Environmental, energy, business and development dynamics have received strong research interest. However, previous studies have mainly explored these topics separately. Conversely, we study these aspects jointly, constructing a composite indicator and assessing resulting impact on several SDGs domains. The aim of the analysis is to discover the importance of latent aspects in explaning the environmental, energy and business efficiency for specific countries. Estimating this multidimensional efficiency is relevant for the identification of the conditions for the achievement of CO2 containment and sustainable development progress. We make use of the World Bank's World Development Indicators (WB WDI) for selected emerging countries from the Asia-Pacific region ranging from lower-middle-income to upper-middle-income economies, following the WB Group country classifications by income level. We build a composite indicator for eliciting diverse dimensions related to the environment, energy policy and economic factors. The first steps of the indicators analysis are achieved by the combination of the DEA and Tobit analyses. Therefore, we examine the environmental, energy and business efficiency according to the economic development stage of the analysed countries, making use of an entropy index. The index’ robustness is tested at both stages – first, exploring the Tobit analysis, therefore, by inspecting an additional Asia-Pacific country having a different income with respect to the benchmark. The results suggest the creation of country clusters. Above all, China outstands in terms of environmental efficiency and R&D, as a result of a broader energy development strategic plan in the last few decades. •Environmental, energy, business and development dynamics are analysed jointly for the first time•A composite indicator on selected SDGs components is built•The World Bank's World Development Indicators are used for Asia-Pacific emerging countries•DEA, Tobit, entropy and robustness analyses explore the effect of environmental efficiency on CO2 emissions•We observe different clusters for all sub-regions for the evaluation of efficiency and R&D intensity