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The purpose of this study was to explore the leadership competencies that are effectively transferring into the workplaces of recent military college alumni from both their curricular and co-curricular experiences.

Through semi-structured interviews, this study explored 15 military college alumni’s perspectives on the leadership competencies they developed in college and currently apply in the workplace.

The findings indicated the 15 military college alumni participants developed and applied the following student leadership competencies at work: productive relationships, helping others, supervision, empathy, ethics, functioning independently, resiliency, positive attitude and scope of competence.

Limited research explores leadership learning at military colleges and service academies in the United States. Yet these collegiate military environments have a missional focus on leadership education and development. This article highlights the importance of the alumni lens in assessing leadership learning in collegiate military environments and provides recommendations to administrators of this institution type.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This study explores the moderating effect of board gender diversity (BGD) between a firm's Environmental, Social, and Governance (ESG) performance and Economic value added (EVA) using NSE-listed 331 companies' data from 2015 to 2020, forming 1986 firm-year observations.

Our study is based on panel data; hence, we use a system GMM panel regression model to confirm whether the BGD moderates ESG and EVA. We also address the endogeneity issues.

Overall, our study reported a positive moderating effect of BGD between ESG and EVA. Similar results were observed across the chemical and financial services industries. However, in the case of the healthcare and consumer goods industries, we did not find support for the moderating effect.

The implications of our results are considerable and relevant for regulators, governing bodies, and corporate managers. It helps them understand how BGD plays a vital role in influencing the effect of ESG on a firm's EVA.

No existing research has explored the moderating effect of BGD between ESG and EVA, to the authors' best knowledge. Therefore, our study extends the existing literature and further supports resource dependency, agency, and stakeholder theories of corporate governance.

The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.

Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.

This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.

This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

This paper aims to understand if buy-now-pay-later (BNPL) services, a digital type of credit that targets young consumers, acts as a protective or a risk factor for food insecurity among young consumers in Australia.

The study uses survey data from a representative sample of young consumers aged 18–24 from all internal states and territories in Australia. Propensity score matching is used to test two hypotheses: BNPL drives young consumers to food insecurity, and food insecurity leads young consumers to use BNPL.

There is evidence that BNPL use is driving young Australian consumers to experience food insecurity, but there is no evidence of food insecurity driving the use of BNPL services.

The evidence of BNPL driving young consumers to experience food insecurity calls for the adoption of practices and stronger regulation to ensure that young users from being overindebted.

Although the link with more traditional forms of credit (such as personal loans) and consumer wellbeing has been explored more broadly, this project is the first attempt to have causal evidence of the link between BNPL and food insecurity in a high-income country, to the best of the authors’ knowledge. This evidence helps to fill the gap about the protective or risky nature of this type of digital financial product, as experienced by young Australians.

Co-production improves the quality of healthcare services by prioritizing patient-centred care and ensuring optimal implementation. Current patient participation research have primarily concentrated on the co-production stages, despite patient participation being the central emphasis of its implementation. A study conducted analysed four specific attributes of patient participation, with patient engagement specifically emphasizing the interactions between patients and healthcare workers. Several studies have concluded that the interaction between the two actors is inefficient. This article examines current study trends concerning patient participation and identifies knowledge gaps from these studies.

This study used bibliometric analysis. This study used VOSviewer software for bibliometric analysis. The Scopus database contained 398 publications about patient participation in co-production in healthcare, which served as the basis for the analysis.

The study on patient engagement in a co-production context for healthcare had grown fast in recent years. Patient-centred approach and patient-centred care were two important things in patient engagement. Several factors influenced the implementation of patient engagement: attitude, ability, awareness, responsibility and knowledge. It is still uncommon to do research on the measurement of output and results from patient engagement implementation. Studies on instruments for measuring these two factors, particularly in a quantitative manner, are still few.

Various recommendations have been put forward for additional investigation. Firstly, further examination of outcome measurement in patient engagement is necessary, given the lack of decisive instruments available. Secondly, examining the most influential factors on patient engagement in co-production in healthcare. Thirdly, a more thorough analysis is needed regarding the dimensions of co-production, considering that some dimensions overlap, such as the activation and empowerment dimensions, which are really carried out during engagement. The researcher acknowledges the inherent limitations of bibliometric studies, including the dependence on the Scopus databases for extracting data and the choice of search phrases. Furthermore, conducting a systematic literature review may be necessary to thoroughly examine and delineate the research topics, methodologies and outcomes of this study.

This study updates us on patient engagement study trends and establishes a framework for implementing patient engagement in healthcare services.

The crane plays an essential role in modern construction sites as it supports numerous operations and activities on-site. Additionally, the crane produces a big amount of data that, if analyzed, could significantly affect productivity, progress monitoring and decision-making in construction projects. This paper aims to show the usability of crane data in tracking the progress of activities on-site.

