This study tackles the challenge of identifying optimal investment sectors amid the growing importance of environmental, social, and governance (ESG) factors, which are often complex and conflicting. This research aims to effectively evaluate and prioritize ten investment sectors based on twelve ESG criteria by integrating expert evaluations with two advanced multi-criteria decision-making (MCDM) methods. Three expert teams assessed each sector’s performance based on these criteria using fuzzy logic to manage uncertainties in expert judgments. The MEREC (MEthod based on the Removal Effects of Criteria) identified biodiversity and land use as the most critical factor, while transparency and disclosure was least significant. The AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization) method was further used to rank the ten alternative sectors, with impact investing funds emerging as the top choice, followed by renewable energy and sustainable responsible investment funds. Conversely, ESG-compliant stocks, ESG-focused exchange-traded funds, and ESG-focused real estate investment trusts ranked the lowest. The study’s findings were validated through comparisons with other MCDM tools and sensitivity analysis, confirming the robustness of the proposed model. This research offers a valuable framework for investors looking to incorporate ESG considerations into their decision-making, promoting sustainable and responsible investing practices.

This study examines the association between financial development and selected telecommunications infrastructure indicators in sub-Saharan Africa (SSA), focusing on mobile cellular subscriptions (MBS) and fixed telephone subscriptions (FTS). It also examines whether urbanization moderates these associations and explores the relationships of trade openness, final consumption expenditure, and economic growth with telecommunications infrastructure. The study is based on an unbalanced panel of 44 SSA countries with data for the period 1981–2021 and includes two-way fixed effects (TWFE) models as the baseline specification, Panel Fully Modified Ordinary Least Squares (FMOLS) to estimate long-run associations within the cointegrating framework, and TWFE models with Driscoll–Kraay standard errors as a robustness procedure. The results indicate that financial development is positively and significantly associated with both FTS and MBS across the main specifications, with a substantially stronger association for MBS. These results validate the hypotheses that financial development has a positive relationship with the fixed and mobile telecommunications infrastructure. The moderation analysis also shows that financial development is positively associated with MBS when the level of urbanization increases, while such a positive moderating relationship is not statistically significant for FTS. Trade openness is generally positively associated with telecommunications infrastructure, while the associations of final consumption expenditure and economic growth vary across the MBS and FTS specifications. Overall, the findings suggest that the association between financial development and telecommunications infrastructure is technology-specific and varies with the level of urbanization. Robustness tests with the balanced panel sample and the post-1990s subsample generally give similar results, but caution should be taken in comparing results across specifications because of the differences in samples. The findings provide evidence relevant to the telecommunications infrastructure dimension of the broader Sustainable Development Goal 9 agenda, but they should not be inferred as evidence of comprehensive SDG 9 progress or causal effects. Future studies should use more comprehensive digital infrastructure indicators, disaggregated data, and better identification strategies to mitigate potential reverse causality and other forms of endogeneity.