A farming system typology for the adoption of new technology in Bangladesh

Abstract

Over the last three decades, few studies have been conducted to tackle the complexity and heterogeneity of Bangladesh farming systems. We address these research gaps with a new survey. Accordingly, a survey was conducted in North‐Western Bangladesh to understand how socio‐economic traits influence technology adoption and to identify and characterize key farm types. The survey was based on farm household characteristics, farm structure, farming practices and livestock as well as the economic performance of the farm. Principal component analysis (PCA) and cluster analysis (CA) were used to establish the different farm typologies, and the data set based on 27 variables was carefully analysed. The findings confirmed that the key variables that significantly affect the adoption of new agricultural technologies relate to age, farming experience, level of education of the household head, income, access to markets, land ownership, the proportion of hired labour, savings, food self‐sufficiency and income from off‐farm activities. Four main farm types were identified in the study area based on resource endowment and livelihood orientation. These are (1) well‐resourced farmers entirely dependent on agriculture and less reliant on off‐farm activities; (2) moderately resourced households, which are headed by an older male with greater farming experience and which are engaged in both on‐farm and off‐farm activities; (3) resource‐constrained households with cattle as the main livestock and with income generated by the sale of livestock products; and (4) severely resource‐constrained households which are headed by young farmers/men and where income is generated by off‐farm activities. These four farm categories represent the heterogeneity of farms in North‐West Bangladesh, and it is hoped that the development of this farm household typology will help particularly the extension service, to set up appropriate extension advice that will benefit the farming community.

Contextualisation of salinisation and adaptation preferences in the coastal areas of Bangladesh: Bringing together farmers' salinity perspectives into place‐based policy initiatives

“…However, the existing policy initiatives [e.g. National Agriculture Policy (NAP), National Fisheries Policy NFP)] are highly top‐down and overlook heterogeneity in the coastal farming system, which requires farm‐specific extension advice to improve livelihood as well as to address salinisation (Sarker et al, 2021). Thus, policy initiatives to address salinisation must consider the divergent impacts from multiple farming perspectives equally while considering the ramifications of one group over another with a place‐based approach that could resolve these differing situations.…”

What influences Bangladeshi Boro rice farmers’ adoption decisions of recommended fertilizer doses: A case study on Dinajpur district

“…Dinajpur’s economy is primarily agricultural-based, with rice being its most well-known product [ 33 ]. The majority of land in this district is medium highlands (37 percent), followed by highland (5 percent), and medium lowlands (5 percent) [ 27 ]. Rice farmers prefer to grow paddy in either medium-high or medium lowlands due to several cost-effectiveness factors.…”

“…This could be due to the rise of more valuable substitute crop products or maybe because some implements for production do not respond well to environmental mindedness, but it more likely seems due to long-term process inefficiencies within the sector. Most farmers’ lack of scientific farming knowledge and reliance on inorganic fertilizers, compounded with inconsequential micronutrient uses and meager adoption of soil testing-based fertilizer recommendations, have deteriorated the soil substances in the country [ 17 , 22 – 27 ]. This has driven the government to emphasize adopting sustainable intensification methods to increase yields by adjusting fertilizer use whilst decreasing disparagement to the environment [ 9 , 28 ].…”

Understanding the determinants and impact of the adoption of technologies for sustainable farming systems in water-scarce areas of Bangladesh

“…The explanatory variables for this particular study presented in Table 1 below are chosen from the existing literature on the adoption. The variables include farmers age (Tiwari et al, 2008;Ntshangase et al, 2018), education (Chuchird et al, 2017;Sunny et al, 2018), land typology (Endrias et al, 2013;Reza and Hossain, 2013), farming experience (Sunny et al, 2018;Sarker et al, 2021), household size (Challa and Tilahun, 2014;Araya and Holden, 2018), farm size (Deressa et al, 2011;Ntshangase et al, 2018), knowledge acquisition (Feder and Slade, 1984;Bairagi et al, 2018), off-farm or secondary income (Pandey and Mishra, 2004;Mottaleb et al, 2016), plot fertility (Kassie et al, 2015;Zeng et al, 2018), credit availability (Simtowe and Zeller, 2006;Mottaleb et al, 2016), soil water retention (Albrecht and Ladewig, 1985;Genius et al, 2013), close acquaintances' adoption (Mendola, 2007;Jansson et al, 2017), and environmental awareness (Liu et al, 2013;Irfan et al, 2020).…”