Socio-environmental systems in technology adoption in animal husbandry in South-East Asia: A framework synthesis approach

References

• ACIAR. (2022). Smallholder livestock futures in Southeast Asia. [Online]. https://www.aciar.gov.au/sites/default/files/2022-01/LS-2018-107-final-report.pdf
   Google Scholar
• Adesehinwa, A., Okunola, J., & Adewumi, M. (2004). Socio-economic characteristics of ruminant livestock farmers and their production constraints in some parts of South-western Nigeria. Livestock Research for Rural Development, 16(8), 838–36.
   Google Scholar
• Adnan, N., Nordin, S. M., Bahruddin, M. A., & Tareq, A. H. (2019). A state-of-the-art review on facilitating sustainable agriculture through green fertilizer technology adoption: Assessing farmers behavior. Trends in Food Science & Technology, 86, 439–452. https://doi.org/10.1016/j.tifs.2019.02.040
   Web of Science ®Google Scholar
• Ahuja, V. (2013). Asian livestock: Challenges, opportunities and the response. https://cgspace.cgiar.org/server/api/core/bitstreams/5bffc36f-e986-41fb-a284-f45b4f2318f3/content
   Google Scholar
• Anh, T. S., Knodel, J., Lam, D., & Friedman, J. (1998). Family size and children’s education in Vietnam. Demography, 35(1), 57–70.
   PubMed Web of Science ®Google Scholar
• Ayele, S., Duncan, A., Larbi, A., & Khanh, T. T. (2012, June). Enhancing innovation in livestock value chains through networks: Lessons from fodder innovation case studies in developing countries. Science & Public Policy, 39(3), 333–346. https://doi.org/10.1093/scipol/scs022
   Web of Science ®Google Scholar
• Bantilan, M. C. S., & Padmaja, R. (2008). Empowerment through social capital build-up: Gender dimensions in technology uptake. Experimental Agriculture, 44(1), 61–80.
   Web of Science ®Google Scholar
• Baticados, D. B., Agbayani, R. F., & Quinitio, E. T. (2014). Community-based technology transfer in rural aquaculture: The case of mudcrab scylla serrata nursery in ponds in Northern Samar, Central Philippines, (in English). AMBIO: A Journal of the Human Environment, 43(8), 1047–1058. https://doi.org/10.1007/s13280-014-0528-5
   Google Scholar
• Baumüller, H. (2017). Towards smart farming? Mobile technology trends and their potential for developing country agriculture. In Handbook on ICT in Developing Countries (Vol. 5, p. 20). https://www.taylorfrancis.com/chapters/edit/10.1201/9781003338376-9/towards-smart-farming-mobile-technology-trends-potential-developing-country-agriculture-heike-baum%C3%BCller
   Google Scholar
• Blok, V., & Gremmen, B. (2018). Agricultural technologies as living machines: Toward a biomimetic conceptualization of smart farming technologies. Ethics, Policy & Environment, 21(2), 246–263.
   Web of Science ®Google Scholar
• Bramer, W. M., Rethlefsen, M. L., Kleijnen, J., & Franco, O. H. (2017, July 12). Optimal database combinations for literature searches in systematic reviews: A prospective exploratory study. Systematic Reviews, 6(1), 245. https://doi.org/10.1186/s13643-017-0644-y
   PubMed Web of Science ®Google Scholar
• Brown, B., Paudel, G. P., & Krupnik, T. J. (2021). Visualising adoption processes through a stepwise framework: A case study of mechanisation on the Nepal Terai. Agricultural Systems, 192, 103200. https://doi.org/10.1016/j.agsy.2021.103200
   Web of Science ®Google Scholar
• Brunton, G., Oliver, S., & Thomas, J. (2020). Innovations in framework synthesis as a systematic review method. Research Synthesis Methods, 11(3), 316–330.
