Determinants of Consumer Acceptance of Innovative Agri-Food Products: An Integrated Marketing and Behavioural Framework

Innovative agri-food products combine novel ingredients, production systems, processing technologies, packaging solutions, traceability tools, and sustainability-oriented attributes. Their technical novelty, however, does not automatically generate favourable attitudes or sustained market behaviour. This conceptual review develops a model that follows the complete consumer-response sequence specified for innovative agri-food products. A structured integrative review synthesised 36 academic sources from food marketing, consumer behaviour, innovation diffusion, technology acceptance, perceived quality, trust, risk, engagement, and post-purchase research. The model positions awareness, information, and perceived innovation attributes; perceived ease of use; perceived usefulness; trust; perceived risk; and perceived quality as antecedents of attitude. Attitude is treated as the central mediator and is linked sequentially to consumer engagement, purchase intention, purchase decision making, satisfaction, and recommendation or word of mouth. The model specifies a negative relationship for perceived risk and positive relationships for all other links in the sequence. Examples from hydroponic products, alternative proteins, upcycled foods, non-thermal processing, smart packaging, QR codes, and blockchain-supported traceability illustrate the meaning of each construct. The review contributes by integrating technology-related and food-specific evaluations, separating active engagement from purchase intention, distinguishing intention from the broader purchase-decision process, and extending the model beyond first purchase to satisfaction and advocacy. The proposed relationships are stated as eleven clearly numbered propositions. The article also clarifies the conceptual boundaries required for empirical testing and provides illustrative measurement guidance so that risk, quality, attitude, engagement, intention, decision making, satisfaction, and word of mouth remain empirically distinct. The model provides a direct theoretical foundation for factor analysis, regression, mediation analysis, and structural equation modelling in research on consumer responses to innovative agri-food products.

innovative agri-food products, integrated marketing framework, consumer attitude, technology acceptance, purchase decision making

1. Abdullah, K. M., Putit, L., Humaidi, N., Ying, T. Y., Hidayati, T., & Hendrayati, H. (2025). Consumer innovativeness and uncertainty avoidance in the acceptance of sustainable food innovations. Discover Sustainability, 6, Article 1199. https://doi.org/10.1007/s43621-025-02069-w [Google Scholar] [Crossref]

2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T [Google Scholar] [Crossref]

3. Albertsen, L., Wiedmann, K.-P., & Schmidt, S. (2020). The impact of innovation-related perception on consumer acceptance of food innovations: Development of an integrated framework of the consumer acceptance process. Food Quality and Preference, 84, 103958. https://doi.org/10.1016/j.foodqual.2020.103958 [Google Scholar] [Crossref]

4. Anderson, E. W. (1998). Customer satisfaction and word of mouth. Journal of Service Research, 1(1), 5–17. https://doi.org/10.1177/109467059800100102 [Google Scholar] [Crossref]

5. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921 [Google Scholar] [Crossref]

6. Castellini, G., Romanò, S., Merlino, V. M., Barbera, F., Costamagna, C., Brun, F., & Graffigna, G. (2025). Determinants of consumer and farmer acceptance of new production technologies: A systematic review. Frontiers in Sustainable Food Systems, 9, 1557974. https://doi.org/10.3389/fsufs.2025.1557974 [Google Scholar] [Crossref]

7. Contini, C., Boncinelli, F., Piracci, G., Scozzafava, G., & Casini, L. (2023). Can blockchain technology strengthen consumer preferences for credence attributes? Agricultural and Food Economics, 11, Article 27. https://doi.org/10.1186/s40100-023-00270-x [Google Scholar] [Crossref]

8. D'Amico, A., De Boni, A., Ottomano Palmisano, G., Morea, E., Acciani, C., & Roma, R. (2024). Consumers' perception and willingness to pay for hydroponic tomatoes: The effects of sustainability and quality attributes. British Food Journal, 126(13), 573–592. https://doi.org/10.1108/BFJ-04-2024-0353 [Google Scholar] [Crossref]

