TÜKETİCİ OLARAK ÇİFTÇİLER: İKİLİ MODERATÖRLÜ ARABULUCULUK MODELİYLE UTAUT

Year 2025, Issue: 46, 77 - 92, 12.02.2025

Sefa Emre Yılmazel

https://doi.org/10.18092/ulikidince.1504428

Abstract

Çalışmanın amacı, çiftçiler tarafından temiz ve enerji verimli uygulamaların benimsenmesini ve uygulanmasını etkileyen faktörlerin belirlenmesidir. Bu nedenle UTAUT kapsamında geliştirilen model doğrultusunda iki moderatör değişkenin (çevresel kaygı, finansal fayda) temiz üretim ve enerji verimli üretim uygulamaları için fark yaratıp yaratmadığı araştırılmıştır. Temiz üretim için 400, enerji verimli üretim için ise 400 katılımcıdan veri toplandı. Elde edilen veriler Hayes'in geliştirdiği Process Macro model 4 ve model 21 ile analiz edilmiştir. Sonuç olarak her iki veride de UTAUT değişkenlerinin çiftçilerin benimseme niyeti üzerinde anlamlı etkiye sahip olduğu görülmüştür. Ayrıca UTAUT değişkenleri ile kullanım davranışı arasındaki ilişkide benimseme niyetinin düzenleyici etkisi kanıtlanmıştır. Ayrıca araştırmada her iki moderatör değişkenin etkisi ortaya konmuştur. Çevresel kaygı, temiz üretimde performans beklentisi, çaba beklentisi ve kolaylaştırıcı koşullar ile benimseme davranışı arasında düzenleyici bir etkiye sahiptir. Finansal faydalar, enerji verimli üretimde UTAUT değişkenlerinin dördü için de benimseme niyeti ve kullanım davranışı arasında önemli bir düzenleyici etkiye sahiptir.

Keywords

UTAUT, Benimseme Davranışı, İkili Moderatörlü Aracılık, Temiz Üretim, Enerji Verimli Üretim

FARMERS AS A CONSUMERS: UTAUT WITH DUAL MODERATED MEDIATION MODEL

Abstract

The purpose of the study is to determine the factors that affect the adoption and implementation of clean and energy efficient practices by farmers. For this reason, in line with the model developed within the scope of UTAUT, it was investigated whether two moderator variables (environmental concern, financial benefits) make a difference for clean and energy practices. Data were collected from 400 participants for clean production and 400 participants for energy-efficient production. The data obtained were analyzed with Process Macro model 4 and model 21 developed by Hayes. As a result, it was seen that the UTAUT variables had a significant effect on farmers' adoption intention in both data. In addition, the moderating effect of adoption intention on the relationship between UTAUT variables and usage behavior was proven. Furthermore, the effect of both moderator variables in the study was revealed. While environmental concern has a moderating effect between performance expectancy, effort expectancy and facilitating conditions and adoption behavior in the clean production. Financial benefits has a significant moderating effect between adoption intention and usage behavior for all four of the UTAUT variables in the energy efficient production.

Keywords

UTAUT, Adoption Behavior, Dual Moderated Mediation, Cleaner Production, Energy Efficient Production

