KnE Social Sciences

ISSN: 2518-668X

The latest conference proceedings on humanities, arts and social sciences.

The Impact of Smart Farming Technology on Agricultural Productivity: Evidence from a Large-scale Database in Thailand

Published date: Nov 19 2024

Journal Title: KnE Social Sciences

Issue title: The 1st International Conference on Creative Design, Business and Society (1st ICCDBS) 2023

Pages: 25–55

DOI: 10.18502/kss.v9i32.17425

Authors:

Bang-Ning HwangDepartment and Graduate Institute of Business Administration, National Yunlin University of Science and Technology

Siriprapha Jitanugoonsiriprapha.jitanugoon@gmail.comDepartment and Graduate Institute of Business Administration, National Yunlin University of Science and Technology

Pittinun PunthaDepartment and Graduate Institute of Business Administration, National Yunlin University of Science and Technology

Abstract:

Thailand 4.0 is a national strategy focused on integrating digital technologies and innovation to drive economic development in Thailand. The agricultural sector, a vital part of the economy, plays a crucial role in this strategy. One key initiative is the smart farming project, which aims to enhance agricultural productivity. This study aims to examine the impact of Thailand’s smart farming project on agricultural productivity within the context of this policy. In pursuit of this objective, the study adopts a quantitative research methodology, employing a comprehensive analysis of secondary data. The data utilized in the study is obtained from reliable sources, namely the Office of the National Economic and Social Development Council and the FAOSTAT database. This dataset spans the period from 2006 to 2020 and undergoes meticulous analysis through the application of a specified equation. The study findings demonstrate that higher growth rates of total output relative to total inputs result in noticeable improvements in agricultural total factor productivity. This positive outcome can be attributed to the significant influence exerted by Thailand 4.0 and smart farming policies. Consequently, the adoption of smart farming practices in Thailand leads to significant advancements in agricultural productivity. Based on these results, the study provides valuable insights into the implications of Thailand 4.0 for agricultural development and offers recommendations for policymakers and stakeholders. These recommendations involve strategies to leverage digital technologies in agriculture, promote innovation, enhance digital literacy and skills among farmers, and address challenges that hinder the effective implementation of digital transformation initiatives.

Keywords: Thailand 4.0 policy, smart framing, agricultural total factor productivity, innovation, sustainable development

References:

[1] Manop, Nawarat. Thai agricultural sector: From problems to solutions | United Nations in Thailand [Internet]. thailand.un.org. 2020. Available from: https://thailand.un.org/en/103307-thai-agricultural-sector-problems-solutions

[2] Teng, P. P. S., Caballero-Anthony, M., & Lassa, J. A. The Future of Rice Security Under Climate Change. (NTS Report No. 4). Singapore: Nanyang Technological University. 2016.

[3] Somnuek S, Slingerland MM, Grünbühel CM. The introduction of oil palm in Northeast Thailand: A new cash crop for smallholders? Asia Pac Viewp. 2016;57(1):76–90.

[4] Sinnarong N, Chen CC, McCarl B, Tran BL. Estimating the potential effects of climate change on rice production in Thailand. Paddy Water Environ. 2019;17(4):761–9.

[5] Siamwalla, Ammar, Suthad Setboonsarng, and Direk Patamasiriwat. “The response of Thai agriculture to the world economy.” In Agriculture and Trade In The Pacific, pp. 149-174. Routledge, 2019.

[6] Wailerdsak N. Business groups and the Thailand economy: Escaping the middleincome trap. Taylor & Francis; 2023. DOI: 10.4324/9781003370536.

[7] Silalertruksa T, Gheewala SH. Land-water-energy nexus of sugarcane production in Thailand. J Clean Prod. 2018;182:521–8.

[8] Akano, Oreoluwa, Sinah Modirwa, Azeez Yusuf, and Oladimeji Oladele. “Making smallholder farming systems in Nigeria sustainable and climate smart.” 2018: 1-19.

[9] Sikora J, Niemiec M, Szeląg-Sikora A, Gródek-Szostak Z, Kuboń M, Komorowska M. The impact of a controlled-release fertilizer on greenhouse gas emissions and the efficiency of the production of Chinese cabbage. Energies. 2020;13(8):2063.

