Our own translation box: exploring proximity antecedents and performance implications of customer co-design in manufacturing

Abstract

Customer involvement with design activity is one of the principal components of mass customisation. Whereas many studies proposed methods to enable customer co-design, more research needs to determine co-design predictors and its associations with operations improvements. This study tests relationships between proximity, co-design, and performance, and whether co-design mediates proximity-performance relationships. Following on recent technology and collaborative trends, the study uses a three-dimensional operationalisation of customer proximity that includes physical, virtual, and affinity proximity measures. Regression analyses of data from 698 manufacturers from metal-mechanic industries suggest that virtual and affinity proximity related positively with customer co-design, that co-design explained quality and delivery improvements, and that co-design mediated the relationship between virtual proximity and quality improvements.

Keywords:

• collaboration
• product design
• supply chain management
• mass customisation

Acknowledgements

This research is supported by the Natural Sciences and Engineering Research Council of Canada (Discovery Grant #283134-04) and by the Warren & Marline Dyer Faculty Fellowship in Operations Management at the Haskayne School of Business. The author thanks Flávio Fogliatto and Laurie Milton for valuable comments on earlier manuscript drafts, and an anonymous reviewer whose comments helped to improve the discussion section.

Notes

Notes

1. See, for example, Hemetsberger and Godula (2007) who emphasised the need for sales input in design, and Swink and Song (2007) who found a strong relationship between ‘manufacturing-marketing integration’ in design and ‘product competitive advantage’.

2. To exclude the effects of variances other than common method bias on predictor and outcome variables (see Podsakoff et al. 2003), this test used three partial models, namely one with proximity and co-design variables, another with proximity and performance variables, and a third with co-design and performance variables.