Pre- and Post-Adoption Beliefs about the Diffusion and Continuation of Biogas-Based Cooking Fuel Technology in Pakistan

Abstract

A high level of acceptance and adoption is necessary to facilitate the widespread utilization of renewable energy technologies for cooking, as such utilization is essential for displacing the population’s massive dependence on fossil fuels and solid biomass. Economic and demographic aspects have been the focus of recent literature in exploring the adoption phenomenon of biogas technology. However, literature to date has given little attention to the behavioral factors and the perceptions of the end-users. Our study does not only include behavioral factors, but it employs a hybrid model to explore the continued attentions of users based on their post-adoption beliefs and performance expectations. Using a survey conducted in Pakistan in 2017, the study conducts a multivariate analysis through structural equation modeling to measure the effect of pre- and post-adoption beliefs and expectation on adoption and the continuing intention of households towards biogas technology. Results show that the acceptance of the households towards biogas technology is highly influenced by their perceptions on the benefits, as well as their trust in the technology. The perceived cost and risk attached to the technology are found to be negatively correlated with the acceptance. Households’ intentions to continue the use of biogas technology is highly influenced by the satisfaction level of the users of biogas technology. With the integrated model of adoption and continuation, the study illustrates the dynamic process in obtaining a deeper understanding of a user’s behavior to better formulate the policies for increasing the rate of technology adoption.

Determining the Influencing Factors of Biogas Technology Adoption Intention in Pakistan: The Moderating Role of Social Media

“…Environmental deterioration, the increasing demand for energy, and the scarceness of nonrenewable sources of energy have forced countries to shift from the conventional sources of energy to renewable energy sources worldwide [2]. Renewable energy techniques address environmental issues and provide sustainable solutions for such energy problems [3]. Due to fast-paced industrialization, the demand for energy is increasing, and this increase is not only resulting in higher prices, but also improved economic development and living standards [4].…”

“…However, there are still a limited number of biogas plants in the country (approximately 5357), even though the country has an enormous potential to install many more plants [20]. In spite of social and environmental benefits, the adoption rate of biogas technology in Pakistan is extremely low [2,3]. Hence, at this juncture, it is valuable to understand potential factors that trigger biogas technology adoption [2,20] particularly in the context of a developing country [3] such as Pakistan.…”

“…Meanwhile, the nature of biogas adoption constitutes both egoistic and altruistic values. However, extant studies mainly focused on egoistic values for biogas adoption, e.g., [3,20,24], but the role of altruism (pro-environmental) on biogas adoption was ignored or not thoroughly investigated.…”

The Effects of Epistemic Trust and Social Trust on Public Acceptance of Genetically Modified Food: An Empirical Study from China

“…This causal model has been widely used to explain public acceptance in a variety of technological domains, such as gene technology [ 18 , 39 , 40 , 41 ], financial technology [ 42 , 43 ], nanotechnology [ 44 , 45 , 46 , 47 , 48 , 49 ], renewable energy [ 32 , 50 , 51 , 52 ], unmanned aircraft [ 53 ], and automated driving technology [ 54 , 55 ]. The present study is also based on Siegrist’s causal model.…”

“…In that causal model, Siegrist argued that acceptance of this new technology was determined by both perceived risks and perceived benefits and that social trust exerted a strong indirect influence on acceptance through perceived risks and benefits. This causal model has been widely used to explain public acceptance in a variety of technological domains, such as gene technology [18,[39][40][41], financial technology [42,43], nanotechnology [44][45][46][47][48][49], renewable energy [32,[50][51][52], unmanned aircraft [53], and automated driving technology [54,55]. The present study is also based on Siegrist's causal model.…”