[10] Abegunde VO, Sibanda M, Obi A. The dynamics of climate change adaptation in Sub-Saharan Africa: A review of climate-smart agriculture among small-scale farmers. Climate (Basel). 2019;7(11):132.

[11] Cameron A, Pham T, Atherton J. Vietnam today: First report of the Vietnam’s future digital economy project. Canberra: CSIRO; 2018.

[12] Newell P, Taylor O, Naess LO, Thompson J, Mahmoud H, Ndaki P, et al. Climate smart agriculture? Governing the sustainable development goals in Sub-Saharan Africa. Front Sustain Food Syst. 2019;3:55.

[13] Huyer S, Simelton E, Chanana N, Mulema AA, Marty E. Expanding opportunities: A framework for gender and socially-inclusive climate resilient agriculture. Front Clim. 2021;3:718240.

[14] Srivetbodee S, Igel B. Digital technology adoption in agriculture: Success factors, obstacles and impact on corporate social responsibility performance in Thailand’s smart farming projects. Thammasat Rev. 2021;24(2):149–70.

[15] Smart farmer development project in Thailand [Internet]. Food and fertilizer technology center [cited October 7, 2016]. Available from: https://ap.fftc.org.tw/article/1117

[16] Farmnovation technologies in the field [Internet]. Thailand Board of Investment, Thailand [cited 2020]. Available from: https://www.boi.go.th/en/intro/

[17] FAO (Food and Agriculture Organization). Thailand: FAOSTAT country profile [Internet]. Fao.org. Available from: https://www.fao.org/faostat/en/#country/216. 2021.

[18] Jansuwan P, Zander KK. Getting young people to farm: How effective is Thailand’s young smart farmer programme? Sustainability (Basel). 2021;13(21):11611.

[19] AIS partner with uncle Lee Farm to Apply IoT platform i-Farm for urban farming [Internet]. Sentangsedee [cited 2019]. Available from: https://www.sentangsedtee.com/today-news/article_134891. Accessed on 7 June 2023.

[20] CAT brings IoT Smart Agriculture to Saraburi Wittayaknom School to become learning center of modern agriculture [Internet]. CAT [cited 2019]. Available from: https://www.cattelecom.com/cat/content/3538/216/CAT+. Accessed on 7 June 2023 [in Thailand Language].

[21] TRUE Corporation join Khon Kaen University to develop smart agriculture [Internet]. The Reporter Asia. 2020. Available from https://thereporter.asia/th/2020/02/03/true- 5g-2/. Accessed on 7 June 2023.

[22] Smart Farmer program [Internet]. DTAC. 2022. Available from: https://www.dtac.co.th/sustainability/en/project/Project-SmartFarmer. Accessed on 7 June 2023.

[23] Bustos P, Caprettini B, Ponticelli J. Agricultural productivity and structural transformation: Evidence from Brazil. Am Econ Rev. 2016;106(6):1320–65.

[24] Lal R. Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Glob Change Biol. 2018 Aug;24(8):3285–301.

[25] Fuglie K, Gautam M, Goyal A, Maloney WF. Harvesting prosperity: Technology and productivity growth in agriculture. World Bank Publications; 2019.

[26] Waterman PG, Mole S. Extrinsic factors influencing production of secondary metabolites in plants. Insect-plant interactions. CRC press; 2019. pp. 107–34.

[27] Lankoski J, Thiem A. Linkages between agricultural policies, productivity and environmental sustainability. Ecol Econ. 2020;178:106809.

[28] Binswanger HP, Deininger K, Feder G. Agricultural land relations in the developing world. The economics of land use. Routledge; 2017. pp. 535–41.

[29] Restuccia, Diego, and Raül Santaeulalia-Llopis. “Land misallocation and productivity.” NBER working paper w23128. 2017.

[30] Bai Z, Caspari T, Gonzalez MR, Batjes NH, Mäder P, Bünemann EK, et al. Effects of agricultural management practices on soil quality: A review of long-term experiments for Europe and China. Agric Ecosyst Environ. 2018;265:1–7.