   PubMed Web of Science ®Google Scholar
• Budiman, I., & Alta, A. (2022). Technology and knowledge transfers to dairy farms private sector contribution to improve milk production. https://doi.org/10.35497/557427
   Google Scholar
• Budiman, I., & Smits, M. (2020). How do configuration shifts in fragmented energy governance affect policy output? A case study of changing Biogas regimes in Indonesia. Sustainability, 12(4), 1358.
   Web of Science ®Google Scholar
• Caffaro, F., Roccato, M., Cremasco, M. M., & Cavallo, E. (2019). An ergonomic approach to sustainable development: The role of information environment and social-psychological variables in the adoption of agri-environmental innovations. Sustainable Dev, 27(6), 1049–1062. https://doi.org/10.1002/sd.1956
   Web of Science ®Google Scholar
• Carroll, C., Booth, A., Leaviss, J., & Rick, J. (2013). “Best fit” framework synthesis: Refining the method. BMC Medical Research Methodology, 13(1), 37. https://doi.org/10.1186/1471-2288-13-37
   PubMed Web of Science ®Google Scholar
• Christensen, J. (2016). A critical reflection of Bronfenbrenner s development ecology model. Problems of Education in the 21st Century, 69(1), 22–28.
   Google Scholar
• Dewey, A., & Drahota, A. (2016). Introduction to systematic reviews: Online learning module cochrane training,
   Google Scholar
• Eder, L. V., Kontorovich, A. E., Filimonova, I. V., Provornaya, I. V., & Goosen, E. (2017). Regional innovation cluster: Environmental issues and efficient use of resources. International Multidisciplinary Scientific GeoConference: SGEM, Albena, Bulgaria (Vol. 17. pp. 701–708).
   Google Scholar
• Eriksen, M. B., & Frandsen, T. F. (2018). The impact of patient, intervention, comparison, outcome (PICO) as a search strategy tool on literature search quality: A systematic review. Journal of the Medical Library Association: JMLA, 106(4), 420.
   PubMed Web of Science ®Google Scholar
• European, C., R. Directorate-General for, Innovation, Halberg, N., & Westhoek, H. (2019). The added value of a food systems approach in research and innovation : SCAR SWG food systems policy brief. Publications Office.
   Google Scholar
• Fisher, D. K., Norvell, J., Sonka, S., & Nelson, M. J. (2000). Understanding technology adoption through system dynamics modeling: Implications for agribusiness management. The International Food and Agribusiness Management Review, 3(3), 281–296.
   Google Scholar
• Garaway, C. J., Arthur, R. I., Chamsingh, B., Homekingkeo, P., Lorenzen, K., Saengvilaikham, B., & Sidavong, K. (2006, August). A social science perspective on stock enhancement outcomes: Lessons learned from inland fisheries in southern Lao PDR. Fisheries Research, 80(1), 37–45. https://doi.org/10.1016/j.fishres.2006.03.012
   Web of Science ®Google Scholar
• García, J. M. (2020). Theory and practical exercises of system dynamics: Modeling and simulation with vensim PLE. Preface John Sterman. MIT Sloan School of Management.
   Google Scholar
• Gargiulo, J. I., Eastwood, C. R., Garcia, S. C., & Lyons, N. A. (2018). Dairy farmers with larger herd sizes adopt more precision dairy technologies. Journal of Dairy Science, 101(6), 5466–5473. https://doi.org/10.3168/jds.2017-13324
   PubMed Web of Science ®Google Scholar
• Gaur, A., & Kumar, M. (2018). A systematic approach to conducting review studies: An assessment of content analysis in 25 years of IB research. Journal of World Business, 53(2), 280–289. https://doi.org/10.1016/j.jwb.2017.11.003
   Web of Science ®Google Scholar
• Goldstein, J. E., Budiman, I., Canny, A., & Dwipartidrisa, D. (2022). Pandemics and the human-wildlife interface in Asia: Land use change as a driver of zoonotic viral outbreaks. Environmental Research Letters, 17(6), 063009.
