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The purpose of this study is to explore the diffusion of digital innovation for talent management in Italian learning organizations.

It has been implemented a qualitative methodology to collect data, interviewing 16 experts; a mix method analysis was applied to explore thematic categories and to analyze co-occurrences by a quantitative approach analysis using T-Lab software.

There are some relevant points to underline: digital technologies are meant as a support to human resource management (HRM), and there is often the reference to digital gamification or gamified processes implemented for talent management procedures. Learning is a central element both for employees’ point of view and for HR specialists who feel the need for a major and more specific training on digital technologies.

The limited size and composition of the sample put restrictions on the generalizability of results. The explorative nature of the study provides an in-depth consideration of digital innovation in learning organization, representing a first starting point for future quantitative investigations. From a practical point of view, this study emphasizes a learning organization culture as an essential attitude set to attract, select and retain top talents.

From a practical point of view, this study emphasizes a learning organization culture as an essential attitude set to attract, select and retain top talents.

Giving space and voice to HR and information and communication technologies experts has provided insights regarding the digitalization process in HRM in Italy, in particular, digital learning has been told as a necessary element for the competitiveness of the workforce.

Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.

A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.

The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.

Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

This paper aims to critically examine traditional approaches to paradoxes and propose a new approach and perspective that views “chiasmic” organizing as a intertwining combination of structure and processes that facilitate the handling of multiple interrelations for processing paradoxes and harness their creative potential in organizations.

Employing a cross-disciplinary approach, a literature review and a critical lens, along with conceptual work (typology), are used to identify problems and deficiencies in existing research on paradoxes. Specifically, it draws on Merleau-Ponty's process-oriented phenomenology and post-Cartesian ontology to gain a comprehensive understanding of post-dualistic forms of chiasmic organizing and its relationship with paradoxical phenomena.

The process-oriented phenomenology and post-Cartesian ontology used in this article offer valuable insights and a critical approach to comprehend post-dualistic forms of chiasmic organizing in relation to paradoxes. This understanding can help in tapping into the energizing and creative potential of paradoxes. The paper also highlights the significance of the “in(ter)-between” as a reversible principle in chiasmic organizing and proposes some implications.

Limitations and implications of this study are identified and discussed.

The paper offers practical implications for organizations in processing paradoxes.

This paper contributes to the existing literature by providing a conceptual critique and proposing a novel understanding of chiasmic organizing as an intertwining structure and mediating processes by employing a process-oriented phenomenology and post-Cartesian ontology. It also offers innovative ways to approach paradoxes and tap into their creative potentials, which can bring about change in organizations.

Business Process Reengineering (BPR) eliminates non-value-added (NVA) and essential non-value-added (ENVA) waste through radical process redesign to improve organizational operations. Comprehensive research integrating BPR tools is needed to understand their benefits for manufacturing firms. This research presents an integrated BPR-simulation framework tailored to the manufacturing sector to maximize process improvements and operational excellence.

The BPR design methodology adopts a systematic, multi-stage approach. The first phase involves identifying a specific improvement process aligned with BPR's core objectives. This phase analyses and redesigns workflows to optimize task sequences, roles, and stakeholder interactions while eliminating redundancies and inefficiencies via Workflow Process Reengineering. Visual process mapping tools, including VSM and simulation, pinpoint areas of waste, delay, and potential enhancement. The second phase follows the workflow analysis and aims to improve efficiency and effectiveness by redefining roles, rearranging tasks, and integrating automation and technology solutions. The redesigned process undergoes evaluation against key performance indicators to ensure measurable improvements are achieved. The final phase validates the proposed changes through simulation models, assesses the impact on key performance metrics, and establishes the necessary infrastructure for successful implementation. The proposed model is empirically validated through a case study of a leading apparel company in Vietnam, confirming its effectiveness.

The findings reveal that NVA activities are being eliminated, and ENVA activities in key departments are significantly reduced. This yielded a substantial improvement, reducing 25 out of 186 combined ENVA and NVA operations in the sewing facility, involving a decrease of 15 ENVA operations and the removal of 10 NVA operations. Consequently, this led to an 8.5% reduction in the proportion of ENVA operations, accompanied by a complete 100% elimination of NVA activities.

The single case study limits generalizability; thus, expanded implementation across diverse manufacturing sub-sectors is required to establish validity and broader applicability of the integrated framework.

