This study contributes to sustainable finance literature by exemplifying promotion of sustainable finance through fintech solutions for emerging market economies by presenting the case of Turkey. Turkey is one of the largest emerging market economies in the world with a strong banking system and high adoption of technology, so it has great potential to benefit from fintech solutions to boost sustainable finance. For the case analysis, the data used came from a research platform for a Turkish start-up ecosystem, Turkish regulations, and documents released on Turkey’s sustainable finance strategies by Turkish and international institutions. We found that Turkey has made remarkable progress in increasing financial inclusivity for underbanked individuals and SMEs via providing contactless payment and contract systems and microfinance by mobile carriers and other online platforms. Turkey was also able to promote the responsible consumption goal for sustainable development by improving fintech solutions on payment systems with educational content on this goal. With upcoming developments such as the sandbox environment in Istanbul Financial Center, fintech solutions using Big Data, AI, and blockchain could emerge much faster with collaboration between banking and fintech sectors and regulatory institutions to better assess climate-related financial risks and form a national carbon trading mechanism.

The number of Turkish universities taking place in the global university rankings has been increasing. Hence, it is necessary to develop a mechanism to measure their efficiency. In this study, performance and efficiency measurement of universities in Turkey was conducted via data envelopment analysis (DEA), and the activities included in the performance definition were research indicators and internet and website focused indicators. The analysis was performed for 50 universities in Turkey. It has been observed that some universities which are successful in terms of research activities have not achieved similar success in the interest and traffic to their websites. In the study, suggestions for improvement in this and similar performance and efficiency metrics were presented.

The data presented in this article are related to the research article "Optimal procurement and production planning for multi-product multi-stage production under yield uncertainty" (Talay and Özdemir-Akyıldırım, in press) [1]. The data includes: 1) the input parameters (production yield, demand, and costs) collected through comprehensive review of the literature and diversified further to enrich the analytical results, and 2) results from mathematical modeling and analysis on the optimal procurement and semi-processed material allocation decisions for different parameter sets. The dataset is particularly constructed for a production system with two stages and three final products.