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The purpose of this study is to investigate the effect of the incorporated zirconia (ZrO₂) nanoparticles on the performance of the deposited layer Ni–Cu alloy on steel sheet.

The aim was to produce Ni–Cu–ZrO₂ nanocomposite coatings by electrodeposition technique and estimate the influence of ZrO2 nanoparticles on the performance of Ni–Cu alloy. The surface morphologies and chemical compositions of the deposited layers were assessed using scanning electron microscopy and energy-dispersive X-ray analysis, respectively. Nanoindentation was used as a well-advanced technique for measuring microhardness and Young’s modulus values of different coatings. The corrosion resistance in 3.5 per cent NaCl solution of electrodeposited films has been investigated.

The main conclusion is that the surface morphologies of Ni–Cu–ZrO2 nanocomposite coatings were fine granular compared with Ni–Cu alloy. The corrosion behavior illustrated that the incorporation of ZrO₂ nanoparticles with Ni–Cu film improved the corrosion resistance. Significant improvement was also demonstrated in the hardness of nanocomposite coatings.

The optimized industrial use of steel-coated Ni–Cu alloy with super properties. Consequently, a social benefit can be associated with the reduction in the corrosion rate and increases the microhardness and Young’s modulus.

The results presented in this work are an insight into understanding the incorporation of ceramic reinforcement with metal or alloy films (matrix) on carbon steel using the electrodeposition technique. The development of corrosion resistance of Ni–Cu alloys has been considered as a promising behavior. In this work, a consistent assessment of the results achieved on laboratory scale has been conducted.

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

The present study tries to examine the relationship between financial inclusion and environmental quality as proxied by carbon emissions in India covering the period from 2008 to 2018.

A financial inclusion index has been composed using principal component analysis (PCA) based on three dimensions: access, penetration and usage. After testing for stationarity of the data, the authors adopted the autoregressive distributive lag model (ARDL) methodology.

The study found that financial inclusion and growth lead to increased carbon emissions in India and the government must resort to greener policies, whereas empirical results support that globalization reduced the pollutants emissions in both the long term and short period in India.

Based on the results, several policy prescriptions are rendered for policymakers: (1) need to move toward greener energy policies and (2) enhance the awareness of green financing instruments such as green bonds in India. Therefore, policymakers should be more proactive in accepting green and sustainable financial alternatives.

The present study contributes to the scant literature on the financial inclusion–emission nexus in India. This study considers three inclusion parameters that are not present in previous studies.

This study aims to investigate the impact of empowering leadership (EL) on employee innovative work behavior (IWB), using an interactionist perspective on creativity and conservation of resources theory. Following the premise, the study unravels the mediating role of job crafting (JC) and creative self-efficacy (CSE) as a boundary condition that likely triggers and facilitates this process.

Using a dyadic cross-sectional design, this study focuses on academic staff at four universities in Pakistan. Participants were surveyed, and questionnaires were distributed to collect data pertaining to accomplish the study objectives.

The study results reveal that JC plays a pivotal role as an intervening factor in establishing the connection between EL and employees’ IWB. This implies that EL likely promotes employees’ JC behavior, thus contributing to a greater manifestation of innovative behaviors at work. Furthermore, this interplay is further enhanced by using CSE as a moderator.

This study accentuates the importance of JC in eliciting the mechanism which effectively channelizes and translates the impact of EL on IWB. It also offers the valuable and fresh perspective on the conditions favoring the innovative behaviors at work.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

Financial inclusion policy focuses on bringing the less privileged groups into the formal financial system. Financial inclusion has a lot of benefits in the society. It can reduce the level of poverty, inequality and encourage business startup. This study aims to examine the impact of financial inclusion on entrepreneurship in selected African countries.

This paper examines how financial inclusion impacts entrepreneurship in 13 selected African countries using data from World Bank Development Indicators, IMF’s International Financial Statistics, doing business and World Bank Entrepreneurship Survey for the period of 2005-2016. It uses panel data regression techniques such as random effect, IV estimation and robust least square.

The results show that financial inclusion has a significant and positive effect on entrepreneurship in Africa. This result is robust to both alternative measures of financial inclusion and alternative estimators.

The possible relationship between financial inclusion and entrepreneurial development has been an ongoing debate in other developing countries. However, this issue has been neglected in the African region. There are little or no evidence to support the possible relationship in Africa. This paper makes an important contribution in this respect and further provides insightful information in the ongoing debate.

The aim of the article is to identify and explain the importance of business intelligence and analytics (BI&A) in health destination development.

The article uses a qualitative approach based on the analysis of scientific literature on the subject and an exploratory comparative case study of tourism and health destinations.

