Examinando por Autor "Zabala Iturriagagoitia, Jon Mikel"

Mostrando 1 - 4 de 4
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    Benchmarking performance through efficiency analysis trees: improvement strategies for colombian higher education institutions
    (Elsevier Ltd, 2024-04) Zofío Prieto, José Luis; Aparicio, Juan; Barbero Jiménez, Javier; Zabala Iturriagagoitia, Jon Mikel
    We introduce benchmarking analysis based on state-of-the-art machine learning techniques applied to the measurement of efficiency to assess the performance of Higher Education Institutions (HEIs). We rely on Efficiency Analysis Trees (EAT) and its Convexified frontier counterpart (CEAT) to assess the efficiency of 144 private HEIs in Colombia and compare the results with those achieved with classical Data Envelopment Analysis (DEA). Both EAT and CEAT show a higher discriminatory power than DEA when determining efficiency scores. Our results identify the different splits of the production frontier, corresponding to each node of the efficiency tree, which groups HEIs according to specific management models. By identifying relevant peers for inefficient observations at the node level, we show which strategic guidelines can be adopted to improve the performance of each HEI. This process encourages mutual learning and suggests potential changes within each node leading to efficiency improvements
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    The influence of bottlenecks on innovation systems performance: put the slowest climber first
    (Elsevier Inc., 2023-08) Zofío Prieto, José Luis ; Aparicio, Juan; Aparicio, Juan; Zabala Iturriagagoitia, Jon Mikel
    This paper contributes to the literature with a methodology that helps identify the functions that constrain the overall performance of an innovation system, hence providing clear guidelines to policymakers on the direction of their interventions. This methodology relies on the notion of penalty for bottleneck, which is defined as the weakest link or the binding constraint that holds back system performance. These penalty bottlenecks are applied to all the indicators that characterize innovation systems, and consider its input-output mix when assessing their performance through a Productivity Innovation Index. The data provided by the 2021 edition of the European Innovation Scoreboard are used to illustrate the utility of the method introduced in the paper. We first identify the input and output bottlenecks for every country. Second, we report the productivity loss due to the existence of these bottlenecks. Third, we evidence the responsiveness of the Productivity Innovation Index to bottleneck alleviation, from three different perspectives: (i) application of a 10 % alleviation to the input bottleneck; (ii) application of a 10 % alleviation to the output bottleneck; and (iii) application of a 5 % alleviation to both the input and output bottlenecks, respectively.
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    Is more always better?: on the relevance of decreasing returns to scale on innovation
    (Elsevier Ltd, 2021-06-08) Barbero Jiménez, Javier; Zabala Iturriagagoitia, Jon Mikel; Zofío Prieto, José Luis
    We contribute to the literature on the assessment of innovation systems by relating the amount of inputs available to the system and its performance through the concept of returns to scale (increasing, constant or decreasing). We study to what extent the size or scale of innovation systems relates to their performance, which is estimated through frontier Data Envelopment Analysis-TOPSIS methods, which overcome several limitations of the standard DEA approach. Using the same data provided by the European Innovation Scoreboard (EIS) for years 2010, 2013 and 2016, our results indicate that countries with a high innovation scale tend to overinvest in innovation inputs. This results into scale inefficiencies stemming from decreasing returns, leading to lower productivity levels. Thanks to DEA-TOPSIS we identify the best and worst performing innovation systems. This provides helpful information by setting suitable reference benchmarks for policy analysis and decision-making. Our results question the current allocation of resources and call for a reconsideration of how innovation policies are designed in many European countries. We conclude that for the EIS to become a useful instrument for the definition of innovation policies, it should consider the nature of returns to scale. This would allow policymakers to identify problems and limitations related to the size of their respective innovation systems, and hence, design holistic innovation policies to act upon them
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    Large techno social systems emergence of social welfare techno systems: summary
    (Sociedad de Estudios Vascos = Eusko Ikaskuntza, 2023) Basabe Desmonts, Lourdes; Zabala Iturriagagoitia, Jon Mikel