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This study aims to propose and test a model of educational quality in marketing-management by incorporating resource-capability variables that are linked to learning outcomes for students and the competitive positioning of universities.

Drawing on the resource-dependence theory, this study develops a comprehensive model for measuring educational quality. A sample comprising Spanish university teachers has been used to test the hypothesised relationships by using a two-stage least squares regression analysis while controlling for the possible effect of the public/private nature of the university.

The results validate the model and show that educational capabilities are reliable variables for predicting the educational quality of marketing-management programmes at Spanish universities.

Similar to all educational research studies, certain problems have been acknowledged with respect to the data and the theoretical constructs that are used in the study. Future studies can replicate this study’s model by using more direct objective measures of the theoretical constructs and extend the study to other countries with different educational contexts.

The results provide guidance to marketing teachers at a university in designing high-quality marketing-management educational programmes and in developing self-diagnostic tools that can determine a university’s likelihood of competitive success.

This study is one of the few studies to apply the resource-dependence theory to the analysis of the variables associated with the quality of marketing-management education. In doing so, the study presents original multiitem scales to improve the measurement of model constructs.

Decentralized finance (DeFi), enabled by blockchain, could bring about a new financial system, where peers will interact directly, with little or no place for traditional intermediation. However, some crucial tasks cannot be left solely to an algorithm and, consequently, most DeFi applications still require human decisions. The aim of this research is to assess the role of intermediation in the light of DeFi, analysing how humans and algorithms will interact.

The authors based their work on a twofold qualitative methodology, first analysing publicly available secondary data, particularly from white papers and DeFi Pulse (a website providing data on DeFi solutions) and then running two focus group discussions.

DeFi does not eliminate financial intermediation, but enables it to be performed in new ways, where decentralization means that no single entity can hold too much power or monopoly. DeFi has, however, inherited risks from the underlying technologies that unintentionally facilitate illegal behaviour and can hamper the authorities’ supervision. The complex duality algorithm- vs human-based actions will not be solved indisputably in favour of the former, as DeFi solutions can range from requiring algorithms to play a dominant role, to enabling greater human interaction by actively involving more people.

This research contributes to the emerging debate between algorithm- and human-based intermediation, especially in relation to the standing literature on financial intermediation, where considerations made in the light of the newest theories on blockchain and DeFi are still scarce.