The importance of BI&A in the development of health destinations is to provide information in making decisions about the directions of development of the business model (BM). BI&A in health destinations can be utilized to create new BMs by using the BM analytics elements based on multiple data sources. Full-scale BI&A systems in health destinations are very rare and difficult to find, even in tourism destinations, not only in Central Europe but also in the world.

Our research contributes to the theory of destination management using advanced information systems technology, recognizing the importance of BI&A use in health tourism destinations. The main limitation of the study is the reliance on secondary sources and not reaching for primary sources at the stage of selecting cases, which could have contributed to not capturing a larger number of BI&A class systems in tourist and health destinations.

BI&A systems are not only the acquisition and analysis of large datasets but also a comprehensive set of both hidden and explicit premises for drawing conclusions based on detailed connections between the generated information and the knowledge that is the basis for constructing BMs of health destinations.

The article recognizes the importance of BI&A use in health destinations. The broader the range of data sources used, the greater the scope for analytics used in a destination’s BI&A. The challenge of health destinations is to create BI&A ecosystems in which data are obtained and processed into knowledge-supporting management decisions about the future of BMs. Health destinations should gradually implement BI&A based on an increasing variety of data sources.

The aim of this chapter is to examine the role of real exchange rates in the relationship between tourist arrival and economic growth in Malaysia over the period of 2000–2018. We disaggregate Malaysian tourists into six geographical regions, namely Asia, Singapore, Europe, Pacific region, Americas, and Africa. Using a non-linear autoregressive distributed lag model, we find that the appreciation of real exchange rates with positive growth of economy plays a prominent role in influencing international tourist arrivals from Singapore, other Asian countries, Pacific region, Europe, and Americas. Our study suggests that real appreciation is important in providing some insights into the effectiveness of growth-led-tourism policies. In line with this, some implications are provided at the end of this chapter.

This study’s main goal is to assess how augmented reality (AR) and virtual reality (VR) technologies affect the architectural design process in a learning environment. Enhancing spatial awareness, advancing design communication and encouraging design experimentation are the main goals. This study promotes the reform of design education by incorporating AR/VR technology into architectural programs.

The integration of advanced technologies in design, particularly AR and VR, in architectural education is examined in this theoretical paper. The approach includes a thorough literature analysis to understand the state of AR and VR in design education today. Furthermore, the research incorporates insights and findings from a semester-long course named “Advanced Technologies in Design”. Through the use of AR and VR breakthroughs in design projects, this course gave students a hands-on learning experience and a deeper knowledge of the possibilities of these technologies.

The study discovered that students’ spatial knowledge and communication abilities are greatly impacted when AR/VR technologies are included into architecture instruction. Students learned about the possibilities of these technologies for architectural design through practical experimentation and project-based learning. Furthermore, AR/VR technologies open the door to more creative and environmentally friendly building solutions with their immersive experiences and interactive displays. The results imply that incorporating these technologies into design education fully can better equip aspiring architects to successfully alter the built environment.

By investigating the integration of VR and AR in architecture education, this research sets new standards. With an extensive methodology that incorporates a survey of the literature and learnings from a semester-long course, it presents a distinctive viewpoint. The research offers informative recommendations for educators and institutions by showcasing the revolutionary potential of AR/VR technology in design education. Adopting these technologies helps students become more innovative in sustainable design and more equipped to tackle future architectural difficulties. All things considered, this study emphasizes how unique and beneficial it is to use AR/VR technologies to improve architectural practice and teaching.

The relationships between transformational leadership (TL), organizational climate (OC) and project performance have been investigated by previous studies, but no review of existing studies has systematically analyzed the effects of TL and OC on project performance in the industrial revolution (IR) 5.0 era. Therefore, this study aims to conduct a systematic literature review on the effects of TL and OC on project performance in IR 5.0, and to identify mainstream research topics, research gaps and future research directions.

To do this, a total of 53 included journal articles were obtained after initially retrieving 648 documents from the Scopus database by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. It consists of four main steps, namely, identification of documents, screening, eligibility and included articles. In addition, science mapping analyses were conducted for keyword co-occurrence and document analyses, which aided in identifying the mainstream research topics, research gaps and future research directions.

The results report the annual publication trends, keywords and document analyses. Furthermore, a detailed qualitative discussion highlighted four mainstream research topics including TL in project management; the relationship between TL, OC and innovation; safety climate; and OC in project management. Moreover, this review study identified four research gaps and future research directions aligned with the mainstream research topics. They include: longitudinal investigations and multinational corporation surveys in TL; scope and longitudinal data in innovation; mono-method bias and universality of safety climate; and more comprehensive analyses of OC.

This review study would contribute to not only advancing the effects of TL and OC on project performance in IR 5.0, but also enabling project managers to understand TL or OC issues to improve project performance.