9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar] [Crossref]

10. Elimelech, E., Ert, E., Parag, Y., & Hochman, G. (2024). Exploring the impact of visual perception and taste experience on consumers' acceptance of suboptimal fresh produce. Sustainability, 16(7), 2698. https://doi.org/10.3390/su16072698 [Google Scholar] [Crossref]

11. Guiné, R. P. F., Florença, S. G., Barroca, M. J., & Anjos, O. (2020). The link between the consumer and the innovations in food product development. Foods, 9(9), 1317. https://doi.org/10.3390/foods9091317 [Google Scholar] [Crossref]

12. Günden, C., Atakan, P., Yercan, M., Mattas, K., & Knez, M. (2024). Consumer response to novel foods: A review of behavioral barriers and drivers. Foods, 13(13), 2051. https://doi.org/10.3390/foods13132051 [Google Scholar] [Crossref]

13. Hollebeek, L. D., Glynn, M. S., & Brodie, R. J. (2014). Consumer brand engagement in social media: Conceptualization, scale development and validation. Journal of Interactive Marketing, 28(2), 149–165. https://doi.org/10.1016/j.intmar.2013.12.002 [Google Scholar] [Crossref]

14. Hüppe, R., & Zander, K. (2021). Consumer perspectives on processing technologies for organic food. Foods, 10(6), 1212. https://doi.org/10.3390/foods10061212 [Google Scholar] [Crossref]

15. Kalam, A., Islam, S. M. M., & Akterujjaman, S. M. (2025). Momentum for organic food purchase intention and actual adoption: Moderating effects of social media influencer and celebrity endorser. Food Quality and Preference, 122, 105307. https://doi.org/10.1016/j.foodqual.2024.105307 [Google Scholar] [Crossref]

16. Laureati, M., De Boni, A., Saba, A., Lamy, E., Minervini, F., Delgado, A. M., & Sinesio, F. (2024). Determinants of consumers' acceptance and adoption of novel food in view of more resilient and sustainable food systems in the EU: A systematic literature review. Foods, 13(10), 1534. https://doi.org/10.3390/foods13101534 [Google Scholar] [Crossref]

17. Lin, X., Chang, S.-C., Chou, T.-H., Chen, S.-C., & Ruangkanjanases, A. (2021). Consumers' intention to adopt blockchain food traceability technology towards organic food products. International Journal of Environmental Research and Public Health, 18(3), 912. https://doi.org/10.3390/ijerph18030912 [Google Scholar] [Crossref]

18. Lu, P., Parrella, J. A., Xu, Z., & Kogut, A. (2024). A scoping review of the literature examining consumer acceptance of upcycled foods. Food Quality and Preference, 114, 105098. https://doi.org/10.1016/j.foodqual.2023.105098 [Google Scholar] [Crossref]

19. Mendini, M., Peter, P. C., Bitetti, L., & Castro, I. A. (2024). An interdisciplinary marketing call into food design thinking to create innovative, healthy, and pleasurable food experiences. Italian Journal of Marketing, 2024, 395–417. https://doi.org/10.1007/s43039-024-00104-8 [Google Scholar] [Crossref]

20. Monaco, A., Kotz, J., Al Masri, M., Allmeta, A., Purnhagen, K. P., & König, L. M. (2024). Consumers' perception of novel foods and the impact of heuristics and biases: A systematic review. Appetite, 196, 107285. https://doi.org/10.1016/j.appet.2024.107285 [Google Scholar] [Crossref]

21. Mosikyan, S., Dolan, R., Corsi, A. M., & Bastian, S. E. P. (2024). A systematic literature review and future research agenda to study consumer acceptance of novel foods and beverages. Appetite, 203, 107655. https://doi.org/10.1016/j.appet.2024.107655 [Google Scholar] [Crossref]

22. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405 [Google Scholar] [Crossref]

