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This paper aims to prepare high corrosion-resistant chromium-free zinc-aluminum (Zn–Al) coatings reinforced with multi-walled carbon nanotubes (MWCNTs) and nano-ZnO particle composites.

The morphology, composition and corrosion resistance of the coatings were analyzed by electrochemical tests, water contact angle tests, immersion tests, scanning electron microscopy/energy dispersive spectrometer and X-ray diffraction.

The composite coating with 0.3% MWCNTs and 0.5% nano-ZnO particles demonstrated both high shielding performance and cathodic protection performance, which was attributed to the porosity filling of MWCNTs and nano-ZnO particles together with the electrical connection of MWCNTs between the zinc and aluminum powders.

This work laid an experimental foundation for the preparation and corrosion mechanism of high corrosion-resistant chromium-free Zn–Al coating reinforced with MWCNTs and nano-ZnO particles.

This study aims to tackle the critical issue of detecting stock market manipulation, which undermines the integrity and stability of financial markets globally. Even enhanced with machine learning, traditional statistical methods often struggle to analyze high-frequency trading data effectively due to inherent noise and the limited availability of publicly known manipulation cases. This leads to poor model generalization and a tendency toward over-fitting. Focusing on China's securities market, our study introduces an innovative approach that employs deep learning-based high-frequency jump tests to overcome these challenges and to develop a more effective method for identifying manipulative activities.

We employed the “Jump Variation – Time-of-Day” (JV-TOD) non-parametric technique for jump tests on high-frequency data, coupled with the synthetic minority over-sampling technique (SMOTE) algorithm for re-balancing sample data. Our approach trains a deep neural network (DNN) on refined data to enhance its ability to identify manipulation patterns accurately.

Our results show that the deep neural network model, calibrated with high-frequency price jump data, identifies manipulation behavior more specifically and accurately than traditional models. The model achieved an accuracy rate of 94.64%, an F1-score of 95.26% and a recall rate of 95.88%, significantly outperforming traditional models. These results demonstrate the effectiveness of our approach in mitigating over-fitting and improving the robustness of market manipulation detection.

The proposed model provides regulatory entities and financial institutions with a more efficient tool to monitor and counteract market manipulation, thereby improving market fairness and investor protection.

By integrating the JV-TOD jump test with deep learning, this study proposed a new approach to market manipulation detection. The innovation is in its capacity to detect subtle manipulation signals that traditional methods typically overlook. Our model, which is trained on jump test data enhanced by the SMOTE algorithm, excels at learning complex manipulation patterns. This enhances both detection accuracy and robustness. In contrast to existing methods that are challenged by the noisy and intricate nature of high-frequency data, our approach shows enhanced performance in identifying nuanced market manipulations, offering a more effective and reliable method for detecting market manipulation.

Green innovation and green acquisition are key green marketing strategies. This paper aims to explore and compare the drivers of green acquisition and green innovation strategies firms adopt. Moreover, the moderating role of top management team (TMT) sustainability commitment is investigated.

The research model used secondary data based on 1,565 firm-year observations in the beverage and food industry in the US. The two-stage control function approach was used for data analysis.

Media attention motivates firms to pursue both green innovation and green acquisition. The TMT sustainability commitment plays a pivotal moderating role. It strengthens the link between environmental regulation stringency and green innovation but weakens the impact of media attention on green acquisition.

Managers can leverage the study’s findings to guide sustainable marketing decisions in response to environmental regulations and media scrutiny. Policymakers and investors can encourage firms to adopt more sustainable practices, helping align corporate strategies with Sustainable Development Goals 9 and 12.

Though green innovation determinants are extensively studied, most studies rely on surveys or qualitative methods rather than secondary data. Also, as an alternative to developing in-house green technologies or products, the drivers of green acquisition remain unclear despite its growing prevalence. This study addresses both gaps in the sustainable marketing literature.

This chapter explores how perceived product innovation influences brand loyalty among UK Apple users, extending the technology acceptance model. Using a quantitative approach, data were collected from 101 respondents via an online survey and analysed using SPSS. Objectives included examining the mediating role of perceived product usefulness and ease of use, exploring the relationship between product/brand attitudes and brand loyalty and assessing gender's impact on loyalty perceptions. Findings reveal a significant positive relationship among variables, with perceived product usefulness and ease of use jointly mediating the link between product innovation and attitude, affecting brand loyalty. Gender was found to have no moderating effect. The research contributes by highlighting these mediating effects and deepening understanding of product innovation's impact on loyalty. Managerially, prioritising innovation, usefulness and ease of use can enhance satisfaction and loyalty. Future research could explore additional variables to enrich understanding further.

This book chapter briefly discusses the historical and cultural context of ethnography and evaluation as positioned in the United States and the opportunities made possible by merging techniques and methodology. By merging, methodological pluralism and increased responsiveness to cultural contexts are leveraged, and the critical relevance of engaging communities in evaluation processes is underlined. However, engaging with communities with marginalized backgrounds can present complicated power dynamics in practice that require the evaluator to rethink their role. Equity-centered research practices from the Equity-Centered Research Framework are linked to expound on the need for transforming the evaluator's role to shift and share power with communities throughout engagement. We expand on how transformative work also requires ongoing examinations of positionality in the evaluator role through the lens of relationships. Borrowing from ethnographic concepts, relational dimensions of positionality are conceptualized as alignment, temporality, and place. Each component is illustrated with details on how power dynamics may occur throughout community engagement as well as ways to manage and mitigate power differentials between the roles of the evaluator and community partners. We then offer three broad evaluator practices to support transformation: (a) identify positionality, (b) embed into everyday practice, and (c) negotiate in collaborations with communities. With these practices, we reflect on critical questions and position communities as critical learning partners to promote actions to mitigate and manage ongoing power dynamics. We close this chapter with our experiences interrogating positionality to illustrate distinct burdens and insights as evaluators of color.