The experimental results highlight the proposed model's effectiveness in optimizing resource utilization and its practical implementation potential. This structured BPR methodology enables organizations to validate, evaluate, and establish proposed process changes to enhance operational performance and productivity.

This study aims to investigate the erosion wear rate of a stainless steel automobile exhaust manifold, both computationally and physically.

The experiment was performed on a motorcycle exhaust manifold as well as on a 3D model, created using SolidWorks 2022 CAD software. The analysis was later achieved using ANSYS 19.2 simulation software using Fluent – code.

The analysis of solid particle erosion in the exhaust manifold revealed that erosion wear is concentrated predominantly at the extrados of the manifold, with the most significant wear occurring at the lowermost bend. The erosion wear rate increases with larger particulate sizes and varies among bends, with negligible wear observed in straight pipes. The SEM analysis further confirmed surface degradation, with rugged textures, pits and grooves indicating abrasive wear. Spine-like structures and fractured soot particles suggest erosive and abrasive forces caused by high-speed contact of exhaust gas compounds. Energy dispersive X-ray spectroscopy revealed significant carbon abundance, indicating carbonaceous compounds from fuel combustion, along with notable amounts of oxygen and iron, typical of oxidized metallic constituents. The discrete phase modeling (DPM) analysis highlighted peak particulate matter deposition at the first bend exit, with maximum concentrations observed at specific angles. This deposition is influenced by centrifugal force, leading to increased PM concentration at outer bend walls. Velocity magnitude contours showed asymmetrical flow profiles, with high turbulence levels and secondary flow induced by centrifugal effects in bend areas. Dynamic pressure contours revealed varying pressures at intrados and extrados, with maximum pressure observed at the intrados of the manifold’s bends. These findings provide valuable insights into erosion wear, particulate dispersion and flow dynamics within the exhaust manifold.

The study investigated an automobile exhaust manifold model using ANSYS Fluent code and DPM to analyze erosion wear rate phenomena and its various constituents. This analysis was conducted in comparison with a physically eroded sample. The study offers insights into the mechanism underlying the exhaust manifold of an automobile.

Hybrid learning has become a reality due to the onslaught of the COVID-19 pandemic. Students world over had to switch to this new learning format. This study aims to analyze the impact of innovation attributes of the Unified Theory of Acceptance and User Technology (UTAUT2) model and community of inquiry (COI) framework on the hybrid learning experience and the continued intention for it.

Using a cross-sectional research design, the study has adapted a scale from past studies and collected data using purposive sampling from the student community. The research has used the structural equation modeling technique using SMART-PLS to study the hypothesized relationships.

The study’s findings are that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, teaching presence, cognitive presence and social presence influence hybrid learning experience and continued intention. Further hybrid learning experience mediates the continued intention.

This study has several academic and practical implications for improving the hybrid learning experience. Various stakeholders can get insights on improving the user’s desire to pursue learning in a hybrid environment.

Hybrid learner experience is an upcoming area of research and yet unexplored in India as well as in other countries. A new hybrid experience model was developed by extending the UTAUT2 to include the COI framework and learner experience frameworks.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The paper aims to assess the impact and responses to coronavirus disease 2019 in six European heritage labs (Horizon 2020 Framework Programme) selected for their adaptive heritage re-use practices based on participation, self-organisation and self-management. As they are naturally oriented towards building resilient urban systems, the hypothesis is that the co-production of cultural values and places promoted by these projects could create the conditions for equitable perspectives of resilience in the normality of contemporary urban life.

The paper draws on data collected through a survey of six European Living Labs between January and May 2021. The survey results are framed by a literature review that defines adaptive reuse in terms of resilience. The five resilience characteristics described by Judith Rodin (awareness, diversification, integration, self-regulation and adaptability) are used to navigate the literature and organise the survey results.

Combining survey results and insights from the literature, some modes and elements (territorial, social, financial) are presented that contribute to creating the conditions for resilience through adaptive heritage reuse according to community-based approaches. Without claiming to be exhaustive, this evidence should be considered in the design phase of resilience programmes, policies or projects related to cultural heritage.

The concepts of community and resilience are becoming increasingly important in the field of cultural heritage. This paper makes a creative contribution to the ongoing debate by presenting and evaluating the contribution of adaptive reuse practices to resilience building.