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The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

This paper aims to serve as a commentary on the paper titled “Implementation of an Adapted Handwriting Without Tears® Programme for Children with Developmental Disabilities in a Special Education Setting.”

It provides an overview of educational strategies that can be used in school settings to support professionals in acquiring skills relevant to their practice and promoting the acquisition of new abilities for their students.

It explores three critical aspects of education: measuring academic progress, using evidence-based methods and enhancing educator training.

This work represents the personal perspective of a professional working in the service delivery field for children with developmental disabilities in schools and rehabilitative centres.

Since the first definition of Total Quality Management (TQM) was established, its inseparable relationship with Human Resource Management (HRM) has been undeniable. However, many years have passed since this initial definition was made. During this time, not only have TQM and HRM evolved, but their relationship has also adapted in order to accompany and follow the environmental and technological changes that have ultimately changed the ways the authors work and how the authors perceive quality. This study provides a detailed map of the knowledge evolution of the TQM–HRM relationship. It also identifies interesting gaps for future researchers to consider to enable us to better understand emerging challenges and identify the next steps in the progression of TQM literature.

The study adopted a bibliometric analysis approach, using a systematic literature review of a data set that included 132 peer-reviewed articles published between 1991 and 2021 to identify thematic topics. In exploring each of these, the authors created a framework to spotlight future explorative and exploitative research questions.

The results show that literature on the relationship between HRM and TQM focuses on six topics: a different performance appraisal (PA); a different role for the human resources (HR) department; HRM practices, such as different bridges between JIT and TQM; the integration of job satisfaction into TQM goals; different TQM healers; and the different effects of HRM practices on firm performance. This paper provides clear interpretations of these topics and offers some recommendations for how HRM studies could contribute towards the development of TQM research, thus forming a clear agenda for the future of TQM–HRM research.

This study represents the first attempt to systematize, analyze and critically interpret TQM–HRM studies, promoting a collective reflection on the state of the art and stimulating further discussions on this topic.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

This study aims to investigate the role of negative media coverage of environmental, social and governance (ESG) issues in deterring tax avoidance. Inspired by media agenda-setting theory and legitimacy theory, this study hypothesises that an increase in ESG negative media coverage should cause a reputational drawback, leading companies to reduce tax avoidance to regain their legitimacy. Hence, this study examines a novel channel that links ESG and taxation.

This study uses panel regression analysis to examine the relationship between negative media coverage of ESG issues and tax avoidance among the largest European entities. This study considers different measures of tax avoidance and negative media coverage.

The results show that negative media coverage of ESG issues is negatively associated with tax avoidance, suggesting that media can act as an external monitor for corporate taxation.

The findings have implications for policymakers and regulators, which should consider tax transparency when dealing with ESG disclosure requirements. Tax disclosure should be integrated into ESG reporting.

The study has social implications related to the media, which act as watchdogs for firms’ irresponsible practices. According to this study’s findings, increased media pressure has the power to induce a better alignment between declared ESG policies and tax strategies.

This study contributes to the literature on the mechanisms that discourage tax avoidance and the literature on the relationship between ESG and taxation by shedding light on the role of media coverage.

This article aims to explore how the mapping strategies between user requirements expressed by the humanities researchers lead to a better customization of user-driven digital humanities tools and to the creation of innovative functionalities, which can directly affect the way of doing research in a digital context.

It describes the user-driven development of a tool that helps researchers in the quantitative and qualitative analysis of large textbook collections.

This article presents an exemplary user journey map, which shows the different steps of the digital transformation process and how the humanities researchers are involved for (1) producing innovative research solutions, comprehensive and personalized reports, and (2) customizing access to content data used for the analysis of digital documents. The article is based on a case study on a German textbooks collection and content analysis functionalities.

The focus of this article is the reiterative research process, in which humanists (from the human centred point of view) starts from an initial research question, using quantitative and qualitative data and develops both the research question and the answers to it by with the aim to find patterns in the content and structure of educational media. Thus, from the viewpoint of digital transformation the humanist is part of the interaction between digitization and digitalization processes, where he/she uses digital data, metadata, reports and findings created and supported by the digital tools for research analysis.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.