3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Developing a model of innovation implementation for UK SMEs: A path analysis and explanatory case analysis

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Continuous large-scale changes in technology and the globalization of markets have resulted in the need for many SMEs to use innovation as a means of seeking competitive advantage where innovation includes both technological and organizational perspectives (Tapscott, 2009). However, there is a paucity of systematic and empirical research relating to the implementation of innovation management in the context of SMEs. The aim of this article is to redress this imbalance via an empirical study created to develop and test a model of innovation implementation in SMEs. This study uses Structural Equation Modelling (SEM) to test the plausibility of an innovation model, developed from earlier studies, as the basis of a questionnaire survey of 395 SMEs in the UK. The resultant model and construct relationship results are further probed using an explanatory multiple case analysis to explore ‘how’ and ‘why’ type questions within the model and construct relationships. The findings show that the effects of leadership, people and culture on innovation implementation are mediated by business improvement activities relating to Total Quality Management/Continuous Improvement (TQM/ CI) and product and process developments. It is concluded that SMEs have an opportunity to leverage existing quality and process improvement activities to move beyond continuous improvement outcomes towards effective innovation implementation. The article concludes by suggesting areas suitable for further research.

          Related collections

          Most cited references71

          • Record: found
          • Abstract: not found
          • Article: not found

          Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Comparative fit indexes in structural models.

            P. Bentler (1990)
            Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification.

                Bookmark

                Author and article information

                Journal
                International Small Business Journal: Researching Entrepreneurship
                International Small Business Journal
                SAGE Publications
                0266-2426
                1741-2870
                June 2010
                June 18 2010
                June 2010
                : 28
                : 3
                : 195-214
                Affiliations
                [1 ]University of Ulster, UK,
                [2 ]University of Ulster, UK
                [3 ]Queen's University Belfast, UK
                Article
                10.1177/0266242609360610
                813e3b78-6ee6-466d-bf1c-e8253a64fbab
                © 2010

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

                History

                Comments

                Comment on this article