convergence of GTP. The results showed that: (1) the GTP of China’s mariculture showed a fluctuating upward trend temporally and significant spatial differences. The overall differences showed a dispersion trend over time. The contributions of inter-regional super variable net value difference (Gnb), inter-regional transvariation intensity (Gt), and intra-regional difference (Gw) were 38.813%, 31.256%, and 29.931%, respectively. (2) The degree of dispersion of GTP among different regions has not decreased with time, which means there is no apparent σ convergence. Absolute β convergence and conditional β convergence existed in GTP, and the absolute value of the latter was greater than that of the former. That is, the growth rate of GTP will first reach their respective steady-state levels and then approach a unified steady-state equilibrium level.

With the rapid development of mariculture, environmental pollution is becoming more and more serious. It is particularly important to study the green output bias of technological progress for the long-term sustainable development of mariculture. Based on the input-output data of the mariculture in 10 Chinese coastal areas from 2008 to 2018, the DEA-Malmquist index decomposition method is used to calculate output-biased technological progress index and combines with the change of marginal substitution rate of output factors in different periods to identify the bias of technological progress between output factors, and analyze the green output bias of mariculture technological progress. The results show that green technological progress is a crucial factor affecting green total factor productivity’s growth in China’s mariculture. During the study period, the number of regions where technological progress tends to reduce pollutant emissions shows a fluctuating upward trend, and the degree of technological progress toward green output is high. There are obvious differences among regions. The green output bias of technological progress in the South China Sea area is the highest, followed by the East China Sea area, and the Bohai Sea area is poor. Specifically, the green output bias of technological progress in Fujian, Guangdong and Hainan is higher, while the green output bias of technological progress in Tianjin, Hebei, Shandong and Guangxi is lower. According to the research results, corresponding policy suggestions are provided to realize the green and sustainable development of China’s mariculture.

With the rapid development of mariculture, environmental pollution is becoming more and more serious. It is particularly important to study the green output bias of technological progress for the long-term sustainable development of mariculture. Based on the input-output data of the mariculture in 10 Chinese coastal areas from 2008 to 2018, the DEA-Malmquist index decomposition method is used to calculate the output-biased technological progress index and combines with the change of marginal substitution rate of output factors in different periods to identify the bias of technological progress between output factors and analyze the green output bias of mariculture technological progress. The results show that green technological progress is a crucial factor affecting green total factor productivity's growth in China's mariculture. During the study period, the number of regions where technological progress tends to reduce pollutant emissions shows a fluctuating upward trend, and the degree of technological progress toward green output is high. There are obvious differences among regions. The green output bias of technological progress in the South China Sea area is the highest, followed by the East China Sea area, and the Bohai Sea area is poor. Specifically, the green output bias of technological progress in Fujian, Guangdong, and Hainan is higher, while the green output bias of technological progress in Tianjin, Hebei, Shandong, and Guangxi is lower. According to the research results, corresponding policy suggestions are provided to realize the green and sustainable development of China's mariculture.

Purpose There is no conclusive whether environmental regulation is a constraint or an incentive to the production development. The purpose of this paper is to analyze the non-linear effects of environmental regulations on economic outcomes from the combined perspective of labor productivity and environmental regulation costs. Design/methodology/approach Under the assumption of maximizing the utility of residents and maximizing the profit of firms, this research introduces a mathematical model that incorporates the promotion effect of environmental regulations on labor productivity and the costs of environmental regulations. On this basis, the authors analyze the non-linear relationship between environmental regulations and economic outcomes theoretically. This paper also conducts an empirical test using the panel data of 28 provinces in China from 1998 to 2015 through threshold regression. Findings Theoretical analysis shows that environmental regulations impose both the environmental regulation cost effect and the compensation effect on the labor productivity enhancement. The ultimate impact of environmental regulation on economic outcomes depends on the comparison of these two effects. Under the different intensities of environmental regulation, the magnitude of these two effects may not be equal. The empirical results further confirm the nonlinear relationship between environmental regulations and economic outcomes. Originality/value Previous studies have neglected the role of environmental regulations in improving labor productivity. This work’s main contribution is to propose a novel framework to study the non-linear relationship between environmental regulation and the growth of economic outcomes from perspective of labor productivity and the costs of environmental regulations.