Access to education has been globalized and democratized to a certain extent through massive open online courses (MOOCs) and other open-access platforms and content databases. In a recent study by Inayatullah and Milojević (2014), the recommendations were to establish a pilot project, enhance digital pedagogy and learning, customize degrees, create a culture of change in higher education, enhance collaboration, support research activities, redefine frames of reference, and anticipate and prepare for futures trends. The need for democratization of education has been increasing to meet the need of individuals and groups to assert and highlight their identity and role in society. Education is the means to facilitate this through a practical and active approach through wider stakeholder participation. Religious belief was identified as the main cause of conflicts among multi-ethnic cohorts. Adding socio-cultural differences to the mix and uncontrolled access to various opinions through social media makes the task much more complex. Educational policies must consider mother-tongue learning to improve learning outcomes. However, making the vast learning content accessible in multiple languages could be daunting. This chapter explores these emerging challenges and changing stakeholder expectations from the formal education system. The policy implications, possible technology-driven solutions, and their effectiveness in addressing the growing challenges of a global learning village have been explored.

The appearance of social media in small and medium enterprise (SME) business operations seems to be increasing in recent years. SME owners have started to understand that digital marketing tools can benefit their businesses significantly. Hence, in this study, we explore further the relationship between organisations and customers, and how SMEs use social media as an opportunity to develop their enterprises. We report the results by relying on qualitative methods to explore the insights from a wider stakeholder perspective. The findings contribute to the existing literature in agreement with the latest theories that SMEs in Greece are aware of the hidden opportunities and try to apply branding with the combination of social media. This study explores further the role of electronic word of mouth (eWOM) in a business transition, customers' experience and competitive business advantage.

This chapter adopts a historiographical methodology, meticulously retracing the lineage of Augmented Reality (AR) from the 16th century and scrutinizing the conceptual genesis of Virtual Reality (VR) in the mid-20th century. It rigorously scrutinizes the fundamental principles and applications of AR and VR, extending the discourse to encompass the foundational tenets and ramifications of the burgeoning Metaverse. Thoroughly examining ethical considerations and challenges, there is an emphasis on perpetuating research, judicious implementation, and establishing ethical frameworks. Elucidating the profound ramifications of AR on sundry industries, the transformative potential of VR in crafting immersive environments, and the emergent interconnected virtual realm of the Metaverse, key principles such as spatial mapping, interaction modalities, and cross-platform interoperability are accentuated. Ethical challenges inherent in Metaverse development, notably digital identity, and privacy are identified. The narrative steadfastly underscores the significance of perpetuated research and ethical considerations in steering the evolutionary trajectory of avant-garde technologies. The findings hold far-reaching implications for diverse sectors, encompassing navigation, marketing, healthcare, architecture, education, and entertainment. The Metaverse’s potential to reconfigure digital experiences ubiquitously and its consequential impact on privacy and content moderation accentuate the exigency for circumspect consideration in development and implementation. This chapter fervently advocates for responsible usage and the facilitation of equitable access. This chapter contributes to the scholarly corpus by synthesizing historical perspectives, core principles, and ethical considerations across the domains of AR, VR, and the Metaverse. The unique emphasis on sustained research endeavors and the establishment of ethical frameworks adds distinctive insights, thereby guiding the sagacious evolution of these paradigm-shifting technologies.

This study aims to assess the pitting resistance of austenitic stainless steel welded joints fusion zone (FZ) with high density of inclusions before and after surface treatment, including potentiostatic pulse technique (PPT) and pickling.

The potentiodynamic polarization tests and critical pitting temperature tests were carried out for estimating pitting resistance. The PPT and pickling were performed as surface treatment. Scanning electron microscope (SEM) and energy dispersive spectrometer were used for characterize the microstructure and elemental distribution. Electron back-scattered diffraction (EBSD) was used to assess the portion of phases and morphology of grains.

The weld metal exhibits a higher degree of alloying compared to the base metal, and it contains d-phase and sulfur-containing inclusions. Sulfur-containing inclusions serve as initiation sites for pitting, and they diminish the pitting resistance of weld metal. Both PPT and pickling can remove sulfur-containing inclusions, but PPT causes localized dissolution of the weld metal matrix around the inclusions, while pickling does not. Because of the high density of inclusions, certain pits initiated by PPT are significantly deeper, which makes the formation of stable pitting easier. Because of the high density of inclusions, certain pits initiated by the PPT are deeper. This characteristic facilitates the progression of these initial defects into fully developed, stable pits.

Analysis of pitting initiation in shielded metal arc welding FZ with PPT and ex situ SEM tracking observation. Explanation of why the PPT surface treatment is not able to enhance the pitting resistance of stainless steel with a high inclusion density.

This study aims to examine how firm-specific information in stock prices influences corporate tax behavior.

This study uses ordinary least squares (OLS) regressions to examine the association between stock price informativeness and effective tax rate (ETR) volatility.

Stock price informativeness is positively associated with short-term tax avoidance as measured by ETR volatility.

While prior research examines the association between market activity and the level of ETRs, this study examines other various aspects of tax behavior.