[31] Tian H, Wang T, Liu Y, Qiao X, Li Y. Computer vision technology in agricultural automation—A review. Inf Process Agric. 2020;7(1):1–19.

[32] Agrawal T, Agrawal A. Vocational education and training in India: A labour market perspective. J Vocat Educ Train. 2017;69(2):246–65.

[33] Hussain MI, Muscolo A, Farooq M, Ahmad W. Sustainable use and management of non-conventional water resources for rehabilitation of marginal lands in arid and semiarid environments. Agric Water Manage. 2019;221:462–76.

[34] Kang S, Hao X, Du T, Tong L, Su X, Lu H, et al. Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agric Water Manage. 2017;179:5–17.

[35] Ezui KS, Franke AC, Mando A, Ahiabor BD, Tetteh FM, Sogbedji J, et al. Fertiliser requirements for balanced nutrition of cassava across eight locations in West Africa. Field Crops Res. 2016;185:69–78.

[36] Borase DN, Nath CP, Hazra KK, Senthilkumar M, Singh SS, Praharaj CS, et al. Longterm impact of diversified crop rotations and nutrient management practices on soil microbial functions and soil enzymes activity. Ecol Indic. 2020;114:106322.

[37] Fukuda K. Science, technology and innovation ecosystem transformation toward society 5.0. Int J Prod Econ. 2020;220:107460.

[38] El Bilali H, Allahyari MS. Transition towards sustainability in agriculture and food systems: Role of information and communication technologies. Inf Process Agric. 2018;5(4):456–64.

[39] Israel B. The role of co-operative societies in supply chain of agricultural products: A review of literature. J. int. trade logist. law. 2022;8(2):69-77.

[40] Pe’er G, Zinngrebe Y, Moreira F, Sirami C, Schindler S, Müller R, et al. A greener path for the EU Common Agricultural Policy. Science. 2019 Aug;365(6452):449–51.

[41] Heyl K, Döring T, Garske B, Stubenrauch J, Ekardt F. The Common Agricultural Policy beyond 2020: A critical review in light of global environmental goals. Rev Eur Comp Int Environ Law. 2021;30(1):95–106.

[42] Liao H, Wang B, Li B, Weyman-Jones T. ICT as a general-purpose technology: The productivity of ICT in the United States revisited. Inf Econ Policy. 2016;36:10–25.

[43] Fedderke JW. Exploring unbalanced growth: Understanding the sectoral structure of the South African economy. Econ Model. 2018;72:177–89.

[44] Storm S. The secular stagnation of productivity growth. Handbook of economic stagnation. Academic Press; 2022. pp. 37–58.

[45] Wicki, Ludwik. “The role of technological progress in agricultural output growth in the NMS upon European Union accession.” Roczniki (Annals) 2021, no. 1. 2021.

[46] Moghaddasi R, Pour AA. Energy consumption and total factor productivity growth in Iranian agriculture. Energy Rep. 2016;2:218–20.

[47] Ruzzante S, Labarta R, Bilton A. Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature. World Dev. 2021;146:105599.

[48] Chen C. Technology adoption, capital deepening, and international productivity differences. J Dev Econ. 2020;143:102388.

[49] Eastwood C, Klerkx L, Nettle R. Dynamics and distribution of public and private research and extension roles for technological innovation and diffusion: Case studies of the implementation and adaptation of precision farming technologies. J Rural Stud. 2017;49:1–12.

[50] Sutherland LA, Labarthe P. Introducing ‘microAKIS’: A farmer-centric approach to understanding the contribution of advice to agricultural innovation. J Agric Educ Ext. 2022;28(5):525–47.

[51] North DC. Institutional change: A framework of analysis. Social rules. Routledge; 2018. pp. 189–201.

[52] Fuentelsaz L, González C, Maicas JP. Formal institutions and opportunity entrepreneurship. The contingent role of informal institutions. Bus Res Q. 2019;22(1):5–24.

