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Evaluating efficiency and technology gaps of the national systems of entrepreneurship using stochastic DEA and club convergence

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Abstract

This study aims to develop a framework to analyze the efficiency of the national ecosystems for supporting high-quality early-stage entrepreneurship to gain insights into the rationales and effectiveness of public policies. A model combining a stochastic DEA model and the metafrontier method is used to explore the entrepreneurial ecosystem efficiency across countries that operate under different technologies. Using data from 30 countries over the period 2013–2018, we highlight the efficiency variation of countries according to their level of economic development. Our results suggest that efficiency-driven countries are the technology leaders in entrepreneurship, and innovation-driven countries are the followers. Then a convergence analysis is applied to determine if similar or divergent paths are observed between countries regarding their entrepreneurial efficiency and technology. The results indicate that there is a lack of overall convergence; instead, countries are converging into several clubs with different characteristics. Finally, by combining the convergence clubs of efficiency and technology, we construct a managerial decision-making matrix to provide benchmarks and improvement suggestions.

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References

  • Acs Z (2006) How is entrepreneurship good for economic growth? Innovations 1(1):97–107

    Google Scholar 

  • Acs ZJ, Desai S, Hessels J (2008) Entrepreneurship, economic development and institutions. Small Bus Econ 31(3):219–234

    Google Scholar 

  • Acs Z, Arenius P, Hay M, Minniti M (2005) Global entrepreneurship monitor: 2004 executive report. Babson College and London Business School

  • Acs Z, Szerb L, Autio E, Ainsley L (2017) Global entrepreneurship index 2017. Global Entrepreneurship and Development Institute, London, U.K. and New York, NY

  • Amorós J, Cristi O (2008) Longitudinal analysis of entrepreneurship and competitiveness dynamics in Latin America. Int Entrep Manag J 4(4):381–399

    Google Scholar 

  • Amorós J, Poblete C, Mandakovic V (2019) R&D transfer, policy and innovative ambitious entrepreneurship: evidence from Latin American countries. J Technol Transf 44(5):1396–1415

    Google Scholar 

  • Andersen P, Petersen N (1993) A procedure for ranking efficient units in data envelopment analysis. Manag Sci 39:1261–1264

    Google Scholar 

  • Bai C, Yan H, Yin S, Feng C, Wei Q (2021) Exploring the development trend of internet finance in China: perspective from club convergence. N Am J Econ Finance 58:101505

    Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092

    Google Scholar 

  • Banker RD, Chang H (2006) The super-efficiency procedure for outlier identification, not for ranking efficient units. Eur J Oper Res 175:1311–1320

    Google Scholar 

  • Banker RD, Chang H, Zhiqiang Z (2017) On the use of super-efficiency procedures for ranking efficient units and identifying outliers. Ann Oper Res 250:21–35

    Google Scholar 

  • Barro R (2015) Convergence and modernization. Econ J 125(585):911–942

    Google Scholar 

  • Barro R, Sala-i Martin X (1995) Economic growth. McGraw-Hill, New York

    Google Scholar 

  • Battese G, Rao D (2002) Technology gap, efficiency, and a stochastic metafrontier function. Int J Bus Econ 1(2):87

    Google Scholar 

  • Bosma N (2013) The Global Entrepreneurship Monitor (GEM) and its impact on entrepreneurship research. Found Trends Entrep 9(2):143–248

    Google Scholar 

  • Bruni M, Conforti D, Beraldi P, Tundis E (2009) Probabilistically constrained models for efficiency and dominance in DEA. Int J Prod Econ 117:219–228

    Google Scholar 

  • Calza E, Goedhuys M (2017) Entrepreneurial heterogeneity and the design of entrepreneurship policies for economic growth and inclusive development. In: Williams C, Gurtoo A (eds) Routledge handbook of entrepreneurship in developing economies. Routledge International Handbooks, New York

    Google Scholar 

  • Chang Y, Kim J, Kim Y (2020) Convergence analysis of the entrepreneurship start-up barriers. Int J Manag Enterp Dev 19(1):21–41

    Google Scholar 

  • Charnes A, Cooper WW (1963) Deterministic equivalents for optimizing and satisficing under chance constraints. Oper Res 11:18–39

    Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Manag Sci 27:668–697

    Google Scholar 

  • Chatzistamoulou N, Kounetas K, Tsekouras K (2019) Energy efficiency, productive performance and heterogeneous competitiveness regimes. Does the dichotomy matter? Energy Econ 81:687–697

    Google Scholar 

  • Chen Z, Tzeremes P, Tzeremes N (2018) Convergence in the Chinese airline industry: a Malmquist productivity analysis. J Air Transp Manag 73:77–86

    Google Scholar 

  • Cooper WW, Huang Z, Li SX (2011) Chance-constrained DEA. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis. Springer, Boston, pp 211–240

    Google Scholar 

  • Das GG, Drine I (2020) Distance from the technology frontier: how could Africa catch-up via socio-institutional factors and human capital? Technol Forecast Soc Change 150:119755

