Humayun Kabir
Department of Regional and Project Planning, Justus-Liebig University of Giessen, Germany
Rosaine N. Yegbemey
Department of Regional and Project Planning, Justus-Liebig University of Giessen, Germany
Siegfried Bauer
Department of Regional and Project Planning, Justus-Liebig University of Giessen, Germany
Determinants, Adoption, Biogas plants, Rural areas, Bangladesh
Resource Development and Management
3.1. Study zone and database The study was conducted in rural areas, well known to be agrobased with low energy consumption. A stratified random sampling technique was used for selecting the households to be surveyed. Mymensingh (central zone) from Dhaka division, Pabna (west zone) from Rajshahi division, Thakurgaon and Dinajpur (northern zone) from Rangpur division were selected and finally one or two sub-districts (locally called Upazila) were chosen from each district according to the availability of biogas plants as well as the number of potential biogas households. Then, the purposive random sampling technique was used to carry out samples of biogas users (households already using the biogas plants) and biogas non-users (households not using the biogas plants, either willing to do so or not). Primary data related to the household socio-demographic and economic characteristics, including the motivation of using biogas plants were collected from 300 households divided into two groups: 150 households categorized as “biogas producers and users” and the remaining 150 households categorized as “potential biogas users or biogas non-users”. The head of the household was the respondent.
The data collection was carried out through a household survey based on a questionnaire. A first draft of the questionnaire was designed according to the research objective and the required data as reported in the literature on technology adoption in general, and biogas adoption in particular. Then, this questionnaire was pre-tested during an exploratory survey organized in the study zone. Some focus group discussions with households and local key informants were also organized along with the exploratory survey to get insights on the main driving forces determining the adoption of biogas in rural areas in Bangladesh. From the preliminary results of this survey, the questionnaire was up-dated and later on, used for primary data collection from the biogas users and non-users in the selected areas from July to September 2011. Data were analyzed by using statistical techniques (descriptive statistic, cross tabulation, frequency Tables, means t- test, and logistic regression) with STATA 10.1. Secondary data were collected from different Government offices, NGOs and private entrepreneurs who actively promoted the biogas activities in Bangladesh, Bangladesh Bureau of Statistics (BBS), Bangladesh Economic Review (BER), and scientific research papers.
3.2. Empirical modeling of biogas plants adoption Adoption of biogas technology in this study is the dependant variable defined as production and consumption of biogas from a small-scale bio-digester by a household. The logistic model was applied to investigate the biogas technology adoption process. Both logit and probit are well-recognized approaches in adoption studies. The choice of whether to use a probit or logit model is a matter of computational convenience. Logistic regression is used when the dependent variable is dichotomy and the independent variables are of any type. It applies Maximum Likelihood Estimation (MLE) after transforming the dependent variable into a logit variable. It estimates the odds of a certain event occurring. The dependent variable is a logit, which is the natural log of the odds, that is:
3.3. Selection of the variables likely to explain adoption of biogas technology Explanatory variables considered in the adoption process have often lacked a farm theoretical basis, possibly due to fact that households consider different issues beyond socio-economic incentives, including non-economic factors. In this study, the selection of the prospective variables that could affect the households' decision to adopt biogas plant was grounded in literature and fields experiences. The considerable amount of literature on adoption behavior reports that social, physical, economical, political and institutional factors are the core determinants of the adoption process.
Renewable and Sustainable Energy Reviews 28 (2013) 881–889
Journal