Innovation Modes and Firm's Performance: Evidence from Portugal

Sérgio Nunes (), Raul Lopes and José Dias

ERSA conference papers from European Regional Science Association

Abstract: It has been shown that firms tend to develop different modes of innovation triggered by the relationship between different types of knowledge and learning processes underpinning it. This paper aims at identifying different modes of business innovation; second, relating them to firms' innovative and economic performance; and, analyzing the relationship between the different innovation modes and the economic impact of the crisis on the firms' performance. These hypotheses are tested by regression and latent class models for the Portuguese population of firms using a sample of 397 firms, stratified by level of technological intensity, firm's size and region. Results show three firms' heterogeneous modes of innovation in terms of its relationship to the economic and innovative performance and with significant differences in terms of resilience to the economic crisis. These findings lead to a reflection on innovation, competitiveness and regional policy.

Keywords: economic performance; latent class model; logistic regression; innovation modes; innovation process; governance mechanisms; economic crisis; firm´s resilience; innovation policy (search for similar items in EconPapers)
Date: 2013-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www-sre.wu.ac.at/ersa/ersaconfs/ersa13/ERSA2013_paper_00252.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wiw:wiwrsa:ersa13p252

Access Statistics for this paper

More papers in ERSA conference papers from European Regional Science Association Welthandelsplatz 1, 1020 Vienna, Austria.
Bibliographic data for series maintained by Gunther Maier ().