Determinants of Continued Use of Virtual Livestock Marketplaces: An Extended UTAUT2 Model of Farm Productivity and Business Sustainability among Ruminant Farmers in Jabodetabek

Authors

  • Ummi Endah Kiranastuti IPB University, Bogor, Indonesia
  • Ma'mun Sarma IPB University, Bogor, Indonesia
  • I Made Sumertajaya IPB University, Bogor, Indonesia

DOI:

https://doi.org/10.38035/gijea.v4i4.1287

Keywords:

UTAUT2, SEM PLS, Virtual Livestock Market, Individual Factors Moderation, Ruminant Farmers, Farm Productivity, Agribusiness Sustainability

Abstract

Inefficiencies and middleman price suppression in traditional livestock supply chains necessitate digital transformation in smallholder agriculture. This study analyzes the determinants of virtual livestock market continued use intention among existing smallholder ruminant farmers in Jabodetabek by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with Individual Factors (age and income) moderation, and evaluates its downstream impacts on farm productivity and sustainability. Survey data from 200 smallholders selected via quota sampling were analyzed using SEM-PLS. The empirical results indicate that behavioral intention is substantially explained (R² = 76.7%), with Hedonic Motivation emerging as the primary driver, followed by Effort Expectancy, Habit, Price Value, Social Influence, and Performance Expectancy. Facilitating Conditions and direct Individual Factors are non-significant due to peri-urban infrastructure saturation, although Individual Factors significantly moderate six UTAUT2 adoption pathways. Furthermore, behavioral intention strongly drives actual use behavior (0.715), which is positively associated with farm productivity (R² = 52.0%) and multidimensional sustainability (R² = 47.5%). These findings highlight that user-friendly, engaging, and community-validated digital platforms are vital to strengthening smallholder agribusiness resilience and biosecurity.

References

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110.

Al-Emran, M. (2023). Beyond technology acceptance: Development and evaluation of technology-environmental, economic, and social sustainability theory. Technology in Society, 75, 102383.

Amam, A., Jadmiko, M. W., Harsita, P. A., & Alwafa, A. S. (2025). Analisis fluktuasi harga daging sapi di Provinsi Jawa Timur periode 2019–2023. Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis, 11(2), 2321–2330.

Asosiasi Penyelenggara Jasa Internet Indonesia. (2023). Survei penetrasi internet Indonesia 2023.

Badan Pusat Statistik. (2023). Rekapitulasi data populasi ternak ruminansia Jabodetabek.

Badan Pusat Statistik. (2024). Produk domestik bruto atas dasar harga berlaku menurut lapangan usaha.

Bambio, Y., Deb, A., & Kazianga, H. (2022). Exposure to agricultural technologies and adoption: The West Africa Agricultural Productivity Program in Ghana, Senegal and Mali. Food Policy, 113, 102288.

Blocher, E. J., Chen, K. H., & Lin, T. W. (2000). Manajemen biaya (S. Ambarriani, Penerj.). Salemba Empat.

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.

Fauzi, M. R. (2025). Digital transformation in Indonesian agriculture: Enhancing supply chain performance in the era of smart farming 2025. Journal of Economics and Social Sciences, 4(2), 600–605.

Febrianto, N., Hartono, B., Nugroho, E., Kusumastuti, A. E., Winarto, P. S., Akhiroh, P., Susilawati, T., Yekti, A. P. A., Utami, P., Ramli, N. N., & Helmi, M. (2025). The effects of foot and mouth disease on the profitability of smallholder dairy farms: Evidence from East Java, Indonesia. Indonesian Journal of Animal Science, 35(1), 138–151.

Food and Agriculture Organization of the United Nations. (2023). e-Agriculture national strategy: Master plan for agricultural digitalization.

Gantini, T., Azzahra, C. N. W., Sumawati, D., & Roswinna, W. (2025). The application of e-commerce and digital marketing strategies in marketing agricultural products in Indonesia. Journal of Innovation and Research in Agriculture, 4(1), 31–39.

Geng, W., Liu, L., Zhao, J., Kang, X., & Wang, W. (2024). Digital technologies adoption and economic benefits in agriculture: A mixed-methods approach. Sustainability, 16(11), 4431.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.

Hasanah, N., Prasetyo, B., Nurkholis, Fitri, Z. E., Riansyah, S., Sono, S. H., Prihatiana, D., Wahyono, N. D., & Haryuni, N. (2025). Efficiency of beef cattle supply chain management using digital marketing. International Journal of Technology, Food and Agriculture (TEFA), 2(2), 92–102.

