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SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis

Mohamed Yacine Haddoud, Malcolm J. Beynon, Paul Jones Orcid Logo, Robert Newbery

Journal of Small Business and Enterprise Development, Volume: 25, Issue: 5, Pages: 769 - 790

Swansea University Author: Paul Jones Orcid Logo

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DOI (Published version): 10.1108/JSBED-02-2017-0077

Abstract

The purpose of this paper is to analyse the determinants of small and medium-sized enterprises’ (SMEs) propensity to export using data from a North African country, namely Algeria. Drawing on the extended resource-based view, the study examines the role of firms’ resources and capabilities in explai...

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Published in: Journal of Small Business and Enterprise Development
ISSN: 1462-6004
Published: Emerald Publishing Ltd 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa44705
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spelling 2018-11-07T15:45:54.1090461 v2 44705 2018-10-03 SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis 21e2660aaa102fe36fc981880dd9e082 0000-0003-0417-9143 Paul Jones Paul Jones true false 2018-10-03 BBU The purpose of this paper is to analyse the determinants of small and medium-sized enterprises’ (SMEs) propensity to export using data from a North African country, namely Algeria. Drawing on the extended resource-based view, the study examines the role of firms’ resources and capabilities in explaining the probability to export. The study employs the nascent fuzzy c-means clustering technique to analyse a sample of 208 Algerian SMEs. The sample included both established and potential exporters operating across various sectors. A combination of online and face-to-face methods was used to collect the data. While a preliminary analysis established the existence of five clusters exhibiting different levels of resources and capabilities, further discernment of these clusters has shown significant variances in relation to export propensity. In short, clusters exhibiting combinations that include higher levels of export-oriented managerial resources showed greater export propensity, whereas clusters lacking such assets were less likely to display high export propensity, despite superior capabilities in marketing and innovation. The findings provide a more comprehensive insight on the critical resources shaping SMEs’ internationalisation in the North African context. The paper holds important implications for export promotion policy in this area. The study makes a twofold contribution. First, the use of the fuzzy c-means clustering technique to capture the joint influence of discrete resources and capabilities on SMEs’ export propensity constitutes a methodological contribution. Second, being the first study bringing evidence on SMEs’ internationalisation from the largest country in the African continent, in terms of landmass, constitutes an important contextual contribution. Journal Article Journal of Small Business and Enterprise Development 25 5 769 790 Emerald Publishing Ltd 1462-6004 SMEs; Algeria; Cluster analysis Fuzzy c-means; Export propensity; Resources and capabilities 2 10 2018 2018-10-02 10.1108/JSBED-02-2017-0077 https://www.emeraldinsight.com/doi/abs/10.1108/JSBED-02-2017-0077 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2018-11-07T15:45:54.1090461 2018-10-03T08:04:42.4972205 Faculty of Humanities and Social Sciences School of Management - Business Management Mohamed Yacine Haddoud 1 Malcolm J. Beynon 2 Paul Jones 0000-0003-0417-9143 3 Robert Newbery 4 0044705-26102018092629.pdf PDF_Proofv5.minuscs.pdf 2018-10-26T09:26:29.1100000 Output 934205 application/pdf Accepted Manuscript true 2018-10-26T00:00:00.0000000 true eng
title SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
spellingShingle SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
Paul Jones
title_short SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
title_full SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
title_fullStr SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
title_full_unstemmed SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
title_sort SMEs’ export propensity in North Africa: a fuzzy c-means cluster analysis
author_id_str_mv 21e2660aaa102fe36fc981880dd9e082
author_id_fullname_str_mv 21e2660aaa102fe36fc981880dd9e082_***_Paul Jones
author Paul Jones
author2 Mohamed Yacine Haddoud
Malcolm J. Beynon
Paul Jones
Robert Newbery
format Journal article
container_title Journal of Small Business and Enterprise Development
container_volume 25
container_issue 5
container_start_page 769
publishDate 2018
institution Swansea University
issn 1462-6004
doi_str_mv 10.1108/JSBED-02-2017-0077
publisher Emerald Publishing Ltd
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
url https://www.emeraldinsight.com/doi/abs/10.1108/JSBED-02-2017-0077
document_store_str 1
active_str 0
description The purpose of this paper is to analyse the determinants of small and medium-sized enterprises’ (SMEs) propensity to export using data from a North African country, namely Algeria. Drawing on the extended resource-based view, the study examines the role of firms’ resources and capabilities in explaining the probability to export. The study employs the nascent fuzzy c-means clustering technique to analyse a sample of 208 Algerian SMEs. The sample included both established and potential exporters operating across various sectors. A combination of online and face-to-face methods was used to collect the data. While a preliminary analysis established the existence of five clusters exhibiting different levels of resources and capabilities, further discernment of these clusters has shown significant variances in relation to export propensity. In short, clusters exhibiting combinations that include higher levels of export-oriented managerial resources showed greater export propensity, whereas clusters lacking such assets were less likely to display high export propensity, despite superior capabilities in marketing and innovation. The findings provide a more comprehensive insight on the critical resources shaping SMEs’ internationalisation in the North African context. The paper holds important implications for export promotion policy in this area. The study makes a twofold contribution. First, the use of the fuzzy c-means clustering technique to capture the joint influence of discrete resources and capabilities on SMEs’ export propensity constitutes a methodological contribution. Second, being the first study bringing evidence on SMEs’ internationalisation from the largest country in the African continent, in terms of landmass, constitutes an important contextual contribution.
published_date 2018-10-02T03:56:03Z
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score 11.013148

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