Factors Affecting the Efficiency of the BRICSs' National Innovation Systems: A Comparative Study Based on Dea and Panel Data Analysis

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. (2) In accordance with the NIS approach and the new growth theory, there are many factors that affect the NISs including ICT infrastructure, enterprise R&D, market environment, governance, education systems, economic scale, natural endowments, and external dependence. (3) Enterprise innovation is of particular importance for the NISs. To improve the efficiency of innovation systems, efforts should be made to improve the market conditions, governance, and financial structures, and create a sound environment for R&D. (4) ICT infrastructure, economic scale, and openness affect the diffusion of knowledge and technology, and in turn affect NIS efficiency. (5) The BRICS have low governance levels and a high dependency on natural resources, both of which are determined by their stage of development and extensive growth patterns. To avoid the socalled middle-income trap, the BRICS should transform their factor-driven growth patterns into innovation-driven growth patterns. China still needs to improve its ICT infrastructure, its governance systems, and its education system. During its 12th five-year plan, more effort should be devoted to these fields and to improving external conditions for R&D. Terms of use: Documents inJEL O30, O57, P52

A multilevel and multistage efficiency evaluation of innovation systems: A multiobjective DEA approach

“…For example, Austria's and Denmark's low efficiency may be also found in the work of Cai (2011) , who studied the innovation efficiency of 22 countries, including BRICS and G7. Additionally, this study showed that Norway, Belgium, Italy, and France have a relatively moderate efficiency score.…”

“…Some of these studies applied a second level econometric analysis to examine the effect of environmental factors to efficiency scores ( Afzal (2014), Cai (2011), Guan (2010), Cullmann, Schmidt-Ehmcke, andZloczysti (2011), Guan and Chen (2012), Nasierowski and Arcelus (2003) ). Tobit has been mostly used while more recently Matei and Aldea (2012) and Afzal (2014) employed bootstrap for getting bias corrected estimations.…”

“…For instance, Carayannis and Provance (2008) propose a composite indicator approach for the study of innovation at the micro level pivoting around the 3Ps (Posture, Propensity, and Performance). Also, Cai (2011) refers to three major quantitative approaches in studying national (or regional) innovation systems at the macro level: composite indicators, econometric analysis, and data envelopment analysis. The composite indicators approach focuses mainly on aggregating -using different schemesa set of innovation indicators, which should cover various aspects of the examined innovation systems (e.g., indicators that reflect the different stages of innovation process, organization pattern of http://dx.doi.org /10.1016/j.eswa.2016.06.017 0957-4174/© 2016 Elsevier Ltd. All rights reserved.…”

“…DEA is the most widely used approach for measuring the relative efficiency of a number of Decision Making Units (DMUs) that transforms multiple inputs to multiple outputs in a similar context. Thus, DEA models focus exactly on input-output efficiency of innovation systems, where each country or region is considered as an independent DMU ( Cai, 2011 ).…”

Modeling National Innovation Systems of Eu Countries Using Partial Least Squares Structural Equation Modeling (Pls-Sem)

“…Several studies indicated a significant relationship between innovation outcomes and R&D activities and investment in organizations (Kou et al, 2016;Liu et al, 2015;Wiseman, Anderson 2012;Cai, 2011). According to Morris-King (2014) highly active industrial partners.…”