Modelling Efficiency in Regional Innovation Systems: A Two-Stage Data Envelopment Analysis Problem with Shared Outputs within Groups of Decision-Making Units

Avilés-Sacoto, Sonia Valeria; Cook, Wade D.; Güemes‐Castorena, David; Zhu, Joe

doi:10.1016/j.ejor.2020.04.052

Cited by 27 publications

(12 citation statements)

References 38 publications

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“…[6] Single indicator measures are based on the results of green technology innovation and use a single indicator of green technology patents to measure changes in the efficiency of green technology innovation [7]. SV Avilés-Sacoto et al propose to use DEA to assess the efficiency of green innovation of enterprises and to analyze the relative efficiency of enterprises through inter-firm comparison [8]. Jiyoung et al analyzed the innovation efficiency of firms in the Korean region and used DEA to assess and compare the global Malmquist productivity of firms and concluded that the innovation efficiency generated by DEA can lead to appropriate cooperation strategies between firms, which is important for the development of innovation in the market Significance [9].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Jie [2] Building total factor productivity index of energy and carbon emissions No in-depth analysis of green innovation under environmental regulation Zhou [3] e relationship between environmental regulation and innovative development in the Yangtze River Delta Daming You [4] e impact of China's financial system on environmental regulation SV Avilés-Sacoto [8] DEA evaluation of enterprise green innovation efficiency e influencing factors of green innovation efficiency have not been analyzed Jiyoung [9] Analyze the impact of enterprise innovation on the market Tziogkidis [10] Discuss the efficiency of green technology innovation in different countries…”

Section: Literaturementioning

confidence: 99%

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[Retracted] Environmental Regulation, Financial Resource Allocation, and Regional Green Technology Innovation Efficiency

Bao

Chai

2022

Discrete Dynamics in Nature and Society

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This paper empirically studies the environmental regulation, financial resource allocation, and regional green technology innovation efficiency by using provincial panel data from 2005 to 2019. The results show that the cost-input environmental regulation is negatively correlated with the efficiency of regional green technology innovation, while the government-subsidized environmental regulation is positively correlated with the efficiency of regional green technology innovation. The mechanism test shows that the cost-input environmental regulation reduces the efficiency of green technology innovation by restraining the allocation of financial resources, while the government-subsidized environmental regulation lifts the efficiency of green technology innovation by improving the allocation of financial resources. As far as different regions are concerned, the cost-input environmental regulation has a significant inhibitory effect on the eastern and central regions, while the government-subsidized environmental regulation has a significant improvement effect on the central and western regions.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literaturementioning

confidence: 99%

[Retracted] Environmental Regulation, Financial Resource Allocation, and Regional Green Technology Innovation Efficiency

Bao

Chai

2022

Discrete Dynamics in Nature and Society

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“…DEA methods are widely used (mainly by foreign researchers) to analyse enterprises in various industries: banking, transport, health, education, ICT, space, oil, agriculture, and other sectors. Moreover, using the DEA methods it is possible to assess the effectiveness of public administration, national and regional innovation systems [see for example [14][15][16].…”

Section: Data Envelopment Analysis (Dea)mentioning

confidence: 99%

Regional innovation systems efficiency analyses and evaluation: DEA approach implementation

Dzyubenko

2021

E3S Web Conf.

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The innovative transformation is a necessary condition for sustainable economic development. The study reveals an assessment and comparative analysis of the Regional Innovation Systems’ (RIS) performance in the Russian Federation using Data Envelopment Analysis (DEA). The DEA model under the Variable Return to Scale (VRS) assumption, focused on output parameters, is used to estimate the relative technical efficiency of regions based on several input and output parameters. Based on the obtained results, a rating of regions was compiled: four groups of regions were identified depending on their technical efficiency level. It was revealed that the leading regions by innovative development level are assessed by the DEA somewhat differently. A comparative analysis of the innovation systems performance at the regional and federal levels allowed us to identify the most and least effective subjects of the Russian Federation, federal districts and economic regions. The main conclusion is that less than a third of the Russian regions use their production capabilities as efficient as possible, the remaining regions can significantly improve the way they use the available resources. The results of the study might be used in making managerial decisions at the country, federal districts and regions levels in order to develop measures and mechanisms for improving the efficiency of regional innovation systems.

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“…No specific method has been universally accepted as the best for analyzing and assessing RISs. Different authors have used a broad range of approaches to study RISs; among these approaches are participatory evaluation, network analysis, cluster analysis, data envelopment analysis, qualitative content analysis, case studies, regression models and comparative studies (Stejskal et al , 2018; Avilés-Sacoto et al , 2020; Rodríguez-Soler and Brunet Icart, 2018; Fernández-Serrano et al , 2019; Kofler et al , 2018; Berman et al , 2020; Gasparin and Quinn, 2020; Teng and Chen, 2019; Hajek et al , 2019). Wang et al conducted a thorough review of the literature on RISs and based on their findings, identified four approaches that have been developed to analyze RISs: the structural approach, the functional approach, the effectiveness approach and the triple helix approach.…”

Section: Literature Reviewmentioning

confidence: 99%

Comprehensive evaluation of Iranian regional innovation system (RIS) performance using analytic hierarchy process (AHP)

Sadabadi

Rad

Fartash

2021

JSTPM

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Purpose This study aims to to provide a model based on the context and conditions of the regions in Iran for monitoring regional innovation systems (RISs). Design/methodology/approach In the first stage, after reviewing the literature, interviewing the experts, and then thematic analyzing the content of the obtained data, initial Dimensions and indicators were identified. Then, a fuzzy Delphi technique and a seven-scale questionnaire were used to test the results and expert opinion. Finally, after the extraction and correction of the indicators to evaluate the RISs, a comprehensive model was identified in 5 dimensions, 16 indicators and 176 sub-indicators. In the next step, the importance weights of the main 16 indicators were determined using the analytic hierarchy process method. Findings The proposed RIS assessment model consists of firms’ behavior and regional interactions, economy, human capital, innovative outputs, locational features, that each dimension has its own indicators and sub-indicators, each one is discussed in the paper. Originality/value The research contribution is that the proposed RIS model of this research is the first model that is appropriate to the context of Iran.

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Modelling Efficiency in Regional Innovation Systems: A Two-Stage Data Envelopment Analysis Problem with Shared Outputs within Groups of Decision-Making Units

Cited by 27 publications

References 38 publications

[Retracted] Environmental Regulation, Financial Resource Allocation, and Regional Green Technology Innovation Efficiency

[Retracted] Environmental Regulation, Financial Resource Allocation, and Regional Green Technology Innovation Efficiency

Regional innovation systems efficiency analyses and evaluation: DEA approach implementation

Comprehensive evaluation of Iranian regional innovation system (RIS) performance using analytic hierarchy process (AHP)

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