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Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

The construction industry is one of the most hazardous working environments globally. Studies reveal that wearable sensing technologies (WSTs) have practical applications in construction occupational health and safety management. In the global south, the adoption of WSTs in construction has been slow with few studies investigating the critical drivers for its adoption. The purpose of this study is to investigate the factors driving WSTs adoption in Ghana where investment in such technologies can massively enhance health and safety through effective safety monitoring.

To meet the objectives of this study, research data was drawn from 210 construction professionals. Purposive sampling technique was used to select construction professionals in Ghana and data was collected with the use of well-structured questionnaires. The study adopted the fuzzy synthetic evaluation model (FSEM) to determine the significance of the critical drivers for the adoption of WSTs.

According to the findings, perceived value, technical know-how, security, top management support, competitive pressure and trading partner readiness obtained a high model index of 4.154, 4.079, 3.895, 3.953, 3.971 and 3.969, respectively, as critical drivers for WSTs adoption in Ghana. Among the three broad factors, technological factors recorded the highest index of 3.971, followed by environmental factors and organizational factors with a model index of 3.938 and 3.916, respectively.

Theoretically, findings are consistent with studies conducted in developed countries, particularly with regard to the perceived value of WSTs as a key driver in its adoption in the construction industry. This study also contributes to the subject of WSTs adoption and, in the case of emerging countries. Practically, findings from the study can be useful to technology developers in planning strategies to promote WSTs in the global south. To enhance construction health and safety in Ghana, policymakers can draw from the findings to create conducive conditions for worker acceptance of WSTs.

Studies investigating the driving factors for WSTs adoption have mainly centered on developed countries. This study addresses this subject in Ghana where studies on WSTs application in the construction process are uncommon. It also uniquely explores the critical drivers for WSTs adoption using the FSEM.

Recently, there has been a shift toward the embodied energy assessment of buildings. However, the impact of material service life on the life-cycle embodied energy has received little attention. We aimed to address this knowledge gap, particularly in the context of the UAE and investigated the embodied energy associated with the use of concrete and other materials commonly used in residential buildings in the hot desert climate of the UAE.

Using input–output based hybrid analysis, we quantified the life-cycle embodied energy of a villa in the UAE with over 50 years of building life using the average, minimum, and maximum material service life values. Mathematical calculations were performed using MS Excel, and a detailed bill of quantities with >170 building materials and components of the villa were used for investigation.

For the base case, the initial embodied energy was 57% (7390.5 GJ), whereas the recurrent embodied energy was 43% (5,690 GJ) of the life-cycle embodied energy based on average material service life values. The proportion of the recurrent embodied energy with minimum material service life values was increased to 68% of the life-cycle embodied energy, while it dropped to 15% with maximum material service life values.

The findings provide new data to guide building construction in the UAE and show that recurrent embodied energy contributes significantly to life-cycle energy demand. Further, the study of material service life variations provides deeper insights into future building material specifications and management considerations for building maintenance.

This study aims to understand consumers' reactions to hospitality corporate social responsibility (CSR) campaigns under different resource scarcity reminders, an important but overlooked contextual factor, and examine how such scarcity reminders interact with message framing, a widely used technique in CSR communication.

Three experimental studies were conducted. Studies 1 and 2 examined the main effect of resource scarcity reminders (environmental vs personal) on consumer engagement via self-other orientation. Study 3 further investigated the interactive effect between resource scarcity reminders (environmental vs personal) and message framing (gain vs loss) with hope as a key mediator.

Studies 1 and 2 show that environmental (vs personal) scarcity activates a more salient other orientation, subsequently increasing consumers' donation and word-of-mouth intentions. Study 3 reveals that environmental (vs personal) scarcity makes people more hopeful with gain-framed messages. Moreover, the elevated hope enhances perceived efficacy (attitude toward the company), leading to higher donation (word-of-mouth) intention.

Hospitality marketers could remind consumers of the harsh environment to elicit other orientation and encourage CSR participation. Using gain-framed messages or other hope-inducing appeals would be particularly advantageous in engaging consumers in CSR campaigns during heightened environmental scarcity.

Focusing on consumer responses to CSR campaigns, to the best of the authors’ knowledge, this research is the first to reveal reminders of resource scarcity as a novel antecedent factor and further uncover how such reminders interact with message framing to affect CSR engagement.

