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Many work-related factors particularly affect the mental well-being of young construction workers and subsequently affect their productivity at work. Young construction workers in South Australia are more vulnerable than other workers because they consider the distress arising from work-related factors to be part of adapting to a new work life. Therefore, this study seeks to draw out the work-related factors that affect the mental well-being of young construction workers.

The study employed a sequential mixed method approach including a preliminary qualitative case study and a quantitative survey. Around 20 interviews across two organisations were conducted in the initial case study and content analysis was used to contextualise the factors and identify new factors. Then, the outcome of the case study was fed into a questionnaire survey for further analysis. The survey received 43 valid responses. Principal component analysis (PCA) was performed on the survey outcome to assess and categorise the work-related factors.

The findings indicate ten prominent work-related factors contributing to poor mental well-being of young construction workers related to three main categories of factors, namely “nature of work”, “task-related stress” and “unsupportive behaviour”. The work-related factors that have the greatest impact on mental well-being are the machoism culture of industry, work overload and workplace bullying.

The outcome from this study enhances the understanding of key work-related factors affecting the mental well-being of young construction workers. Research findings would also help inform the development of clear, industry-informed initiatives tailored to protect and support young construction workers.

The world population is getting older and housing decisions matter to the security of retirement life and well-being. However, senior housing and financing decisions are largely overlooked in the literature. This study aims to provide a comprehensive overview of the senior housing and financing decisions in the USA.

Using 2021 American Housing Survey data and ordinary least squares estimates, this paper studies senior housing and financing decisions in the 15 most populous US metropolitan areas. Multiple regressions are used to analyze the whole sample as well as various subsamples.

This paper finds strong evidence that seniors are more likely to own a house with a higher market value compared with nonseniors. More specifically, although race and gender do not matter in this relationship, it is less pronounced among those with higher education. Also, seniors, especially white senior homeowners, are more likely to have a lower mortgage debt burden due to a higher upfront down payment than nonseniors. Last, seniors are more likely to refinance their homes and receive cash than nonseniors.

Constrained by the data limitations, this study specifically focuses on seniors’ housing and mortgage decisions. Future research could involve exploring seniors’ mortgage decisions by considering factors such as mortgage loan terms, borrower credentials and the evolving landscape of the senior housing market, among other aspects.

The findings would help policymakers and contractors in the construction industry better understand the uniqueness of challenges in the senior housing market and develop effective housing policies and programs that cater to the needs of the elderly. A comprehensive understanding of the senior housing market would also help seniors make informed purchase and financing decisions.

The authors propose providing financial education to the elderly, particularly those of disadvantaged status, to improve their expertise and bargaining skills in the mortgage loan application process.

This paper contributes to understanding the dynamic senior housing market, which encounters challenges and opportunities associated with the aging population. The study fills the gap of limited research regarding seniors’ housing decision and their financing choices in the USA and would help policymakers and contractors in the construction industry develop effective housing policies and programs that cater to the needs of the elderly.

This study aims to develop a novel diagnostic methodology for implementing ISO13485:2016 and test its applicability to improve quality management systems (QMS) in the medical devices industry context.

First, a literature review on the topic was conducted. Second, insights gained from the literature and expert interviews were employed to develop the new maturity assessment methodology. Subsequently, the methodology was tested on a medical device manufacturer. Next, based on the evaluation of the intervention, actions were recommended to improve the QMS.

Research findings have developed a maturity assessment methodology comprising 52 certifiable requirements structured into four macro-requirements derived from ISO 13485:2016. Findings show that the methodology is valuable for aiding QMS implementation, and the diagnosed maturity levels corresponded with the company’s empirical perceptions of the requirement’s maturity.

Empirical evidence validates the significance and practical utility of the proposed methodology, as evidenced by the company’s attainment of FDA (US Food and Drug Administration) approval after the intervention. Findings suggest that the methodology could be replicated within the medical products industry or adapted to assess other QMS, leveraging the organizational alignment with the international regulations of the sector and the ISO 9000 requirements.

