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Cost overrun is inherent to project chaos, which is one of the key drivers of project failure. The purpose of this paper is to explore the critical elements of complexity-risk interdependency for cost-chaos in the construction management domain by utilizing a multi-criteria decision model.

A total of 12 complexity and 60 risk attributes are initially identified from the literature and using expert’s judgements. For the development of a structured hierarchy of key complexity and risk drivers, a real-time Delphi process is adopted for recording and evaluating the responses from experts. Afterwards, a pair-wise comparison using analytical network processing is performed to measure complexity-risk interdependencies against cost alternatives.

The findings of the integrated priority decision index (IPDI) suggest that uncertainties related to contingency and escalation costs are the main sources of cost overrun in project drift, along with the key elements such as “the use of innovative technology,” “multiple contracts,” “low advance payment,” “change in design,” “unclear specifications” and “the lack of experience” appear to be more significant to chaos in complexity-risk interdependency network.

This study did not address the uncertainty and vulnerability exit in the judgment process, therefore, this framework can be extended using fuzzy logic to better evaluate the significance of cost-chaos drivers.

These results may assist the management of cost overrun to avoid chaos in a project. The proposed model can be applied within project risk management practices to make better-informed technical decisions in the early phases of the project life cycle where uncertainty is high.

This research addresses the importance of cost overruns as a source of project chaos in dynamic systems where projects reach the edge of chaos and progress stops. A new IPDI index contributes toward evaluating the severity of complexity and risk and their interdependencies which create cost-chaos in infrastructure transport projects.

Cost estimation is a major concern while planning projects on public–private partnership (PPP) terms in developing countries. To bridge the gap of the right approximation of cost of capital, this study aims to sermon a significant role of investor’s risk perception as unsystematic risk in PPP-based energy projects.

To investigate the effective mechanism of determining cost of capital and valuing the capital budgeting, a pure-play method has been acquired to measure systematic risk. In addition, dynamic conditional correlation (DCC) and generalized autoregressive conditional heteroscedasticity (GARCH) models have been applied to calculate weighted average cost of capital.

Initially, a joint cost of capital of energy-related projects has been calculated using DCC-GARCH and pure-play method. Investors risk perception has been discussed through market point of view using country risk premium modeling. Latter yearly betas have been calculated using DCC signifying the final outcomes that applying a dynamic model can provide a better cost estimation in emerging economies.

The findings are implicating that due to the involvement of international investors, domestic risk is linked with country risk. In such situations, market-related information is a key factor to find out the market performance, helping in the estimation of cost of capital through capital asset pricing model (CAPM). High dynamic nature of emerging economies causes an impediment in the estimation of cost of capital. Consequently, to calculate risk in dynamic markets, this study has acquired DCC model that can predict the value of beta factor.

Study contributes to the body of knowledge by addressing an important issue of investor’s risk perception and effective implication of CAPM using pure-play and DCC-GARCH when data is not promptly available in dynamic situations.

Because of the growing financial market integration, China’s stock market’s volatility spillover effect has gradually increased. Traditional strategies do not capture stock volatility in dependence and dynamic conditions. Therefore, this study aims to find an effective stochastic model to predict the volatility spillover effect in the dynamic stock markets.

To assess the time-varying dynamics and volatility spillover, this study has used an integrated approach of dynamic conditional correlation model, copula and extreme-value theory. A daily log-returns of three leading indices of Pakistan Stock Exchange (PSX) and Shanghai Stock Exchange (SSE) from the period of 2009 to 2019 is used in the modeling of value-at-risk (VaR) for volatility estimation. The Student’s t copula has been selected based on maximum likelihood estimation and Akaike’s information criteria values of all the copulas using the goodness-of-fit test.

The model results show stronger dependency between all major portfolios of PSX and SSE, with the parametric value of 0.98. Subsequently, the results of dependence structure positively estimate the spillover effect of SSE over PSX. Furthermore, the back-testing results show that the VaR model performs well at 99% and 95% levels of confidence and gives more accurate estimates upon the maximum level of confidence.

