Modeling the intention to consume and willingness to pay premium price for 3D-printed food in an emerging economy

The paper addresses the rapid growth of 3D food printing and explores factors shaping Indonesian consumers’ intention to consume and willingness to pay a premium (WPP) for 3D-printed foods. Despite increasing global interest, consumer perspectives in Indonesia remain underexplored. Using the Theory of Planned Behavior (TPB) as the base, the study extends the model by incorporating personal innovativeness, attitude toward 3D-printed food, subjective norms, perceived behavioral control, perceived compatibility, and perceived product value as determinants of intention to consume 3D-printed food (ITF) and WPP. The research question centers on which factors significantly drive ITF and WPP and whether intention mediates the relationships between antecedents and WPP. The study’s importance lies in informing stakeholders about consumer adoption drivers in an emerging Asian economy, aiding market strategy and policy.

The review traces the evolution from the Theory of Reasoned Action (TRA) to the Theory of Planned Behavior (TPB), highlighting the roles of attitude, subjective norms, and perceived behavioral control (PBC) in shaping intentions and behavior. Recognizing limits of volitional control, TPB includes perceived control (aligned with self-efficacy) as a predictor of intention and behavior. Prior research recommends extending TPB with additional variables to capture nuances in adoption contexts. In 3D-printed food, the study posits: personal innovativeness (PIN) positively affects ITF and WPP; attitude (ATT) positively affects ITF and WPP; subjective norms (SNM) positively affect ITF and WPP; perceived compatibility (PCM) positively affects ITF and WPP; perceived product value (PPV) positively affects ITF and WPP; PBC positively affects WPP; and ITF positively affects WPP. The study also hypothesizes that ITF mediates the relationships between PIN, ATT, SNM, PCM, PPV and WPP. Conceptual relationships are depicted in a research framework extending TPB to the 3D-printed food context.

Design: Quantitative, deductive, cross-sectional survey based on extended TPB. Population: Indonesian consumers aware of or who consumed 3D-printed food. Sampling: Convenience sampling via social media (Twitter, WhatsApp); screening question ensured eligibility. Power analysis (G*Power 3.1) indicated a minimum of 160 responses (power=0.95, effect size=0.15, 8 predictors). Final valid sample: 1540 respondents. Demographics: 56% female; largest age group 18–25 (62.6%); varied education and income levels; employment statuses included self-employed (32.3%), full-time employed (30%). Measures: Structured questionnaire with 5-point Likert scales. Constructs and sources: PIN (5 items; Agarwal & Prasad, 1998), ATT and SNM (5 items each; Al Mamun et al., 2020), PBC (5 items; Gao et al., 2017), PCM (5 items; Kapoor & Dwivedi, 2020), PPV (5 items; Kim et al., 2019), ITF (5 items; Gao et al., 2017; Alam et al., 2020), WPP (single item; Alam et al., 2020). Data quality: Common method variance was acceptable (single factor 36.85%; all full collinearity VIFs <5). Multivariate normality not met (Mardia p<0.05), justifying PLS-SEM. Analysis: Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 4.0. Measurement model showed acceptable reliability (Cronbach’s alpha and composite reliability >0.70), convergent validity (AVE >0.50), and discriminant validity (HTMT <0.90, Fornell–Larcker criterion met, factor loadings >0.5). Structural model assessed direct and mediating effects with bootstrapped confidence intervals.

- Predictors of intention to consume (ITF): PIN (β=0.224, CI 0.182–0.267, p<0.01), ATT (β=0.159, CI 0.123–0.194, p<0.01), SNM (β=0.077, CI 0.043–0.114, p<0.01), PCM (β=0.252, CI 0.200–0.306, p<0.01), PPV (β=0.066, CI 0.020–0.120, p<0.05) were all significant positive predictors. - Predictors of willingness to pay premium (WPP): PBC (β=0.329, CI 0.295–0.365, p<0.01) and ITF (β=0.035, CI 0.005–0.065, p<0.05) were significant positive predictors. - Explanatory power: R² for ITF=0.420 (high); R² for WPP=0.118 (moderate). - Mediation by ITF: Significant for PIN→WPP (indirect β=0.008, p<0.05), ATT→WPP (indirect β=0.006, p<0.05), and PCM→WPP (indirect β=0.009, p<0.05). Not significant for SNM→WPP (indirect β=0.003, p>0.05) and PPV→WPP (indirect β=0.002, p>0.05). - All hypothesized direct paths H1–H7 were supported at the 5% level; mediation hypotheses HM1, HM2, HM4 supported; HM3, HM5 not supported.

Findings demonstrate that extending TPB with personal innovativeness, perceived compatibility, and perceived product value enhances understanding of consumers’ intention to consume and willingness to pay a premium for 3D-printed food in Indonesia. Personal innovativeness and attitude robustly drive intention, indicating openness to novel technologies strongly relates to adopting 3D-printed foods. Subjective norms have a smaller yet significant effect on intention, suggesting social influence plays a role but may be muted among younger consumers. Perceived compatibility exerts a strong influence on intention and, via intention, on WPP, highlighting the importance of alignment with consumers’ values and routines. PPV positively affects intention, but intention did not significantly mediate PPV’s effect on WPP, implying price sensitivity and value perceptions may translate into WPP through other pathways. PBC shows the strongest direct effect on WPP, underscoring that perceived resources and control (ability to pay, opportunities) are pivotal in premium pricing contexts. Overall, the results validate the extended TPB in a new food technology setting, explaining 42% of variance in intention and 11.8% in WPP, and offer context-specific insights for emerging Asian markets.

The study advances theory by extending TPB with personal innovativeness, perceived compatibility, and perceived product value to explain intention to consume and willingness to pay a premium for 3D-printed food in Indonesia. It shows that PIN, ATT, SNM, PCM, PPV, and PBC significantly shape ITF and/or WPP, with ITF mediating some but not all antecedent–WPP relationships. Practically, marketers should stimulate consumers’ intentions (e.g., through demonstrations, trials, compatibility cues) and enhance perceived control (e.g., pricing strategies, payment options) to increase WPP. The model broadens TPB’s applicability in novel food contexts and Asian markets and suggests designing hierarchical models of WPP that account for personality, attitude, compatibility, and control factors. Future research should incorporate moderators (e.g., gender, age, education), conduct longitudinal designs, include experiential and qualitative components (e.g., interviews), and examine facilitating conditions and trust to bridge intention–WPP gaps.

- Convenience sampling limits generalizability; future studies should use targeted or probabilistic sampling (e.g., focused on millennials). - Cross-sectional design precludes causal inference; longitudinal studies are recommended. - Moderating effects (e.g., gender, age, education) were not examined. - Many respondents lacked prior experience with 3D-printed food; experiential differences may affect perceptions. - Theoretical model did not incorporate some context-specific intentions or moderating factors (e.g., facilitating conditions, trust). - Reliance on self-reported measures may introduce bias despite CMV checks.