Abstract
Understanding and integrating the user’s decision-making process into product design and distribution strategies is likely to lead to higher adoption rates and ultimately increased impacts, particularly for those products that require a change in habit or behavior such as clean energy technologies. This study applies the Theory of Planned Behavior (TPB) in design for global development, where understanding the tendency to adopt beneficial technologies based on parsimonious approaches is critical to programmatic impact. To investigate robustness and applicability of behavioral models in a data scarce setting, this study applies TPB to the adoption of biomass cookstoves in a sample size of two remote communities in Honduras and Uganda before and after a trial period. Using multiple ordinal logistic regressions, the intention to adopt the technology was modeled. Results quantify the influence of these factors on households’ intentions to cook their main meals with improved cookstoves. For example, the intention of participants with slightly stronger beliefs regarding the importance of reducing smoke emissions was 3.3 times higher than average to cook more main meals with clean cookstoves. The quantitative method of this study enables technology designers to design and develop clean technologies that better suit user behavior, needs, and priorities. In addition, the data driven approach of this study provides insights for policy makers to design policies such as subsidies, information campaigns, and supply chains that reflect behavioral attributes for culturally tailored clean technology adoption initiatives. Furthermore, this work discusses potential sources of bias and statistical challenges in data-scarce regions, and outlines methods to address them.
Highlights
Examining and quantifying drivers of users’ intentions for adopting clean technologies can provide insight and inform models for design, marketing strategies, and policies to maximize product effectiveness and uptake
Recognizing that technology adoption in low- and middle-income countries (LMICs) is a complex process involving a variety of critical factors including awareness, accessibility, usability, satisfaction, and motivation [60], this study focuses on the motivation piece by applying Theory of Planned Behavior (TPB) to estimate user intentions to adopt Improved cookstoves (ICS)
Intention is explained based on attitude toward behavior (ATB), social norms (SN), and perceived behavior control (PBC) which are quantified based on data collected through surveys in target communities
Summary
Examining and quantifying drivers of users’ intentions for adopting clean technologies can provide insight and inform models for design, marketing strategies, and policies to maximize product effectiveness and uptake. Energies 2020, 13, 3021 promote population scale adoption of clean technologies could benefit from systematic integration of dominant user perspectives, priorities and behavioral attributes for increased efficacy of clean technology adoption for improved public health and environment. For this purpose, comprehensive approaches are required to include energy services that bind user needs, culture, and social norms along with supply side challenges such as efficiency [2] and policies that create an enabling environment. Despite the findings of studies that suggest understanding the users’ motivations and decision-making process is essential to successful ICS dissemination, systematic integration of user attributes in design and implementation process still poses a challenge
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