Along with the rapid growth of the coastal economy as well as the broadening and deepening of ocean exploration, the extensive growth pattern of China's marine economy led to such problems as more consumption of marine resources, more waste emissions, and the deterioration of the marine ecological system. Therefore, the study of marine economic efficiency has great significance for achieving cleaner production and sustainable development of China's marine economy. Based on the global Malmquist-Luenberger index model, this paper brings undesirable output into the measurement of total factor productivity to evaluate the green efficiency of China's marine economy under environmental constraints. In order to better depict the dynamic nature of marine economic efficiency, eleven coastal regions in China were selected as the objects of this study, with data collected from 2006 to 2014. The results indicate that total factor productivity of China's marine economy without considering undesirable output is markedly higher than that considering it. China's coastal regions differed in the green efficiency of the marine economy. The green efficiency of the marine economy in Tianjin rose the fastest, while in Guangxi it dropped the fastest, and the average annual growth rate varied by 8.18% between the two provinces. Moreover, the green efficiency of the East China Sea Economic Circle is the highest in the three coastal regions followed by the Bohai Economic Rim, while that of the South China Sea Economic Circle is the lowest. The improvement of the green efficiency of China's marine economy mainly stems from technological progress, while the improvement of technical efficiency has little influence on it, sometimes even adversely affecting it. Based on these findings, we discuss the corresponding policy suggestions on the sustainable development of China's marine economy.

The development of China's marine economy has never been more challenging due to serious problems such as the waste of marine resources, pollution of the marine environment and uneven development in the region. Therefore, the study of China's marine economic growth pattern has great significance and may ensure the sustainable development of the marine economy. This study utilizes data on China's eleven coastal regions from 2006 to 2014 and applies the Cobb-Douglas production function and the Solow residual method to evaluate the contribution rate of the total factor productivity of the marine economy of China's coastal regions. To more objectively illustrate the marine economic growth pattern, this paper introduces the intensive coefficient of marine economic growth. The results indicate that the contribution rate of the total factor productivity of the marine economy of China showed a slightly rising trend from 2006 to 2014, and its average growth rate increased from − 0.58% to 3.39% between 2006 and 2014. China's coastal regions differed in their contributions to the total factor productivity of the marine economy. During the same period, the main driving factor of marine economic growth was factor inputs and China's marine economic growth pattern was still extensive. In terms of regions, although most coastal regions in China experienced extensive growth, the extent of the growth of the marine economy of China's coastal regions has declined after the pilot projects implemented by the Chinese government in 2012.

Informatization is the dynamic development process of using information technology to promote information exchange and knowledge sharing in all aspects of social life, which is crucial for the development of fisheries. Based on a review of the development process and the current informatization situation for China’s fisheries, this study selects relevant data on 28 Chinese provinces from 2006 to 2018 and uses the improved entropy method and the DEA-Malmquist index method to calculate the informatization implementation level and economic efficiency of the fisheries in each province, then the panel VAR model is used to test the dynamic impact of informatization on fisheries’ economic efficiencies. The results show that fishery informatization has a long-term significant positive effect on fishery economic efficiency, and this effect gradually increases over a short period and then tends to remain stable in the long term.

