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Airline self-service technology (SST) has attracted attention from both the academic and aviation sectors. As the use of SST can reduce airlines’ operating costs, investigating SST usage at airports is particularly important for the aviation sector. The extant literature has explored users’ SST usage intention, but users’ switching intentions from traditional manual counter services to SST is still limited. Therefore, to address this issue, we used the push–pull–mooring (PPM) theoretical framework to develop a research model to explore user switching intention.

We utilized a mixed-methods approach. A qualitative approach (i.e., semistructured interviews) was first employed to recognize and choose the candidate factors. Then, we collected 450 valid responses through an online survey to test the model. The partial least squares method was used for data analysis.

We found that several push (perceived dissatisfaction and perceived inconvenience), pull (perceived ease of use, perceived usefulness and service process fit), and mooring (personal innovativeness and inertia) factors significantly influence switching intention. Additionally, mooring factors exert contextual effects on the relationships between push and switching intentions and between pull factors and switching intentions.

This study contributes to the literature by further increasing our understanding of user switching intentions regarding SSTs from the PPM perspective and offering guidance for the aviation sector to attract and retain customers.

This paper aims to investigate the problem of estimating the angle of attack (AoA) and relative velocity for vertical axis wind turbine (VAWT) blades from computational fluid dynamics data.

Two methods are implemented as function objects within the OpenFOAM framework for estimating the blade’s AoA and relative velocity. For the numerical analysis of the flow around and through the VAWT, 2 D unsteady Reynolds-averaged Navier–Stokes (URANS) simulations are carried out and validated against experimental data.

To gain a better understanding of the complex flow features encountered by VAWT blades, the determination of the AoA is crucial. Relying on the geometrically-derived AoA may lead to wrong conclusions about blade aerodynamics.

This study can lead to the development of more robust optimization techniques for enhancing the variable-pitch control mechanism of VAWT blades and improving low-order models based on the blade element momentum theory.

Assessment of the reliability of AoA and relative velocity estimation methods for VAWT’ blades at low-Reynolds numbers using URANS turbulence models in the context of dynamic stall and blade–vortex interactions.

This study aims to explore what and how digital innovation, as a knowledge-based and multi-dimensional process, can be used to increase the accountability of public and private sector organizations during the COVID-19 pandemic.

Taking an interpretivist approach, qualitative research is designed around Strong Structuration Theory (SST). A content analysis of relevant documents and semi-structured interviews focusing on the relationships between digital innovation and accountability in extraordinary times is conducted.

The results show the existence of digital innovation barriers and facilitators that can have an impact on accountability during extraordinary times. The research highlights how managers of public organizations focus largely on the social dimension of knowledge (i.e., competencies shaped by collective culture), while managers of private organizations focus mainly on the human dimension of knowledge (i.e., skills gained through learning by doing).

The paper enriches the accountability literature by historicizing SST for extraordinary times and by utilizing a multiple-dimensional approach to digital innovation. Also, the work underlines specific strategies organizations could usefully adopt to improve accountability through digital innovation in the public and private sectors during extraordinary times.

This article emphasizes the crucial integration of technological components with knowledge. In particular, the digital innovation is considered as a strong synergy of human and social dimensions that compels organizations toward enhanced accountability, particularly in the face of extraordinary challenges.

Future service interactions are anticipated to use humanoid robots in a society that is shifting to a digitalized era. Currently, it is evident that many businesses are replacing service interactions with self-service technologies (SSTs). This movement creates substantial societal changes that researchers have not paid sufficient attention to comprehend. In this setting, the purpose of this study is to examine the social drivers that influence customer mobility toward co-creating value via SSTs. The study also seeks to discover variations in customers' willingness and capacity to adopt SSTs.

To fulfill the research aims, a qualitative technique was adopted, with semistructured interviews conducted with 25 SST users from varied demographic backgrounds. To recruit individuals for the study, a nonprobabilistic purposeful sampling technique was adopted, with the goal of employing information-rich instances. The data were analyzed using thematic analysis.

