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In the era of artificial intelligence, natural language processing (NLP) models are revolutionizing numerous sectors. This research aims to explore the perceived value of them among university students. In particular, it aims to investigate how gender may influence students’ intention to use these models in educational contexts, highlighting potentially significant differences that could inform the implementation and adoption of educational technologies.

This study investigates the relationship between perceived value and students' intention to adopt NLP models, considering gender as a moderator. The research involves 562 students from the University of Salerno, in Italy, and uses confirmatory factor analysis to evaluate the reliability and validity of the measurement scales. A regression model with robust errors is used to explore the moderating role of gender on the relationship between perceived value and intentions of use of NLP models.

The results reveal a significant positive association between perceived value and intention to use NLP models, confirming that students with higher perceived value are more likely to adopt these technologies. Furthermore, gender moderates this relationship, indicating that females are less prone to use NLP models than male counterparts.

Research takes on a significant role in the academic field, underlining the importance of adapting teaching practices to the increasingly widespread digitalization. The inclusion of NLP models in university programs emerges as a possible improvement of the learning experience, ensuring cutting-edge education in tune with the needs of the digital society.

This paper aims to investigate the relationship between employee training and bank risk to verify whether and to what extent an increase in employee training, as a soft component of total quality management (TQM), affects bank risk.

The research adopts a panel regression, based on a unique dataset of a sample of Italian banks over the period 2011–2018, to test whether employee training affects bank risk, measured alternatively in terms of Z-score, a proxy of bank stability and non-performing loans (NPLs)/gross loans ratio as a proxy of credit risk.

Research findings reveal that increasing employee training leads to growing bank stability. In contrast, credit risk is not affected by employee training. However, by investigating training heterogeneity, this study found that the increase in the number of managerial training hours, as a proxy for soft skills training, negatively impacts credit risk. Therefore, an increase in soft skills leads to a reduction in bank credit risk.

This study provides empirical evidence in support of the relationship between employee training and bank risk, which seems novel in the literature. From a managerial point of view, this study highlights the need for banks to pay attention to the skills, particularly soft skills, that banks' employees must possess to effectively manage bank risk and, more specifically, the core bank risk.

Empirical evidence on the relationship between employee training, soft/hard skills and bank risk appears limited if not absent. Therefore, the findings provide insights for a more nuanced interpretation of variables that affect bank risk.

This paper aims to analyze unexplored connections between economic, environmental and social dimensions of corporate social responsibility (CSR) and knowledge management (KM) strategies (exploration, exploitation), also considering environmental dynamism as an influencing variable on these connections. The predicted CSR-KM interplay suggests, from stakeholder and knowledge-based views of the firm, the existence of ideal configurations between CSR and KM strategies that generate differentiated impacts on companies’ innovation capabilities, especially in dynamic environments.

Structural equation modeling by means of the partial least squares technique was used to test the study’s hypotheses after collecting survey data from Spanish companies of the renewable energy sector.

The study findings show that in highly dynamic environments, companies will tend to commit prominently in CSR, although their orientation (economic, environmental, social) and effects on innovation capabilities will depend mainly on the selected KM strategies. Social and environmental CSR are found to be highly related to KM exploration, whereas economic CSR is highly related to KM exploitation. Nevertheless, while a significant indirect effect of economic CSR by means of the KM exploitation strategy on innovation capabilities is found, the proposed indirect effect of both environmental and social CSR through the KM exploration strategy on innovation capabilities is not significant.

The results suggest that company managers should be aware of the advantages of following specific paths of investment in KM and CSR initiatives in highly dynamic environments, as there is a potential payoff in terms of innovation capability improvement. The results also suggest that “good” relationships with stakeholders, built from specific CSR investments, make firms able to get valuable knowledge that it is useful to develop KM strategies for innovation capability development.

Previous studies do not consider the interplay between KM strategies and CSR as a catalyzer for developing a firm’s innovation capabilities. This paper contributes to the KM and innovation literatures by introducing CSR into the conversation about how to improve innovation capabilities in dynamic and sustainable industries by using configurations of KM strategies and specific CSR investments in economic, social and environmental areas.

The goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).

The methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.

The authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.

The methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.