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This paper aims to investigate the non-financial reporting (NFR) practices of Hungarian listed public interest entities for 2016–2018 in terms of the required disclosure content based on the 2014/95/EU Directive (ED).

The authors apply content analysis methodology on Hungarian firms subject to mandatory reporting under the ED. The target variable in the multivariate model is the reporting quality (Q_i) measured by a combined index.

The authors find that the ED had a moderate impact on Hungary's reporting quality because the overall disclosure of the sample only increased from low to medium level. The authors found that the value of intangible assets is a determinant of the reporting quality before and after the implementation of the ED. The findings support the effect of coercive isomorphism on Hungarian NFR practices.

The limitation of the research is the number of firms examined. However, the authors covered the entire (non-bank) community of the Hungarian firms subject to the ED.

The authors suggest that reporting entities build upon the synergy between intellectual capital disclosure and NFR when elaborating their reporting strategies. The authors recommend the integration of ethical matters into corporate strategies and policies. Policymakers may consider the revision of the Hungarian regulations. The authors suggest academics embrace these topics in teaching.

To the best of the authors’ knowledge, this is the first study that investigates the impact of ED in the context of Hungary. The authors contribute to the existing literature by adding the results of the ridge regression model, highlighting the importance of intangible assets.

This paper aims to analyse how emerging technologies (ETs) impact on improving performance in disaster management (DM) processes and, concretely, their impact on the performance according to the different phases of the DM cycle (preparedness, response, recovery and mitigation).

The methodology is based on a systematic review of the literature. Scopus, ProQuest, EBSCO and Web of Science were used as data sources, and an initial sample of 373 scientific articles was collected. After abstracts and full texts were read and refinements to the search were made, a final corpus of 69 publications was analysed using VOSviewer software for text mining and cluster visualisation.

The results highlight how ETs foster the preparedness and resilience of specific systems when dealing with different phases of the DM cycle. Simulation and disaster risk reduction are the fields of major relevance in the application of ETs to DM.

This paper contributes to the literature by adding the lenses of performance measurement, management and accountability in analysing the impact of ETs on DM. It thus represents a starting point for scholars to develop future research on a rapidly and continuously developing topic.

This paper aims to examine the influence of big data (BD) on human resource management (HRM). It defines how these data can be a useful tool in the decision-making process of companies’ human resources to obtain a sustainable competitive advantage.

This paper emphasizes the need to develop a holistic approach to emphasize these relations. Starting from these observations, the document proposes empirical research employing Eurostat data to test the benefits of BD in HRM decisions that optimize the relationship between training, productivity, and well-being.

The findings estimate HRM decisions and their impact in a broader macroeconomic and microeconomic perspective.

BD research is emerging as a crucial discipline in human resources. To overcome this problem, the paper develops an analysis of the literature on cleaner production and sustainability context; it creates a conceptual framework to clarify whether the existing studies consider the growing intensity of BD on human resources.