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At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications.

Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications.

This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development.

To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.

Construction progress monitoring (CPM) is considered a difficult and tedious task in construction projects, which focuses on identifying discrepancies between the as-built product and the as-planned design. Computer vision (CV) technology is applied to automate the CPM process. However, the synergy between the CV and CPM in literature and industry practice is lacking. This study aims to fulfil this research gap.

A Delphi qualitative approach was used in this study by conducting two interview rounds. The collected data was analysed using manual content analysis.

This study identified seven stages of CPM; data acquisition, information retrieval, verification, progress estimation and comparison, visualisation of the results and schedule updating. Factors such as higher accuracy in data, less labourious process, efficiency and near real-time access are some of the significant enablers in instigating CV for CPM. Major challenges identified were occlusions and lighting issues in the site images and lack of support from the management. The challenges can be easily overcome by implementing suitable strategies such as familiarisation of the workforce with CV technology and application of CV research for the construction industry to grow with the technology in line with other industries.

This study addresses the gap pertaining to the synergy between the CV in CPM literature and the industry practice. This research contributes by enabling the construction personnel to identify the shortcomings and the opportunities to apply automated technologies concerning each stage in the progress monitoring process.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The rise of cryptocurrencies and other digital assets has triggered concerns about regulation and security. Governments and regulatory bodies are challenged to create frameworks that protect consumers, combat money laundering and address risks linked to digital assets. Conventional approaches to confiscation and anti-money laundering are deemed insufficient in this evolving landscape. The absence of a central authority and the use of encryption hinder the identification of asset owners and the tracking of illicit activities. Moreover, the international and cross-border nature of digital assets complicates matters, demanding global coordination. The purpose of this study is to highlight that the effective combat of money laundering, legislative action, innovative investigative techniques and public–private partnerships are crucial.

The focal point of this paper is Australia’s approach to law enforcement in the realm of digital assets. It underscores the pivotal role of robust confiscation mechanisms in disrupting criminal networks operating through digital means. The paper firmly asserts that staying ahead of the curve and maintaining an agile stance is paramount. Criminals are quick to embrace emerging technologies, necessitating proactive measures from policymakers and law enforcement agencies.

It is argued that an agile and comprehensive approach is vital in countering money laundering, as criminals adapt to new technologies. Policymakers and law enforcement agencies must remain proactively ahead of these developments to efficiently identify, trace and seize digital assets involved in illicit activities, thereby safeguarding the integrity of the global financial system.

This paper provides a distinctive perspective by examining Australia’s legal anti-money laundering and counterterrorism financing framework, along with its law enforcement strategies within the realm of the digital asset landscape. While there is a plethora of literature on both asset confiscation and digital assets, there is a noticeable absence of exploration into their interplay, especially within the Australian context.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

This paper aims to examine the effect of critical mass of women managers on corporate boards on the voluntary disclosure of climate change in a developing country in which the regulations on climate change disclosure is an area of growing research interest.

This study uses logistic panel regression models with a sample of 1,001 firm-years for companies in the Borsa Istanbul 100 Index that were asked to disclose voluntary climate change indicators over the seven-year period from 2014 to 2020 through the Carbon Disclosure Project.

This paper provides evidence from an emerging country that the critical mass of women on the board has no impact on voluntary climate change disclosure. In addition, the presence of independent managers on the board was found to have a significant impact on climate change disclosure. In addition, the results show that larger companies are more likely to report their climate change activities. Large companies are more visible due to their size, are perceived by stakeholders as more polluting and are, therefore, more likely to report on the environment.

The results show that the critical mass of women on the board has no effect on voluntary disclosure of climate change. Empirical tests are still needed to strengthen the overall validity of the critical mass of at least three women on boards in Türkiye.

Despite many valuable insights provided by critical mass theory, very few studies directly address critical mass and voluntary disclosure of climate change. To the best of the authors’ knowledge, this study is the first empirical and comprehensive paper in the Turkish context evaluating critical masses and voluntary corporate climate change giving a comparison between firms listed on financial industry and nonfinancial industry.

The aim of this study was to observe how a user’s individual factors in a commercial weight-loss treatment app affect their perceived usefulness of its features and how they relate to each other.

