The influence of bottlenecks on innovation systems performance: Put the slowest climber first

Jose Luis Zofio; Juan Aparicio; Javier Barbero; Jon Mikel Zabala-Iturriagagoitia

doi:10.1016/j.techfore.2023.122607

The influence of bottlenecks on innovation systems performance: Put the slowest climber first

Jose Luis Zofio
, Juan Aparicio
, Javier Barbero
, Jon Mikel Zabala-Iturriagagoitia^*

^*Corresponding author for this work

Department of Technology and Operations Management

Miguel Hernández University
Universidad Autónoma de Madrid
University of Deusto
University of South-Eastern Norway
Lund University

Research output: Contribution to journal › Article › Academic › peer-review

9 Citations (Scopus)

63 Downloads (Pure)

Abstract

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.

Original language	English
Article number	122607
Journal	Technological Forecasting and Social Change
Volume	193
DOIs	https://doi.org/10.1016/j.techfore.2023.122607
Publication status	Published - Aug 2023

Bibliographical note

Funding Information:
The authors are indebted to the editor and three anonymous referees for their comments on an earlier draft. The authors thank the grant PID2019-105952GB-I00 funded by Ministerio de Ciencia e Innovación / Agencia Estatal de Investigación / 10.13039/501100011033 . José L. Zofío thanks grant EIN2020-112260 funded by Ministerio de Ciencia e Innovación / Agencia Estatal de Investigación / 10.13039/501100011033 . Javier Barbero and José L. Zofío acknowledge financial support from the project INNJOBMAD-CM (Ref. H2019/HUM-5761 ), funded by the Comunidad de Madrid . Juan Aparicio acknowledges the financial support from the Spanish Ministry for Economy and Competitiveness , the State Research Agency and the European Regional Development Fund under grant MTM2016-79765-P (AEI/FEDER, UE). Jon Mikel Zabala-Iturriagagoitia acknowledges financial support from the Basque Government Department of Education, Language Policy and Culture ( IT 1429-22 ) and from the 2021 Membership Research Grant Scheme of the Regional Studies Association .

Funding Information:
Jon Mikel Zabala-Iturriagagoitia is Associate Professor at the University of Deusto in San Sebastian (Spain). His research skills and interests include innovation policy, innovation management, and the use of indicators to inform policy decisions and evaluations related to innovation. His research has received numerous recognitions and awards, having had a strong policy impact. Due to the impact of his research, he has been appointed as a member of the Basque Academy of Sciences, Arts and Letters (Jakiunde), the Spanish Foundation for innovation (COTEC), the United Nations Economic Commission for Europe Task Force on Innovation Policy Principles, and the Science, Technology and Innovation Advisory Council (CACTI) under the Ministry of Science and Innovation of the Spanish Government.

Publisher Copyright:
© 2023 The Authors

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Cite this

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title = "The influence of bottlenecks on innovation systems performance: Put the slowest climber first",

abstract = "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.",

author = "Zofio, \{Jose Luis\} and Juan Aparicio and Javier Barbero and Zabala-Iturriagagoitia, \{Jon Mikel\}",

note = "Funding Information: The authors are indebted to the editor and three anonymous referees for their comments on an earlier draft. The authors thank the grant PID2019-105952GB-I00 funded by Ministerio de Ciencia e Innovaci{\'o}n / Agencia Estatal de Investigaci{\'o}n / 10.13039/501100011033 . Jos{\'e} L. Zof{\'i}o thanks grant EIN2020-112260 funded by Ministerio de Ciencia e Innovaci{\'o}n / Agencia Estatal de Investigaci{\'o}n / 10.13039/501100011033 . Javier Barbero and Jos{\'e} L. Zof{\'i}o acknowledge financial support from the project INNJOBMAD-CM (Ref. H2019/HUM-5761 ), funded by the Comunidad de Madrid . Juan Aparicio acknowledges the financial support from the Spanish Ministry for Economy and Competitiveness , the State Research Agency and the European Regional Development Fund under grant MTM2016-79765-P (AEI/FEDER, UE). Jon Mikel Zabala-Iturriagagoitia acknowledges financial support from the Basque Government Department of Education, Language Policy and Culture ( IT 1429-22 ) and from the 2021 Membership Research Grant Scheme of the Regional Studies Association . Funding Information: Jon Mikel Zabala-Iturriagagoitia is Associate Professor at the University of Deusto in San Sebastian (Spain). His research skills and interests include innovation policy, innovation management, and the use of indicators to inform policy decisions and evaluations related to innovation. His research has received numerous recognitions and awards, having had a strong policy impact. Due to the impact of his research, he has been appointed as a member of the Basque Academy of Sciences, Arts and Letters (Jakiunde), the Spanish Foundation for innovation (COTEC), the United Nations Economic Commission for Europe Task Force on Innovation Policy Principles, and the Science, Technology and Innovation Advisory Council (CACTI) under the Ministry of Science and Innovation of the Spanish Government. Publisher Copyright: {\textcopyright} 2023 The Authors",

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N1 - Funding Information: The authors are indebted to the editor and three anonymous referees for their comments on an earlier draft. The authors thank the grant PID2019-105952GB-I00 funded by Ministerio de Ciencia e Innovación / Agencia Estatal de Investigación / 10.13039/501100011033 . José L. Zofío thanks grant EIN2020-112260 funded by Ministerio de Ciencia e Innovación / Agencia Estatal de Investigación / 10.13039/501100011033 . Javier Barbero and José L. Zofío acknowledge financial support from the project INNJOBMAD-CM (Ref. H2019/HUM-5761 ), funded by the Comunidad de Madrid . Juan Aparicio acknowledges the financial support from the Spanish Ministry for Economy and Competitiveness , the State Research Agency and the European Regional Development Fund under grant MTM2016-79765-P (AEI/FEDER, UE). Jon Mikel Zabala-Iturriagagoitia acknowledges financial support from the Basque Government Department of Education, Language Policy and Culture ( IT 1429-22 ) and from the 2021 Membership Research Grant Scheme of the Regional Studies Association . Funding Information: Jon Mikel Zabala-Iturriagagoitia is Associate Professor at the University of Deusto in San Sebastian (Spain). His research skills and interests include innovation policy, innovation management, and the use of indicators to inform policy decisions and evaluations related to innovation. His research has received numerous recognitions and awards, having had a strong policy impact. Due to the impact of his research, he has been appointed as a member of the Basque Academy of Sciences, Arts and Letters (Jakiunde), the Spanish Foundation for innovation (COTEC), the United Nations Economic Commission for Europe Task Force on Innovation Policy Principles, and the Science, Technology and Innovation Advisory Council (CACTI) under the Ministry of Science and Innovation of the Spanish Government. Publisher Copyright: © 2023 The Authors

PY - 2023/8

Y1 - 2023/8

N2 - 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.

AB - 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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The influence of bottlenecks on innovation systems performance: Put the slowest climber first

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