Abstract
Use of weather information by the Sri Lankan farmers is based on two information sources: traditional knowledge and agromet advisories provided by the Department of Meteorology through the Department of Agriculture. In this context the weather information use behaviour of Sri Lankan paddy farmers was investigated by using the theory of planned behaviour. The necessary data were collected through a pretested structured questionnaire administered with a multi-stage random sample of 900 farmers representing six districts in Sri Lanka. Two structural equation models (SEM) were built with respect to the two information systems. For both SEMs, the use frequency of information was considered as the behaviour, while subjective norm, perceived behaviour control, attitude and intention were considered as the behaviour specific beliefs. The structural validity of the questions and sample adequacy were separately checked for both SEM models. Results of the two SEM models showed significant (p<0.05) relationships for (1) attitude and intention, (2) attitude and behaviour, (3) subjective norm and intention, (4) perceived behavioural control and intention, and (5) intention and behaviour. It was revealed that the behavioural beliefs are important to determine the use of information systems. Therefore, the correct intervention is required to change or improve the existing behavioural beliefs when promoting weather information systems which are specifically designed against future climate turbulences.
Highlights
Farmers throughout the history used to foretell the future climate and weather events
The study concludes that, the structural equation models (SEM) based on the theory of panned behaviour (TPB) can be used to study the weather information use behaviour of Sri Lankan farmers to estimate the multiple dependence relationships
The behaviourspecific beliefs were stronger predictors of intention related to the both weather information systems studied
Summary
Farmers throughout the history used to foretell the future climate and weather events. These include, appearance of some animals, sounds of some specific animals, presence of some conditions like heat or cold, and flowering of trees. Such observations and experience, have been accumulated as local knowledge which transferred from generation to generation (Luseno et al, 2003; Stigter et al, 2005; Orlove et al, 2010). The scientific weather forecasting was introduced to support the farming decisions (Salinger et al, 2000). With the concerns on anticipated climate change, demand for precise forecasts increased unprecedented manner to support the climate change adaptation (Ensor and Berger, 2009; Giorgi et al, 2009)
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