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

Iqbal, Shuja; Akhtar, Shamim; Anwar, Farooq; Kayani, Arqam Javed; Sohu, Jan Muhammad; Khan, Aamir

doi:10.1007/s12144-021-02403-1

Cited by 32 publications

(32 citation statements)

References 127 publications

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“…The competitive business environment in transition economies, such as China, has made it difficult for entrepreneurial-based high-tech small and medium enterprises (SMEs) to survive and grow. Organizations that want to succeed in such a tumultuous environment must rethink their priorities to align their business models with technological advancements and climate change (CC) issues [1]. Along with this challenge, growing public awareness of environmental problems has compelled businesses to invest in environmentally friendly practices to improve their green innovation performance, as predicted by a set of green activities [2].…”

Section: Introductionmentioning

confidence: 99%

“…Acknowledgments: This research is part of [1] Research on correlation indicators of integrated development of urban ecological services and population quality of life (5611160004); [2] Perception of fairness in self-organized mass entrepreneurship (4061160); [3] Research on high-quality development driven by scientific and technological innovation in Jiangsu (1721160306).…”

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confidence: 99%

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

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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

et al. 2022

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“…Zhou et al [15] proposed that accelerating the flow of innovation factors and optimizing the allocation of innovation factors can improve the efficiency of the green economy. And many scholars also analyzed the impact of innovation factors such as capital or talent on green innovation efficiency [16][17][18]. Focusing on capital input, some scholars show that the increase of capital input can effectively improve the input level of enterprises in environmental governance, thus promoting environmental product innovation and improving green innovation efficiency [16,17].…”

Section: Literature Reviewmentioning

confidence: 99%

“…And many scholars also analyzed the impact of innovation factors such as capital or talent on green innovation efficiency [16][17][18]. Focusing on capital input, some scholars show that the increase of capital input can effectively improve the input level of enterprises in environmental governance, thus promoting environmental product innovation and improving green innovation efficiency [16,17]. Some scholars believe that capital input can be transformed into R&D capital, education capital and other forms to promote human capital accumulation and effectively improve green innovation [17].…”

Section: Literature Reviewmentioning

confidence: 99%

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

2022

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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.

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“…Scholars have conducted in-depth analysis from different perspectives on green innovation efficiency (GIE), such as the measurement of green innovation performance [18,19], the characteristics of green innovation performance [20][21][22][23], environmental regulations [24][25][26][27][28][29], manufacturing [30][31][32][33], foreign direct investment [34][35][36][37][38][39][40], and so on [41][42][43]. As an effective means to promote the renewal of economic development modes and green development, green finance solves some problems in financing and transformation and upgrading urgently needed by the country to achieve high-quality economic development through green investment.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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

Cited by 32 publications

References 127 publications

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

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

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

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

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