The study identified eight social drivers that are important in the customer transition toward co-creating value with SSTs. According to the study, SSTs are characterized as a social trend in which adoption is accepted (social norm) and modifies social connections in a new direction. Using SSTs has evolved into a socializing tool that gives people social acknowledgment. Some people see SSTs as social pressure, putting them at a disadvantage if they do not adopt. People, on the other hand, acquire sufficient social support and independence to use SSTs. Customers were categorized into four groups depending on their willingness and ability to embrace SSTs: trendsetters, dreamers, old-fashioned and stragglers.

In practice, service providers can use this knowledge to successfully promote their SSTs and create enhanced client experiences through technological interfaces.

The study adds new knowledge by identifying social determinants in customer shifts toward SSTs, a phenomenon that has not been studied previously, and it adds to marketing theory by proposing a typology to group customers based on their ability and willingness to embrace SSTs.

The performance of a bladeless Tesla turbine is closely tied to momentum diffusion, kinetic energy transfer and wall shear stress generation on its rotating disks. The surface roughness adds complexity of flow analysis in such a domain. This paper aims to assess the effect of roughness on flow structures and the application of roughness models in flow cross sections with submillimeter height, including both stationary and rotating walls.

This research starts with the examination of flow over a rough flat plate, and then proceeds to study flow within minichannels, evaluating the effect of roughness on flow characteristics. An in-house test stand validates the numerical solutions of minichannel. Finally, flow through the minichannel with corotating walls was analyzed. The k-ω SST turbulent model and Aupoix's roughness method are used for numerical simulations.

The findings emphasize the necessity of considering the constricted dimensions of the flow cross section, thereby improving the alignment of derived results with theoretical estimations. Moreover, this study explores the effects of roughness on flow characteristics within the minichannel with stationary and rotating walls, offering valuable insights into this intricate phenomenon, and depicts the appropriate performance of chosen roughness model in studied cases.

The originality of this investigation is the assessment and validation of flow characteristics inside minichannel with stationary and corotating walls when the roughness is implemented. This phenomenon, along with the effect of roughness on the transportation of kinetic energy to the rough surface of a minichannel in an in-house test setup, is assessed.

Industrial simulations of turbulent flows often rely on Reynolds-averaged Navier-Stokes (RANS) turbulence models, which contain numerous closure coefficients that need to be calibrated. This paper aims to address this issue by proposing a semi-automated calibration of these coefficients using a new framework (referred to as turbo-RANS) based on Bayesian optimization.

The authors introduce the generalized error and default coefficient preference (GEDCP) objective function, which can be used with integral, sparse or dense reference data for the purpose of calibrating RANS turbulence closure model coefficients. Then, the authors describe a Bayesian optimization-based algorithm for conducting the calibration of these model coefficients. An in-depth hyperparameter tuning study is conducted to recommend efficient settings for the turbo-RANS optimization procedure.

The authors demonstrate that the performance of the k-ω shear stress transport (SST) and generalized k-ω (GEKO) turbulence models can be efficiently improved via turbo-RANS, for three example cases: predicting the lift coefficient of an airfoil; predicting the velocity and turbulent kinetic energy fields for a separated flow; and, predicting the wall pressure coefficient distribution for flow through a converging-diverging channel.

To the best of the authors’ knowledge, this work is the first to propose and provide an open-source black-box calibration procedure for turbulence model coefficients based on Bayesian optimization. The authors propose a data-flexible objective function for the calibration target. The open-source implementation of the turbo-RANS framework includes OpenFOAM, Ansys Fluent, STAR-CCM+ and solver-agnostic templates for user application.

This paper aims to describe a proposal for an innovative method of normal shock wave–turbulent boundary layer interaction (SBLI) and shock-induced separation control.

The concept is based on the introduction of a tangentially moving wall upstream of the shock wave and in the interaction region. The SBLI control mechanism may be implemented as a closed belt floating on an air cushion, sliding over two cylinders and forming the outer skin of the suction side of the airfoil. The presented exploratory numerical study is conducted with SPARC solver (steady 2D RANS). The effect of the moving wall is presented for the NACA 0012 airfoil operating in transonic conditions.