References

• Abbad, M. M. (2021). Using the UTAUT Model to Understand Students’ Usage of E-Learning Systems in Developing Countries. Education and information technologies, 26(6), 7205-7224.
• Barbosa Junior, M., Pinheiro, E., Sokulski, C. C., Ramos Huarachi, D. A., & de Francisco, A. C. (2022). How to Identify Barriers to the Adoption of Sustainable Agriculture? A Study Based on a Multi-Criteria Model. Sustainability, 14(20), 13277.
• Cachero-Martínez, S. (2020). Consumer Behaviour towards Organic Products: The Moderating Role of Environmental Concern. Journal of Risk and Financial Management, 13(12), 330.
• Chaveesuk, S., Chaiyasoonthorn, W., Kamales, N., Dacko-Pikiewicz, Z., Liszewski, W., & Khalid, B. (2023). Evaluating The Determinants of Consumer Adoption of Autonomous Vehicles in Thailand—An extended UTAUT model. Energies, 16(2), 855.
• Da Silva, P. C., de Oliveira Neto, G. C., Correia, J. M. F., & Tucci, H. N. P. (2021). Evaluation of Economic, Environmental and Operational Performance of The Adoption of Cleaner Production: Survey in Large Textile Industries. Journal of Cleaner Production, 278, 123855.
• Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory And Results, [doctoral dissertation, MIT Sloan School of Management]. Cambridge, MA. Retrieved from http://dspace.mit.edu/handle/1721.1/ 15192
• 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
• De Canio, F., Martinelli, E., and Endrighi, E. (2021). Enhancing Consumers’ Proenvironmental Purchase Intentions: The Moderating Role of Environmental Concern. Int. J. Retail Distrib. Manag. 49, 1312–1329.
• FAOSTAT. (2022). World Food and Agriculture – Statistical Yearbook 2022. Rome. https://doi.org/10.4060/cc2211en
• Fernandez L., (2023). Global Renewable Energy Market Size 2021-2030. Statista Derived from https://www.statista.com/statistics/1094309/renewable-energy-market-size-global/
• Foroughi, B., Nhan, P. V., Iranmanesh, M., Ghobakhloo, M., Nilashi, M., & Yadegaridehkordi, E. (2023). Determinants of Intention to Use Autonomous Vehicles: Findings From PLS-SEM and ANFIS. Journal of Retailing and Consumer Services, 70, 103158.
• Gabriel, A., & Gandorfer, M. (2023). Adoption of Digital Technologies in Agriculture—An Inventory in a European Small-Scale Farming Region. Precision Agriculture, 24(1), 68-91.
• Giua, C., Materia, V. C., & Camanzi, L. (2022). Smart Farming Technologies Adoption: Which Factors Play a Role in The Digital Transition?. Technology in Society, 68, 101869.
• Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., Ray, S., ... & Ray, S. (2021). Evaluation of Reflective Measurement Models. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, 75-90.
• Hair, J., Blake, W., Babin, B., & Tatham, R. (2006). Multivariate Data Analysis. New Jersey: Prentice Hall.
• Han, M. S., Hampson, D. P., Wang, Y., & Wang, H. (2022). Consumer Confidence and Green Purchase Intention: An Application of The Stimulus-Organism-Response Model. Journal of Retailing and Consumer Services, 68, 103061.
• Hayes, A. F. (2022). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Vol. 3). The Guilford Press.
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
• Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2021). A Meta-Analysis of The UTAUT Model in The Mobile Banking Literature: The Moderating Role of Sample Size And Culture. Journal of Business Research, 132, 354-372.
• Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and Managing The Threat of Common Method Bias: Detection, Prevention And Control. Tourism Management, 86, 104330.
• MacKenzie, S. B., & Podsakoff, P. M. (2012). Common Method Bias in Marketing: Causes, Mechanisms, And Procedural Remedies. Journal of Retailing, 88(4), 542-555.
• Manrai, R., & Gupta, K. P. (2020). Integrating Utaut with Trust and Perceived Benefits to Explain User Adoption of Mobile Payments. In Strategic system assurance and business analytics (pp. 109-121). Singapore: Springer Singapore.
• Michels, M., Bonke, V., Wever, H., & Musshoff, O. (2024). Understanding Farmers' Intention to Buy Alternative Fuel Tractors in German Agriculture Applying The Unified Theory of Acceptance and Use of Technology. Technological Forecasting and Social Change, 203, 123360.
• Molina-Maturano, J., Verhulst, N., Tur-Cardona, J., Güereña, D. T., Gardeazábal-Monsalve, A., Govaerts, B., & Speelman, S. (2021). Understanding Smallholder Farmers’ Intention to Adopt Agricultural Apps: The Role of Mastery Approach and Innovation Hubs in Mexico. Agronomy, 11(2), 194.
