Abstract:

Open hardware (OH) represents an emergent paradigm of user-driven innovation that enables individuals to collaboratively design, modify, and share physical technological artifacts (Barrett and Dooley, 2025). Despite conceptual similarities to open-source software (OSS), empirical investigations into the determinants of OH adoption remain limited (Reinauer and Hansen, 2021). This study addresses this gap by examining OH adoption through the lens of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) (Venkatesh et al., 2012) and by extending the model with two constructs particularly salient to OH communities: Educational Value and Recognition Benefits. The UTAUT2 framework comprises seven key determinants of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit which are widely validated across diverse technological contexts (Oliveira et al., 2016; Limayem et al., 2007; Taylor and Todd, 1995). Within the OH context, performance expectancy captures perceived functional utility (Pavlou and Fygenson, 2006; Duan et al., 2024); effort expectancy reflects usability and reduced learning barriers (Agarwal and Karahanna, 2000); social influence encapsulates peer expectations (Hars, 2002); facilitating conditions involve access to tools, documentation, and community support (Oliveira et al., 2016); hedonic motivation pertains to intrinsic enjoyment (Hsu and Lu, 2004); price value concerns cost–benefit evaluations (Dodds et al., 1991); and habit predicts continued engagement (Limayem et al., 2007). The first extension, Educational Value, reflects the learning and skill-development outcomes derived from hands-on engagement with OH. Rooted in experiential learning theory (Dewey, 1986; Kolb, 1984), this construct acknowledges that the tangible and iterative nature of OH fosters cognitive and creative growth (Kostakis et al., 2023; Pearce, 2013; Heradio et al., 2018). The second extension, Recognition Benefits, captures motivations related to professional visibility, reputation, and peer acknowledgment. Prior research indicates that recognition substantially influences contribution and sustained participation within open innovation ecosystems (Lakhani and Wolf, 2005; Li et al., 2025; Eisenberger et al., 1986; Kuvaas, 2006; O’Mahony and Ferraro, 2007). Positioning OH within the broader framework of “free user innovation” (Von Hippel, 2025), this study employs a survey of OH makers, users, and followers to test the extended UTAUT2 model using structural equation modeling. Theoretically and empirically, performance expectancy, facilitating conditions, educational value, and recognition benefits are anticipated to be strong predictors of behavioral intention. The proposed model contributes to a more nuanced understanding of OH adoption and offers actionable insights for educators, community organizers, and platform developers aiming to enhance engagement within OH ecosystems.

Please choose your submission type: Developmental Paper

Primary Track: Innovation

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Prof Alessandro Rossi