[53] Mbalyohere C, Lawton TC. Engaging informal institutions through corporate political activity: Capabilities for subnational embeddedness in emerging economies. Int Bus Rev. 2022;31(2):101927.

[54] Bhatt B, Singh A. Stakeholders’ role in distribution loss reduction technology adoption in the Indian electricity sector: An actor-oriented approach. Energy Policy. 2020;137:111064.

[55] Liu T, Bruins RJ, Heberling MT. Factors influencing farmers’ adoption of best management practices: A review and synthesis. Sustainability (Basel). 2018;10(2):432.

[56] Kumar G, Engle C, Tucker C. Factors driving aquaculture technology adoption. J World Aquacult Soc. 2018;49(3):447–76.

[57] Taylor M, Bhasme S. Model farmers, extension networks and the politics of agricultural knowledge transfer. J Rural Stud. 2018;64:1–10.

[58] Diewert WE. The measurement of productivity. Bull Econ Res. 1992;44(3):163–98.

[59] Key N. Farm size and productivity growth in the United States Corn Belt. Food Policy. 2019;84:186–95.

[60] Gong B. Agricultural reforms and production in China: Changes in provincial production function and productivity in 1978–2015. J Dev Econ. 2018;132:18–31.

[61] Andersen MA, Alston JM, Pardey PG, Smith A. A century of US farm productivity growth: A surge then a slowdown. Am J Agric Econ. 2018;100(4):1072–90.

[62] O’Grady MJ, O’Hare GM. Modelling the smart farm. Inf Process Agric. 2017;4(3):179– 87.

[63] Pivoto D, Waquil PD, Talamini E, Finocchio CP, Dalla Corte VF, de Vargas Mores G. Scientific development of smart farming technologies and their application in Brazil. Inf Process Agric. 2018;5(1):21–32.

[64] Raja L, Vyas S. The study of technological development in the field of smart farming. Smart farming technologies for sustainable agricultural development. IGI Global; 2019. pp. 1–24.

[65] Virk, Ahmad Latif, Mehmood Ali Noor, Sajid Fiaz, Saddam Hussain, Hafiz Athar Hussain, Muzammal Rehman, Muhammad Ahsan, and Wei Ma. “Smart farming: an overview.” Smart village technology: concepts and developments. 2020: 191-201.

[66] Navarro E, Costa N, Pereira A. A systematic review of IoT solutions for smart farming. Sensors (Basel). 2020 Jul;20(15):4231.

[67] Mohamed ES, Belal AA, Abd-Elmabod SK, El-Shirbeny MA, Gad A, Zahran MB. Smart farming for improving agricultural management. Egypt J Remote Sens Space Sci. 2021;24(3):971–81.

[68] Moysiadis V, Sarigiannidis P, Vitsas V, Khelifi A. Smart farming in Europe. Comput Sci Rev. 2021;39:100345.

[69] Fuglie K. Accounting for growth in global agriculture. Bio-Based Appl Econ. 2015;4(3):201–34.

[70] Chávez-Dulanto PN, Thiry AA, Glorio-Paulet P, Vögler O, Carvalho FP. Increasing the impact of science and technology to provide more people with healthier and safer food. Food Energy Secur. 2021;10(1):e259.

[71] Mockshell J, Kamanda J. Beyond the agroecological and sustainable agricultural intensification debate: Is blended sustainability the way forward? Int J Agric Sustain. 2018;16(2):127–49.

[72] Vesco P, Kovacic M, Mistry M, Croicu M. Climate variability, crop and conflict: Exploring the impacts of spatial concentration in agricultural production. J Peace Res. 2021;58(1):98–113.

[73] Cotterman KA, Kendall AD, Basso B, Hyndman DW. Groundwater depletion and climate change: Future prospects of crop production in the Central High Plains Aquifer. Clim Change. 2018;146(1-2):187–200.

[74] Li N, Jiang Y, Yu Z, Shang L. Analysis of agriculture total-factor energy efficiency in China based on DEA and Malmquist indices. Energy Procedia. 2017;142:2397–402.

Download
HTML
Cite
Share
statistics

2 Abstract Views

0 PDF Downloads