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Entrepreneurial activity in the international trade in cultural goods: A fuzzy clustering analysis

Malcolm Beynon, David Pickernell Orcid Logo, Paul Jones Orcid Logo

Technological Forecasting and Social Change, Volume: 210, Start page: 123914

Swansea University Authors: David Pickernell Orcid Logo, Paul Jones Orcid Logo

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Abstract

This study offers a novel country-level longitudinal investigation of conditions, including, income, urbanity, education, R&D, and entrepreneurial activity, driving international trade, for imports and exports. The configurational (clustering) approach places emphasis on country and year groupin...

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Published in: Technological Forecasting and Social Change
ISSN: 0040-1625 1873-5509
Published: Elsevier BV 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa68387
Abstract: This study offers a novel country-level longitudinal investigation of conditions, including, income, urbanity, education, R&D, and entrepreneurial activity, driving international trade, for imports and exports. The configurational (clustering) approach places emphasis on country and year groupings, offering ‘targeted’ understanding on country level variations of international trade in cultural goods. The study explores context sensitive conditions affecting international trade in cultural goods, including environment for entrepreneurship, and entrepreneurial processes. Emphasis is given to configurational considerations of clusters of country-year observations based on conditions. Inferences inferred will be country groups-based perspectives. Using UIS and GEM datasets, fuzzy c-means clustering is employed for economic development-related conditions measuring, income, urbanity, education, R&D, and entrepreneurial activity, to establish clusters of country-year observations, based on differences in the condition values describing them. These clusters are defined to give qualitative understanding of their individuality. Validation of clusters is undertaken with consideration of differences on levels of international trade of cultural goods, in terms of forms of imports and exports. To complement the validation, cluster profiling is undertaken, with consideration of population age and poverty levels. The study contributes increased understanding concerning drivers (conditions) of trade in cultural goods, and impact of entrepreneurship in both imports and exports.
Keywords: Cultural goods; Export; Import; Fuzzy c-means; Country level; Clustering; Trade
College: Faculty of Humanities and Social Sciences
Funders: Swansea University
Start Page: 123914