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Individual Placement and Support (IPS) is an evidence-based employment model, effective in supporting individuals with severe mental health difficulties to gain competitive employment. Irish mental health policy recognises its value and IPS is being rolled out in a national programme. Employment is recognised an important contributor to mental health recovery and social inclusion. However, research on IPS has tended to focus on competitive job outcomes. The purpose of this study was to explore the non-vocational outcomes of IPS in an Irish context.

A qualitative research approach was used to interview participants taking part in IPS within community mental health teams. Twelve interviews were included in the data analysis process which was informed by a thematic analysis approach.

Participants experienced increased confidence and positivity, both within a work context and whilst job seeking. More purposeful time use, participation in activities and engagement with society were also experienced by those employed and those at the job search stage of IPS.

This study contributes to the literature about the non-vocational benefits of IPS within an Irish context, highlights the mental health recovery benefits of taking part in IPS and supports the need for ongoing development of IPS throughout mental health services in Ireland.

This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.

From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.

The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.

This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.

Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

The purpose of this paper was to study the color change kinetics of lac dye in response to aldehydes, carbon dioxide and other food spoilage metabolites for its potential application in intelligent food packaging.

UV–Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A₅₂₈/A₄₈₈) with time using zero and first-order reaction kinetics. Lac dye-based indicator was prepared to validate the result of study for monitoring quality of strawberries.

Lac dye was orange-red in acidic medium and purple in alkaline medium. Color change of dye in response to benzaldehyde followed zero-order reaction kinetics, whereas for carbon dioxide first-order model was found best. No color change of dye solution was observed for alcohols, ketones and sulfur compounds. In the validation part, the color of the indicator label changed from purple to orange when the strawberries spoiled.

The study expands application area for lac dye as sensing reagent in intelligent food packaging for spoilage or ripeness detection of fruits and vegetables.

The study investigates the antecedents and consequences of digital ad avoidance in the e-commerce industry. This study aims to investigate how digital ad avoidance relates to internet usage over time, using a two-wave longitudinal research design. This study also explores how real-world advertising clutter (clutter and non-clutter) affects these relationships.

The data were collected from 192 online consumers in Türkiye, and a two-wave longitudinal research design and structural equation modeling were conducted to test the hypotheses of the conceptual model.

The results indicated that perceived goal impediment and prior negative experience had positive effects on affective avoidance in both ad-clutter and non-clutter periods. Further, affective avoidance had a significant positive effect on both cognitive and behavioral avoidance in either period. In addition, ad clutter moderated the effects of cognitive and behavioral avoidance on online purchase intention.

This research provides new evidence of the crucial role perceived goal impediment, prior negative experience and perceived control each play in driving digital ad avoidance. This paper contributes to the body of knowledge in the field by exploring how advertising clutter (both cluttered and non-cluttered settings) moderates these relationships through a two-wave longitudinal study.

This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).

The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.

Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.

Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.

Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

This study aims to present a framework for automatically collecting, cleaning and analyzing text (news articles, in this case) to provide valuable decision-making information to destination management organizations. Keeping a record of certain aspects of the projected destination image of an attraction (Cancun in this study) will grant the design of better strategies for the promotion and administration of destinations without the time-consuming effort of manually evaluating high quantities of textual information.

Using Web scraping, news articles were collected from the USA, Mexico and Canada over an interval of one year. The documents were analyzed using an automatic topic modeling method known as Latent Dirichlet Allocation and a coherence analysis to determine the number of themes present in each collection. With the data provided, the authors were able to extract valuable information to understand how Cancun is presented to the countries.

It was found that in all countries, Cancun is an important destination to travel and vacation; however, given the period defined for this study (from July 2021 to July 2022), an important part of the articles analyzed was concerned with the sanitary measures derived from the COVID-19 pandemic. Besides, given the rise of violence and the threat of organized crime, many articles from the three countries are focused on warning potential tourists about the risks of traveling to Cancun.

The examination of the relevant literature revealed that similar analyses are manually performed by the experts on a set of predefined categories. Although those approaches are methodologically sound, the logistic effort and the time used could become prohibitively expensive, precluding carrying out this analysis frequently. Additionally, the preestablished categories to be studied in press articles may distort the results. For these reasons, the proposed framework automatically allows for gathering valuable information for decision-making in an unbiased manner.

This research focuses on the distinct group of high-status employees commonly referred to as workplace vigilantes, and conceptually investigates how unethical requests by these individuals impact the behavior and attitude of other employees over time using the social identity theory.

For developing a conceptual model, literature from the domains of social identity, organizational behavior and general management was searched through Google Scholar. To search the literature, some key terms such as “unethical activities”, “Islamic work ethics” and “social identity” were searched and analyzed.

Using the social identity theory, a conceptual process model is developed which suggests that when high-status employees propose unethical requests to employees, individuals with high morality are likely to refuse those unethical requests to protect their self-categorizations. However, taking the unfair advantage of their illegitimate powers, high-status employees are likely to eventually make wrong judgments and give unnecessary punishments to moral employees. It is further argued that consistent victimization is likely to negatively impact the social identity of such employees and leads to irritability in moral employees, particularly when such individuals are unable to get the requisite social support from their leaders.

While a considerable body of literature has focused on the antecedents and consequences of intense unethical business practices and the crucial role of leaders in such activities, limited attention has been given to the role of other employees and how they engage in mild unethical misconduct regularly, which is the key focus of this research. The novel conceptual framework needs to be tested in diverse contexts for further development and validation.

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.

This study aims to explore the gender differences in working from home (WFH) experiences during the pandemic from the Australia’s construction workforce perspective. Specifically, it explores gender differences in terms of: (1) the respondents’ family responsibilities during the pandemic; (2) their WFH experiences prior to and during the pandemic; and (3) their perceptions of the impacts of challenges associated with WFH on their work activities and performance along with their self-reported work performance when WFH, overall satisfaction with WFH and preference for WFH post-COVID.

This study adopted a survey design to reach the targeted sample population, i.e. construction workforce in the Australian construction industry who has had experienced WFH during the pandemic. Data was collected using an online anonymous questionnaire survey.

The results show notable gender differences in various aspects including family responsibilities, workplace arrangements and perceptions of the impacts of the challenges associated with WFH on work activities and performance. Also, statistically significant associations are detected between gender and the respondents’ self-reported work performance when WFH, overall satisfaction with WFH and preference for WFH post-COVID.

Even prior to the COVID-19 pandemic, little is known about WFH experiences among construction workforce due to the low prevalence of regular and planned remote working in the industry. This is the first study sheds light on construction workforce WFH experiences using gender lenses. The findings have implications for construction-related firms continuing with WFH arrangement post the pandemic, which may include the formulation of policy responses to re-optimize their present WFH practices.