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A note on the configuration of the digital ecosystem in Latin America

Author

Listed:
  • Acs, Zoltan

    (George Mason University)

  • Lafuente, Esteban

    (UPC Barcelona Tech)

  • Szerb, László

    (University of Pécs)

Abstract

We evaluate the main characteristics of the digital ecosystem of North American (USA and Canada) and 16 Latin American economies for 2019. By employing the ‘benefit of the doubt’ model rooted in non-parametric techniques to scrutinize a composite indicator designed to assess the digital ecosystem (i.e., the Digital Platform Economy (DPE) index), the analysis allows the computation of endogenous (country-specific) weights that can be used for developing more informed policy making. The results show that countries prioritize different aspects of their digital ecosystem which confirms that, contrary to homogeneous prescription, tailor-made policy is a more desirable approach if the objective is to optimize the resources deployed to enhance the countries’ digital ecosystem.

Suggested Citation

  • Acs, Zoltan & Lafuente, Esteban & Szerb, László, 2022. "A note on the configuration of the digital ecosystem in Latin America," TEC Empresarial, School of Business, Costa Rica Institute of Technology (ITCR), vol. 16(1), pages 1-19.
  • Handle: RePEc:ris:tecemp:2201
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    References listed on IDEAS

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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Avi Goldfarb & Catherine Tucker, 2019. "Digital Economics," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 3-43, March.
    3. Lovell, C. A. Knox & Pastor, Jesus T., 1999. "Radial DEA models without inputs or without outputs," European Journal of Operational Research, Elsevier, vol. 118(1), pages 46-51, October.
    4. Zoltán J. Ács & Erkko Autio & László Szerb, 2015. "National Systems of Entrepreneurship: Measurement issues and policy implications," Chapters, in: Global Entrepreneurship, Institutions and Incentives, chapter 28, pages 523-541, Edward Elgar Publishing.
    5. Karagiannis, Roxani & Karagiannis, Giannis, 2018. "Intra- and inter-group composite indicators using the BoD model," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 44-51.
    6. L Cherchye & W Moesen & N Rogge & T Van Puyenbroeck & M Saisana & A Saltelli & R Liska & S Tarantola, 2008. "Creating composite indicators with DEA and robustness analysis: the case of the Technology Achievement Index," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(2), pages 239-251, February.
    7. Araya, Manuel, 2019. "Efficiency assessment of Costa Rica’s counties: A non-parametric analysis of the county competitiveness index," TEC Empresarial, School of Business, Costa Rica Institute of Technology (ITCR), vol. 13(3), pages 78-92.
    8. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    9. Katz, Raul & Callorda, Fernando, 2018. "Accelerating the development of Latin American digital ecosystem and implications for broadband policy," Telecommunications Policy, Elsevier, vol. 42(9), pages 661-681.
    10. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    11. Karagiannis, Giannis & Knox Lovell, C.A., 2016. "Productivity measurement in radial DEA models with a single constant input," European Journal of Operational Research, Elsevier, vol. 251(1), pages 323-328.
    12. D K Despotis, 2005. "A reassessment of the human development index via data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 969-980, August.
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    Cited by:

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    4. Fanjul, Ana P. & Herrera, Liliana & Munoz-Doyague, Maria F., 2023. "Fostering rural entrepreneurship: An ex-post analysis for Spanish municipalities," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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