The study examines the effect of natural resources (NRs) and the control of corruption, voice and accountability and regulatory quality on carbon emissions in Africa. Aside from their individual effects, the moderation effect of institutional quality is assessed.

Data from 32 African countries from 2002 to 2021 and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression methods were used for the investigation.

In the long term, the NRs effect is sensitive to the estimation technique employed. However, quality regulatory framework, robust corruption control and voice and accountability abate any positive effect of NRs on carbon emissions. Institutional quality can be argued to moderate the CO2-emitting potentials of resource extraction in the selected African countries.

Enhancing regulation quality, enforcing corruption control and empowering citizens towards greater participation in governance and demanding accountability are essential catalyst to effectively mitigate CO2 emissions resulting from NRs.

The moderation effect of control of corruption, voice and accountability and regulatory quality on the NR–carbon emission nexus is examined.

This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability.

Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index.

U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO₂ emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO₂ reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality.

This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

Prodigious teamwork is the basis for augmenting the level of productivity on construction projects. Globalisation of the construction market has meant that many practitioners work outside of their geographical spectrum; however, the multicultural dissimilarities of construction workforces within the project management team (and how these may impact upon project productivity performance) have been given scant academic attention. To bridge this knowledge gap, this paper aims to analyse the effects of a multicultural workforce on construction productivity.

The epistemological positioning of the research adopted mixed philosophies (consisting of both interpretivism and postpositivism) to undertake a deductive and cross-sectional survey to collate primary quantitative data collected via a closed-ended structured questionnaire. Census sampling and convenience sampling techniques were adopted to target Ghana’s construction workforce and their opinions of the phenomenon under investigation. Out of 96 questionnaires administered, 61 were retrieved. The data obtained were analysed by using mean score ranking, relative important index, one sample t-test and multiple regression. The reliability of the scale was checked by using Cronbach’s alpha coefficient.

From the t-test analysis, 11 variables sourced from extant literature, and the null hypothesis for the study was not rejected and all factors (except high cost of training and improper gender diversity management) were affirmed as negative effects of the multicultural workforce on construction productivity. Using multiple regression analysis, six of the independent variables were shown to impact upon productivity. The goodness of fit was verified by collinearity and residual analysis. The model’s validation revealed a relatively high predictive accuracy (R² = 0. 589), implying that the results could be generalized. In culmination, these findings suggest that the predictors can be used to accurately predict the effects of multicultural workforce on construction productivity performance.

The findings indicate that multicultural workforce/teams have a substantial effect on overall construction productivity in the construction sector; consequently, stakeholders must address this issue to enhance productivity across the sector.

The current study significantly contributes to our understanding of how multicultural workers/teams affect construction productivity in the construction business perspective and how to respond to the negative menace.

This paper explores the effect of perceived service quality, trust, perceived value and perceived cost on patient satisfaction and loyalty as well as exploring the moderating role of the sociodemographic factors.

The data were gathered from 462 patients via a structured questionnaire, while structural equation modeling was utilized for the analysis.

Results indicated that trust, perceived value and patient satisfaction have important roles in shaping the patient loyalty, while patient satisfaction was found to fully mediate the patient’s perceived service quality. Loyalty relationship was also found to partially mediate the trust–loyalty relationship. Nonetheless, the patient’s satisfaction–loyalty relationship was found to be only moderated by the age factor.

Implications are provided to the Egyptian private hospitals in order for them to formulate improvement plans as well as set higher standards of conduct.

This original research is the first one, up to the researcher knowledge, that explores the drivers of patient satisfaction in the private hospitals in Egypt.

The purpose of this study is to investigate the benefits and challenges of implementing circular economy (CE), as well as shed light on the influence of procurement strategy in CE implementation in construction projects.

A qualitative research approach with abductive reasoning was adopted. The empirical data were collected from the construction industry in the United Arab Emirates (UAE).

The results reveal that clients, consultants and contractors have limited awareness, knowledge and motivation to implement CE in construction projects. The absence of incentives to design projects following CE principles, lack of involvement of contractors and suppliers, non-use of materials that use CE principles and current procurement strategies are the main challenges for the implementation of CE in the UAE.

Previous research offers limited knowledge on CE and its implementation in construction projects particularly from a procurement strategy perspective. The findings of the study provide new knowledge of the benefits, challenges and role of procurement strategy for implementing CE. It is suggested that collaborative and partnering-based procurement methods are needed to facilitate the effective implementation of CE.