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.

Hidayat, A. R., Alifah, N., Astuti, A. W., Solehudin, Cahya, M. N., & Lutfia, L. (2025). Utilization of innovation in digital marketing: Qualitative study of SMEs in Indonesia. Multidisciplinary Science Journal, 7(1), 1–6.

Hussam, H., Rombe, E., Parani, S. B. D., & Palawa, M. R. (2025). The role of digital marketing in enhancing the goat farming economy: A case study of CV. Prima Mandiri Abadi. International Journal of Development Economics Research, 6(1), 228–241.

Kai, C., Ping, W., Siyu, K., & Chunzhen, Z. (2025). Breaking through the bottleneck in the promotion of artificial intelligence in agriculture: An analysis of the moderating role of individuals' heterogeneity among farmers in Shandong Province. Frontiers in Sustainable Food Systems, 9, 1621832.

Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705–737.

Michels, M., Bonke, V., & Musshoff, O. (2020). Understanding the adoption of smartphone apps in crop protection. Precision Agriculture, 21(6), 1209–1226.

Molina-Maturano, J., Verhulst, N., Tur-Cardona, J., Guereña, D. T., Gardeazabal Monsalue, A., & De Steur, H. (2021). Understanding smallholder farmers' intention to adopt agricultural apps. Agronomy, 11(2), 215.

Pienwisetkaew, T., Wongsaichia, S., Pinyosap, B., Prasertsil, S., Poonsakpaisarn, K., & Ketkaew, C. (2023). The behavioral intention to adopt circular economy-based digital technology for agricultural waste valorization. Foods, 12(12), 2341.

Saragih, B. C., Sutrisno, J., & Fajarningsih, R. U. (2023). Analisis faktor-faktor yang mempengaruhi permintaan daging sapi di Provinsi DKI Jakarta. AGRISTA, 11(2), 21–31.

Sarkar, A., Azim, J. A., Asif, A. Al., Qian, L., & Peau, A. K. (2021). Structural equation modeling for indicators of sustainable agriculture: Prospective of a developing country's agriculture. Land Use Policy, 109, 105638.

Schukat, S., & Heise, H. (2021). Towards an understanding of the behavioral intentions and actual use of smart products among German farmers. Sustainability, 13(12), 6666.

Sugandini, D., Effendi, M. I., Sugiarto, B., Kundarto, M., Hardiastuti, S., & Kawuryan, E. (2023). Resistance to agricultural commercialization with lack of marketing digital adoption in Indonesia's Dieng Plateau. International Journal of Sustainable Development and Planning, 18(6), 1715–1724.

Sugiyono. (2020). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.

Sujarwanta, R. O., Afidah, U., Suryanto, E., Triyannanto, E., Hoffman, L. C., & Rusman. (2024). Review: Goat and sheep meat production in Indonesia. Sustainability, 16(11), 4448.

Thimthong, S., Musikapun, P., Tarai, N., Saenjio, T., & Khanthonghao, B. (2026). Technology adoption among Thai farmers: The mediating role of resistance to change in a UTAUT2 framework. Journal of Logistics and Digital Supply Chain, 4(1), 1–13.

Triatmojo, A., Muzayyanah, M. A. U., Syahlani, S. P., & Guntoro, B. (2024). Demographic targeting of users in mobile applications for livestock digital marketing among smallholder cattle farmers. Agrisocionomics: Jurnal Sosial Ekonomi dan Kebijakan Pertanian, 8(2), 602–613.

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.

Wahyuni, N. M., Pratama, A. R., & Shihah, H. D. (2025). Introduction to digital business for marketing livestock products to smallholder farmers in Pakintelan Village, Gunung Pati District, Semarang. Farmers: Journal of Community Services, 6(2), 264–269.

Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming: A review. Agricultural Systems, 153, 69–80.

Yahya, S., & Sugiyanto, C. (2020). Indonesian demand for online shopping: Revisited. Journal of Indonesian Economy and Business, 35(3), 188–203.

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.

Published

2026-10-31

How to Cite

Kiranastuti, U. E., Sarma, M., & Sumertajaya, I. M. (2026). Determinants of Continued Use of Virtual Livestock Marketplaces: An Extended UTAUT2 Model of Farm Productivity and Business Sustainability among Ruminant Farmers in Jabodetabek. Greenation International Journal of Economics and Accounting, 4(4), 1549–1562. https://doi.org/10.38035/gijea.v4i4.1287