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This study aims to characterize the behavior of blended concrete, including metakaolin (MK) and quarry dust (QD), as supplementary cementing materials. The study focuses on evaluating the effects of these materials on the fresh and hardened properties of concrete.

MK, a pozzolanic material, and QD, a fine aggregate by-product, are potentially sustainable alternatives for enhancing concrete performance and reducing environmental impact. The addition of different percentages of MK enhances the pozzolanic reaction, resulting in improved strength development. Furthermore, the optimum dosage of MK, mixed with QD, and mechanical properties like compressive, flexural and split tensile strength of concrete were evaluated to investigate the synergetic effect of MK and quarry dust for M20-grade concrete.

The results reveal the influence of metakaolin and QD on the overall performance of blended concrete. Cost analysis showed that the optimum mix can reduce the 7%–8% overall cost of the materials for M20-grade concrete. Energy analysis showed that the optimum mix can reduce 7%–8% energy consumption.

The effective utilization is determined with the help of the analytical hierarchy process method to find an optimal solution among the selected criteria. According to the AHP analysis, the optimum content of MK and quarry dust is 12% and 16%, respectively, performing best among all other trial mixes.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

It is documented that companies and government agencies in the USA invest more in the fourth fiscal quarter without having higher investment opportunities. While previous studies focus on the agency conflicts and information asymmetry within organizations, this study is motivated by Scharfstein and Stein's (2000) two-tiered agency model and aims to examine how firms' external business environment affects the “fourth quarter effect.”

The authors implement this study in a sample of 41 countries and observe similar seasonality in firm investment as documented in the US market.

More importantly, using country characteristics, this study finds that firms from countries with better investor rights and protection, and more developed financial markets show less severe over-investment in the fourth fiscal quarter.

This paper contributes to the literature of law and finance, and the internal capital market, by investigating the quarterly investment patterns of firms from 41 countries. The authors find that similar to the results in earlier studies on the US market, firms in the global market increase their capital expenditure in the fourth fiscal quarter, indicating that the internal agency conflicts between the headquarters and divisional managers are widespread across the world. The authors also find that firms that operate in countries with higher investor rights and protection, and more developed financial markets, tend to show less severe “fourth quarter effect”.

The purpose of this paper is to analyse the impact of political connections and gender diversity on the performance of Iberian companies as a singular market and considering Portugal and Spain separately.

The authors used panel data methodology, specifically GMM system estimation model by Arellano and Bond (1991) for the period from 2015 to 2020.

Results show that the performance of listed Iberian companies is influenced by political connections, by gender diversity and that gender diversity has a mitigating effect on the effects of political connections in each country. The mitigating effect of women is evident in both Portugal and Spain, as they are more cautious and principled, which is valued by short-term investors interested in an immediate investment. However, considering the Iberian Peninsula as a whole, the results indicate that – in the long term – women's political relationships can benefit performance through a better reputation and image, which can lead to better social and economic results in the long term.

To the best of the authors’ knowledge, this paper is original and covers an important gap in the literature when considering political connections and women's impact on these connections as determinants of the performance of Iberian companies.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

This study investigates the nexus between the returns on oil prices (OP) and unemployment (UR) while taking into account the influences of two of the most representative measures of uncertainty, the Baker et al. (2016) and Caldara and Iacovello (2021) indexes of economic policy uncertainty (EP) and geopolitical risks (GP), in the relationship.

The authors use data on the US, Canada, France, Italy, Germany and Japan from January 2000 to February 2022 and the UK from January 2000 to December 2021. The authors then apply the continuous wavelet transform (CWT), wavelet coherence (WC), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) to examine the returns within a time and frequency framework.

The CWT tracks the movement and evolution of individual return series with evidence of high variances and heterogenous tendencies across frequencies that also align with critical events such as the GFC and COVID-19 pandemic. The WC reveals the presence of a bidirectional relationship between OP and UR across economies, showing that the two variables affect each other. The authors’ findings establish the predictive influence of oil price on unemployment in line with theory and also show that the variation in UR can impact the economy and alter the dynamics of OP. The authors employ the PWC and MWC to capture the impact of uncertainty indexes in the co-movement of oil price and unemployment in line with the theory of “investment under uncertainty”. Taking into account the common effects of EP and GP, PWC finds that uncertainty measures significantly drive the co-movement of oil prices and unemployment. This result is robust when the authors control for the influence of economic activity (proxied by the GDP) in the co-movement. Furthermore, the MWC reveals the combined intensity, strength and significance of both oil prices and the uncertainty measures in predicting unemployment across countries.

This study investigates the relationship between oil prices, uncertainty measures and unemployment under a time and frequency approach.

1. Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

2. We account for uncertainty measures in the dynamics of oil prices and unemployment.

3. We observe a bidirectional relationship between oil prices and unemployment.

4. Uncertainty measures significantly drive oil prices and unemployment co-movement.

5. Both oil prices and uncertainty measures significantly drive unemployment.

Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

We account for uncertainty measures in the dynamics of oil prices and unemployment.

We observe a bidirectional relationship between oil prices and unemployment.

Uncertainty measures significantly drive oil prices and unemployment co-movement.

Both oil prices and uncertainty measures significantly drive unemployment.

This paper aims to reveal how different types of events and top management teams' (TMTs’) cognitive frames affect the generation of breakthrough innovations.

