Linking green innovation performance and green innovative human resource practices in SMEs; a moderation and mediation analysis using PLS-SEM

Factors Affecting on Environmental Strategy in SMEs manufacturing Firms of a developing country: Mediating role of Green Employee Behavior

Background

Sustainability in small and medium-sized enterprises (SMEs) which engage heavily in manufacturing provides them with an essential platform for implementing environmental strategy, which is aimed at reducing environmental damage and promoting environmental protection. This study aims to examine the impact of the reduction in resource use, the greening of processes and products on environmental strategy and the mediating role of green employee behaviour.

Methods

Primary data gathered with the help of questionnaires from employees of SMEs manufacturing in developing countries, Pakistan. The research gathered data from 211 participants by applying a pre-tested instrumental questionnaire and structural equation modelling (SEM) for data analysis.

Results

The results confirmed all direct effects, including a reduction in resource use, the greening of processes and products and green employee behaviour of environmental strategies in small and medium manufacturing firms. Also, confirmed partial mediation effect of green employee behavior between greening of processes and products and environmental strategy.

Conclusion

The current study clearly showed the need for programs and infrastructures that support resource reduction and greening businesses in SMEs. Companies' implementation of green processes and technologies allows SMEs to take an environmentally responsible stand and become part of the movement toward sustainability. The research stresses the importance of green employee conduct as a mediator, the central point being the individual employee being engaged and aware of the subject and willing to participate in environmentally friendly practices. Therefore, small and medium enterprises should enlighten their staff to practice green behaviour, give them what they need and empower them to be change drivers that will trigger sustainability throughout the organisations.

Assessment of the impact of management commitment and supply chain integration on SMEs' innovation performance: Moderation role of government support

This study aims to investigate the effect of management commitment (MC), supply chain integration (SCI), and government support (PGS) on small and medium enterprises (SMEs) innovation performance. The study was quantitative, and the cross-sectional method was used to gather 685 valid data through a structured questionnaire. Confirmatory factor analysis in Analysis of Moment Structures version 26 software was engaged in checking the constructs' validity. Hierarchical regression analysis was employed to examine the hypothesized relationships using Statistical Package for Social Sciences version 26 software. The regression analysis findings revealed that management commitment influenced the three dimensions of SCI (internal, customer, and supplier integration) and SMEs' innovation performance. The results from the mediation analysis indicated a partial mediation effect of internal, customer, and supplier integration in the relationship between management commitment and SMEs' innovation performance. Also, PGS significantly moderated the relationship between SCI and SMEs' innovation performance. The present study is critical as it explains the medium through which MC, SCI, PGS, and SMEs' innovation performance relate in one conceptual model.

Factors affecting firms' green technology innovation: an evolutionary game based on prospect theory

In the context of green development and the construction of ecological civilization, a key issue for governments is how to promote firms' green technology innovation. Assuming the bounded rationality of decision-makers, this paper constructs a game model of green technology innovation between firms and the government based on prospect theory. It dynamically analyzes the decision process and optimal strategy under different scenarios and uses numerical simulation to identify the influencing factors. There are three main findings. (1) Firms' green technology innovation decisions depend on the net income difference between strategies. Environmental regulation encourages firms to carry out green technology innovation by increasing the environmental costs to non-green technology innovation firms and increasing the income of green technology innovation firms. (2) Uncertainty and the behavioral characteristics of managers significantly affect green technology innovation. Firms' green technology innovation is positively correlated with the success rate of green technology innovation, whereas is negatively correlated with perceived value sensitivity and loss aversion. (3) There is instrumental heterogeneity in the incentive effect of environmental regulation on firms' green technology innovation. The most effective tool is comprehensive environmental regulation, followed by punishment and then subsidy. The research provides a reference for governments to formulate environmental regulations and firms to manage innovation.