The developed methodology fills existing gaps in both literature and practice within the medical devices industry, providing a valuable contribution by addressing the limited research on diagnostic methodologies designed for ISO 13485:2016 implementation. The article assists medical device enterprises in addressing QMS maturity levels as a metric for evaluating QMS requirements, which is an underexplored avenue in existing QMS evaluation approaches.

This study’s purpose is to analyze the effects of trade interventions and non-tariff impediments between the exporters (the United States and Brazil) and China for soybean trade.

A spatial model is developed and solved using an optimized Monte Carlo simulation (OMCS) and is used to minimize the costs of supplying soybeans to China. The costs included the origin basis; transportation to ports, including trucks, railways and barges; demurrage; and ocean freight. The sum of these charges determines the delivered costs to China from each origin. Most variables are random and correlated. Time-series distributions are based on historical data. Production and exports are highly seasonal and important.

Base-case flows are highly seasonal, are risky and reflect actual trade. Sensitivities illustrate the effects of mitigating the quality differentials and interpreting a term of the Phase One agreement that purchases would be made so long as the prices are competitive. The results are also used to illustrate the influence of diversifying from the United States as a supplier. Finally, the policy implications are discussed.

Removing the quality discounts for US soybeans raises the US market share by 9%. These results also illustrate that diversification of supply sources is important for the importing country. Indeed, if China were to pursue less diversification import costs and/or risks would escalate. Hence, these results suggest that diversification is an appealing element of an import strategy. The results suggest a large distribution of prices and costs, particularly in Brazil. On average, the United States is most likely to be competitive for only a few months of the year, and the results are highly seasonal.

Competition in supplying soybean to China is extremely competitive and the underlying factors impacting spatial competition are risk, correlated and spatially dependent. In addition to these, there are quality differences, and there are trade policies and strategies that affect competition. The empirical model and results illustrate the intensity of competition in this market as well the impacts of these non-tariff barriers and trade strategies in this market.

Important policies have been taken and continue to be under review regarding competition and trade among these countries. These results illustrate the impacts of these policies on market shares and competition.

This problem is important to the world soybean trading sector, and the methodology captures important seasonal and random variables that affect trade flows. The OMCS model is appropriate for this problem and has only been used minimally in the recent literature about commodity trade.

This study explores tourists' virtual reality experiences during the transition to the Metaverse.

Qualitative approach was employed to capture tourists' virtual reality experiences and knowledge of the Metaverse at two five-star hotels in Kusadasi (Republic of Turkey). The data were collected from Kusadasi using a purposive sampling technique. The research design focused on data collection with the structured interview technique. The interview form consisted of 7 questions in total, and a voice recorder was used to record the answers of the participants. After the first 4 questions were asked, the participants were presented a virtual reality experience with the virtual reality (VR) glasses. The interview was held face-to-face with thirty-five participants consisting of domestic and foreign tourists in two five-star hotels in the summer season of 2022. The collected data were analyzed with the content analysis technique and themes were created.

This study's findings enhance the conceptual capital in this emerging field and provide insights into many of the participants who have and have never experienced virtual reality applications and who are familiar and unfamiliar with the Metaverse as a concept.

This study generates empirical data that informs contemporary debates about virtual reality and the Metaverse.

The findings show that most participants have never experienced a virtual reality application. Hotels and travel agencies should be aware of this new futuristic technology before the Metaverse transition. Metaverse is for generation Y and Z instead of Baby Boomers and generation X.

This study is unique in terms of depth and fills the gap as it provides useful insights regarding the evaluation of tourists' virtual reality experiences in the transition process to the Metaverse.

The purpose of this study is to contribute to previous research on customer relationships by quantitatively examining differences in the monetary benefits obtained by consumers using social and commercial relationships to make purchases from small and medium-sized enterprises (SMEs).