   Web of Science ®Google Scholar
• Guerin, L., & Guerin, T. (1994). Constraints to the adoption of innovations in agricultural research and environmental management: A review. Australian Journal of Experimental Agriculture, 34(4), 549–571. https://doi.org/10.1071/EA9940549
   Google Scholar
• Habib-Ur-Rahman, M., Ahmad, A., Raza, A., Hasnain, M. U., Alharby, H. F., Alzahrani, Y. M., Bamagoos, A. A., Hakeem, K. R., Ahmad, S., Nasim, W., Ali, S., Mansour, F., & EL Sabagh, A. (2022, October 10). Impact of climate change on agricultural production; issues, challenges, and opportunities in Asia. Frontiers in Plant Science, 13. https://doi.org/10.3389/fpls.2022.925548
   Web of Science ®Google Scholar
• Hemme, T., & Otte, J. (2010). Status and prospects for smallholder milk production: A global perspective. Rome, Italy: Food and Agriculture Organization of the United Nations (FAO). https://www.cabidigitallibrary.org/doi/full/10.5555/20103254292
   Google Scholar
• Higgins, S., Schellberg, J., & Bailey, J. S. (2019, May). Improving productivity and increasing the efficiency of soil nutrient management on grassland farms in the UK and Ireland using precision agriculture technology. European Journal of Agronomy, 106, 67–74. https://doi.org/10.1016/j.eja.2019.04.001
   Web of Science ®Google Scholar
• Hoang, G. H. (2020, October). Adoption of good agricultural practices by Cattle Farmers in the binh dinh province of Vietnam. Journal of Agricultural Extension, 24(4), 151–160. https://doi.org/10.4314/jae.v24i4.15
   Web of Science ®Google Scholar
• Hoang, H. G. (2020). Exploring farmers’ adoption of VietGAP from systemic perspective: Implication for developing agri-food systems. British Food Journak, Article. 122(12), 3641–3661. https://doi.org/10.1108/BFJ-09-2019-0724
   Web of Science ®Google Scholar
• Hogeveen, H., Klaas, I. C., Dalen, G., Honig, H., Zecconi, A., Kelton, D. F., & Sánchez Mainar, M. (2021). Novel ways to use sensor data to improve mastitis management. Journal of Dairy Science, 104(10), 11317–11332. https://doi.org/10.3168/jds.2020-19097
   PubMed Web of Science ®Google Scholar
• Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., Gagnon, M.P., Griffiths, F., Nicolau, B., O’Cathain, A. & Rousseau, M. C. (2018). The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Education for Information, 34(4), 285–291.
   Web of Science ®Google Scholar
• Houben, V. (2014). Socio cultures of insular southeast Asia: Between history, area and social studies. Transcience, 5(1), 28–35.
   Google Scholar
• IndoDairy. (2020). IndoDairy smallholder household survey (ISHS) ‘farm-to-fact’ series. [Online]. Available. https://www.indodairy.net/en/resources/ishs-factsheets
   Google Scholar
• Indodairy. (2022). Improving milk supply, competitiveness and livelihoods of smallholder dairy chains in Indonesia. https://www.adelaide.edu.au/global-food/research/international-development/indodairy#indodairy-smallholder-household-survey-ishs
   Google Scholar
• Ismail, C. J., Takama, T., Budiman, I., & Knight, M. (2019). Comparative study on agriculture and forestry climate change adaptation projects in Mongolia, the Philippines, and timor leste. In P. Castro, A. Marisa Azul, W. Leal Filho & U. M. Azeiteiro (Eds.), Climate change-resilient agriculture and agroforestry (pp. 413–430). Springer.
