(Green) Knowledge spillovers and regional environmental support: do they matter for the entry of new green tech-based firms?

Coll-Martínez, Eva; Kedjar, Malia; Renou-Maissant, Patricia

doi:10.1007/s00168-022-01111-3

Cited by 3 publications

(3 citation statements)

References 89 publications

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“…Furthermore, research on environmental disclosure has found that substantial environmental disclosure reduces information asymmetry between enterprises and banks because disclosure quality reflects better environmental information; it can increase company value, while symbolic disclosure can increase information asymmetry. Public interest in environmental concerns impacts stock index returns [7], yet it fails to enhance the performance of publicly traded companies [3]. The revelation of illicit environmental practices by U.S. firms results in a detrimental impact on their market valuation [29].…”

Section: Literature Reviewmentioning

confidence: 99%

“…This advantage can lower corporate debt costs [37], promote green management outputs, and consequently enhance financial performance. Research has increasingly focused on the realm of green technological innovation [3,10,24,38], highlighting how such innovation not only elevates environmental performance but also bolsters a company's competitive edge [9,20]. Through enhancing a firm's environmental reputation, green innovation serves to indirectly boost its economic outcomes, a perspective echoed by various scholars [24].…”

Section: Literature Reviewmentioning

confidence: 99%

“…With the deepening of the ESG concept, enterprises have gradually become the main participants in the green technology innovation market. However, green innovation is distinguished by its quasipublic good nature [1], leading enterprises' green technological innovation endeavors to be subject to the dual externalities of knowledge and environmental spillover [2,3]. Quasipublic goods in green innovation refer to those goods or services that are neither entirely public nor completely private, possessing certain characteristics of non-exclusivity and noncompetitiveness.…”

Section: Introductionmentioning

confidence: 99%

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Green Technology Innovation and Enterprise Performance: An Analysis Based on Causal Machine Learning Models

Huang,

Wang,

Chen

et al. 2024

Sustainability

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As increasingly stringent environmental regulations are put into effect, Environmental, Social, and Governance (ESG) concepts are being seamlessly integrated into the core of corporate innovation strategies. Due to the quasi-public product perspective of green innovation, the performance of enterprises as a result of green innovation activities exhibits significant heterogeneity. This heterogeneity exists not only between corporate value and financial performance but also among individual enterprises. This paper is based on a sample of 1510 listed Chinese companies examined from 2013 to 2020 and uses machine learning algorithms and quasi-natural experiments to precisely estimate the causal relationship and mechanisms between green innovation and corporate performance. The findings elucidate several critical aspects of green innovation within the corporate sphere: Firstly, rather than attracting green incentives from financial markets, green innovation activities inadvertently stifle the enhancement of corporate value. Secondly, these activities markedly bolster corporate financial performance, primarily by diminishing operational costs, which in turn elevates the return on assets (ROA). Lastly, of all corporate characteristics examined, enterprise size and equity concentration stand out as key determinants influencing the variability in outcomes of green innovation performance. The above findings provide information on the significant implications of enhancing green technology innovation systems and green incentive mechanisms.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Green Technology Innovation and Enterprise Performance: An Analysis Based on Causal Machine Learning Models

Huang,

Wang,

Chen

et al. 2024

Sustainability

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What are the drivers of eco-innovation? Empirical evidence from French start-ups

Abdesselam,

Kedjar,

Renou-Maissant

2024

Technological Forecasting and Social Change

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Global–Local Knowledge Spillover Strategic Coupling Network: Biopharmaceutical Industry Study of GBA, China

et al. 2022

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Strategic coupling is a hot field in the research of global production networks. The existing literature mostly consists of studies from the perspective of countries, regions, and enterprises, and relatively lacks the content for describing global–local strategic coupling networks and their evolution path with industries as carriers. The GBA is a bridgehead for China to participate in the global production network. Based on the systematic construction of the strategic coupling network analysis framework of global–local knowledge spillovers, this paper, taking the biopharmaceutical industry of GBA as an example, depicts the evolution process of its coupling network nodes, structures, and networks from 1990 to 2019 by using system analysis, social network analysis, and other methods, and analyzes node centrality, network structure, coupling paths, and their influencing factors. We found that the strategic coupling of global–local knowledge spillover is typically a networked structure, with the network organization presenting a multi-element sub-system hierarchical state. The overall network structure, with knowledge spillover as the carrier, shows obvious phased differences, having gone through three path stages from exploratory to expanding to stable. The path selection shows a spatial progression and a temporal sequence. The main factors affecting the path selection of the coupling network are the bargaining power of regional knowledge, behavioral subjects’ will, and multi-dimensional proximity.

show abstract

(Green) Knowledge spillovers and regional environmental support: do they matter for the entry of new green tech-based firms?

Cited by 3 publications

References 89 publications

Green Technology Innovation and Enterprise Performance: An Analysis Based on Causal Machine Learning Models

Green Technology Innovation and Enterprise Performance: An Analysis Based on Causal Machine Learning Models

What are the drivers of eco-innovation? Empirical evidence from French start-ups

Global–Local Knowledge Spillover Strategic Coupling Network: Biopharmaceutical Industry Study of GBA, China

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