Customer transaction and relationship data from an SME in the USA is used to quantitatively assess the value of different marketplace relationships in an entrepreneurial context. Tobit regression is used to empirically model and test the impact of specific relationship characteristics on customer discounts.

Customers using social connections to make purchases obtain significantly larger discounts than customers using commercial connections; customers using direct connections attain significantly larger discounts than consumers using indirect connections (referrals). Interestingly, when examined by connection type, direct and indirect connections do not produce significant differences for social connections, yet they yield notable differences for commercial connections. The findings provide valuable insights to entrepreneurs for understanding and managing customer relationships.

This study empirically demonstrates that social relationships can be both prevalent and influential in the marketplace. The methodology used to quantitatively assess the monetary value associated with different methods of engaging with SMEs allows objective comparisons among different types of customer relationships. Quantification also allows important relationship characteristics to be empirically examined, including how the relationships compare to one another and to nonpersonal marketing activities. Ultimately, these novel contributions generate important insights to help marketers and entrepreneurs better understand customer relationships.

Taking the element of saving face into account, this chapter uses LJN Resources as an example, specifically the communication pattern between the manager, Mr John (Gen Y category), and the founder, Mr Lim (Baby Boomers category), in which the son-in-law and father-in-law relationship complicates the communication dynamics. Communication exchange in the western versus eastern society is explained. Utilising lifespan development perspective as the framework, communication among employees of different ages in family business is examined, particularly those at the establishment stage versus maintenance stage. Application of two models of communication in choice theory, namely (a) caring habits replacing deadly habits and (b) circle of strength replacing triangle of pain, is being discussed.

To remain sustainable, open source software (OSS) projects must attract new members—or newcomers—who make contributions. In this paper, the authors develop a set of hypotheses based on the knowledge barriers framework that examines how OSS communities can encourage contributions from newcomers.

Employing longitudinal data from the source code repositories of 232 OSS projects over a two-year period, the authors employ a Poisson-based mixed model to test how community characteristics, such as the main drivers of knowledge-based costs, relate to newcomers' contributions.

The results indicate that community characteristics, such as programming language choice, documentation effort and code structure instability, are the main drivers of knowledge-based contribution costs. The findings also suggest that managing these costs can result in more inclusive OSS communities, as evidenced by the number of contributing newcomers; the authors highlight the importance of maintaining documentation efforts for OSS communities.

This paper assumes that motivational factors are a necessary but insufficient condition for newcomer participation in OSS projects and that the cost to participation should be considered. Using the knowledge barriers framework, this paper identifies the main knowledge-based costs that hinder newcomer participation. To the best of the authors' knowledge, this is the first empirical study that does not limit data collection to a single hosting platform (e.g., SourceForge), which improves the generalizability of the findings.

This study sought to investigate the attitudes of Vietnamese undergraduate business students towards English-Medium Instruction (EMI) courses.

Data were collected through purposive sampling using structured questionnaires, resulting in a dataset comprising 291 responses. This study employs a combination of Importance–Performance Analysis (IPA) and structural equation modeling (SEM) to evaluate students' perceptions of effectiveness of EMI courses, their satisfaction and loyalty.

The study’s findings revealed a noteworthy pattern: students assigned higher levels of importance to various aspects of EMI courses than the actual performance levels of these elements. Additionally, the analysis identified specific attributes that fell into different IPA quadrants, shedding light on their relative significance. Notably, the students placed their teachers' professional expertise and English proficiency in the “keep up the good work” quadrant, indicating the strengths of these attributes. In contrast, learning assessment techniques, course learning materials and electronic teaching platforms were situated in the “concentrate here” quadrant, implying room for improvement in these areas. Furthermore, it was observed that attributes falling within the “keep up the good work” quadrant had a positive effect on students' overall satisfaction and loyalty, while other characteristics did not significantly contribute to predicting these outcomes.

Based on these findings, the study offers recommendations for educational institutions and educators concerning the planning and implementation of EMI courses.