    Google Scholar 

  • Dionisio E, Júnior E, Fischer B (2021) Country-level efficiency and the index of dynamic entrepreneurship: contributions from an efficiency approach. Technol Forecast Soc Change 162:120406

    Google Scholar 

  • Dyson R, Shale E (2010) Data envelopment analysis, operational research and uncertainty. J Oper Res Soc 61:25–34

    Google Scholar 

  • Faghih N, Zali M, R. Vafaei N. (2018) Entrepreneurial national efficiency based on GEM data: benchmarks for the MENA countries. In: Faghih N, Zali MR (eds) Entrepreneurship ecosystem in the Middle East and North Africa (MENA). Springer, Cham, pp 95–112

    Google Scholar 

  • Feng Y, Zhang H, Chiu YH, Chang TH (2021) Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model. Scientometrics 126(4):3091–3129

    Google Scholar 

  • Fernández-Serrano J, Berbegal V, Velasco F, Expósito A (2018) Efficient entrepreneurial culture: a cross-country analysis of developed countries. Int Entrep Manag J 14(1):105–127

    Google Scholar 

  • GEM (2018). Global report 2017/18. Global Entrepreneurship Research Association. https://www.gemconsortium.org/report/gem-2017-2018-global-report (accessed 25 November 2021).

  • Ghasemi M, Ignatius J, Rezaee B (2019) Improving discriminating power in data envelopment models based on deviation variables framework. Eur J Oper Res 278:442–447

    Google Scholar 

  • Giotopoulos I, Kontolaimou A, Tsakanikas A (2017) Drivers of high-quality entrepreneurship: what changes did the crisis bring about? Small Bus Econ 48:913–930

    Google Scholar 

  • Gundry L, Welsch H (2001) The ambitious entrepreneur: high growth strategies of women-owned enterprises. J Bus Ventur 16(5):453–470

    Google Scholar 

  • Hermans J, Vanderstraeten J, Van Witteloostuijn A, Dejardin M, Ramdani D, Stam E (2015) Ambitious entrepreneurship: A review of growth aspirations, intentions, and expectations. Entrepreneurial growth: Individual, firm, and region 17:127–160

    Google Scholar 

  • Islam N (2003) What have we learnt from the convergence debate? J Econ Surv 17(3):309–362

    Google Scholar 

  • Izzeldin M, Johnes J, Ongena S, Pappas V, Tsionas M (2021) Efficiency convergence in Islamic and conventional banks. J Int Finan Markets Inst Money 70:101279

    Google Scholar 

  • Kontolaimou A, Giotopoulos L, Tsakanikas A (2016) A typology of European countries based on innovation efficiency and technology gaps: the role of early-stage entrepreneurship. Econ Model 52:477–484

    Google Scholar 

  • Kounetas K, Polemis M, Tzeremes N (2021) Measurement of eco-efficiency and convergence: evidence from a non-parametric frontier analysis. Eur J Oper Res 291(1):365–378

    Google Scholar 

  • Lafuente E, Szerb L, Acs Z (2016) Country level efficiency and national systems of entrepreneurship: a data envelopment analysis approach. J Technol Transfer 41(6):1260–1283

    Google Scholar 

  • Lafuente E, Acs ZJ, Sanders M, Szerb L (2020) The global technology frontier: productivity growth and the relevance of Kirznerian and Schumpeterian entrepreneurship. Small Bus Econ 55(1):153–178

    Google Scholar 

  • Land KC, Lovell CAK, Thore S (1993) Chance-constraint data envelopment analysis. Manag Decis Econ 14:541–554

    Google Scholar 

  • Levie J, Ali A, Amoros E, Hart M, Kelley D, Morris R, Gratzke P (2015) Leveraging entrepreneurial ambition and innovation: a global perspective on entrepreneurship, competitiveness and development. World Economic Forum. Available online: https://www3.weforum.org/docs/WEFUSA_EntrepreneurialInnovation_Report.pdf. Accessed 12 Feb 2023

  • Magrini S, Gerolimetto M, Engin DH (2015) Regional convergence and aggregate business cycle in the United States. Reg Stud 49(2):251–272

    Google Scholar 

  • Minniti M, Bygrave W, Autio E (2006) Global entrepreneurship monitor: 2005 executive report. London Business School, London

    Google Scholar 

  • Mitropoulos P, Mitropoulos A (2022) Productivity growth and technology gaps of the national systems of entrepreneurship: Is there a convergence pattern between efficiency-driven and innovation-driven countries? Int J Innov Technol Manag 19(5):2241005

    Google Scholar 

  • Mitropoulos P, Talias MA, Mitropoulos I (2015) Combining stochastic DEA with Bayesian analysis to obtain statistical properties of the efficiency scores: an application to Greek public hospitals. Eur J Oper Res 243:302–311

    Google Scholar 

  • Mitropoulos P, Zervopoulos P, Mitropoulos I (2020) Measuring performance in the presence of noisy data with targeted desirable levels: evidence from healthcare units. Ann Oper Res 294:537–566

    Google Scholar 

  • O’Donnell C, Rao D, Battese G (2008) Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empir Econ 34(2):231–255