   Google Scholar
• Kebebe, E. (2019). Bridging technology adoption gaps in livestock sector in Ethiopia: A innovation system perspective. Technology in Society, 57, 30–37. https://doi.org/10.1016/j.techsoc.2018.12.002
   Web of Science ®Google Scholar
• Khoiriyah, N., Anindita, R., Hanani, N., & Muhaimin, A. W. (2020). Animal food demand in Indonesia: A quadratic almost ideal demand system approach. Agris On-Line Papers in Economics and Informatics, 12(665–2020–1237), 85–97.
   Google Scholar
• Kiptot, E., Hebinck, P., Franzel, S., & Richards, P. (2007). Adopters, testers or pseudo-adopters? Dynamics of the use of improved tree fallows by farmers in western Kenya. Agricultural Systems, 94(2), 509–519.
   Web of Science ®Google Scholar
• Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS-Wageningen Journal of Life Sciences, 90–91, 100315. https://doi.org/10.1016/j.njas.2019.100315
   Web of Science ®Google Scholar
• Knodel, J., Friedman, J., Si Anh, T., & Cuong, B. T. (2000). Intergenerational exchanges in Vietnam: Family size, sex composition, and the location of children. Population studies, 54(1), 89–104.
   PubMed Web of Science ®Google Scholar
• Köksal, Ö., & Tekinerdogan, B. (2019). Architecture design approach for IoT-based farm management information systems. Precision Agriculture, 20(5), 926–958.
   Web of Science ®Google Scholar
• Komaladara, A. A. S. P., Patrick, I., & Hoang, N. (2018). Contract bonus systems to encourage biosecurity adoption on small-scale broiler farms in Indonesia. Animal Production Science, 58(3), 595–600.
   Web of Science ®Google Scholar
• Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3, 33–67. https://doi.org/10.1007/s13194-012-0056-8
   Web of Science ®Google Scholar
• Laksono, A. D., & Wulandari, R. D. (2021). The factors correlate to family size in Indonesia. Aspirasi: Jurnal Masalah-masalah Sosial, 12(1), 1–13.
   Google Scholar
• Langford, E. (2006). Quartiles in elementary statistics. Journal of Statistics Education, 14(3).
   Google Scholar
• Lapar, M. L. A., & Ehui, S. (2003, December). Adoption of dual-purpose forages: Some policy implications. Tropical Grasslands, 37(4), 284–291. https://WOS:000188536400012
   Google Scholar
• Lee, E., Karimi, F., Wagner, C., Jo, H.-H., Strohmaier, M., & Galesic, M. (2019). Homophily and minority-group size explain perception biases in social networks. Nature Human Behaviour, 3(10), 1078–1087. https://doi.org/10.1038/s41562-019-0677-4
   PubMed Web of Science ®Google Scholar
• Lestari, V. S., Natsir, A., Sirajuddin, S. N., Kasim, K., Ali, H. M., Saadah, S., & Mawardi, M. (2012). Factors influencing biosecurity adoption on laying hen farmers. Journal of the Indonesian Tropical Animal Agriculture. 37(4), 302–307. https://doi.org/10.14710/jitaa.37.4.302-307
   Google Scholar
• Lioutas, E. D., Charatsari, C., & De Rosa, M. (2021). Digitalization of agriculture: A way to solve the food problem or a trolley dilemma? Technology in Society, 67, 101744. https://doi.org/10.1016/j.techsoc.2021.101744
   Web of Science ®Google Scholar
• Lisson, S., MacLeod, N., McDonald, C., Corfield, J., Pengelly, B., Wirajaswadi, L., Rahman, R., Bahar, S., Padjung, R., Razak, N., Puspadi, K. D, Sutaryono, Y., Saenong, S., Panjaitan, T., Hadiawati, L., Ash, A., & Brennan, L. (2010, September). A participatory, farming systems approach to improving Bali cattle production in the smallholder crop–livestock systems of Eastern Indonesia. Agricultural Systems, 103(7), 486–497. https://doi.org/10.1016/j.agsy.2010.05.002
   Web of Science ®Google Scholar
• Ly, N. T., Nanseki, T., & Chomei, Y. (2015, September). Determinants of biogas adoption in manure management of Vietnamese household pig production: A case study in Tien Lu District, Hung Yen Province. Journal of the Faculty of Agriculture, Kyushu University, 60(2), 577–581. https://WOS:000362390700040
   Web of Science ®Google Scholar
• Mahindarathne, M., & Min, Q. (2018). Developing a model to explore the information seeking behaviour of farmers. Journal of Documentation, 74, 781–803.
