Do Innovation Metrics Reflect Sustainable Policy Making in Europe? A Comparative Study Case on the Carpathian and Alpine Mountain Regions
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作者:
Coca, Andrei
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George Emil Palade Univ Med Pharm Sci & Technol Ta, Doctoral Sch IOSUD, Targu Mures 540142, RomaniaGeorge Emil Palade Univ Med Pharm Sci & Technol Ta, Doctoral Sch IOSUD, Targu Mures 540142, Romania
Coca, Andrei
[1
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Gabor, Manuela Rozalia
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George Emil Palade Univ Med Pharm Sci & Technol Ta, Fac Econ & Law, Dept ED1 Econ Sci, Targu Mures 540142, RomaniaGeorge Emil Palade Univ Med Pharm Sci & Technol Ta, Doctoral Sch IOSUD, Targu Mures 540142, Romania
Gabor, Manuela Rozalia
[2
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Susanu, Irina Olimpia
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Dunarea Jos Univ Galati, Fac Econ & Business Adm, Dept Business Adm, Galati 800008, RomaniaGeorge Emil Palade Univ Med Pharm Sci & Technol Ta, Doctoral Sch IOSUD, Targu Mures 540142, Romania
Susanu, Irina Olimpia
[3
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机构:
[1] George Emil Palade Univ Med Pharm Sci & Technol Ta, Doctoral Sch IOSUD, Targu Mures 540142, Romania
[2] George Emil Palade Univ Med Pharm Sci & Technol Ta, Fac Econ & Law, Dept ED1 Econ Sci, Targu Mures 540142, Romania
[3] Dunarea Jos Univ Galati, Fac Econ & Business Adm, Dept Business Adm, Galati 800008, Romania
This paper questions the evaluation of innovation systems and innovation measurements and the effectiveness of innovation policies applied at the territorial level by assessing whether the existing European regional scoreboard is effective in providing accurate inputs for decision-makers in mountainous regions. The aim of the research is to provide, through comparative analysis by using statistical multi-methods of two mountainous macro-regions (the Alps and the Carpathians), a possible and available path to develop novel perspectives and alternative views on innovation systems' performance for informed and territorial-based policy making by using the indicators of the Regional Innovation Scoreboard. The methodology used includes descriptive statistics, chi-square bivariate test, Student's t test, one-way ANOVA with Bonferroni post hoc multiple comparisons, multilinear regression analysis, and decision tree with CRT (classification and regression trees) algorithm. Our results emphasize the similarities and differences between the Alpine and Carpathian mountain regions, find the best predictors for each mountain region, and provide a scientific basis for the development of a holistic approach linking measurement theory, innovation systems, innovation policies, and their territorial approach toward sustainable development of mountain areas. The paper's contribution is relevant in the context of remote, rural, and mountain areas, which are usually left behind in terms of innovation chances and in the context of the COVID-19 aftermath with budget constraints. The present results are pertinent for designing effective smart specialization strategies in these regions due to the difficulties that most remote areas and less developed regions are facing in developing innovation policies.