National innovation efficiency: a DEA-based measurement of OECD countries

Erdin, Ceren; Çağlar, Mehmet

doi:10.1108/ijis-07-2021-0118

Cited by 15 publications

(4 citation statements)

References 106 publications

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“…Scientists distinguish various classical approaches, within the framework of which innovation is analyzed. One of them embraces changes, resources, processes, result (Schumpeter, 1939;Schlesinger Jr., 1986;Twiss, 1989;Chekulina & Tamakhina, 2011;Freeman, 1995Freeman, , 2017Zhits, 2007;Danko, 1999;Porter & Stern 2002;Hudakova, Fila & Marosh, 2018;Zhizhlavsky, 2011;Zholnierski, 2005;Alekseyev, 2009;Pichlak, 2012;Chehabeddine, Grabowska & Adekola, 2022;Atwa, 2022;Davies, Gann & Douglas, 2009;Waldron & Wetherbe, 2020;Prud'homme van Reine, 2022;Sinclair-Desgagne, 2022;Acemoglu, Akcigit & Celik, 2022;Agarwal et al, 2022;Andriushchenko et al, 2022;Birkner, Meszaros & Szabo 2022;Bora, Brazda & Slíva 2021;Bychin, 2022;Cantarelli & Genovese, 2021;Carlström, 2022;Erdin & Caglar, 2022;Farrow, 2021;Franco et al, 2022;Gijon, Lozano & Molina, 2022;Giuliano et al, 2022;Heilala, 2022;Jaiswal et al, 2022;Krivosheya, 2022;Kulakov, Verstina & Meshcheryakova, 2022;Langham & Paulsen, 2020;Liu & Shao, 2022;…”

Section: Theoretical and Methodological Framework Of Innovation Poten...mentioning

confidence: 99%

Assessment of the innovation potential of the regions of Latvia, Lithuania and Belarus

Gladevich¹

2022

JESI

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The concept of innovation potential is complicated and complex, its evolution is closely related to the concept of innovation. There are several approaches to define the innovation potential. Some scientists and researchers define innovation potential as a set of several resources, other scientists -as a result of innovative activity. The author is a supporter of the resource approach and explores the potential of innovation from the perspective of resources. There are several approaches to determining the innovation potential from the resource perspective, however, they are mostly intended for the evaluation of the innovation potential at the national level or at the level of large regions. In addition, most of the assessment methodologies are tailored to the analysis of specific regions and it is difficult to adapt them to the evaluation of other regions. Therefore, the author develops his own methodology for assessing innovation potential, adapted for NUTS3 regions, and uses it to assess the innovation potential of Latvian, Lithuanian and Belarusian regions. The given approach makes it possible to promptly evaluate existing resources and define opportunities, thus providing the region with a stable market position, especially within the regional context, which is required by the ever-increasing and fierce competition.

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Section: Theoretical and Methodological Framework Of Innovation Poten...mentioning

confidence: 99%

Assessment of the innovation potential of the regions of Latvia, Lithuania and Belarus

Gladevich¹

2022

JESI

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“…The author does not analyze most of GII (Global Competitiveness Index) indicators, which is since many of these indicators are not collected in official statistics in the regions of the given research, some of them are not available at all or are only available at the national level or are available in several regions. Thus, the author uses selected (Schumpeter, 1939;Schlesinger Jr., 1986;Freeman, 1995;Farrow, 2021;Carlström, 2022;Erdin & Caglar, 2022;Franco et al, 2022.;Jaiswal et al, 2022;Liu & Shao, 2022) and available indicators, which will be used for evaluation of innovation potential of the regions of selected countries.…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Assessment of the innovation potential of the selected regions

Gladevich¹

2023

JESI

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Assessment of innovation potential is becoming an increasingly urgent problem. Many scientists and researchers are interested in this issue, alas, evaluate innovation potential differently. Some scholars emphasize resources, while others think about the achieved result. Another group of researchers focus on the transition process from resources to results while evaluating innovation potential. This paper attempts to integrate the three basic approaches (resource, process and resulting) and suggest a combination of known innovation potential assessment methods. The author claims that the innovation development goal is the result (abilities) and initial resources (opportunities) and stresses a process of transformation into an innovative product. The author offers an original definition of the innovation potential of a region. Complex evaluation with the sum method leads to an original integral indicator. Selected geographical areas are grouped into quintiles; the obtained results are depicted on maps for more convenient perception and visualization. The obtained results are interpreted, and policy implications are suggested.

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“…The NDEA model has been used to quantify the efficiency of R&D projects in sectors and companies in various periods and in various phases (Zhou et al, 2019;Mete and Belgin, 2022). Innovation is a complex process whose evaluation requires some treatment and flexibility (Tidd and Bessant, 2020;Erdin and Ça glar, 2023). The NDEA model offers this flexibility from an efficiency point of view, since it allows combining multiple aspects and facets of innovation, thus allowing it to be quantified in multiple periods.…”

Section: Introductionmentioning

confidence: 99%

Knowledge production and commercialization from R&D: the pharmaceutical sector

Valderrama

Sánchez-Ortiz

Mulero-Mendigorri

2023

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PurposeThe objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.Design/methodology/approachA Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.FindingsThe results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.Originality/valueThe authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

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National innovation efficiency: a DEA-based measurement of OECD countries

Cited by 15 publications

References 106 publications

Assessment of the innovation potential of the regions of Latvia, Lithuania and Belarus

Assessment of the innovation potential of the regions of Latvia, Lithuania and Belarus

Assessment of the innovation potential of the selected regions

Knowledge production and commercialization from R&D: the pharmaceutical sector

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