Determinants of beekeepers’ behavioral intention to adopt digital platforms
PDF

Keywords

beekeeping
behavioral intention
digital platform adoption
information systems
honey value chains

How to Cite

Maruszewska, E.W., Ziemba, E.W. and Karmańska, A. (2026) “Determinants of beekeepers’ behavioral intention to adopt digital platforms”, Economics and Environment, 96(1), p. 1284. doi:10.34659/eis.2026.96.1.1284.

Abstract

The beekeeping industry faces several challenges, including fraudulent honey production, market pressure, growing traceability requirements, and fragmented communication among stakeholders. Digital solutions can support market transparency, but they cannot eliminate fraudulent practices on their own without coherent legal regulations and analytical methods enabling the verification of product authenticity. This study explores beekeepers’ intention to adopt digital platforms for honey traceability and customer communication. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), we analyzed behavioral intention through performance expectancy, effort expectancy, and facilitating conditions. We also extended UTAUT by incorporating strategic benefits associated with apiary operations and beekeepers' willingness to share information. A structured survey was conducted among Polish beekeepers between August and October 2024 (n = 949), and Partial Least Squares Structural Equation Modeling was used to test hypotheses. Results confirm that performance expectancy, effort expectancy, willingness to share information, and strategic benefits significantly predict behavioral intention to adopt digital platforms. These findings suggest that platform developers and policymakers should emphasize economic returns and effective communication tools when promoting digital solutions in beekeeping.

PDF

References

Ammann, J., Walter, A., & El Benni, N. (2022). Adoption and perception of farm management information systems by future Swiss farm managers. Journal of Rural Studies, 89, 298–305. https://doi.org/10.1016/j.jrurstud.2021.12.008

Bertoglio, R., Corbo, C., Renga, F. M., & Matteucci, M. (2021). The digital agricultural revolution: A bibliometric analysis literature review. IEEE Access, 9, 134762-134782. https://doi.org/10.1109/ACCESS.2021.3115258

Bilík, S., Bostik, O., Kratochvila, L., Ligocki, A., Pončák, M., Zemčík, T., Richter, M., Janáková, I., Honec, P., & Horák, K. (2023). Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey. (CoRR, abs/2208.00085). https://arxiv.org/abs/2208.00085

Birner, R., Daum, T., & Pray, C. (2021). Who drives the digital revolution in agriculture? A review of supply side trends, players and challenges. Applied Economic Perspectives and Policy, 43(4), 1260–1285. https://doi.org/10.1002/aepp.13145

Camilleri, M. A. (2019). The SMEs’ technology acceptance of digital media for stakeholder engagement. Journal of Small Business and Enterprise Development, 26(4), 504–521. https://doi.org/10.1108/JSBED-02-2018-0042

Crane, E. (2000). The World History of Beekeeping and Honey Hunting. Routledge.

Danieli, P. P., & Lazzari, F. (2022). Honey traceability and authenticity: Review of current methods. Journal of Apicultural Science, 66(2), 101-119. https://doi.org/10.2478/jas-2022-0012

Dissanayake, C. A. K., Jayathilake, W., Wickramasuriya, H. V. A., Dissanayake, U., Kopiyawattage, K. P. P., & Wasala, W. M. C. B. (2022). Theories and Models of Technology Adoption in Agricultural Sector. Human Behavior and Emerging Technologies, 9258317. https://doi.org/10.1155/2022/9258317

Dong, Y., Ahmad, S. F., Irshad, M., Al-Razgan, M., Ali, Y. A., & Awwad, E. M. (2023). The digitalization paradigm: Impacts on agri-food supply chain profitability and sustainability. Sustainability, 15(21), 15627. https://doi.org/10.3390/su152115627

Engebretson, J. M., Nelson, K. C., Steinhauer, N., Rennich, K., Spivak, M., & van Engelsdorp, D. (2022). Perceptions of honey bee management information sources among backyard and sideliner beekeepers in the United States. Journal of Rural Studies, 96, 190–197. https://doi.org/10.1016/j.jrurstud.2022.10.020

Etxegarai‑Legarreta, O. & Sanchez‑Famoso, V. (2022). The Role of Beekeeping in the Generation of Goods and Services: The Interrelation between Environmental, Socioeconomic, and Sociocultural Utilities. Agriculture, 12(4), 551. https://doi.org/10.3390/agriculture12040551

European Commission (2023). Coordinated Action “From the Hives”. Sampling, investigations and results. https://food.ec.europa.eu/system/files/2023-03/official-controls_food-fraud_2021-2_honey_report_euca.pdf

