Exploratory factor analysis of backshoring drivers 2010–2015 and 2020–2022
| Period | Construct | Items | Factor loadings |
|---|---|---|---|
| 2010–2015 | Trade and cost | Country-specific conditions | 0.912 |
| Trade barriers | 0.899 | ||
| Exchange rates | 0.799 | ||
| Labor cost | 0.726 | ||
| Access to raw materials | 0.685 | ||
| Lack of qualified personnel | 0.676 | ||
| Cronbach’s alpha | 0.899 | ||
| Eigenvalue | 3.925 | ||
| % of variance explained | 35.678 | ||
| Development | Flexibility | 0.814 | |
| Proximity to R&D | 0.811 | ||
| Access to technology | 0.777 | ||
| Access to skills and knowledge | 0.744 | ||
| Lead-time | 0.712 | ||
| Cronbach’s alpha | 0.852 | ||
| Eigenvalue | 3.340 | ||
| % of variance explained | 30.363 | ||
| 2020–2022 | Short supply chains | Production close to or in the market | 0.911 |
| Logistics costs | 0.848 | ||
| Lead-time | 0.716 | ||
| Risk | 0.657 | ||
| Cronbach’s alpha | 0.787 | ||
| Eigenvalue | 2.855 | ||
| % of variance explained | 25.957 | ||
| Development | Quality | 0.797 | |
| Flexibility | 0.789 | ||
| Access to skills and knowledge | 0.736 | ||
| Proximity to R&D | 0.697 | ||
| Cronbach’s alpha | 0.731 | ||
| Eigenvalue | 2.698 | ||
| % of variance explained | 24.524 | ||
| Trade | Country-specific conditions | 0.856 | |
| Trade barriers | 0.827 | ||
| Lack of qualified personnel | 0.825 | ||
| Cronbach’s alpha | 0.880 | ||
| Eigenvalue | 2.518 | ||
| % of variance explained | 22.891 |
| Period | Construct | Items | Factor loadings |
|---|---|---|---|
| 2010–2015 | Trade and cost | Country-specific conditions | 0.912 |
| Trade barriers | 0.899 | ||
| Exchange rates | 0.799 | ||
| Labor cost | 0.726 | ||
| Access to raw materials | 0.685 | ||
| Lack of qualified personnel | 0.676 | ||
| Cronbach’s alpha | 0.899 | ||
| Eigenvalue | 3.925 | ||
| % of variance explained | 35.678 | ||
| Development | Flexibility | 0.814 | |
| Proximity to R&D | 0.811 | ||
| Access to technology | 0.777 | ||
| Access to skills and knowledge | 0.744 | ||
| Lead-time | 0.712 | ||
| Cronbach’s alpha | 0.852 | ||
| Eigenvalue | 3.340 | ||
| % of variance explained | 30.363 | ||
| 2020–2022 | Short supply chains | Production close to or in the market | 0.911 |
| Logistics costs | 0.848 | ||
| Lead-time | 0.716 | ||
| Risk | 0.657 | ||
| Cronbach’s alpha | 0.787 | ||
| Eigenvalue | 2.855 | ||
| % of variance explained | 25.957 | ||
| Development | Quality | 0.797 | |
| Flexibility | 0.789 | ||
| Access to skills and knowledge | 0.736 | ||
| Proximity to R&D | 0.697 | ||
| Cronbach’s alpha | 0.731 | ||
| Eigenvalue | 2.698 | ||
| % of variance explained | 24.524 | ||
| Trade | Country-specific conditions | 0.856 | |
| Trade barriers | 0.827 | ||
| Lack of qualified personnel | 0.825 | ||
| Cronbach’s alpha | 0.880 | ||
| Eigenvalue | 2.518 | ||
| % of variance explained | 22.891 |
Source(s): Authors’ own elaboration