With the rapidly increasing consumption of seafood in China, mariculture obtains a prominent position in the national economy. However, ecological security of the mariculture industry remains an important issue in China and cannot be ignored. In this paper, Lokta–Volterra model is adopted to uncover the symbiotic relationships between the economic and the ecological system over time. The results reveal that, the symbiotic relationships of mariculture industry in China can be divided into four types:mutualistic symbiosis pattern, industrial damage pattern, ecological damage pattern and mutual inhibition competition pattern. The frequency of mutualistic symbiosis and mutual inhibition competition pattern is relatively low, while the unbalanced pattern represented by ecological damage and industrial damage is dominant. When it comes to regional mariculture ecological health, Guangxi, Fujian and Tianjin are dominated by the healthy state, and Shandong and Hebei are in the sub-health state. Liaoning was in a state of high risk. For other provinces, the health states fluctuate greatly. Thus, enhancing coordination, pollution control, intensive farming, and overall planning is critical to mariculture ecological sustainability.

As marine economy has entered a new normal, the transformation and upgrading of marine economy has reached a crossroads in coastal regions, and there is an urgent need to change the development mode and the growth momentum of marine economy. Exploring reasonable environmental regulation means and appropriate environmental regulation intensity to promote green technological innovation and lead the transformation of marine economy is the only way for China's marine sustainable development in the future. Through theoretical analysis and empirical tests, this study examines the influential mechanisms of environmental regulation and technological innovation on GTFP of marine economy to provide a theoretical basis for local government and enterprises to make decisions under environmental regulation. The empirical process adopts a direct effect, an intermediary effect, and a threshold effect model based on panel data from 11 provinces and cities in China's coastal regions. The results show that China's marine environmental regulation is still in its initial stage, which is not conducive to the improvement of GTFP of marine economy. Technological innovation plays an intermediary role between environmental regulation and GTFP of marine economy, but the intermediary effect is very small-only 0.0920, so there is still significant room to improve. During the sample period, taking marine technological innovation as the threshold variable, environmental regulation has significant double threshold effect of technological innovation on GTFP of marine economy. Different levels of technological innovation decide which effect, either the “offset effect” or the “compensation effect” dominates. Finally, this paper puts forward the corresponding policy recommendations.

Purpose Efficiency of a commercial bank affects both its competitiveness and the role it plays in the process of economic development. Although great efforts have been exerted in developing the various aspects of banking efficiency, there seems to be a lack of research on examining the impact of the bank efficiency from the employee wage perspective. The mechanism of how employee wage affects commercial bank efficiency and the relationship between the two were analyzed in this paper. Based on the growing body of research on efficiency in banking, the aim of this paper is to examine if competitiveness of employee wages at any commercial bank has any impact on the bank efficiency score. Design/methodology/approach The method used was quantitative analysis, which was based on comparing the evaluated efficiencies of the banks with employee wages published in the bank reports. The empirical data in this paper were based on 16 Chinese listed commercial banks from 2004 to 2012. The per capita wage of commercial banks was selected as the wage indicator, and the efficiency value obtained by the slack-based measure (SBM) model was selected as the efficiency indicator. According to the calculated data, the Tobit regression model was built to analyze the relationship between employee wage and commercial bank efficiency. Findings The research results show that employee wage is the key variable that influences the efficiency of Chinese commercial banks, and the inverted U-shaped relationship between employee wage and commercial banks efficiency shows up. Practical implications The wage structure data of the composition of basic pay and bonus were not available at the time of conducting the research. Per capita wages were used instead to reflect the employee wage levels of Chinese banks. Originality/value This study can provide some help for the banking industry by analyzing the wage levels from the perspective of efficiency and also further enriches the theoretical system of the relationship between employee wage and bank efficiency.

Taking the aquaculture area, the number of farming boats and that of aquaculturist as input variables, the aquaculture production as desirable output variable and polluted economic loss as undesirable output variable, this paper conducts SBM model to evaluate the aquaculture efficiency based on the data of 16 aquaculture-developed provinces in China from 2004 to 2011. The results show the efficiency in China has not changed much in recent years with the efficiency values mainly between 0.39 and 0.53, and the efficiency of marine-aquaculture-dominated provinces is generally higher than that of freshwater-aquaculture-dominated ones. To analyze the difference under the efficiency, the panel Tobit model is used with education level factor, training factor, technology extension factor, technical level factor, scale factor and species factor as the efficiency influencing factors. The results show that technology extension factor and technical level factor have significant positive influence.