The information was obtained from an online survey with a sample of 412 users from a branded app for a commercial weight-loss treatment using body mass index (BMI), self-efficacy, social support and perceived usefulness as variables.

Users with higher self-efficacy perceived the app’s features as more useful. However, BMI was not a factor except for the psycho-emotional support features, which individuals with obesity perceived as more useful. Likewise, it was found that there weren’t any significant differences in self-efficacy based on their BMI. Lastly, it was found that social support could not be used as a factor to predict self-efficacy.

This study helps understand how individual factors for behavioural change may affect the perceived usefulness of a weight-loss app. Furthermore, the significance of self-efficacy as an influencing factor provides useful information for companies and app developers alike when developing their branded apps.

This study contributes to the body of knowledge on factors affecting user perceptions of weight-loss apps. It also adds to the literature of branded apps as complimentary resources for companies, which has not been studied in detail.

The aim of this review is to present together the studies on textile-based moisture sensors developed using innovative technologies in recent years.

The integration levels of the sensors studied with the textile materials are changing. Some research teams have used a combination of printing and textile technologies to produce sensors, while a group of researchers have used traditional technologies such as weaving and embroidery. Others have taken advantage of new technologies such as electro-spinning, polymerization and other techniques. In this way, they tried to combine the good working efficiency of the sensors and the flexibility of the textile. All these approaches are presented in this article.

The presentation of the latest technologies used to develop textile sensors together will give researchers an idea about new studies that can be done on highly sensitive and efficient textile-based moisture sensor systems.

In this paper humidity sensors have been explained in terms of measuring principle as capacitive and resistive. Then, studies conducted in the last 20 years on the textile-based humidity sensors have been presented in detail. This is a comprehensive review study that presents the latest developments together in this area for researchers.

This study examined the determinants of mobile health (M-Health) application, adoption, usage and discontinuation among corporate workers diagnosed with hypertension and diabetes in Ghana.

The diffusion innovation and reasoned action theories were employed using an exploratory design. Three hundred corporate workers diagnosed with diabetes and hypertension from three health facilities for the past six months were sampled for the study using a multi-stage sampling technique and administered questionnaires. Descriptive statistics and logistic regression tools were employed in the analysis of data.

The study found a significant number of factors influencing m-health applications adoption, usage and discontinuity. These factors include nature and demand of job, perceived advantage, compatibility, complexity, triability, aesthetics and trust. Aesthetics emerged as the strongest predictive factor for the adoption, usage and discontinuity of use among diabetic and hypertensive corporate workers. With the adoption of M-Health applications, compatibility, as well as nature and demand of job, were significant predictors. With the usage of M-Health applications, complexity, triability, aesthetics and trust were significant predictors. Moreover, perceived advantage, compatibility, complexity and triability influenced significantly the choice to discontinue using M-Health applications. The study concluded that M-Health application functionalities play a valuable role in patients’ intention to adopt, use and discontinue the use of an M-Health application in Ghana.

This exploratory study offers in-depth insight into how major M-Health application features affect its adoption, usage and discontinuity, providing crucial information for future research and the improvement of chronic condition healthcare delivery.

The purpose of this study is to compare violent and non-violent extremists in terms of their age when they first perpetrate an extremist act, and to understand how this relates to other factors underlying extremist behaviours. While the end goal of many extremists may be functionally similar, the pathways into extremism vary, and the literature has demonstrated that a “one-size-fits-all” explanation does not exist. Motivational drivers are complex and dynamic; therefore, attempting to identify a terrorist “profile” has limited applied efficacy.

This study applied a temporal approach (“crime script analysis” or CSA) to identify, map and compare the sequential stages (or “scenes”) in the life histories of violent and non-violent extremists who have committed acts of extremism across different age groups. Crime scripts comprising mainly qualitative data for 40 male extremists (20 violent, 20 non-violent “cases”) were developed, and CSA was conducted according to the age at which they committed their first extremist offence.

Results demonstrated key temporal, developmental differences between the pathways of extremists who commit their first offence at different ages. One key difference was that for both the violent and non-violent extremists, those under 30 used the internet as a main means of joining networks and spreading information, whereas the over 30s made more personal, community links.

This research can aid identification of potential environmental triggers and potential increased susceptibility to triggers across certain age groups.