Fadeyi, O. A., Ariyawardana, A., & Aziz, A. A. (2022). Factors influencing technology adoption among smallholder farmers: a systematic review in Africa. Journal of Agriculture and Rural Development in the Tropics and Subtropics, 123(1), 13-30. https://doi.org/10.17170/kobra-202201195569

Finlay-Smits, S., Ryan, A., de Vries, J. R., & Turner, J. (2023). Chasing the honey money: Transparency, trust, and identity crafting in the Aotearoa New Zealand mānuka honey sector. Journal of Rural Studies, 100, 103004. https://doi.org/10.1016/j.jrurstud.2023.03.012

Fitz, L. R. G., & Scheeg, J. (2023). Small businesses participating in digital platform ecosystems: A descriptive literature review. In: Maślankowski, J., Marcinkowski, B., & Rupino da Cunha, P. (Eds.) Digital Transformation. PLAIS EuroSymposium 2023. Lecture Notes in Business Information Processing, 495. Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-031-43590-4_3

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Fu, S., Han, Z., & Huo, B. (2017). Relational enablers of information sharing: Evidence from Chinese food supply chains. Industrial Management & Data Systems, 117(5), 838–852. https://doi.org/10.1108/IMDS-04-2016-0144

García, N. L. (2018). The current situation on the international honey market. Bee World, 95(3), 89–94. https://doi.org/10.1080/0005772X.2018.1483814

Giua, C., Materia, V.C. & Camanzi, L. (2022). Smart farming technologies adoption: Which factors play a role in the digital translation? Technology in Society, 68, 101869. https://doi.org/10.1016/j.techsoc.2022.101869

Guiné, R. P. F., Costa, C. A., Correia, P., Costa, D., Cardoso, A. P., Figueiredo, A. C., & Ferreira, M. (2021). The beekeeping and honey production practices and the characteristics of the beekeepers in different countries across the world. Foods, 10(5), 1096. https://doi.org/10.3390/foods10051096

Hair, J. F., Hult, G. T., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hamza, A. S., Tashakkori, R., Underwood, B., O’Brien, W., & Campell, C. (2023). BeeLive: The IoT platform of Beemon monitoring and alerting system for beehives. Smart Agricultural Technology, 6, 100331. https://doi.org/10.1016/j.atech.2023.100331

Harring, J. R., Weiss, B. A., & Li, M. (2015). Assessing spurious interaction effects in structural equation modeling. Educational and Psychological Measurement, 75(5), 721-738. https://doi.org/10.1177/0013164414565007

Jonkman, J., Badraoui, I., & Verduijn, T. (2022). Data sharing in food supply chains and the feasibility of cross-chain data platforms for added value. Transportation Research Procedia, 67, 21–30. https://doi.org/10.1016/j.trpro.2022.12.031

Kamilaris, A., Fonts, A., & Prenafeta-Boldú, F. X. (2019). The rise of blockchain technology in agriculture and food supply chains. https://arxiv.org/pdf/1908.07391

Karmańska, A., Ziemba, E. W., Maruszewska, E. W., & Jarka, S. (2025). Socio-demographic factors influencing adoption of digital technologies in beekeeping. Journal of Apicultural Science, 69(1), 29–41. https://doi.org/10.2478/jas-2025-0005

Knierim, A., Kernecker, M., Erdle, K., Kraus, T., Borgers, F. & Wurbs, A. (2019). Smart farming technology innovations – Insights and reflections from the German Smart-AKIS hub. NJAS - Wageningen Journal of Life Sciences, 90-91. https://doi.org/10.1016/j.njas.2019.100314

Krishnasamy, V., Sridhar, N., & Niranjan, L. (2023). An IoT-based beehive monitoring system for real-time monitoring of Apis cerana indica colonies. Sociobiology, 70(4), e9352. https://doi.org/10.13102/sociobiology.v70i4.9352

Langer, G., Schulze, H., & Kühl, S. (2024). From intentions to adoption: Investigating the attitudinal and emotional factors that drive IoT sensor use among dairy farmers. Smart Agricultural Technology, 7, 100404. https://doi.org/10.1016/j.atech.2024.100404

Li, J. Q., Sikora, R., & Shaw, M. (2006). A strategic analysis of inter-organizational information sharing. Decision Support Systems, 42(1), 251–266. https://doi.org/10.1016/j.dss.2004.11.003

Li, L., Min, X., Guo, J., & Wu, F. (2024). The influence mechanism analysis on the farmers’ intention to adopt Internet of Things based on UTAUT-TOE model. Scientific Reports, 14, Article 15016. https://doi.org/10.1038/s41598-024-65415-4