This paper presents a pattern-based recognition method to detect concrete pouring activities on any concrete-based construction sites. A case study is presented to assess the methodology with a real-life example.

The analysis of the data helped build a theoretical pattern for concrete pouring activities and detect the different phases and progress of these activities. Accordingly, the data become useable to track progress and identify problems in concrete pouring activities.

The paper presents an example for construction practitioners and researcher about a practical and easy way to analyze the big data that comes from cranes and how it is used in tracking projects' progress. The current study focuses only on concrete pouring activities; future studies can include other types of activities and can utilize the data with other building methods to improve construction productivity.

The proposed approach is supposed to be simultaneously efficient in terms of concrete pouring detection as well as cost-effective. Construction practitioners could track concrete activities using an already-embedded monitoring device.

While several studies in the literature targeted the optimization of crane operations and of mitigating hazards through automation and sensing, the opportunity of using cranes as progress trackers is yet to be fully exploited.

This short paper builds on and critiques work presenting potential non-disasters: disasters that did not seem to happen despite a major hazard. Previous work does not differentiate among different types of potential non-disasters. This short paper uses local information to propose three categories according to reasons for vulnerability being low or absent. These proposed categories are used to critique the construct of “potential non-disasters”.

This short paper uses a subjective approach to examples of potential non-disasters in 2022, focusing on local information that describes what happened. This information is applied and analysed for the three proposed categories using examples from Japan, Nepal, the Philippines and Vietnam. Such comparisons are useful for critiquing “potential non-disasters”, by understanding better local approaches and information available for reporting on situations that could be disasters.

Potential non-disasters remain relevant for exploring mechanisms, tools and actions for educating about vulnerability causes and vulnerability reduction to avert disasters. Limitations are evident by relying on media reports, even local ones with local authors. A suggestion is to implement a grant programme for collecting data immediately after a major hazard without an evident, major disaster. Additionally, an annual report and critique of each year's potential non-disasters, categorised and analysed, would help to evidence the presence and limits of the “potential non-disaster” construct.

This short paper contributes a much deeper theoretical dive into understanding potential non-disasters, both describing them and the drawbacks of the construct. To practitioners, the construct now offers more avenues for actions while illustrating their effectiveness in reducing vulnerabilities. Thus, this paper supports multiple, linked pathways towards more non-disasters.

Prefabricated building (PB) uses factory production and onsite assembly, which differs from traditional construction methods. This special construction approach may lead to dissimilar safety risks and challenges. Traditional safety assessment methods may not adequately and accurately assess the safety risks of PB construction. This paper aims to develop a new concept and methodology for targeted improvement in assessing PB safety risks.

Risk factors and indicators were established based on literature review and expert inputs. A structural equation model (SEM) was developed to investigate the relationships among three main risk categories: objects, workers and management. SEM analyzed the intricate associations between indicators and deepened understanding of safety risks. The model was tailored for China’s PB construction projects to enhance safety-risk management.

The cloud model evaluation validated the SEM model. A PB case study project tested and verified the model, evaluated its efficacy and quantified its safety performance and grade. We identified significant safety risk impacts across the three risk categories, safety-control level and specific areas that require improvement. The SEM model established a robust safety evaluation indicator system for comprehensive safety assessment of PB construction.

Practical recommendations provide valuable insights for decision-makers to enhance construction efficiency without compromising safety. This study contributed to the conceptual foundation and devised a novel method for evaluating safety performance in PB construction for safer and more efficient practices.

This study departed from the traditional method of calculating weights, opting instead for the SEM method to determine the weights of individual risk indicators. Additionally, we leveraged the cloud model to mitigate the influence of subjective factors in analyzing questionnaire survey responses. The feasibility and reliability of our proposed method were rigorously tested and verified by applying it to the PB case.

Peer-to-peer accommodation (P2PA) has witnessed remarkable growth across the globe recently. However, acceptance of P2PA among residents in developing economies is still fraught with several challenges. The paper aims to extend the constraint–negotiation framework to examine the motivations, perceived constraints, negotiation strategies and the role of learned helplessness of local residents to host tourists.

The data was collected through a self-administered questionnaire by using cluster random sampling technique. In total, 454 usable questionnaires were collected through on-site research. The structural model was tested by using survey data by applying PLS-SEM 4.0.

The results suggest that while perceived constraints can inhibit residents from hosting, negotiation strategies can reduce helplessness and encourage residents to host tourists.

Theoretically, this study advances P2PA literature by integrating learned helplessness in the constraint–negotiation framework and it offers insights for the P2PA providers as well as policymakers.

This is a pioneering study to examine the role of learned helplessness using constraint–negotiation framework in the context of P2PA, thus paving the way to advance P2PA-related research from the residents’ perspective.