Private investment in China, as a developing country, is an important source of financing for Chinese SMEs (Small and Medium-Size Enterprises) and has played a major role in the development of the real economy. However, in 2016, the growth rate of private investment in China dropped from 10.18% to 3.17%, which had a significant impact on the real economy. At the same time, China&rsquo, s real estate market has developed rapidly, attracting a large number of capital inflows. The relationship between real estate development and private investment in China is worth considering. This study first, theoretically analyzes the influence mechanism of real estate industry on private investment, pointing out that within a modest development range, the development of real estate industry can promote private investment through the industrial linkage, urbanization, and balance sheet effects, but when real estate is overdeveloped, it has an inhibitory effect on private investment through vampire effect, raising costs and reducing demand effect. In other words, real estate has different effects on private investment in different developmental periods. Therefore, there is a non-linear relationship between the two variables. Second, the relevant provincial panel data of 31 provinces in mainland China from 2003 to 2015 were selected. Using the dynamic panel system Generalized Method of Moments (GMM), this study estimated the correlation between real estate development and private investment. The empirical results showed that the development of the real estate industry has a significant impact on the level of private investment, the two showing an &ldquo, inverted U-shaped&rdquo, relationship. At present, in some provinces in China, the real estate industry has exceeded the inverted U-shaped threshold. To boost the vitality of private investment in promoting real economic growth, the development of the real estate industry should be restricted, and house prices should be properly regulated.

Based on partial differential analysis of Spatial Durbin Model (SDM), this paper selects provincial panel data of 11 coastal provinces in China from 2006 to 2014 to empirically study the spatial spillover effects of financial development on regional marine economy. The results show that there are significant spatial correlations in China's marine economy, and it is manifested as spatial exclusion, that is, there is a certain “congestion effect”. At this stage, Financial Interrelations Ratio (FIR) and Venture Capital (VC) have positive direct effects and negative spatial spillover effects on the development of marine economy. Government investment, on the contrary, has a negative direct effect and a positive spatial spillover effect on it. The impact of insurance on the marine economy is not significant.

Based on the modern contract theory, expectancy theory, and stakeholder theory, this paper analyzes how stakeholders relationship influences the efficiency of commercial banks and finds that the efficiency is a function of stakeholders relationship. A DEA model with Seiford's linear transformation function is developed to evaluate the efficiency in consideration of the undesirable output. The panel Tobit model is established to conduct empirical research with data of 14 Chinese commercial banks from 2004 to 2012. The study finds that except for business customer relation, stakeholder relationship is the key variable that influences comprehensive efficiency of commercial banks.

By employing principal component analysis, Granger causality test and impulse response function, this paper aims to investigate the dynamic relationship of energy consumption and environmental pollution, using Qingdao time series data set during 1985-2007. The result shows that energy consumption will result in environmental pollution with the impact of time lags because environment has certain bearing capacity itself. So we should deal with the pollution in time and make the pollution quantity always under environmental capacity.

The economic growth is one kind of risk sources for environmental pollution. Taking Qingdao as sample, using principal component analysis, Granger causality test and impulse response function, this paper aims to find the relationship between economic growth and environmental pollution. The result shows that the economic growth is Granger cause of environmental risk which are influenced by time lags. The influence is progressive, gradual, and long-standing.

Portfolio selection of oil/ gas projects is a fundamental subject of capital budgeting in the energy sector. In industry, strategic planning requires the selection of a portfolio of projects to advance the corporate goals. The term portfolio selection is more devoted to a set of financial assets that are easily traded and divisible. The principles and fundaments of portfolio selection can be used to compare strategies of investments, so that firms get maximum returns. In this paper, we discuss the oil/gas projects valuation methods first. Considering the characteristic of the oil/gas project, Real options method is more suitable for the oil/gas project than NPV method, and then a new model extended from the Black-Scholes model is built up. Finally, this paper put forward the portfolio selection model and gives a Computational case.