University of Tasmania
Browse

File(s) under permanent embargo

Exploring innovation success recipes in low-technology firms using fuzzy-set QCA

journal contribution
posted on 2023-05-18, 19:32 authored by Reichert, FR, Torugsa, N(A), Zawislak, PA, Arundel, A
This study explores the configurations of innovation capabilities (“recipes”) that enable firms in low-technology industries (“low-tech firms”) to achieve high innovative performance. Using a sample of 614 Brazilian low-tech firms, the study employs fuzzy-set qualitative comparative analysis (QCA) to identify how the four capabilities - development, operations,management and transaction - combine to produce high innovative performance. The analyses identify two recipes for innovation success, both of which include high levels of development and transaction capabilities. However, these two capabilities (while necessary) are not sufficient for achieving high innovative performance: they are meaningful only when combined with either a management or an operations capability. The study contributes to a comprehensive understanding of innovation in low-tech industries by showing that low-tech firms, even with limited research and development capacities, can successfully innovate when they develop and use an appropriate set of capabilities. The study results should help managers uncover potential ways of combining capabilities for innovation success and suggest that low-tech firms could benefit from policy support and training to develop such capabilities.

History

Publication title

Journal of Business Research

Volume

69

Issue

11

Pagination

5437-5441

ISSN

0148-2963

Department/School

TSBE

Publisher

Elsevier Science Inc

Place of publication

360 Park Ave South, New York, USA, Ny, 10010-1710

Rights statement

© 2016 Elsevier Inc. All rights reserved.

Repository Status

  • Restricted

Socio-economic Objectives

Technological and organisational innovation

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC