Profiling Digital Printing Technology Adoption in the Fashion Industry: A New Approach to Exploring Innovation Diffusion

Yanan Yu, Lisa Parrillo Chapman and Marguerite M. Moore
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Yanan Yu: Beijing International Studies University, Chaoyang, Beijing, P. R. China
Lisa Parrillo Chapman: ��North Carolina State University, USA
Marguerite M. Moore: ��North Carolina State University, USA

International Journal of Innovation and Technology Management (IJITM), 2022, vol. 19, issue 02, 1-21

Abstract: Digital printing technology (DPT) represents a core innovation that is currently revolutionizing the global decorated apparel market by automating the printing process, facilitating customization, and reducing energy costs and production lead time. However, the fundamental understanding of the emerging DPT market remains unexplored due to its novelty. This study aims to identify DPT diffusion patterns over the past decade in the U.S. market and establish a predictive user profile employing social media-based analytics along with data mining and traditional statistical modeling. A proxy variable is used to measure likely adoption which reflects an S-shaped diffusion curve consistent with Diffusion of Innovations Theory. Additionally, the outcome profile suggests that likely DPT adopters reside in locations that reflect higher levels of education (bachelor’s degrees or higher), relatively young populations (i.e. between 19–34 years of age), proportionately higher incomes generated from art and design occupations, but with lower household annual incomes.

Keywords: Digital printing technology; innovation diffusion; decision trees; logistic regression; textile and apparel (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219877022500043

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