Li, S. H., & Lin, B. S. (2006). Accessing information sharing and information quality in supply chain management. Decision Support Systems, 42(3), 1641–1656. https://doi.org/10.1016/j.dss.2005.03.008

Lin, J., Shen, Z., Zhang, A., & Chai, Y. (2018). Blockchain and IoT based food traceability for smart agriculture. In Proceedings of the 3rd International Conference on Crowd Science and Engineering (ICCSE'18) (Article 3, pp. 1–6). Association for Computing Machinery. https://doi.org/10.1145/3265689.3265692

Marzi, G., Marrucci, A., Vianelli, D., & Ciappei, C. (2023). B2B digital platform adoption by SMEs and large firms: Pathways and pitfalls. Industrial Marketing Management, 114, 80–93. https://doi.org/10.1016/j.indmarman.2023.08.002

Narcia-Macias, C. I., Guardado, J., Rodriguez, J., Rampersad Ammons, J., Enriquez, E., & Kim, D. C. (2023). IntelliBeeHive: An Automated Honey Bee, Pollen, and Varroa Destructor Monitoring System. (arXiv:2309.08955) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2309.08955

Ornelas Herrera, S. I., Baba, Y., Erraach, Y., Ouertani, E., Arfa, L., Çamoğlu, S. M., de-Magistris, T., & Kallas, Z. (2025). Analysing blockchain adoption in beekeeping: Application of theoretical models and their effectiveness. Frontiers in Sustainable Food Systems, 9, 1566341. https://doi.org/10.3389/fsufs.2025.1566341

Otter, V., & Robinson, D. M. (2024). Transparency and changing stakeholder roles in the digital age of sustainable agri-food supply chain networks. Frontiers in Sustainable Food Systems, 8, 1449684. https://doi.org/10.3389/fsufs.2024.1449684

Pivoto, D., Waquil, P. D., Talamini, E., Finocchio, C. P. S., Dalla Corte, V. F. & de Vargas Mores, G. (2018). Scientific development of smart farming technologies and their application in Brazil. Information Processing in Agriculture, 5(1), 21-32. https://doi.org/10.1016/j.inpa.2017.12.002

Rajala, A., & Hautala-Kankaanpää, T. (2023). Exploring the effects of SMEs’ platform-based digital connectivity on firm performance. Journal of Business & Industrial Marketing, 38(13), 15–30. https://doi.org/10.1108/JBIM-01-2022-0024

Reissig, L., Wiseman, L., & Cockburn, M. (2024). Farmers and their data: Evaluating the Swiss conception of data sharing through the lens of digital farming. Journal of Rural Studies, 111, 103390. https://doi.org/10.1016/j.jrurstud.2024.103390

Ringle, C. M., Wende, S., & Becker, J.-M. (2024). SmartPLS 4. SmartPLS GmbH. https://www.smartpls.com

Romera, A. J., Sharifi, M. & Charters, S. (2024). Digitalization in agriculture: Towards an integrative approach. Computers and Electronics in Agriculture, 219, 108817. https://doi.org/10.1016/j.compag.2024.108817

Ronaghi, M. H., & Forouharfar, A. (2020). A contextualized study of the usage of the Internet of Things (IoTs) in smart farming in a typical Middle Eastern Country within the context of Unified Theory of Acceptance and Use of Technology Model (UTAUT). Technology in Society, 63, 101415. https://doi.org/10.1016/j.techsoc.2020.101415

Roy, M., & Medhekar, A. (2025). Transforming smart farming for sustainability through agri-tech innovations: Insights from the Australian agricultural landscape. Farming system, 100165. https://doi.org/10.1016/j.farsys.2025.100165

Uyar, H., Karvelas, I., Rizou, S., & Fountas, S. (2024). Data value creation in agriculture: A review. Computers and Electronics in Agriculture, 227, 109602. https://doi.org/10.1016/j.compag.2024.109602

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

Verbeke, W., Diallo, M. A., van Dooremalen, C., Schoonman, M., Williams, J. H., Van Espen, M., D’Haese, M., & de Graaf, D. C. (2024). European beekeepers’ interest in digital monitoring technology adoption for improved beehive management. Computers and Electronics in Agriculture, 227, 109556. https://doi.org/10.1016/j.compag.2024.109556

Ziemba, E. W., Maruszewska, E. W., Karmańska, A., Aydın, M. N., & Aydın, Ş. (2026). Critical digital data enabling traceability for smart honey value chains. Journal of Computer Information Systems, 66(1), 109-122. https://doi.org/10.1080/08874417.2025.2469092

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Copyright (c) 2026 Economics and Environment

Downloads

Download data is not yet available.