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Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

Research on the practice of child marriage has been extensive, with studies recommending local strategies that are peculiar to the countries involved. Rights-based literature also recommends stringent laws; portraying the girls involved as helpless victims needing external agencies to rescue them from parochial and oppressive cultural practices. This chapter, however, presents their resilience as they navigate through the challenges and trauma of demeaning marriage practices. Their ability to rise above the challenges of child marriage contradicts the stereotypical perception of being passive and unable to develop agency and empower themselves. The author also draw from the experiences of these young women to argue for restorative justice (RJ) to tackle child marriage issues. Indeed, a restorative process is likely to prove far more effective in achieving social discipline than the current reliance on punishment and sanctions. More so, harm as a result of child marriage is a violation against the victim and not necessarily the state. Hence, RJ, which is future-focussed with healing and prevention as key goals, would be more suitable.

This paper aims to present a comprehensive overview of the patterns and trends of publications on artificial intelligence (AI) in personalised learning. It addresses the need to investigate the intellectual structure and development of this area in view of the growing amount of related research and practices.

A bibliometric analysis was conducted to cover publications on AI in personalised learning published from 2000 to 2022, including a total of 1,005 publications collected from the Web of Science and Scopus. The patterns and trends in terms of sources of publications, intellectual structure and major topics were analysed.

Research on AI in personalised learning has been widely published in various sources. The intellectual bases of related work were mostly on studies on the application of AI technologies in education and personalised learning. The relevant research covered mainly AI technologies and techniques, as well as the design and development of AI systems to support personalised learning. The emerging topics have addressed areas such as big data, learning analytics and deep learning.

This study depicted the research hotspots of personalisation in learning with the support of AI and illustrated the evolution and emerging trends in the field. The results highlight its latest developments and the need for future work on diverse means to support personalised learning with AI, the pedagogical issues, as well as teachers’ roles and teaching strategies.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

Recycling construction waste is a promising way towards sustainable development in construction. Recycled aggregate (RA) is obtained from demolished concrete structures, laboratory crushed concrete, concrete waste at a ready mix concrete plant and the concrete made from RA is known as RA concrete. The purpose of this study is to apply multiple linear regressions (MLRs) and artificial neural network (ANN) to predict the mechanical properties, such as compressive strength (CS), flexural strength (FS) and split tensile strength (STS) of concrete at the age of 28 days curing made completely from the recycled coarse aggregate (RCA).

MLR and ANN are used to develop a prediction model. The model was developed in the training phase by using data from a previously published research study and a developed model was further tested by obtaining data from laboratory experiments.

ANN shows more accuracy than MLR with an R²-value of more than 0.8 in the training phase and 0.9 in a testing phase. The high R²-value indicates strong relation between the actual and predicted values of mechanical properties of RCA concrete. These models will help construction professionals to save their time and cost in predicting the mechanical properties of RCA concrete at 28 days of curing.

ANN with rectified linear unit transfer function and backpropagation algorithm for training is used to develop a prediction model. The outcome of this study is the prediction model for CS, FS and STS of concrete at 28 days of curing.

While the idea of the resilience of information systems security exists, there is a lack of research that conceptualizes, defines and specifies a way to measure it as a dynamic capability. Drawing on relevant cybersecurity and dynamic capabilities literature, this study aims to define Information Systems Security Resilience (ISSR) as a “dynamic capability of a firm to respond to, and recover from, a security attack” and test it as a new construct.

The authors employ a methodology including multiple phases to develop and test this construct of ISSR. The authors first interview senior managers from various organizations to establish the face validity of the construct; then develop and analyze a pilot survey for internal validity and reliability; and finally, design and deploy a field survey to test and externally validate the construct.

The authors conceptualize and define the construct of ISSR as a dynamic capability, develop a scale for its measurement and test it in a pilot and field survey. The construct is valid, and the measurement tool works. It demonstrates that resilience is something that is done, rather than had. As a capability, organizations need to track and measure ISSR, which is what this tool provides the ability to do.

This research contributes to the information systems and cybersecurity literature and offers valuable insights for organizations to manage their security effectively.

The textile sector is one of the sectors where competition is intense and requires the production of high-value-added products. This study aims to conduct patent analysis to find the technology status, recent trends, applications and technological evaluations of protective textile technologies in practice.

More than 36,840 patent documents related to protective textile technologies are available for researchers, patent examiners and patent researchers. Patent analysis is conducted to report the technology status, recent trends and applications of protective textile technologies. This analysis provides insights into the possible future directions of protective textile technologies in practice. Additionally, association rule mining (ARM) is performed to find the hidden patterns among protective textile technologies.

The development of protective textile technologies is revealed by the technology evaluation in this study. In addition, the sub-technology classes affecting protective textile technologies are examined using the cooperative patent classification (CPC) codes of the patent documents. Technology status and recent trends of protective textile technologies are provided in detail. The results of this study show that (1) protective textile technologies are constantly being developed, (2) the working areas of medical protective textiles are increasing, (3) there are frequent studies on fabric structures for saving lives within the framework of human needs and (4) there are four technology classes, namely A41D, Y10T, B32B and A62B impacting the other technology classes related to textile technologies such as D10B, Y10T, F41H, A62D, D04H, Y10S and D10B.

To have a competitive advantage in the marketplace, evaluation of textile technologies is critical in developing “functionalized” and “technologized” textile products. In particular, evaluating technologies in developing protective textile products is extremely important to meet customer demands and present competitive products in the market. Examining these patents for technology developers, decision-makers and policymakers is an urgent and necessary job. However, studies examining the development of protective textile technologies with patent analysis are very limited in the literature. To fill this gap, technology status, recent trends and applications of protective textile technologies are reported based on patent analysis and ARM in this study.

The purpose of this study is to perform comprehensive investigation to assess the mechanical properties of nano-modified ternary cement concrete blend. Nano silica (NS) (1%, 2% and 3%) and waste marble dust powder (MD) (5%, 10% and 15%) was incorporated as a fractional substitution of cement in the concrete matrix.

In this experimental study, 10 cementitious blends were prepared and tested for compressive strength, flexural strength, splitting tensile strength and static modulus of elasticity. The microstructural characteristics of these blends were also explored using a scanning electron microscope along with energy dispersive spectroscopy and X-ray reflection.

The results indicate an enhancement in mechanical properties and refinement in pore structure due to improved pozzolanic activities of NS and the filling effect of MD.

To the best of the authors’ knowledge, no study has reported the mechanical and microstructural behavior of concrete containing marble and NS.

Based on the extended theory of planned behavior, this study aims to examine potential intentions-related factors that affect Islamic tax compliance moderated by information and communication technology (ICT) adoption.

A quantitative cross-sectional design was used to distribute questionnaire sets to 975 working Muslim Omanis by using convenience sampling method. PLS-SEM was mainly used to examine the data.

All the factors determine behavioral intention to pay Islamic tax (BIIT), which significantly predicts Islamic tax compliance behavior (ITCB). However, perceived control behavior negatively determines intention. ICT adoption moderates the link between BIIT and ITCB.

This study offers both practical and theoretical implications that can guide efforts to promote Islamic tax compliance and advance our understanding of tax behavior within the ETPB framework.

This study accounted for crucial factors determining intention than earlier ones using the ETPB. Considering technological advancements, the study also assessed the moderating role of ICT between BIIT and ITCB.