IDEAS home Printed from https://ideas.repec.org/a/ris/tecemp/2201.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://revistas.tec.ac.cr/index.php/tec_empresarial/article/view/5926
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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, April.
    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. 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.
    7. 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.
    8. 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.
    9. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    10. 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.
    11. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lafuente, Esteban & Vaillant, Yancy & Rabetino, Rodrigo, 2023. "Digital disruption of optimal co-innovation configurations," Technovation, Elsevier, vol. 125(C).
    2. Rojas-Segura, Javier & Faith-Vargas, Margie & Martinez-Villavicencio, Jose, 2023. "Conceptualizing digital transformation using semantic decomposition," TEC Empresarial, School of Business, Costa Rica Institute of Technology (ITCR), vol. 17(3), pages 63-75.
    3. Vaillant, Yancy & Lafuente, Esteban & Vendrell-Herrero, Ferran, 2023. "Assessment of industrial pre-determinants for territories with active product-service innovation ecosystems," Technovation, Elsevier, vol. 119(C).
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lafuente, Esteban & Araya, Manuel & Leiva, Juan Carlos, 2022. "Assessment of local competitiveness: A composite indicator analysis of Costa Rican counties using the ‘Benefit of the Doubt’ model," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Lafuente, Esteban & Ács, Zoltán J. & Szerb, László, 2022. "A composite indicator analysis for optimizing entrepreneurial ecosystems," Research Policy, Elsevier, vol. 51(9).
    3. Lafuente, Esteban & Vaillant, Yancy & Rabetino, Rodrigo, 2023. "Digital disruption of optimal co-innovation configurations," Technovation, Elsevier, vol. 125(C).
    4. D'Inverno, Giovanna & Carosi, Laura & Ravagli, Letizia, 2018. "Global public spending efficiency in Tuscan municipalities," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 102-113.
    5. Nguyen, Trang Thi Thuy & Pham, Binh Thai & Prior, Diego & van Hemmen, Stefan, 2022. "Performance of tax simplification around the world: A panel frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    6. Yiming Zhuang & Meltem Denizel & Frank Montabon, 2023. "Examining Firms’ Sustainability Frontier: Efficiency in Reaching the Triple Bottom Line," Sustainability, MDPI, vol. 15(11), pages 1-22, May.
    7. 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.
    8. Dyckhoff, Harald & Souren, Rainer, 2022. "Integrating multiple criteria decision analysis and production theory for performance evaluation: Framework and review," European Journal of Operational Research, Elsevier, vol. 297(3), pages 795-816.
    9. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    10. Barbero, Javier & Zabala-Iturriagagoitia, Jon Mikel & Zofío, José L., 2021. "Is more always better? On the relevance of decreasing returns to scale on innovation," Technovation, Elsevier, vol. 107(C).
    11. Tüselmann, Heinz & Sinkovics, Rudolf R. & Pishchulov, Grigory, 2016. "Revisiting the standing of international business journals in the competitive landscape," Journal of World Business, Elsevier, vol. 51(4), pages 487-498.
    12. Ruiz, José L. & Segura, José V. & Sirvent, Inmaculada, 2015. "Benchmarking and target setting with expert preferences: An application to the evaluation of educational performance of Spanish universities," European Journal of Operational Research, Elsevier, vol. 242(2), pages 594-605.
    13. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2016. "Potential gains from carbon emissions trading in China: A DEA based estimation on abatement cost savings," Omega, Elsevier, vol. 63(C), pages 48-59.
    14. Sarmento, Joaquim Miranda & Renneboog, Luc & Verga-Matos, Pedro, 2017. "Measuring highway efficiency : A DEA approach and the Malquist index," Other publications TiSEM 23264815-321e-45a3-83ee-9, Tilburg University, School of Economics and Management.
    15. Kottas, Angelos T. & Madas, Michael A., 2018. "Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 1-17.
    16. Raith, Andrea & Ehrgott, Matthias & Fauzi, Fariza & Lin, Kuan-Min & Macann, Andrew & Rouse, Paul & Simpson, John, 2022. "Integrating Data Envelopment Analysis into radiotherapy treatment planning for head and neck cancer patients," European Journal of Operational Research, Elsevier, vol. 296(1), pages 289-303.
    17. Halkos, George & Petrou, Kleoniki Natalia, 2018. "Assessment of national waste generation in EU Member States’ efficiency," MPRA Paper 84590, University Library of Munich, Germany.
    18. Tüselmann, Heinz & Sinkovics, Rudolf R. & Pishchulov, Grigory, 2015. "Towards a consolidation of worldwide journal rankings – A classification using random forests and aggregate rating via data envelopment analysis," Omega, Elsevier, vol. 51(C), pages 11-23.
    19. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    20. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:tecemp:2201. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Esteban Lafuente (email available below). General contact details of provider: https://edirc.repec.org/data/eaitccr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.