Purpose: The purpose of this paper is to investigate the impact of ownership structure on bank performance in EU-15 countries. Specifically, it examines to what extent shareholder type and the degree of shareholder concentration affect the banks’ profitability, risk and technical efficiency.Design/methodology/approach: This study uses a sample of 1,459 banks operating in EU-15 countries from 2011 to 2015. It constructs a set of continuous variables capturing the ownership nature, the concentration and their interactions, and estimates an instrumental variable random effect (IV-RE) model. In addition, a panel data stochastic frontier analysis is conducted to estimate the time-varying technical efficiency for profitability and costs.Findings: The empirical analysis shows that bank performance is affected by shareholder type. When regressed against the entrenchment behavior of the controlling owner hypothesis, banks with large-block shareholders are more profitable, less risky and more profit efficient. Further, ownership concentration reverts the negative effect related to the institutional, bank and industry ownership.Research limitations/implications: The results support the hypothesis that concentrated ownership helps to overcome agency problems. They also confirm that managerial involvement in banks’ capital enhances a bank’s profit and its volatility.Originality/value: To the best of the authors’ knowledge, this is the first study to consider the ownership nature, the concentration and their interaction using continuous variables, which allows for more precise inferences. The results provide new evidence that bank profitability, cost efficiency and risk are affected by the type of direct shareholders.

This paper has two principal purposes. The first is to measure the operational efficiency gain that adopting new advanced technologies, defined as the fourth industrial revolution allows firms to achieve. The second is to challenge whether Industry 4.0 investments bring about strong enough improvement in firm performance to address the historical regional development gaps in Italy. Using a sample of 2609 firms observed during the period 2016–2019, we estimate technical efficiency scores by applying a one–step stochastic frontier analysis. This technique allows us to simultaneously relate operating performance to a set of regional dummy variables and assess the Industry 4.0 investment share of total firm investment expenditure. The stylised facts indicate substantial efficiency disparities between smart factories and firms that do not implement such investments. The adoption of new technologies partially mitigates the Italian regional efficiency gap, bridging the distance between Southern Italy and the rest of Italy.