Causes and Evolution Characteristics of Green Innovation Efficiency Loss: The Perspective of Factor Mismatch under Local Government Competition

The objective of this paper is to measure the efficiency loss of green innovation caused by local government competition and explore its causes and evolution characteristics. Based on the equimarginal principles such as the deviation of the allocation of green innovation output factors, this paper uses the panel data of China’s provinces (excluding Tibet, Hong Kong, Macao and Taiwan) from 2000 to 2020 and employs the spatial panel measurement model and the Kernel density estimation. The study finds that first, local government competition causes the mismatch of local innovation factors not only locally but also in neighboring regions. Second, the mismatch of innovative talents and capital caused by local government competition lowers the green innovation efficiency. Third, the shortage of innovative talents caused by local government competition is the main reason for the loss of green innovation efficiency in Beijing, Tianjin, and Shanghai. Fourth, the degree of efficiency loss of green innovation at the provincial level in China is heterogeneous in government competition strategies, and the loss due to tax competition is the most significant. Fifth, although the loss of green innovation efficiency generally decreases yearly, in the future, the institutional competition will still hinder the improvement of green innovation efficiency in the eastern, central and western regions of China. Our policy suggestions include promoting regional cooperation and cultivating innovative talents to further improve the efficiency of green innovation.

Impact of Green Finance and Environmental Regulations on the Green Innovation Efficiency in China

Innovation is the first driving force for development, and green innovation efficiency (GIE) plays a very important role in regional sustainable development. Data from 31 provinces and cities in China from 2011 to 2020 were used to select the proportion of energy saving and environmental protection costs in GDP as the green financial value, and the proportion of industrial pollution control input in GDP as the environmental regulation index. Green innovation efficiency is measured from two aspects of input and output by DEA method, and carried out for 31 provinces and cities in three regions. Using the DEA-Malmquist index to measure regional green innovation efficiency, the results show that the green innovation efficiency in three regions basically presents an upward trend, but the upward trend of green innovation efficiency is different between the three regions. A Tobit regression model is constructed to explore the impact of green finance and environmental regulations on the green innovation efficiency in these three regions. Research indicates that environmental regulations, the proportion of output value of tertiary industry in GDP, industrial structure, and foreign direct investment have significant impacts on the green innovation efficiency in all regions. Green finance, industrial structure, and power consumption have a significant impact on the green innovation efficiency in eastern China. Industrial structure has a significant impact on green innovation efficiency in central China, while power consumption and industrial structure have a significant impact on green innovation efficiency in western China. Therefore, each region needs to improve the standard of environmental regulation innovation, and introduce and use foreign investment in a scientific and reasonable way so as to promote the improvement of industrial infrastructure.

Does Entrepreneur Moral Reflectiveness Matter? Pursing Low-Carbon Emission Behavior among SMEs through the Relationship between Environmental Factors, Entrepreneur Personal Concept, and Outcome Expectations

The intensity and severe impact of carbon emissions on the environment has been witnessed globally. This study aims to unravel how environmental factors, personal factors, and entrepreneur outcome expectations affect entrepreneur low-carbon emission behavior (LCB) through the lens of social cognitive theory (SCT). To achieve the aims of this study, we gathered data from 1015 entrepreneurs and small, medium-sized enterprises (SMEs) in the Jiangsu province of China to analyze the predictors of entrepreneur low-carbon behavior. The proposed relationships were tested using the partial least square structural equation modelling (PLS-SEM) technique. The findings from the study indicate that environmental factors (i.e., climate change (CC), public media (PM), and corporate social responsibility (CSR) have a significant and positive relationship with entrepreneur LCB. Moreover, entrepreneur green production self-efficacy (GPS) is positively associated with entrepreneur LCB. The findings further revealed that entrepreneur personal concepts such as entrepreneur self-monitoring (SM), entrepreneur self-esteem (SE), and entrepreneur self-Preference (SP) significantly and completely affect entrepreneur GPS. Likewise, entrepreneur moral reflectiveness (EMR) substantially moderates the relationship between entrepreneur green production outcome expectation and LCB. This study concludes with recommendations for researchers interested in enhancing knowledge in this field. In summation, this study shows that a behavioral science viewpoint is critical for improving knowledge of low-carbon environment, CC drivers, mitigation strategies, and sustainable transition to our complex environment.