To assess the accuracy of obtained solutions, validation of the computational model is demonstrated against the experimental data of Harris, Ladson & Hill and Mineck & Hartwich (NASA Langley). The comparison is conducted not only for the reference (impermeable) but also for the perforated (permeable) surface NACA 0012 airfoils. Subsequent numerical analysis of SBLI control by moving wall confirms that for the selected velocity ratios, the method is able to improve the shock-upstream boundary layer and counteract flow separation, significantly increasing the airfoil aerodynamic performance.

The moving wall concept as a means of normal shock wave–turbulent boundary layer interaction and shock-induced separation control has been investigated in detail for the first time. The study quantified the necessary operational requirements of such a system and practicable aerodynamic efficiency gains and simultaneously revealed the considerable potential of this promising idea, stimulating a new direction for future investigations regarding SBLI control.

The study's objective is to estimate the association of specific perceived employer-provided benefits on employees' intention to leave in different age cohorts during coronavirus disease 2019 (COVID-19). Informed by the psychological theories of ageing, the authors propose three age-cohort-specific hypotheses in three motivational domains: security and health benefits, flexible work arrangement and education-related benefits.

The authors use a large survey of employees in Estonia (n = 7,209) conducted in 2020 and test the association of specific benefits and their interactions with age on employees' intention to leave.

The results show that older cohorts are generally less prone to leave their jobs. Benefits that employers could use during the COVID-19 crisis generally had negative associations with the intention to leave, but age-specific differences were negligible; only the perceived provision of flexible work arrangements reduced the younger cohort's intention to leave relatively more.

This study is one of the few that allows us to make inferences regarding the benefits preferences amongst the working population during an unprecedented health crisis.

The purpose of this paper is to study the aerodynamic characteristics and uplift force tendencies of pantographs within the operational height span of 1,600–2,980 mm, aiming to offer valuable insights for research concerning the adaptability of pantograph-catenary systems on double-stack high container transportation lines.

Eight pantograph models were formulated based on lines with the contact wire of 6,680 mm in height. The aerodynamic calculations were carried out using the SST k-ω separated vortex model. A more improved aerodynamic uplift force method was also presented. The change rule of the aerodynamic uplift force under different working heights of the pantograph was analyzed according to the transfer coefficients of the aerodynamic forces and moments.

The results show that the absolute values of the aerodynamic forces and moments of the upper and lower frame increase with the working height, whereas those of the collector head do not change. The absolute values of the transfer coefficients of the lower frame and link arm were significantly larger than those of the upper frame. Therefore, the absolute value of the aerodynamic uplift force increased and then decreased with the working height. The maximum value occurred at a working height of 2,400 mm.

A new method for calculating the aerodynamic uplift force of pantographs is proposed. The specifical change rule of the aerodynamic uplift force of the pantograph on double-stack high container transportation lines was determined from the perspective of the transfer coefficients of the aerodynamic forces and moments.

Working remotely in a COVID-19-induced lockdown has been challenging for both organisations and their employees; studies report that job demands changed, and teleworkers experienced increased burnout. This paper explores the negative employee outcomes that this work arrangement brings along and offers possible solutions to counter such negative outcomes since they could be detrimental to the much-touted future of work.

The study adopted a time-lagged longitudinal design and collected two-waved data from 403 quaternary sector employees. The data were analysed using structural equation modelling and model-21 in PROCESS macro for SPSS.

Findings affirm that employees experienced increased job demands during this crisis. Employees reported an increase in turnover intention because of burnout caused by increased job demands. However, increased task interdependence alone did not have any effect on turnover intention. The perceived organisational task support (POTS) was found to forestall the negative effect of job demands on burnout, and employee resilience (ER) buffered the burnout and turnover intention relationship.

Providing remote work task support and boosting resilience among employees will help in doing away with the negative effects of teleworking. However, managers shall prioritise reducing job demands for teleworkers.

The linkage between work factors and turnover intention is well established. Drawing on the event system theory and using the COVID-19 context, the present study added to the existing knowledge by studying the role of job demands (workload pressure and task interdependence) on turnover intention through the mediation of burnout. The study goes beyond the existing literature by accounting for POTS as a first-level moderator between job demands and burnout relationship, and ER as a second-level moderator between burnout and turnover intention relationship.