In this paper, we expand the value-added intellectual coefficient (VAIC) model by constructing a comprehensive financial capital (FC) component. Human capital efficiency is subdivided into executive (EHCE) and nonexecutive human capital efficiency (NHCE). We have sampled listed agriculture companies (LAC) in China’s Shanghai and Shenzhen A-share markets from 2009 to 2018 and categorized them as high-tech (HTAC) and non-high-tech agriculture companies (NHTAC). We find that capital employed efficiency (CEE) and EHCE have a significant positive effect on corporate sustainable growth (CSG) of HTAC but no significant effect on CSG of NHTAC, while FC has a significant positive effect on both. These results suggest that companies, especially HTAC, should invest in human capital, and their executives and policymakers should develop effective knowledge management tools and begin accumulating the necessary intellectual capital to allow adaptation to their changing environment. In the spirit of the intellectual agriculture concept, we present some new ways to study the performance of agricultural companies using intellectual capital and offer suggestions that can help to modernize the industry.

When managing a new product development (NPD) problem, a firm needs to consider the cooperation with its strategic partners in a network because surviving independently in the industry is almost impossible. However, due to the large variances among partners in terms of leadership, management, IT infrastructure and organizational cultures, it may lead to poor communication and cooperation and slow responses. A severe impact on the process and outcome of NPD may result. To facilitate buyer–supplier cooperation, suitable knowledge management and product development process management need to be adopted to match the characteristics of the selected NPD mix. In this paper, a supermatrix analytic network process (ANP) model with sensitivity analysis is first developed to select the most appropriate NPD mix. A balanced scorecard (BSC) using ANP with sensitivity analysis is used next to demonstrate the effectiveness of the proposed model in the execution of NPD process.

We define renewable energy generation (REG) inputs as the installed capacity of solar energy, wind power, geothermal energy, and bio-fuel production and define electricity from renewable energy as an output indicator. Based on balanced panel data from 2007 to 2016 for 20 countries, we use stochastic frontier analysis to calculate the efficiency of REG and analyze the influencing factors. We find the following results: the efficiency of global REG is improving; increased carbon emissions have not influenced it; the proportion of natural resource rent has a positive effect; increasing urbanization rates have hindered efficiency; and higher per capita income can lead to higher efficiency. Based on these findings, we propose that more attention should be given to the coordination of policies associated with the expansion of installed capacity and the acceleration of REG. Research and development should be increased for energy storage technology to take advantage of regional natural resource endowments.

Environmental management plays a pivotal role in the financial performance of the energy industry. A number of studies have focused on the relationship between environmental management and financial sustainability, but the results are inconsistent. In addition, the existing literature failed to study the indirect and nonlinear relationship between the two. To fill this gap, this paper aims to seek out a mediator (debt financing) and employ a threshold effect model to explore the relationship between environmental management and financial sustainability in the energy industry. First, this paper uses least square dummy variable method to examine the relationship among environmental management, debt financing, and financial sustainability, and the results show that environmental management and debt financing have a positive relationship with financial sustainability. Second, the mediating effect model and threshold effect model are employed to examine the relationship among environmental management, debt financing, and financial sustainability, and the results reveal that debt financing can mediate the effect of environmental management on financial sustainability, and there is a nonlinear impact of debt financing on financial sustainability for different thresholds of environmental management. Finally, this paper presents policy proposals to promote the development of the energy industry based on the conclusions.