    Google Scholar 

  • Odeck J (2000) Assessing the relative efficiency and productivity growth of vehicle inspection services: an application of DEA and Malmquist indices. Eur J Oper Res 126(3):501–514

    Google Scholar 

  • OECD (2017). Entrepreneurship at a glance. OECD Publishing https://www.oecd.org/sdd/business-stats/entrepreneurship-at-a-glance-22266941.htm (accessed 25 November 2021)

  • Oh D, Lee J (2010) A metafrontier approach for measuring Malmquist productivity index. Empir Econ 32:46–64

    Google Scholar 

  • Olesen OB, Petersen NC (2016) Stochastic data envelopment analysis—a review. Eur J Oper Res 251(1):2–21

    Google Scholar 

  • Phillips P, Sul D (2007) Transition modeling and econometric convergence tests. Econometrica 75(6):1771–1855

    Google Scholar 

  • Phillips P, Sul D (2009) Economic transition and growth. J Appl Econom 24(7):1153–1185

    Google Scholar 

  • Porter M, Sachs J, McArthur J (2002) Executive summary: competitiveness and stages of economic development. In: Porter M, Sachs J, Cornelius P, McArthur J, Schwab K (eds) The global competitiveness report 2001–2002. Oxford University Press, New York

    Google Scholar 

  • Reynolds P, Camp M, Bygrave W, Autio E, Hay M (2001) Global entrepreneurship monitor, 2001 summary report. London Business School and Babson College, London

    Google Scholar 

  • Romer PM (1994) The origins of endogenous growth. J Econ Perspect 8(1):3–22

    Google Scholar 

  • Shane S (2009) Why encouraging more people to become entrepreneurs is bad public policy? Small Bus Econ 33(2):141–149

    Google Scholar 

  • Sitaridis I, Kitsios F (2020) Competitiveness analysis and evaluation of entrepreneurial ecosystems: a multi-criteria approach. Ann Oper Res 224:397–399

    Google Scholar 

  • Spigel B (2017) The relational organization of entrepreneurial ecosystems. Entrep Theory Pract 41(1):49–72

    Google Scholar 

  • Stam E, Bosma N, Van Witteloostuijn A, De Jong J, Bogaert S, Edwards N, Jaspers F (2012) Ambitious entrepreneurship. A review of the academic literature and new directions for public policy. Advisory Council for Science and Technology Policy (AWT), The Hague

  • Stenholm P, Acs ZJ, Wuebker R (2013) Exploring country-level institutional arrangements on the rate and type of entrepreneurial activity. J Bus Ventur 28(1):176–193

    Google Scholar 

  • Sun LX, Xia YS, Feng C (2021) Income gap and global carbon productivity inequality: a meta-frontier data envelopment analysis. Sustain Prod Consum 26:548–557

    Google Scholar 

  • Talluri S, Narasimhan R, Nair A (2006) Vendor performance with supply risk: a chance-constrained DEA approach. Int J Prod Econ 100(2):212–222

    Google Scholar 

  • Tasnim N, Afzal M (2018) An empirical investigation of country level efficiency and national systems of entrepreneurship using Data Envelopment Analysis (DEA) and the Tobit model. J Glob Entrep Res 8:37

    Google Scholar 

  • Van Vuuren J, Alemayehu B (2018) The role of entrepreneurship in transforming efficiency economies into innovation-based economies. S Afr J Entrep Small Bus Manag 10(1):1–12

    Google Scholar 

  • Von Lyncker K, Thoennessen R (2017) Regional club convergence in the EU: evidence from a panel data analysis. Empir Econ 52(2):525–553

    Google Scholar 

  • Walheer B (2023) Meta-frontier and technology switchers: a nonparametric approach. Eur J Oper Res 305(1):463–474

    Google Scholar 

  • Wang M, Feng C (2021) Revealing the pattern and evolution of global green development between different income groups: a global meta-frontier by-production technology approach. Environ Impact Assess Rev 89:106600

    Google Scholar 

  • Wang SX, Lu WM, Hung SW (2020) Industrial upgrading efficiency and free markets in emerging economies: a two-stage meta-frontier approach. Manag Decis Econ 41(6):1084–1095

    Google Scholar 

  • Wennekers S, Stel A, Thurik R, Reynold P (2005) Nascent entrepreneurship and the level of economic development. Small Bus Econ 24(3):293–309

    Google Scholar 

  • Wong P, Ho Y, Autio E (2005) Entrepreneurship, innovation and economic growth: evidence from GEM data. Small Bus Econ 24(3):335–350

    Google Scholar 

  • Wu W, Lan L, Lee Y (2013) Benchmarking hotel industry in a multi-period context with DEA approaches: a case study. Benchmarking Int J 20(2):152–168

    Google Scholar 

Download references

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Mitropoulos, P., Mitropoulos, A. Evaluating efficiency and technology gaps of the national systems of entrepreneurship using stochastic DEA and club convergence. Oper Res Int J 23, 1 (2023). https://doi.org/10.1007/s12351-023-00746-0

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