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Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.

Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.

The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.

This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.

The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.

This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

This study assesses the factors influencing customers’ intention to adopt e-banking in the context of the technology acceptance model and the moderation role of cybercrime.

The variables in the study are measured using a five-point Likert scale with measures adopted from existing literature. The independent variables are perceived ease of use, perceived usefulness and security and privacy. These are postulated to be moderated by the perceived risk of cybercrime and to influence e-banking adoption intentions. A quantitative approach is used. Primary data are collected from a sample of 209 randomly selected bank customers. The study uses a two-step (measurement model and structural model) approach to data analysis.

The key findings in this study are that perceived risk of cybercrime strengthens the positive relationship between perceived ease of use and e-banking adoption intentions but dampens or weakens the positive relationship between perceived usefulness and customers’ e-banking adoption intentions. The study makes several recommendations to inform scholarship, policy and practice.

Unlike existing literature, the study makes a unique contribution by including perceived risk of cybercrime as a moderating variable of theoretical significance in the relationship between adoption of e-banking and its determinants.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.

In this article, the authors draw-upon an extended unified theory of acceptance and use of technology (UTAUT) and propose a research model involving performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and competitive pressure (CP) as potential salient factors explaining the adoption of digitalization in European SMEs. The authors also postulate that there may be cross-cultural differences, thereby leading us to include the country as a moderator in the model.

The authors validate this model with a cross-cultural sample involving 188 owner-managers from the Czech Republic and Slovakia and through the partial least square structural equation modeling (PLS-SEM) techniques as well as multi-group analysis.

The results using the study’s global dataset indicate that PE, FC and CP significantly affect owner-managers intentions toward digitalization in SMEs. The authors’ application of the multi-group analysis also suggests that although the two countries differ in digitalization adoption intention, the differences are statistically insignificant. In the conclusion, the authors highlight several implications these findings have for theory and practice.

The authors recommend that the providers of emerging digital technologies should improve on the performance features of those technologies and ensure they are relevant to the SMEs. By doing so, the adoption of digitalization will grow, because owner-managers of SMEs will have the confidence that adopting such technologies will improve their operations. Second, SMEs are required to provide adequate organizational and technical infrastructure to support digitalization adoption.

Aside from being among the few attempts to extend the explanatory power of UTAUT with PE, EE, FC and CP in investigating digitalization adoption in SMEs context, this study also validates its model with rigorous methodological approach as well as three datasets (global, Czech Republic and Slovakia) thereby strengthening the validity of the results.

This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental (TOE) and diffusion of innovation (DOI) model.

The TOE and DOI were considered the primary theoretical models but are combined and extended by including few additional variables. Data were collected from 220 respondents of travel and tour operating businesses in Malaysia and analyzed by applying PLS structural equation model technique.

The empirical results established that perceived cost, relative advantages, complexity and compatibility, observability, competitor pressure, value alignment, customer pressure, and trialability are positively connected with the behavioral intention except for external support. The results reveal that value alignment partially mediates the association between relative advantages and behavioral intention, complexity and behavioral intention, compatibility and behavioral intention, perceived cost and behavioral intention except in between trialability and observability.

This research is unique as the value alignment construct is included in the model, and thus it fulfills the literature gap by adding the mediation construct. This study contributes to enhancing AR's understanding of the Malaysian travel and tour operator industry through the lenses of owners or managers. It offers an integrated model that combines the TOE and DOI models, rare in this sector, and can be replicated or extended with validated scales.

Massive open online courses (MOOCs), a Taylorist attempt to automate instruction, help make course delivery more efficient, economical and better. As an implementation of Digital Taylorism Implementation (DTI), MOOCs enable individuals to obtain an occupation-oriented education, equipping them with knowledge and skills needed to stay employable. However, learning through online platforms can induce tremendous amounts of technology-related stress in learners such as complexity of platforms and fears of redundancy. Thus, the aim of this paper is to study how student perceptions of DTI and technostress (TS) influence their perceived employability (PE). The role of TS as a mediator between DTI and PE has also been studied.

Stratified sampling technique has been used to obtain data from 305 students from 6 universities. The effect of DTI and TS on PE, and the role of TS as a mediator, has been examined using the partial least squares (PLS) structural equation modelling approach with SMART PLS 4.0. software. Predictive relevance of the model has been studied using PLSPredict.

Results indicate that TS completely mediates the relationship between DTI and PE. The model has medium predictive relevance.