   Web of Science ®Google Scholar
• Mak, S. (2001). Continued innovation in a Cambodian rice-based farming system: Farmer testing and recombination of new elements. Agricultural Systems, 69(1–2), 137–149. https://doi.org/10.1016/s0308-521x(01)00022-1
   Web of Science ®Google Scholar
• Makarapong, D., Tantayanon, S., Gowanit, C., & Inchaisri, C. (2020). Intention to adopt and diffuse innovative ultraviolet light C system to control the growth of microorganisms in raw milk among Thais dairy farmers. Animal Science Journal, 91(1), e13375. https://doi.org/10.1111/asj.13375
   PubMed Web of Science ®Google Scholar
• Maralani, V. (2008). The changing relationship between family size and educational attainment over the course of socioeconomic development: Evidence from Indonesia. Demography, 45, 693–717.
   PubMed Web of Science ®Google Scholar
• Michalk, D. L., Kemp, D. R., Badgery, W. B., Wu, J., Zhang, Y., & Thomassin, P. J. (2019). Sustainability and future food security—A global perspective for livestock production. Land Degradation & Development, 30(5), 561–573.
   Web of Science ®Google Scholar
• Moglia, M., Alexander, K. S., Larson, S., (Giger)-Dray, A., Greenhalgh, G., Thammavong, P., Thephavanh, M., & Case, P. (2020, July). Gendered roles in agrarian transition: A study of lowland rice farming in Lao PDR. Sustainability, 12(13), 5403. https://doi.org/10.3390/su12135403
   Web of Science ®Google Scholar
• Monjardino, M., Philp, J. N. M., Kuehne, G., Phimphachanhvongsod, V., Sihathep, V., & Denton, M. D. (2020, January). Quantifying the value of adopting a post-rice legume crop to intensify mixed smallholder farms in Southeast Asia. Agricultural Systems, 177(102690), 102690. https://doi.org/10.1016/j.agsy.2019.102690
   Google Scholar
• Monteiro, A., Santos, S., & Gonçalves, P. (2021). Precision agriculture for crop and livestock farming—brief review. Animals, 11(8), 2345.
   Web of Science ®Google Scholar
• Mouri, G., & Aisaki, N. (2015). Using land-use management policies to reduce the environmental impacts of livestock farming. Ecological Complexity, 22, 169–177. 06/1/2015. https://doi.org/10.1016/j.ecocom.2015.03.003
   Web of Science ®Google Scholar
• Muller, A., Schader, C., El-Hage Scialabba, N., Brüggemann, J., Isensee, A., Erb, K.H., Smith, P., Klocke, P., Leiber, F., Stolze, M., & Niggli, U. (2017). Strategies for feeding the world more sustainably with organic agriculture. Nature Communications, 8(1), 1–13.
   PubMedGoogle Scholar
• Mutune, J., & Nunow, A. (2018). Community participation in transformation of rural livelihoods and climate smart farming technologies in the semi-arid lands of Kenya. International Journal of Peace and Development Studies, 9(4), 53–59.
   Google Scholar
• Navarro, J. L., & Tudge, J. R. (2022). Technologizing Bronfenbrenner: Neo-ecological theory. Current Psychology, 42, 1–17.