• Nguyen, H. N., & Tran, M. D. (2022). Stimuli to Adopt E-Government Services During Covid-19: Evidence From Vietnam. Innovative Marketing, 18(1), 12.
• Nguyen, N., & Drakou, E. G. (2021). Farmers Intention to Adopt Sustainable Agriculture Hinges on Climate Awareness: The Case of Vietnamese Coffee. Journal of cleaner production, 303, 126828.
• Nowak, B. (2021). Precision Agriculture: Where Do We Stand? A Review of The Adoption of Precision Agriculture Technologies on Field Crops Farms in Developed Countries. Agricultural Research, 10(4), 515-522.
• Puriwat, W., & Tripopsakul, S. (2021). Explaining Social Media Adoption for A Business Purpose: An Application of The UTAUT Model. Sustainability, 13(4), 2082.
• Ricart, S., Gandolfi, C., & Castelletti, A. (2023). Climate Change Awareness, Perceived Impacts, and Adaptation From Farmers’ Experience And Behavior: A Triple-Loop Review. Regional Environmental Change, 23(3), 82.
• Rizzo, G., Migliore, G., Schifani, G., & Vecchio, R. (2024). Key Factors Influencing Farmers’ Adoption of Sustainable Innovations: A Systematic Literature Review and Research Agenda. Organic Agriculture, 14(1), 57-84.
• Rübcke von Veltheim, F., Theuvsen, L., & Heise, H. (2021). German Farmers’ Intention to Use Autonomous Field Robots: A PLS-Analysis. Precision agriculture, 1-28.
• Sewandono, R. E., Thoyib, A., Hadiwidjojo, D., & Rofiq, A. (2023). Performance Expectancy of E-Learning on Higher Institutions of Education Under Uncertain Conditions: Indonesia Context. Education and information technologies, 28(4), 4041-4068.
• Shi, Y., Siddik, A. B., Masukujjaman, M., Zheng, G., Hamayun, M., & Ibrahim, A. M. (2022). The Antecedents of Willingness to Adopt and Pay for The Iot in The Agricultural Industry: An Application of The UTAUT 2 Theory. Sustainability, 14(11), 6640.
• Thomas, F. B. (2022). The Role of Purposive Sampling Technique As A Tool for Informal Choices in A Social Sciences in Research Methods. Just Agriculture, 2(5), 1-8.
• Thompson, B., Leduc, G., Manevska‐Tasevska, G., Toma, L., & Hansson, H. (2024). Farmers' Adoption of Ecological Practices: A Systematic Literature Map. Journal of Agricultural Economics, 75(1), 84-107.
• Triandini, E., Wijaya, I. G. N. S., Suniantara, I. K. P., Wulandari, R., Pratami, W. C. A., Djarkasih, A. R., ... & Larasati, N. (2023, March). Analysis Adoption of Information Technology Using The UTAUT Method on Off-Taker Poultry Farmers in Indonesia. In Proceedings of the 13th Annual International International Conference on Industrial Engineering and Operations Management, Manila, Philippines (pp. 6-9).
• Twum, K. K., Ofori, D., Keney, G., & Korang-Yeboah, B. (2022). Using The UTAUT, Personal Innovativeness and Perceived Financial Cost to Examine Student’s Intention to Use E-Learning. Journal of Science and Technology Policy Management, 13(3), 713-737.
• Utomo, P., Kurniasari, F., & Purnamaningsih, P. (2021). The Effects of Performance Expectancy, Effort Expectancy, Facilitating Condition, and Habit on Behavior Intention in Using Mobile Healthcare Application. International Journal of Community Service & Engagement, 2(4), 183-197.
• Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of The Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
• Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.
• Xie, K., Zhu, Y., Ma, Y., Chen, Y., Chen, S., & Chen, Z. (2022). Willingness of Tea Farmers to Adopt Ecological Agriculture Techniques Based on The UTAUT Extended Model. International Journal of Environmental Research and Public Health, 19(22), 15351.
• Yaşlıoğlu, M., & Yaşlıoğlu, D. T. (2020). How and When to Use Which Fit Indices? A Practical And Critical Review of The Methodology. Istanbul Management Journal, (88), 1-20.
• Zameer, H., Wang, Y., & Yasmeen, H. (2020). Reinforcing Green Competitive Advantage through Green Production, Creativity and Green Brand Image: Implications for Cleaner Production in China. Journal of cleaner production, 247, 119119.
• Zhang, S., Guo, Y., Zhao, H., Wang, Y., Chow, D., & Fang, Y. (2020). Methodologies of Control Strategies for Improving Energy Efficiency in Agricultural Greenhouses. Journal of Cleaner Production, 274, 122695.
• Zhao, J., Liu, D., & Huang, R. (2023). A Review of Climate-Smart Agriculture: Recent Advancements, Challenges, and Future Directions. Sustainability, 15(4), 3404.