Drawing on the event system theory and upper echelon theory, this study chose a Chinese manufacturing enterprise as the case firm and conducted an exploratory single-case study to unpack how breakthrough innovation generates over time.

By conducting the in-depth case analysis, the study revealed that firms do not produce breakthrough innovation in the catch-up stage and parallel-running stage but achieve it in the leading stage. It also indicated that when facing proactive events in the catch-up stage, TMTs often adopt a contracted lens, being manifested as consistency orientation, less elastic organizational identity and narrower competitive boundaries. In addition, they tend to adopt a contracted lens when facing reactive and proactive events in the parallel-running stage. In the face of reactive and proactive events in the leading stage, they are more inclined to adopt an expanded lens, being manifested as a coexistence orientation, more elastic organizational identity and wider competitive boundaries.

First, by untangling how TMT's cognitive frame functions in breakthrough innovations, this paper provides a micro-foundation for producing breakthrough innovations and deepens the understanding of upper echelon theory by considering the cognitive dimension of TMTs. Second, by teasing out several typical events experienced by the firm, this paper is the first attempt to reveal how events affect the generation of breakthrough innovation. Third, the work extends the application of the event system theory in technological innovation. It also provides insightful implications for promoting breakthrough innovations by considering the role of proactive and reactive events a firm experiences and TMT's perceptions.

This study aims to explore the relationship between folk religious place-making and the development of urban public spaces and summarize its influence on community network construction and daily behavior to discover the authentic practices and role of folk faith culture in social space.

Taking Macau's Shi Gandang Temple and its belief culture as an example, on-site research, historical evidence and interviews were used to elaborate and analyze the processes of place-making, social functions, management mechanisms and folk culture to establish a new perception of folk religious place-making in contemporary urban spaces.

The article argues that the culture of folk beliefs profoundly influences urban spaces and the social management system of Macau and has a positive significance in building the local community and geopolitical relations. In addition, it suggests that the participation of folk religious places in local practices is important as key nodes and emotional hubs of local networks, reconciling conflicts between communities of different backgrounds and driving urban spaces toward diversity while forming a positive interaction and friendly cooperation between regional development and self-contained management mechanisms, governance models and cultural orientations.

This study takes an architectural and anthropological perspective of the impact of faith on urban spaces and local governance, using the Shi Gandang Temple in Macau as an example, to complement related studies.

Historically, investments in innovation are perceived as one of the paramount decisions businesses opt to thrive and the impact of such investments on businesses' market performance is well documented in the literature. However, the environmental aspects of making such investments are yet to be addressed by the firms, which in turn, present considerable damage to the environment. Coupling with the natural resource-based view (NRBV) and the stakeholder theory of the firm, this research builds on an earlier work of Khalil and Nimmanunta (2021) in an attempt to examine the link between innovation and firms' environmental and financial value. The authors extend their analysis and document a more consistent approach to measuring environmental innovation which allows the authors to investigate the firms from three additional economies with respect to firms' investments in both traditional and environmental innovations.

The underlying models are tested using the time fixed-effects panel regression by utilizing information from publicly traded companies of ten Asian economies, including Japan, Hong Kong, Taiwan, Thailand, Turkey, Malaysia, Singapore, India, Indonesia, and Saudi Arabia. The reported sample covers annual firm-level ESG data obtained from Thomson Reuters' Datastream and Refinitiv Eikon during the 2015–2019 period.

This research offers support to the conventional wisdom that innovation is advantageous to the firms' market value. The authors further decompose innovation into traditional innovation and environmental innovation. The findings of this research suggest that traditional innovation is favorable only for the firms' market valuation and traditional innovation is strongly ineffectual for the environment – traditional innovation produces sizeable environmental distress by contributing substantially to carbon emissions. In contrast, the resultant effects of investments in environmental innovation are evident to be instrumental for both firms' financial performance and the environment.

This research has primarily focused on only two components of a company's environmental performance: reduction in carbon emissions (CO2) and corporate social responsibility (CSR). Given the complexity of firms' environmental strategies and the multidimensionality of the variable, which encompasses a wide range of corporate behavior in terms of relationships with communities, suppliers, consumers, and broader environmental responsibilities broadening the scope of the study by including other important aspects of environmental sustainability is, therefore, critical.

The findings of this research signify environmental innovation as one of the vital investment approaches as firms can exploit benefits related to the market from firms' sustainable practices, developing eco-friendly processes by introducing steady yet systematic chains of green products and services. Such products and services may have a feature of enhanced functionality with a better layout in terms of improved product life with better recycling options, and lower consumption and exploitation of energy and natural resources. These sustainable practices would be advantageous for the firms regarding the possibility of setting prices above the standard level through establishing green brands and gaining market share of environmentally anxious consumers. For those companies that are striving to take the leading role in the green industry and longing to seek superior returns on the companies' environmental investments, these benefits, in particular, are exceptionally critical to them.

The linkage between firms' financial and environmental performance in the context of simultaneous inclusion of both green and traditional innovations remains unclear and is yet to be investigated by researchers. Thus, this research shed light on the role of environmental innovation and traditional innovation on firms' environmental performance and financial performance. The authors utilize a novel dataset with a clear indication of measuring different elements of innovation that allows us to develop a more robust approach to corporates' environmental, social and governance (ESG) performance metrics having the slightest biases related to transparency and firm size.