Technological innovation capabilities and competitive advantage: a measurement model using PLS-SEM in the automotive Industry in Malaysia
Study on technological innovation capabilities (TICs) and competitive advantage have been emerged in recent years. However, the conceptualization and measurement of technological innovation capabilities and competitive advantage in the automotive industry has little come to attention. This study aim...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Malaysia Pahang
2018
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/23097/7/Technological%20Innovation%20Capabilities.pdf http://umpir.ump.edu.my/id/eprint/23097/ http://ncon-pgr.ump.edu.my/index.php/en/download/program-book/file |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Study on technological innovation capabilities (TICs) and competitive advantage have been emerged in recent years. However, the conceptualization and measurement of technological innovation capabilities and competitive advantage in the automotive industry has little come to attention. This study aims to specify and assess technological innovation capabilities dimensions and competitive advantage as a second-order formative construct and provide empirical support for their measurement model. Based on the literatures, this study proposes four dimensions to measure technological innovation capabilities (R&D capability, manufacturing capability, networking capability and human resource capability). For competitive advantage, four dimensions which are cost advantage, differentiation advantage, product innovation and process innovation have been proposed to measure competitive advantage. This study adopted the two-stage approaches in partial least squarestructural equation modelling to examine the appropriateness of hierarchical modelling for technological innovation capabilities and competitive advantage. Partial least squares-structural equation modeling (PLS-SEM) to approach using WarpPLS 6.0 software was utilized to analyze the data. The findings confirmed the convergent and discriminant validity of eighteen reflective first-orders constructs establishing validity and reliability of five formative second-order constructs. The analysis of secondorder formative technological innovation capabilities and competitive advantage constructs revealed that Variance Inflation Factor (VIF) was found lower than five and the outer weights were significant at the level of .05 through survey data from 136 companies in the automotive industry in Malaysia. Finally, this study also concludes with limitations and directions for future research |
|---|