Framework: Financial Technology (FinTech) is an industry composed of diversified firms that combine financial services with innovative technologies. The research question and main goal are attempting to answer whether they are more similar to traditional banks or trendy technological firms deploying their innovativeness to favor financial inclusion and sustainability. Justification: Evaluators may wonder if FinTechs follow the typical evaluation patterns of bank/financial intermediaries or those of technological firms. Preliminary empirical evidence shows that the latter interpretation is the one consistent with the stock-market mood. Objective: This study goes beyond the extant literature, analyzing the differences between FinTechs and traditional banks in market valuation, and showing the potential for digital interaction and cross-pollination of complementary business models. Methodology: The differences will be empirically analyzed with the stock market valuation and the multipliers associated with these firms. Results: The main contribution of this paper is that the appraisal approaches of FinTechs follow those of technological startups, having a revenue model much more scalable than that of a typical bank. FinTechs may so provide a solution for sustainable finance with microfinance and crowdfunding among others. FinTechs and traditional banks may eventually converge towards a common market exploiting co-opetition strategies.

This study aims to explore the impact of healthcare digitalization on smart hospital project financing (PF) fostered by pay-for-performance (P4P) incentives. Digital platforms are a technology-enabled business model that facilitates exchanges between interacting agents. They represent a bridging link among disconnected nodes, improving the scalable value of networks. Application to healthcare public–private partnerships (PPPs) is significant due to the consistency of digital platforms with health issues and the complexity of the stakeholder’s interaction. In infrastructural PPPs, public and private players cooperate, usually following PF patterns. This relationship is complemented by digitized supply chains and is increasingly patient-centric. This paper reviews the literature, analyzes some supply chain bottlenecks, addresses solutions concerning the networking effects of platforms to improve PPP interactions, and investigates the cost–benefit analysis of digital health with an empirical case. Whereas diagnostic or infrastructural technology is an expensive investment with long-term payback, leapfrogging digital applications reduce contingent costs. “Digital” savings can be shared by key stakeholders with P4P schemes, incentivizing value co-creation patterns. Efficient sharing may apply network theory to a comprehensive PPP ecosystem where stakeholding nodes are digitally connected. This innovative approach improves stakeholder relationships, which are re-engineered around digital platforms that enhance patient-centered satisfaction and sustainability. Digital technologies are useful even for infectious disease surveillance, like that of the coronavirus pandemic, for supporting massive healthcare intervention, decongesting hospitals, and providing timely big data.

The objective of this study is to determine the impact of artificial intelligence (AI) on the earnings before interest, taxes, depreciation, and amortization (EBITDA) of firms as a proxy of their financial and economic margins by improving revenues and minimizing expenses. This impact is positive on the market value and scalability by improving the economic and financial sustainability of companies. The methodology is based on a business plan that considers the savings obtained by a traditional firm implementing AI. Specifically, a sensitivity analysis will demonstrate that AI savings impact key parameters, leading to economic and financial sustainability. Additionally, a mathematical interpretation, based on network theory, will be produced to provide and compare the added value of two ecosystems (without and with AI that adds up new nodes and strengthens the existing ones). The main contribution of this paper is the combination of two unrelated approaches, showing the potential of AI in scalable ecosystems. In future research, this innovative methodology could be extended to other technological applications.

This study aims to detect if and how big data can improve the quality and timeliness of information in infrastructural healthcare Project Finance (PF) investments, making them more sustainable, and increasing their overall efficiency. Interactions with telemedicine or disease management and prediction are promising but are still underexploited. However, given rising health expenditure and shrinking budgets, data-driven cost-cutting is inevitably required. An interdisciplinary approach combines complementary aspects concerning big data, healthcare information technology, and PF investments. The methodology is based on a business plan of a standard healthcare Public-Private Partnership (PPP) investment, compared with a big data-driven business model that incorporates predictive analytics in different scenarios. When Public and Private Partners interact through networking big data and interoperable databases, they boost value co-creation, improving Value for Money and reducing risk. Big data can also help by shortening supply chain steps, expanding economic marginality and easing the sustainable planning of smart healthcare investments. Flexibility, driven by timely big data feedbacks, contributes to reducing the intrinsic rigidity of long-termed PF healthcare investments. Healthcare is a highly networked and systemic industry, that can benefit from interacting with big data that provide timely feedbacks for continuous business model re-engineering, reducing the distance between forecasts and actual occurrences. Risk shrinks and sustainability is fostered, together with the bankability of the infrastructural investment.

After describing the main features of the Spanish companies belonging to the FinTech, InsurTech, and PropTech sectors, the main objective of this study is to analyze whether their B2B/B2C business models are related to the existence of sustainability plans. Specifically, this paper analyzes whether the existence of a sustainability department is a determining factor for the business model adopted by the Spanish FinTechs, InsurTechs, and PropTechs. By using the multinomial logit regression, other factors such as the current closeness of companies to the sustainable development goals (SDGs), the sensitivity to domestic and European FinTech/InsurTech regulations, and the perception of FinTechs about such European regulations are debated before conclusions are drawn for a future research agenda.

Rural populations experience several barriers to accessing clinical facilities for malaria diagnosis. Increasing penetration of ICT and mobile-phones and subsequent m-Health applications can contribute overcoming such obstacles. GIS is used to evaluate the feasibility of m-Health technologies as part of anti-malaria strategies. This study investigates where in Uganda: (1) malaria affects the largest number of people; (2) the application of m-Health protocol based on the mobile network has the highest potential impact. About 75% of the population affected by Plasmodium falciparum malaria have scarce access to healthcare facilities. The introduction of m-Health technologies should be based on the 2G protocol, as 3G mobile network coverage is still limited. The western border and the central-Southeast are the regions where m-Health could reach the largest percentage of the remote population. Six districts (Arua, Apac, Lira, Kamuli, Iganga, and Mubende) could have the largest benefit because they account for about 28% of the remote population affected by falciparum malaria with access to the 2G mobile network. The application of m-Health technologies could improve access to medical services for distant populations. Affordable remote malaria diagnosis could help to decongest health facilities, reducing costs and contagion. The combination of m-Health and GIS could provide real-time and geo-localized data transmission, improving anti-malarial strategies in Uganda. Scalability to other countries and diseases looks promising.