This study is helpful for the investment managers to manage the risk associated to portfolios under dependence conditions. Moreover, this study is also helpful for the researchers in the field of financial risk management who are trying to improve the returns by addressing the issues of volatility estimations.

This study contributes to the body of knowledge by providing a practical model to manage the volatility spillover effect in dependence conditions between as well as across the financial markets.

Flexibility in the workplace is increasingly considered an important aspect of human resource strategy aimed at attracting and retaining a high-quality workforce. The purpose of this study is to explore the direct relationships between both employee- and employer-centered flexible work arrangements and turnover intentions, specifically focusing on Generation Z employees. In addition, this study also examines the mediating role of supervisor support and total rewards in these relationships.

This study used a quantitative research design using a cross-sectional survey method to gather data from employees born from 1995 across three industries – logistics, retail sales, and manufacturing. Partial least-squares structural equation modeling was used to analyze the data. The survey was conducted online, ensuring a diverse geographical spread and adherence to the representativeness of Generation Z within these sectors.

Contrary to existing literature, the findings reveal no direct correlation between flexible working arrangements (FWAs) and turnover intentions in this demographic. Instead, the results highlight the significant mediating roles of perceived supervisor support and total rewards. Specifically, these factors were found to influence turnover intentions in relation to the availability of employee-centered FWAs. The findings provide theoretical and practical implications, suggesting an adaptation of human resource strategies to better align with the preferences and expectations of Generation Z in the workplace.

In contrast to existing literature, this study examines the relationship between the availability of two different types of flexible work arrangements (employee- and employer-centered) and turnover intentions, specifically among Generation Z employees. In addition, this research introduces mediation analysis to investigate the roles of perceived supervisor support and total rewards – constructs that have been rarely considered in the context of these relationships.

This study is the maiden attempt to understand the influence of four specific sources of employee support (SES), on the life insurance agents’ retention (AR) with the mediation of felt obligation (FO) in the context of the life insurance industry.

This study adopted a quantitative methodology and used the partial least squares-structural equation modelling to test the hypotheses of the study. Using convenience sampling method and a web-based questionnaire, this study gathered data from agents (n 265) of life insurance companies located in the central region of Malaysia.

The results reveal a positive relationship between all SES and AR. This means when agents perceive higher levels of support from their supervisors, peers, technology and mentors, they are more likely to remain in the industry. Contrary to the expectations, FO does not mediate the relationship between SES and AR, indicating that SES directly influences AR without the involvement of FO.

This study is the first to explore how an integrated model of SES influences AR within the Malaysian life insurance industry. The model takes a comprehensive approach, incorporating various SES including the less studied perceived technological support in influencing AR through the framework of social exchange theory.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

This study investigates the impact of the COVID-19 pandemic on investors' sentiments, behavioral biases and investment decisions in the Pakistan Stock Exchange (PSX).

The authors have assessed investors' behaviors and sentiments and the stock market overreaction during COVID-19 using a questionnaire and collected data from 401 investors trading in the PSX.

Results of structural equation modeling revealed that the COVID-19 pandemic affected investors' behaviors, investment decisions and trade volume. It created feelings of fear and uncertainty among market participants. Evidence suggests that behavioral heuristics and biases, including representative heuristic, anchoring heuristic, overconfidence bias and disposition effect, negatively influenced investors' decisions at the PSX.

This study will contribute to behavioral finance literature in the context of developing countries as it has revealed the impact of COVID-19 on the emerging stock market, and its results are generalizable to other emerging stock markets.

The findings of this study will help academicians, researchers and policymakers of developing countries. Academicians can formulate new behavioral models that can depict the solutions of dealing with an uncertain situation like COVID-19. Policymakers like the Securities Exchange Commission and the PSX can formulate crisis management strategies based on behavioral finance concepts to cope with situations like COVID-19 in the future and help lessen investors' losses in the stock markets. The role of the Securities Exchange Commission is crucial as it regulates the financial markets. It can arrange workshops to educate investors to manage their decisions during crisis time and focus on the best use of irrational and rational decision-making at the same time using Lo (2004) adaptive market hypothesis.