   PubMed Web of Science ®Google Scholar
• Ngo, H. T. (2020). ‘Standing between the flows’: Interactions among neoliberalism, socialism and Confucianism in Vietnamese higher education. In P. Le Ha & D. Ba Ngoc (Eds.), Higher Education in Market-Oriented Socialist Vietnam: New Players, Discourses, and Practices. Cham: Palgrave Macmillan. https://doi.org/10.1007/978-3-030-46912-2_3
   Google Scholar
• Nguyen, L. T., Nanseki, T., & Chomei, Y. (2020, December). The impact of VietGAHP implementation on Vietnamese households’ pig production. Environment, Development and Sustainability, 22(8), 7701–7725. https://doi.org/10.1007/s10668-019-00543-w
   Web of Science ®Google Scholar
• Nhan, D. K., Phong, L. T., Verdegem, M. J. C., Duong, L. T., Bosma, R. H., & Little, D. C. (2007, May). Integrated freshwater aquaculture, crop and livestock production in the Mekong delta, Vietnam: Determinants and the role of the pond. Agricultural Systems, 94(2), 445–458. https://doi.org/10.1016/j.agsy.2006.11.017
   Web of Science ®Google Scholar
• Niles, M. T., Horner, C., Chintala, R., & Tricarico, J. (2019). A review of determinants for dairy farmer decision making on manure management strategies in high-income countries. Environmental Research Letters, 14(5), 053004. 05/3/2019. https://doi.org/10.1088/1748-9326/ab1059
   Web of Science ®Google Scholar
• Njisane, Y. Z., Mukumbo, F. E., & Muchenje, V. (2020, June). An outlook on livestock welfare conditions in African communities - a review. Asian-Australasian Journal of Animal Sciences, 33(6), 867–878. https://doi.org/10.5713/ajas.19.0282
   PubMed Web of Science ®Google Scholar
• Notenbaert, A., Pfeifer, C., Silvestri, S., & Herrero, M. (2017, February). Targeting, out-scaling and prioritising climate-smart interventions in agricultural systems: Lessons from applying a generic framework to the livestock sector in sub-saharan Africa. Agricultural Systems, 151, 153–162. https://doi.org/10.1016/j.agsy.2016.05.017
   PubMed Web of Science ®Google Scholar
• Otte, J., Pica-Ciamarra, U., & Morzaria, S. (2019). A comparative overview of the livestock-environment interactions in Asia and sub-saharan Africa. (In English), Frontiers in Veterinary Science, Review vol. 6. February/22 2019. https://doi.org/10.3389/fvets.2019.00037
   Google Scholar
• Panmethis, W., & Islam, N. (2016). Exploring the development of sustainable livestock innovations: Evidence from Thailand. International Journal of Innovation and Sustainable Development, 10(4), 399–418. https://doi.org/10.1504/IJISD.2016.079583
   Google Scholar
• Parsons, T. (1991). The social system. Psychology Press.
   Google Scholar
• Pathak, H. S., Brown, P., & Best, T. (2019). A systematic literature review of the factors affecting the precision agriculture adoption process. Precision Agriculture, 20(6), 1292–1316. January 12 2019. https://doi.org/10.1007/s11119-019-09653-x
   Web of Science ®Google Scholar
• Phuong, L. T. H., Biesbroek, G. R., Sen, L. T. H., & Wals, A. E. (2018). Understanding smallholder farmers’ capacity to respond to climate change in a coastal community in Central Vietnam. Climate and Development, 10(8), 701–716.
