Exploring the influence of resource management between green innovation strategy and sustainable competitive advantage: the differences between emerging and traditional industries

Gao, Yang; Sun, Yu; Yuan, Yu‐Hsi; Xue, Xingqun; Sheng, Fan

doi:10.1504/ijtm.2021.115267

Cited by 12 publications

(7 citation statements)

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“…The direct, indirect and total effects of variable govsts in Table 7 is statistically significant at the 10% level, confirming Hypothesis H 6 . According to the theoretical analysis, by increasing R&D expenditures, the government can remove the worries for enterprises to carry out green technology innovation [72], thus enhancing the enthusiasm and initiative of enterprises in terms of green technology innovation and improving green technology innovation efficiency in the region. Along with the innovation-driven transformation and upgrading of industries in the Central Plains city cluster, the government has provided substantial support in establishing basic innovation platforms and increasing investment in innovation R&D. The policy guiding effect of green innovation is remarkable, which has laid a solid foundation for improving the efficiency of green technology innovation in the Central Plains city cluster.…”

Section: Analysis On the Estimated Resultsmentioning

confidence: 99%

Study on the Evaluation of Green Technology Innovation Efficiency and Its Influencing Factors in the Central Plains City Cluster of China

Dong

Yang

et al. 2022

Sustainability

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Green technology innovation, containing economic, social and ecological triple value effects, plays an important role in promoting regional high-quality development. In this paper, we take the Central Plains city cluster, one of China’s top ten national city clusters, as the research object and use the super-efficiency SBM-DEA model to measure and analyze its green technology innovation efficiency. The panel spatial Durbin model (SDM) is used to empirically investigate the market-based, policy and social factors that affect green technology innovation efficiency in the Central Plains city cluster. The main findings are as follows: (1) The green technology innovation efficiency in the Central Plains city cluster shows a fluctuating upward trend from 2009 to 2019, and the spatial differences are obvious, but this spatial difference has converged somewhat over time; (2) Economic development and industrial structure upgrading are the dominant market forces driving green technology innovation efficiency in the Central Plains city cluster, while opening up and enterprise performance hurt the efficiency of green technology innovation; (3) By strengthening environmental regulation and fiscal expenditures on science and technology, the government plays a guiding role in promoting green technology efficiency; (4) Human capital can provide talent support for green technology innovation to effectively promote the efficiency of green technology innovation in the Central Plains city cluster, while the impact of urbanization on green technology innovation efficiency is not significant; (5) In addition to urbanization, the market-based, policy, and social factors that affect green technology innovation efficiency in the Central Plains city cluster also present significant spatial spillover effects. To further promote green technology innovation efficiency in the Central Plains city cluster in the future, we should significantly promote the green transformation and upgrading of industrial structure, improve the quality of opening up to the outside world, strengthen environmental supervision and optimize its governance model, increase government support for green innovation, improve the talent cultivation and introduction system, and mobilize enterprises’ enthusiasm for green technology innovation.

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Section: Analysis On the Estimated Resultsmentioning

confidence: 99%

Study on the Evaluation of Green Technology Innovation Efficiency and Its Influencing Factors in the Central Plains City Cluster of China

Dong

Yang

et al. 2022

Sustainability

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“…The MinDS model uses the shortest distance from the frontier plane to evaluate the efficiency values of the DMUs. This model applies a mixed-integer linear programming approach by adding constraints to restrict all evaluated DMUs to the same hyperplane and then determines all efficient DMUs by the SBM model and solves the planning model with an efficient subset as its reference set [ 60 , 61 , 62 , 63 ]. Compared with the traditional DEA model and SBM model, the MinDS model has the following advantages: (1) it addresses the problem of slackness of variables not considered in traditional DEA models; and (2) it overcomes the problem that the objective function of the SBM model minimizes the efficiency value.…”

Section: Methodological Description and Selection Of Indicatorsmentioning

confidence: 99%

Environmental Performance Evaluation of Key Polluting Industries in China—Taking the Power Industry as an Example

Liu

Qiu

Sun

et al. 2022

IJERPH

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This paper analyzes the environmental performance, spatial and temporal characteristics, and optimization paths of key polluting industries, represented here by the power industry, using the super-efficient MinDS model. The study shows that the environmental performance as a whole presents the characteristics of an inverted U-shaped and then a U-shaped trend; each region presents an asymmetric state of convergent development followed by differentiated development, with 2014 as the structural change point; the development trend of environmental performance in each region is divided into three categories (rising, falling, and stable) and four types of spatial clustering (ultra-high, high, medium, and low levels); and input–output indicators of environmental performance in China and across regions have varying degrees of redundancy, with labor input redundancy being the greatest, followed by capital input, technology input, and pollution emissions. On this basis, we propose to improve the monitoring and inspection mechanism of the implementation process of pollution control in key polluting industries and to improve the level of environmental performance of key polluting industries by optimizing the combination of labor, capital, and technology input factors in each region according to local conditions and adopting differentiated strategies. The main contributions of this paper are threefold: first, we incorporate technological inputs into the environmental performance evaluation index system of the electric power industry, which can better reflect the real inputs of the electric power industry and measure the results more accurately; second, we adopt the MinDS model for measuring the environmental performance level, which can quantitatively analyze the gap between each indicator and the optimal level; and third, we propose a redundancy index, which can be used to compare the redundancy of each indicator and then judge the main efficiency levels of the different factors.

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“…However, at the same time, this advantage also attracts competitors to get involved, so the competitive advantage carried out has a limited time (Lin et al, 2020). Sustainable competitive advantage (SCA) is an advantage that develops in a company in assessing and surpassing its competitors continuously (Gao et al, 2021). Companies need to build SCA and gain excess advantages by effectively integrating resources and developing resources that meet the needs for future development (Gonyora et al, 2021).…”

Section: Research Papermentioning

confidence: 99%

Sustainable Competitive Advantage: A Literature Review and Future Research

Liwafa,

Suyanto,

Choirunnisa

2023

bmss

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Sustainable competitive advantage (SCA) is very important for companies in analyzing the quality of human resources and the company's environment that continues to change. Besides that, SCA is also able to provide short-term revenue increases and product advantages to customers. This research aims to map the topic of SCA in various scientific fields by visualizing it into a landscape map to see its development and novelty using bibliographic data. Thus, the novelty of research related to strategic management from previous studies can be known with certainty. This research is quantitative research with a descriptive approach. Documentation and literature studies in this study were obtained through the Scopus database with the keyword "sustainable competitive advantage". Bibliometric techniques were used for analysis and processed using Vosviewer software. The results of this study indicate that from 2017-2023, there are 205 articles related to the keywords used, the results of the Vosviewer analysis show 168 keywords that are connected to the keywords used, keywords that are widely used related to the keywords in this study are SCA, Sustainability, Sustainable Development, Innovation, while keywords that are rarely used are SME, Supply Chain, Competitive Strategy, these rarely used keywords can be used as a choice of future research topics.

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Exploring the influence of resource management between green innovation strategy and sustainable competitive advantage: the differences between emerging and traditional industries

Cited by 12 publications

References 0 publications

Study on the Evaluation of Green Technology Innovation Efficiency and Its Influencing Factors in the Central Plains City Cluster of China

Study on the Evaluation of Green Technology Innovation Efficiency and Its Influencing Factors in the Central Plains City Cluster of China

Environmental Performance Evaluation of Key Polluting Industries in China—Taking the Power Industry as an Example

Sustainable Competitive Advantage: A Literature Review and Future Research

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