The novelty of the paper is that the authors have introduced overconfidence and disposition effect as mediators that create a connection between representative and anchoring heuristics and investment decisions using primary data collected from investors (institutional and retail) to demonstrate the presence of psychological biases during COVID-19, and it has been done for the first time according to authors' knowledge. It is a contribution and addition to the behavioral finance literature in the context of developing countries' stock markets and their efficiency.

This study aims to assess the nutritional status and physical fitness status of school children among major ethnic and Dalit populations, in Rajshahi, Bangladesh.

Data were collected through structured questionnaires administered to mothers or caregivers of the children, followed by physical fitness assessments. Anthropometric indicators were used to evaluate nutritional status, including body mass index-for-age, height-for-age, and weight-for-height, based on Centre for Disease Control guidelines. Physical fitness was assessed through tests for flexibility, abdominal, muscular, speed, and lower limb strength. Statistical analysis was performed using SPSS.

Approximately 45% of boys and 55% of girls had normal nutritional status. However, the study also identified varying percentages of children with stunted, underweight, wasted, and mixed nutritional issues, highlighting the prevalence of malnutrition among this population. Boys consistently outperformed girls in terms of physical fitness across all age groups, with 84% to 90% of boys meeting established fitness criteria. Girls face a 1.8-fold and 2.2-fold increased risk of wasted and underweight conditions compared to boys. Lower-income group children exhibit a 2.6-fold and 1.6-fold increased risk of wasted conditions and underweight conditions. Children consuming meals twice a day have a 2.1-fold and 2.5-fold elevated risk of wasted and underweight conditions compared to others.

This study highlights the need for interventions and strategies to improve the nutritional and health status of ethnic children in Rajshahi, Bangladesh, considering their diverse dietary habits and lifestyles. By addressing these issues, the authors can empower these communities to actively contribute to the social and economic development of the region.

The purpose of this paper is to provide a comprehensive overview of multiple functions and their underlying mechanisms for two common spices, garlic and onion, containing organosulphur compounds.

Literature review of chemistry, physiology, molecular biology, clinical studies.

Both garlic and onions exert their effects on human health via multiple different functions, including antioxidant, anti‐inflammatory, and antibacterial properties. The organosulphur compounds in these spices scavenge oxidizing agents, inhibit the oxidation of fatty acids, thereby preventing the formation of pro‐inflammatory messengers, and inhibit bacterial growth, via interaction with sulphur‐containing enzymes.

Currently available information on the optimal amount for consumption for each spice is insufficient.

This review is unique in its comprehensive nature, considering multiple different effects of the spices examined as well as multiple studies from molecular to clinical approaches.

This paper aims to address the pressing challenges in research data management within institutional repositories, focusing on the escalating volume, heterogeneity and multi-source nature of research data. The aim is to enhance the data services provided by institutional repositories and modernise their role in the research ecosystem.

The authors analyse the evolution of data management architectures through literature review, emphasising the advantages of data lakehouses. Using the design science research methodology, the authors develop an end-to-end data lakehouse architecture tailored to the needs of institutional repositories. This design is refined through interviews with data management professionals, institutional repository administrators and researchers.

The authors present a comprehensive framework for data lakehouse architecture, comprising five fundamental layers: data collection, data storage, data processing, data management and data services. Each layer articulates the implementation steps, delineates the dependencies between them and identifies potential obstacles with corresponding mitigation strategies.

The proposed data lakehouse architecture provides a practical and scalable solution for institutional repositories to manage research data. It offers a range of benefits, including enhanced data management capabilities, expanded data services, improved researcher experience and a modernised institutional repository ecosystem. The paper also identifies and addresses potential implementation obstacles and provides valuable guidance for institutions embarking on the adoption of this architecture. The implementation in a university library showcases how the architecture enhances data sharing among researchers and empowers institutional repository administrators with comprehensive oversight and control of the university’s research data landscape.

This paper enriches the theoretical knowledge and provides a comprehensive research framework and paradigm for scholars in research data management. It details a pioneering application of the data lakehouse architecture in an academic setting, highlighting its practical benefits and adaptability to meet the specific needs of institutional repositories.