Fuzzy-Set QCA on Performance and Sustainability Determinants of Ports Supporting Floating Offshore Wind Farms

Author:

Caldeirinha Vítor12ORCID,Felício J. Augusto3,Pinho Tiago2ORCID,Rodrigues Ricardo3ORCID

Affiliation:

1. Escola Náutica Infante D. Henrique, 2770-058 Paço de Arcos, Portugal

2. Escola Superior de Ciências Empresariais, Instituto Politécnico de Setúbal, 2914-504 Setúbal, Portugal

3. Instituto Superior de Economia e Gestão, Universidade de Lisboa, 1249-078 Lisbon, Portugal

Abstract

The present study explores the relationship between the characteristics, performance, and sustainability of ports that will, in the future, support the logistical chains of new floating offshore wind farms, considering the crucial advancement and expansion of the offshore wind energy sector for the transition to a low-carbon economy. Through a detailed analysis, which includes international case studies in America and Europe utilizing expert interviews and quantitative methods through surveys, the importance of the location, new types of infrastructure and superstructure, and new planning and governance models for the performance and sustainability of ports that will be involved in this new energy industry is highlighted. Also, the context in which ports associated with floating wind turbines are located influences the performance and sustainability. This research employs Fuzzy-Set Qualitative Comparative Analysis (fsQCA), based on a survey of 22 European sector company experts, to emphasize the critical port characteristics for the performance and sustainability. This study reveals the significant contribution of supporting ports for the future floating offshore wind sector for the gross added value and the expansion of regional employment, and the need for new planning, construction, operation, and management models for ports instead of the traditional models applied to simple cargo loading and unloading ports, offering valuable new insights for port managers, policymakers, and academics. However, a future research trajectory with a more geographically diverse sample is suggested to enhance the applicability and generalizability of the results.

Publisher

MDPI AG

Reference44 articles.

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