SMEs’ Degree of Openness: The Case of Manufacturing Industries
This paper clusters SMEs based on their degree of openness. In addition, it explores both the internal and external determinants of the different clusters obtained. Based on a survey of 1214 firms in manufacturing industries and using both the dimensions of openness, breadth and depth, we find that SMEs could be clustered in four classes, depending on their degree of openness. We find that SMEs could adopt a closed, an open, an interactive or a user approach to innovation. With respect to the determinants of different classes of SMEs, the results of the logistic regression model, developed in this study, show variables such as national and regional proximities that account for explaining the likelihood that SMEs will be in a more open cluster rather than in a low open cluster. Also, this quantitative study shows that external obstacles to innovation may lead these SMEs from a closed approach to innovation to an interactive, user, or open approach to innovation. Finally, we find that the age of the firm is important in explaining the likelihood that SMEs will be in an open cluster rather than in a closed cluster.
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Universidad Alberto Hurtado. Facultad de Economía y Negocios
2012
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oai:scielo:S0718-272420120001000132012-05-14SMEs’ Degree of Openness: The Case of Manufacturing IndustriesOthman Idrissia,MoulayAmaraa,NabilLandrya,Réjean SMEs open innovation openness external sources of information cluster analysis This paper clusters SMEs based on their degree of openness. In addition, it explores both the internal and external determinants of the different clusters obtained. Based on a survey of 1214 firms in manufacturing industries and using both the dimensions of openness, breadth and depth, we find that SMEs could be clustered in four classes, depending on their degree of openness. We find that SMEs could adopt a closed, an open, an interactive or a user approach to innovation. With respect to the determinants of different classes of SMEs, the results of the logistic regression model, developed in this study, show variables such as national and regional proximities that account for explaining the likelihood that SMEs will be in a more open cluster rather than in a low open cluster. Also, this quantitative study shows that external obstacles to innovation may lead these SMEs from a closed approach to innovation to an interactive, user, or open approach to innovation. Finally, we find that the age of the firm is important in explaining the likelihood that SMEs will be in an open cluster rather than in a closed cluster.info:eu-repo/semantics/openAccessUniversidad Alberto Hurtado. Facultad de Economía y NegociosJournal of technology management & innovation v.7 n.1 20122012-03-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-27242012000100013en10.4067/S0718-27242012000100013 |
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Othman Idrissia,Moulay Amaraa,Nabil Landrya,Réjean |
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Othman Idrissia,Moulay Amaraa,Nabil Landrya,Réjean SMEs’ Degree of Openness: The Case of Manufacturing Industries |
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Othman Idrissia,Moulay Amaraa,Nabil Landrya,Réjean |
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Othman Idrissia,Moulay |
title |
SMEs’ Degree of Openness: The Case of Manufacturing Industries |
title_short |
SMEs’ Degree of Openness: The Case of Manufacturing Industries |
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SMEs’ Degree of Openness: The Case of Manufacturing Industries |
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SMEs’ Degree of Openness: The Case of Manufacturing Industries |
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SMEs’ Degree of Openness: The Case of Manufacturing Industries |
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smes’ degree of openness: the case of manufacturing industries |
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This paper clusters SMEs based on their degree of openness. In addition, it explores both the internal and external determinants of the different clusters obtained. Based on a survey of 1214 firms in manufacturing industries and using both the dimensions of openness, breadth and depth, we find that SMEs could be clustered in four classes, depending on their degree of openness. We find that SMEs could adopt a closed, an open, an interactive or a user approach to innovation. With respect to the determinants of different classes of SMEs, the results of the logistic regression model, developed in this study, show variables such as national and regional proximities that account for explaining the likelihood that SMEs will be in a more open cluster rather than in a low open cluster. Also, this quantitative study shows that external obstacles to innovation may lead these SMEs from a closed approach to innovation to an interactive, user, or open approach to innovation. Finally, we find that the age of the firm is important in explaining the likelihood that SMEs will be in an open cluster rather than in a closed cluster. |
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Universidad Alberto Hurtado. Facultad de Economía y Negocios |
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2012 |
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http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-27242012000100013 |
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