Modeling of Regional Innovation Spillover Effects Based on DEA Malmquist Index

Firsova, Аnna; Chernyshova, Galina

doi:10.2991/ahcs.k.191206.019

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…The conclusion, which was based on the results of the analysis, included the detection of reasons for the efficiency gap by region. For example, one of the reasons for weak innovation activity in the region may be low demand for innovative products and an underdeveloped information infrastructure, which makes information on innovative products inaccessible to consumers [84,85].…”

Section: Methodsmentioning

confidence: 99%

Regional Open Innovation Systems in a Transition Economy: A Two-Stage DEA Model to Estimate Effectiveness

Rudskaya

Kryzhko

Skhvediani

et al. 2022

Journal of Open Innovation: Technology, Market, and Complexity

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The development of innovation at a regional level in a transition economy is characterised by complex multidirectional processes of generating and commercialising innovation, indicating the need for systematic research and rethinking of the existing methods of managing such territorial entities to stimulate innovation. For the successful introduction and implementation of innovative solutions, the deployment of appropriate amounts of intellectual, material and financial resources as well as their concentration in space and time is important. This article aims to develop a model for assessing the effectiveness of regional innovation systems (RISs) during the shift from the transition economy to the market economy. The authors developed a two-stage data envelopment analysis (DEA) model connected with patent activities and the output of innovative goods and services. The model’s application made it possible to build maps describing the rating of regions concerning the performance indicator and to identify the availability of unutilised resources. For example, we identified efficient and inefficient regions in terms of producing innovative products, which is especially important for developing additional measures for developing the institutional environment of regions with considerable resources but very low utilisation efficiency. The data obtained will allow for more effective management of the structural elements of RISs as well as the detection of changes in the dynamics of key development indicators by identifying the size of efficiency reserves and the causes of their occurrence at the individual subject level.

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Section: Methodsmentioning

confidence: 99%

Regional Open Innovation Systems in a Transition Economy: A Two-Stage DEA Model to Estimate Effectiveness

Rudskaya

Kryzhko

Skhvediani

et al. 2022

Journal of Open Innovation: Technology, Market, and Complexity

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“…In this regard, in economic science and practice, a tendency has emerged to consider universities and system of higher education as full-fledged economic agents involved in economic and innovative national and regional development [5][6][7][8]. The significant role of the regional higher education system, affecting the innovative development of the regional socio-economic system, leads to the need of diagnosing the state of congruence and the relationship of these systems and searching for the most effective management tools.…”

Section: Introductionmentioning

confidence: 99%

Institutional Management Elaboration through Cognitive Modeling of the Balanced Sustainable Development of Regional Innovation Systems

Firsova

Makarova

Tugusheva

2020

Journal of Open Innovation: Technology, Market, and Complexity

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The main aim of this research was to search for relevant indicators and effective instruments for modeling the impact and institutional management of the regional innovation system for its balanced development. The objective of the study was to justify approaches for institutional management elaboration for balanced sustainable development of regional innovation systems regarding related factors and the needs of the region. The methodology of cognitive modeling and scenario impulse modeling are used for the analysis of the interconnection between the regional innovation system and higher education institutions and developing an instrument to diagnose the problems of no-congruence and improving the institutional management elaboration in the regional innovation policy. The analysis of system indicators of the cognitive map allowed to define the basic patterns in the regional system, determine the most significant factors and relationships for the economic system of the region and visualize them in the form of a cognitive map, identify the influence of the innovation environment elements on the target indicators, quantify its positive and negative impact, forecast and determine the directions of its improvement and enhancing the interaction of regional actors. The results of the study have practical value for use in improving institutional management in planning reforms and transformations of regional innovation systems.

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Efficiency Analysis of Regional Innovation Development Based on DEA Malmquist Index

Firsova

Chernyshova

2020

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The aim of the work was to evaluate the dynamics of regional innovation development and compare the Russian regions according to their innovation efficiency, used resources, and achieved results. To estimate direct and indirect innovation effects, this study used the data on Russian regions according to variables of the innovative product volume, the share of high-tech products in the gross regional product (GRP) structure, the number of used patents, and investment in innovation activity for 2006–2017. To obtain a representative sample, a cluster analysis was applied as a preliminary step, which made it possible to select a group of regions that were most advanced in terms of their innovative development. Output-oriented data envelopment analysis models were applied for Malmquist Productivity Index calculation. The obtained results indicate the average growth of total factor productivity of regional innovation development over time. The main source of innovative development is largely derived from the economy of scale, while the effectiveness of regional innovation systems is basically increasing through broader resource bases, rather than through its effective utilization. The research findings can be applied to diagnose regional innovation effectiveness, justify public investment in research and development (R & D), and identify the priorities of regional innovation policy for specific regions.

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Modeling of Regional Innovation Spillover Effects Based on DEA Malmquist Index

Cited by 4 publications

References 10 publications

Regional Open Innovation Systems in a Transition Economy: A Two-Stage DEA Model to Estimate Effectiveness

Regional Open Innovation Systems in a Transition Economy: A Two-Stage DEA Model to Estimate Effectiveness

Institutional Management Elaboration through Cognitive Modeling of the Balanced Sustainable Development of Regional Innovation Systems

Efficiency Analysis of Regional Innovation Development Based on DEA Malmquist Index

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