Results show that rural residents have different cognitions of PV-PAPs, the composition of the cognitive element collection is the fundamental reason for the difference of individual degree of knowledge. Based on coding technique of grounded theory, principal component analysis, and stepwise multiple linear regression methods, this research explored rural residents' cognition of PV-PAPs as well as quantitatively verified the relationship between the key factors and their adoption willingness. However, there is a lack of research on the public support and cognitive process of PV-PAPs, and motivations and influencing mechanisms of rural residents' willingness to adopt PV-PAPs still need to be further explored. Also, it is appropriate for analyzing large samples or longitudinal qualitative data in marketing and management.The photovoltaic poverty alleviation project (PV-PAP) is an innovative policy for renewable energy diffusion and sustainable development achievement in China. The methodology described in this paper is applicable to other educational or program evaluations.

From a methodological perspective, this approach capitalizes on NVivo’s features to mine qualitative data. Using this approach, the Clinical Translational Science Institute (CTSI) evaluation team acquired deeper insight into the participants’ experiences and perspectives about CTSI programs and received insights that may lead to improvement. The authors explain this approach by presenting a step by step overview: data cleaning and case coding data import word frequency analysis text coding and reference extracting and matrix coding and inductive analysis. The authors show how the matrix coding feature maximizes NVivo utilities in an analysis of open-ended responses and highlights differences across and within participants’ groups. The purpose of this paper is to describe and demonstrate how the NVivo word frequency, text search, and matrix coding features can be used to analyze qualitative data from a longitudinal evaluation project. As one of the most powerful computer-assisted qualitative data analysis software, NVivo allows researchers to analyze open-ended responses to survey and/or interview questions, as well as other text data like reflective writing, image, and videos.

Open-ended responses are widely used to explore and understand participants’ experiences and perspectives in a variety of fields.

Nvivo matrix coding