The significance of incorporating spatial disparities in scale development for assessing latent constructs in the field of bioenergy

Abstract

Abstract This study explored the importance to account for spatial disparities while measuring latent variables. Specifically, we investigated the potential influence of spatial disparities on scale validity and reliability with the purpose of developing a new scale for assessing biomass supply intention for bioenergy production along with five common intention predictors (environmental concern, attitudes, subjective norms, perceived behavioral control and knowledge of renewable energy). We generated our data from a sample of 247 participants randomly surveyed in two socioeconomically disparate regions. We used factor analysis, confirmatory factor analysis, and Cronbach alpha (α) as methodological frameworks. We found 21 (33.33%) items out of the initial pool that were deemed reliable (α = 0.84 to 0.98) for future use. We found that spatial disparities impacted the scale items, with substantial divergence in scale reliability and composition between geographic regions. However, we found excellently reliable items that hold consistency across geographic regions. Our findings imply that ignoring region-specific context in scale development may lead to distorting inferences and ineffective policies. We aspire to bolster the reliability rate in forthcoming studies using a more rigorous item selection method.