   Web of Science ®Google Scholar
• Phuong, L. T. H., Biesbroek, G. R., Sen, L. T. H., & Wals, A. E. J. (2018). Understanding smallholder farmers’ capacity to respond to climate change in a coastal community in Central Vietnam. Climate and Development, 10(8), 701–716. https://doi.org/10.1080/17565529.2017.1411240
   Web of Science ®Google Scholar
• Phuong, L. T. H., Tuan, T. D., & Phuc, N. T. N. (2019, December). Transformative Social Learning for Agricultural Sustainability and Climate Change Adaptation in the Vietnam Mekong Delta. Sustainability, 11(23), 6775. Art. no. 6775. https://doi.org/10.3390/su11236775
   Web of Science ®Google Scholar
• Pierpaoli, E., Carli, G., Pignatti, E., & Canavari, M. (2013). Drivers of precision agriculture technologies adoption: A literature review. Procedia Technology, 8, 61–69. 01/1/2013. https://doi.org/10.1016/j.protcy.2013.11.010
   Google Scholar
• Pramuwidyatama, M. G., Hogeveen, H., & Saatkamp, H. W. (2020). Understanding the Motivation of Western Java Smallholder Broiler Farmers to uptake measures against highly pathogenic avian influenza (HPAI). Frontiers in Veterinary Science, 7, 362–362. https://doi.org/10.3389/fvets.2020.00362
   PubMed Web of Science ®Google Scholar
• Putra, A. R. S., & Pedersen, S. M. (2018). Biogas Technology Diffusion Among Farmers Through Rural Communication Network: A case from Indonesia. Journal of Rural and Community Development, 13(4), 107–117. [Online]. Available://WOS:000461730300007.
   Google Scholar
• Putra, A. R. S., Pedersen, S. M., & Liu, Z. (2019). Biogas diffusion among small scale farmers in Indonesia: An application of duration analysis. Land Use Policy, Article. 86, 399–405. https://doi.org/10.1016/j.landusepol.2019.05.035
   Web of Science ®Google Scholar
• Razavi, S. (2009). The gendered impacts of liberalization: Towards“Embedded liberalism”? Routledge.
   Google Scholar
• Rice, R. E., & Aydin, C. (1991). Attitudes toward new organizational technology: Network proximity as a mechanism for social information processing. Administrative Science Quarterly, 36, 219–244.
   Web of Science ®Google Scholar
• Richardson, R. B., & Suvedi, M. (2018, July). Assessing the potential for small-scale aquaculture in Cambodia. Environments, 5(7), 76. Art no. 76, https://doi.org/10.3390/environments5070076
   Web of Science ®Google Scholar
• Ritchie, J., Lewis, J., McNaughton Nicholls, C., & Ormston, R. (2014). Qualitative research practice : A guide for social science students and researchers (Second ed.). Sage (in English.
   Google Scholar
• Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.
   Google Scholar
• Ronaghi, M., & Ronaghi, M. H. (2021). Investigating the impact of economic, political, and social factors on augmented reality technology acceptance in agriculture (livestock farming) sector in a developing country. Technology in Society, 67, 101739. 11/1/2021. https://doi.org/10.1016/j.techsoc.2021.101739
   Web of Science ®Google Scholar
• Sadeghi, E., Kappers, C., Chiumento, A., Derks, M., & Havinga, P. (2023). Improving piglets health and well-being: A review of piglets health indicators and related sensing technologies. Smart Agricultural Technology, 5, 100246.
   Google Scholar
• Salmon, G. R., MacLeod, M., Claxton, J. R., Ciamarra, U. P., Robinson, T., Duncan, A., & Peters, A. R. (2020). Exploring the landscape of livestock ‘facts’. Global Food Security, 25, 100329. https://doi.org/10.1016/j.gfs.2019.100329
   PubMedGoogle Scholar
• Sambodo, L. A. A. T., & Nuthall, P. L. (2010). A behavioural approach to understanding semi-subsistence farmers’ technology adoption decisions: The case of improved paddy-prawn system in Indonesia. The Journal of Agricultural Education and Extension, 16(2), 111–129. https://doi.org/10.1080/13892241003651373
   Google Scholar
• Schläpfer, M. (2016). Visions for complexity. Visions for Complexity. Opening Conference of the Complexity Science Hub Vienna, Vienna, Austria.
   Google Scholar
• Scholten, M. T., De Boer, I., Gremmen, B., & Lokhorst, C. (2013). Livestock farming with care: Towards sustainable production of animal-source food. Elsevier.