Learning outcomes from Digitally Taylored programs can be improved with certain reforms that bring the human touch to online learning.

This study extends Taylorism literature by linking DTI to PE of students via technostress as a mediator.

This techno-centric and too much busy day-to-day living style of citizens pressurizes the implementation of E-ticketing service to adapt with change. Thus, this study aims to examine the factors influencing railway passengers’ E-ticketing service acceptance and usage intention in Bangladesh and to extend the widely used Technology Acceptance Model through inserting two new constructs.

This paper employs structural equation modeling to test model’s paths developed through theoretical research framework. Moreover, a structured questionnaire was administered at different railway stations in northern and western parts of Bangladesh to collect data. Total of 302 responses were considered for statistical analysis to test hypotheses after considering anomalies and outliers in raw data.

The study results show that technology trust (TT) has the strongest impact on passengers’ E-ticketing usage intention rather than perceived ease of use and perceived usefulness (PU). Meanwhile, the easiness of using technology to reserve tickets does matter to female passengers rather than male passengers wherein PU and TT do not do that.

The findings of this study might be helpful for the railway authorities to improve the ticket reservation service quality online by developing the advanced booking application and minimizing the pressure on other transportation. Therefore, this empirical study will contribute to this domain for further study that ensures full satisfaction of passengers and uplift the railway passengers’ usage intention for E-ticketing which then helps the government to implement the digitization slogan with efficiency and effectiveness.

This study aims to address customer focus as an important component of total quality management (TQM) and explore the key drivers of member satisfaction in tennis clubs via a novel theory-based member satisfaction index (MSI) model with high explanatory and predictive power. Furthermore, the study aims to investigate the relationship between satisfaction and behavioral intentions (willingness to stay; WTS) with consideration of the mediating effect of identification with the club.

This study uses variance-based partial least squares structural equation modeling (PLS-SEM) to estimate the MSI model, which was tested in a leading tennis club in Germany (n = 185).

The results reveal that club atmosphere, club facilities and the price/quality ratio of the membership fee are the most important drivers of member satisfaction in tennis clubs. Member satisfaction has a large influence on the WTS of tennis club members. Identification with the club, when included as a mediator in the model, increases the variance explained in WTS considerably.

The small sample limits the generalizability of findings, and further research is recommended.

The MSI model is a useful benchmark tool for club managers who want to quantify the satisfaction and WTS of their club members. In addition, because of the integrated formative measurement models, the PLS-SEM results show which indicators can be used to positively impact satisfaction with each of the service quality dimensions, overall member satisfaction and WTS. The most important of these results are discussed in an importance-performance map analysis.

The MSI model is a multi-attribute index model through which members' evaluations of various dimensions of service and value are derived through multivariable linear function with each dimension weighted according to its importance in one holistic model. The model shows the strong impact of satisfaction on WTS of sports club members and reveals that findings of previous research on the relationship between fan and spectator identification and loyalty are transferable to sports club members. The MSI represents a new contribution to the literature; it was applied here to tennis clubs but is also suitable for application to other sports clubs.

Drawing on social exchange theory, this study clarifies the roles of authenticity, interactivity and involvement in predicting customer engagement (CE) and, ultimately, customer loyalty towards an online peer-to-peer accommodation platform. In addition, the study explores the effect of interactivity in increasing authenticity.

Data were collected through an online questionnaire of a sample of Italian tourists who had previously booked a service on Airbnb. The analyses were conducted by adopting partial least squares structural equation modelling.

The model has high power in predicting customer loyalty to an online peer-to-peer accommodation platform. Specifically, involvement is the primary predictor of CE and customer loyalty. Authenticity and interactivity also have a significant and positive effect both on CE and customer loyalty. In addition, CE partially mediates the relationship between authenticity, interactivity and involvement and customer loyalty. Finally, interactivity has a significant positive effect on authenticity.

The results encourage hospitality service providers to invest in the creation (and co-creation) of authentic experiences to increase CE and customer loyalty. Hospitality managers can also enhance CE by increasing involvement and interaction with customers through various touchpoints (online and offline) in different moments of the customer journey.

This study proposes an original model to predict customer loyalty to peer-to-peer hospitality platforms. The findings shed new light on the drivers of CE and provide empirical support for the mediating effect of CE. The study also contributes to the literature on authenticity by demonstrating the positive effect of interactivity on authenticity.