23. Onwezen, M. C., Bouwman, E. P., Reinders, M. J., & Dagevos, H. (2021). A systematic review on consumer acceptance of alternative proteins: Pulses, algae, insects, plant-based meat alternatives, and cultured meat. Appetite, 159, 105058. https://doi.org/10.1016/j.appet.2020.105058 [Google Scholar] [Crossref]

24. Reitano, M., Pappalardo, G., Selvaggi, R., Zarbà, C., & Chinnici, G. (2024). Factors influencing consumer perceptions of food tracked with blockchain technology: A systematic literature review. Applied Food Research, 4(2), 100455. https://doi.org/10.1016/j.afres.2024.100455 [Google Scholar] [Crossref]

25. Risitano, M. (2017). The impact of consumer-brand engagement on brand experience and behavioural intentions: An Italian empirical study. British Food Journal, 119(8), 1884–1896. https://doi.org/10.1108/BFJ-11-2016-0579 [Google Scholar] [Crossref]

26. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. [Google Scholar] [Crossref]

27. Román, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food naturalness for consumers: Results of a systematic review. Trends in Food Science & Technology, 67, 44–57. https://doi.org/10.1016/j.tifs.2017.06.010 [Google Scholar] [Crossref]

28. Schrobback, P., Zhang, A., Loechel, B., Ricketts, K., & Ingham, A. (2023). Food credence attributes: A conceptual framework of supply chain stakeholders, their motives, and mechanisms to address information asymmetry. Foods, 12(3), 538. https://doi.org/10.3390/foods12030538 [Google Scholar] [Crossref]

29. Shehawy, Y. M., & Khan, S. M. F. A. (2024). Consumer readiness for green consumption: The role of green awareness as a moderator of the relationship between green attitudes and purchase intentions. Journal of Retailing and Consumer Services, 78, 103739. https://doi.org/10.1016/j.jretconser.2024.103739 [Google Scholar] [Crossref]

30. Siegrist, M., & Hartmann, C. (2020). Consumer acceptance of novel food technologies. Nature Food, 1(6), 343–350. https://doi.org/10.1038/s43016-020-0094-x [Google Scholar] [Crossref]

31. Silva, A., Rocha, C., Ribeiro, J. C., Aganovic, K., Lima, R. C., Methven, L., & Cunha, L. M. (2024). Consumer perception of risk towards new sustainable non-thermal food processing technologies: A cross-cultural study between Portugal, Germany, and the UK. Innovative Food Science & Emerging Technologies, 96, 103772. https://doi.org/10.1016/j.ifset.2024.103772 [Google Scholar] [Crossref]

32. Sun, J., Wang, Y., Yang, C., Chen, J., Wei, W., Miao, W., Sun, H., & Gu, C. (2024). Is there any way to increase consumers' purchase intention regarding surplus food blind-boxes? An exploratory study. BMC Psychology, 12, Article 103. https://doi.org/10.1186/s40359-024-01587-y [Google Scholar] [Crossref]

33. Wang, O., Perez-Cueto, F. J. A., Scarpa, R., & Scrimgeour, F. (2024). The influence of innovation-adoption characteristics on consumers' trust and purchase intentions of innovative alternative proteins: A comparison between plant-based food, cultured food, and insect-based food. Food Quality and Preference, 113, 105072. https://doi.org/10.1016/j.foodqual.2023.105072 [Google Scholar] [Crossref]

34. Wu, W., Zhang, A., van Klinken, R. D., Schrobback, P., & Muller, J. M. (2021). Consumer trust in food and the food system: A critical review. Foods, 10(10), 2490. https://doi.org/10.3390/foods10102490 [Google Scholar] [Crossref]

35. Young, E., Mirosa, M., & Bremer, P. (2020). A systematic review of consumer perceptions of smart packaging technologies for food. Frontiers in Sustainable Food Systems, 4, Article 63. https://doi.org/10.3389/fsufs.2020.00063 [Google Scholar] [Crossref]

36. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302 [Google Scholar] [Crossref]