   Google Scholar
• Shang, L., Heckelei, T., Gerullis, M. K., Börner, J., & Rasch, S. (2021). Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction. Agricultural Systems, 190, 103074. https://doi.org/10.1016/j.agsy.2021.103074
   Web of Science ®Google Scholar
• Shimahata, A., Farghali, M., & Fujii, M. (2020, Factors influencing the willingness of dairy farmers to adopt biogas plants: A case study in Hokkaido, Japan, (in English). Sustainability, 12(18), 7809. https://doi.org/10.3390/SU12187809
   Web of Science ®Google Scholar
• Simelton, E. S., Catacutan, D. C., Dao, T. C., Dam, B. V., & Le, T. D. (2017, February). Factors constraining and enabling agroforestry adoption in Viet Nam: A multi-level policy analysis. Agroforestry Systems, 91(1), 51–67. https://doi.org/10.1007/s10457-016-9906-2
   Web of Science ®Google Scholar
• Singh, C., Dorward, P., & Osbahr, H. (2016). Developing a holistic approach to the analysis of farmer decision-making: Implications for adaptation policy and practice in developing countries. Land Use Policy, 59, 329–343.
   Web of Science ®Google Scholar
• Sirajuddin, S. N., Sudirman, I., Bahar, L. D., Al Tawaha, A. R., & Al-Tawaha, A. R. (2018, August). Social economic factors that affect cattle farmer’s willingness to pay for artificial insemination programs. Bulgarian Journal of Agricultural Science, 24(4), 574–580. https://WOS:000448988600006
   Google Scholar
• Teno, G., Lehrer, K., & Koné, A. (2018). Factors influencing the adoption of new technologies in agriculture in Sub-Saharan Africa: A review of the literature(In French). African Journal of Agriculture Resources Economics, 13(2), 140–151. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050134817&partnerID=40&md5=0241cc43c24b2c8cbd207a646652852a
   Google Scholar
• Tesfa, A., & Mekuriaw, S. (2014). The effect of land degradation on farm size dynamics and crop-livestock farming system in Ethiopia: A review. Open Journal of Soil Science, 4, 1–5.
   Google Scholar
• Tey, Y. S., & Brindal, M. (2012). Factors influencing the adoption of precision agricultural technologies: A review for policy implications. Precision Agriculture, 13(6), 713–730. 12/1/2012. https://doi.org/10.1007/s11119-012-9273-6
   Web of Science ®Google Scholar
• Thapa, G. (2010). Smallholder or family farming in transforming economies of Asia and Latin America: Challenges, and opportunities. international conference on dynamics of rural transformation in emerging economies, New Delhi, India (Vol. 14. pp. 16).
   Google Scholar
• Thapa, G., & Gaiha, R. (2011). Smallholder farming in Asia and the Pacific: Challenges and opportunities. IFAD conference on new directions for smallholder agriculture, Rome, Italy (Vol. 25). International Fund for Agricultural Development Rome.
   Google Scholar
• Ugochukwu, A. I., & Phillips, P. W. B. (2018). Technology adoption by agricultural producers: A review of the literature. In N. Kalaitzandonakes, E. G. Carayannis, E. Grigoroudis, & S. Rozakis (Eds.), From agriscience to agribusiness: Theories, policies and practices in technology transfer and commercialization (pp. 361–377). Springer International Publishing.
   Google Scholar
• Wiesner, K., & Ladyman, J. (2021). Complex systems are always correlated but rarely information processing. Journal of Physics: Complexity, 2(4), 045015.
   Google Scholar
• Zheng, W., Wang, C., Liu, W., Li, B., & Xin, H. (2016). First Asian conference on Precision Livestock Farming (PLF-Asia 2016) held in Beijing, China. International Journal of Agricultural and Biological Engineering, 9(5), 235–236.
   Google Scholar