Search results

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 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.

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.

The organizational digital transformation (ODT) in companies presents small and medium-sized enterprises (SMEs) – who remain at the beginning of this transformation – with the challenge of offering digital services based on sensor technologies. Against this backdrop, the present paper identifies ways SMEs can enable digital servitization through sensor technology and defines the possible scope of the organizational transformation process.

Around 21 semi-structured interviews were conducted with experts from different hierarchical levels across the German manufacturing SME ecosystem. Using the Gioia methodology, fields of action were identified by focusing on influencing factors and opportunities for developing these digital services to offer them successfully in the future.

The complexity of existing sensor offerings must be mastered, and employees' (data) understanding of the technology has increased. Knowledge gaps, which mainly relate to technical and organizational capabilities, must be overcome. The potential of sensor technology was considered on an individual, technical and organizational level. To enable the successful implementation of service offerings based on sensor technology, all relevant stakeholders in the ecosystem must network to facilitate shared value creation. This requires standardized technical and procedural adaptations and is an essential prerequisite for data mining.

Based on this study, current problem areas were analyzed, and potentials that create opportunities for offering digital sensor services to manufacturing SMEs were identified. The identified influencing factors form a conceptual framework that supports SMEs' future development of such services in a structured manner.

Integrating person-job fit theory with the stressor-emotion model of counterproductive work behavior (CWB), the current study aims to examine which behavioral pattern (fight: CWB vs flight: withdrawal) employees are more likely to adopt when they experience perceived overqualification (POQ). We further investigate anger as the underlying emotional mechanism for these relations because anger can be expressed and thus reflected in CWB, or constrained and thus reflected in withdrawal behavior. Furthermore, different stressor-attenuating strategies including relaxation during work breaks and mastery experiences at work are examined as mitigating factors of these relations.

Time-lagged data were collected from 176 full-time employees in China using a field survey research design.

We found that employees who experience POQ are more likely to engage in withdrawal than in CWB. Anger mediated the relations of POQ with both CWB and withdrawal. Relaxation moderated the relation between POQ and anger, as well as the indirect relations of POQ with CWB and withdrawal through anger.

This study enhances understanding of employees’ affective and behavioral reactions to POQ. However, the survey design was not longitudinal and causality cannot be established.

POQ is associated with undesirable employee behaviors and should therefore be avoided by organizations. If POQ is unavoidable, organizations can use job design and offer training to foster relaxation in between tasks among employees.

In the framework of person-job fit theory, our study provides insight about employees’ “fight” or “flight” responses to POQ, and further illustrates the mechanism and the attenuating factors in this processes.

This paper aims to identify the combination of innovation determinants driving the creation of innovative products amongst market leaders and market followers in food and beverage (F&B) firms.

This research is based on the case study methodology by using two types of data sources: (1) semi-structured interviews with industry experts and (2) in-depth interviews with managers. In addition, a questionnaire adapted from prior research was used to consider market and firm types.

Suggesting an integrated theoretical framework based on firm-based factors and market-based factors, this study identified a combination of determinants significantly impacting innovative products in the market. Specifically, these determinants are competition intensity and innovation capability (a combination of research and development (R&D) investment and marketing capabilities). The study also examined how these determinants vary depending on whether the firms are market leaders or market followers.

This research provides practical insights for managers working in the F&B industry by using case studies and exploring the determinants of developing innovative products. In doing so, suitable strategies can be selected according to the market and firm situations.

The originality of the study is shown by focussing on how different combinations of market and firm factors could be applied in creating successful innovative products in the food sector.

Taking the dialogic organizational development perspective, this study aims to investigate the framing processes when engaging in dialogue for strategy implementation and how these enable the evolution of implementation opportunities.

Through a qualitative exploratory study conducted in a large multinational, the authors analyse the dialogue and interactions among 25 dyads when identifying opportunities to contribute to strategy implementation. The data analysis relies on a process-coding approach and linkography, a valuable protocol analysis for identifying recursive interaction schemas in conversations.

The authors identify four main framing processes – shaping, unveiling, scattering and shifting – and provide a framework of how these processes affect individuals’ mental models through increasing the tangibility of opportunities or elevating them to new value hierarchies.

From a theoretical perspective, this study contributes to the strategy implementation and organizational development literature, providing a micro-perspective of how dialogue allows early knowledge structures to emerge and shape the development of opportunities for strategy implementation.

From a managerial perspective, the authors offer insights to trigger action and change in individuals to contribute to strategy when moving from formulation to implementation.

Rather than focusing on the structural control view of strategy implementation and the role of the top management team, this study considers strategy implementation as a practice and what it takes for organizational actors who do not take part in strategy formulation to enact and shape opportunities for strategy implementation through constructive dialogue.

The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

The study aims to empirically investigate whether the disclosure of Sustainable Development Goals (SDGs) affects the level of integrated thinking and reporting (ITR) on a sample of European listed companies.

The sample focusses on companies listed to the STOXX Europe 600 Index. Data have been gathered from Refinitiv DataStream for the period 2019–2020 for the measures of ITR level and SDG disclosure. Then, a multivariate regression analysis is developed to test whether or not, and if so, to what extent, SDG disclosure affects the level of ITR.

SDG disclosure has been increased over time and companies have primarily focussed on SDG 8, SDG12 and SDG 13 demonstrating their awareness on sustainability issues close to the core business and on the climate urgency. Furthermore, SDG disclosure leads to a higher level of ITR meaning that SDG disclosure is an important pillar contributing to ITR.

The empirical analysis has not deeply investigated each component of ITR and SDG disclosure.

The research can be useful for companies aiming to improve their commitment towards the SDG implementation with an integrated approach. Moreover, the study sheds light on the importance of the SDG disclosure as a determinant of ITR.

The research contributes to literature in the stream of sustainability accounting, by adding new insights on ITR linked to SDG disclosure. To the best of the authors’ knowledge, the originality of the study lies in the inclusion of SDG disclosure as a determinant for ITR that has not been analysed by academics yet.

The purpose of this paper is to analyze the impact of the coronavirus (COVID-19) pandemic on participation and time allocated to work from home (WFH) by ethnic/racial group.

The authors employ USA time-use data [American Time Use Survey (ATUS)] for the 2017–2020 period and a parametric approach in their analysis.

Estimates show that the time allocated to WFH increased during COVID-19, especially for women. This increase is likely driven by more workers shifting to WFH (higher participation) rather than by longer hours worked by those who already teleworked. The authors also find relevant differences in the impact of COVID-19 on WFH by ethnic/racial group. Among ethnic/racial groups, only Asians increased WFH compared to White Americans. Within this ethnic group, the authors find significant differences across genders. Asian men increased participation in WFH, whereas Asian women increased both participation and hours worked, compared to White American women. Differences in this racial/ethnic group could be explained by previous research, which demonstrates a higher ability of Asians to perform job tasks remotely. However, this finding could also be attributed to an increase in discrimination during the COVID-19 pandemic.

This paper contributes to the recent and limited literature exploring the heterogeneous impact of COVID-19 on participation and time allocated to WFH by ethnic/racial group. Understanding the mechanisms driving vulnerable populations' abilities to work during socioeconomic downturns is of high policy importance.