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This paper aims to investigate the different analytical methods used to predict the performance of seaplanes to define the weaknesses in each method and be able to extend the analytical approach to include the nonlinear terms (unsteadiness).

First, the elemental hydrodynamic characteristics of seaplanes are discussed. Second, five different analytical methods are reviewed. The advantages and disadvantages of each method are stated. After that, the heave and pitch equations of seaplane motion are illustrated. The procedure of obtaining the solution of the heave and pitch equations of seaplane motion is explained. Finally, the results obtained from the most common methods are compared.

The results show that the methods are based on different assumptions and considerations. As a result, no method is optimal for all types of seaplanes. Moreover, some of the analytical methods do not study the stability of the seaplane, which is a major issue in the design of seaplanes. In addition, all methods consider the motion as steady and linear. The objective is to extend the work to include the nonlinear effects.

This paper presents some of the analytical methods used in describing the performance of seaplanes and explains how can they be applied. Moreover, it summarises the advantages and disadvantages of each method.

This paper aims to address Passive Design Strategies (PDSs) in the traditional houses of Sabzevar and to assess the adaptation level of these strategies to the climate of the region.

Identifying the Sabzevar climate, five samples of traditional houses have been chosen to be analyzed via two stages. In stage one, the efficiency of each strategy is weighted through qualitative analysis, and in stage two, the houses are simulated in EnergyPlus 9.3.0 to quantitatively evaluate their heating and cooling performances.

The obtained results from the energy performance analysis of the case studies indicate that the houses present diverse energy performances in different seasons. Those buildings with PDSs for both cold-arid and hot-arid climates, however, are more adaptable cases to the climate of the region.

The results of this study are expected to provide a basis of materials and methods for the climatic assessment of the traditional buildings, specifically traditional houses and will open new doors to future studies about the integration of these potential PDSs with the new technological developments and climate considerations as well as protecting the conservation policies of these buildings by means of optimizing and improving their energy performance and implementing effective retrofit scenarios.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.

This paper aims to explore the impact of metaverse technology on the hospitality and tourism industry. The introduction of metaverse technology has revolutionised the way the hospitality and tourism industry works. In the present study, the authors have investigated the role of social media marketing in the adoption of metaverse technology in hotel booking in India.

An extended technology acceptance model was proposed for an empirical investigation in the Indian context. Sample of 344 respondents was collected across India using a purposive sampling technique for the purpose of data analysis. The structural model analysis is used to analyse the data collected from the respondents using the SmartPLS software to check the structural and the measurement fit of the model.

The adoption intentions were largely influenced by the utility, attitude (ATT) and ease of use of the technology, and social media marketing plays a major role in influencing the perceived usefulness (PU) and ease of use (PEU). The study finds positive ATTs of the customers for using metaverse technology for booking their hotels. PU and PEU significantly influence the ATT of the consumer indicating the traveller’s perception of the usefulness and ease of metaverse technology influence their ATTs towards adoption.

Influence of metaverse technology is at a nascent stage in India specifically for hotel booking and tourism. The authors have used discriminant validity by using the criteria for both the square root of the average variance extracted and heterotrait–monotrait ratio tests, and the results suggest that the constructs in the research are distinct from other.

With the advent of the COVID-19 and increased access to Internet technologies, students tend to use e-learning technologies for improved academic results, and since then, improving student engagement in a virtual space became a difficult task for educational institutions globally. The present study aims to examine the effect of key e-learning factors (i.e. perception, hedonic motivation (HM), usefulness, empowerment and attitude) on student engagement among open and distance learners (ODLs) of the central region of India.

Simple random sampling was applied to collect data from ODLs of Chhattisgarh. ODLs who are using e-learning platforms for at least one year were chosen to be the participant in the study. The authors collected 1,137 responses using both online and offline modes of collection.

The test results indicated that usefulness, HM and attitude factors were found to have a significant relationship with student engagement in e-learning, while perception and empowerment variables did not contribute to the engagement of students.

The present study is novel in its approach. It clarifies the key factors to student engagement which might increase the students' level of involvement in e-learning technologies, if these factors are addressed tactfully by the educational institutions or concerned administration.

Young consumers are increasing using electronic word-of-mouth (eWOM) in travel social networking sites to make purchase decisions. This paper aims to test the extended Information Adoption Model (IAM) that places perceived usefulness and information adoption as consequences of argument quality, source credibility, information quantity and emotive word comprehension, and as an antecedent of purchase intentions.

Data are collected through survey questionnaire from 405 hotel young customers in Malaysia, who had experienced travel social networking sites. The hypothesized relationships were analysed using structural equation modelling.

The results show that argument quality, source credibility, information quantity and emotive word comprehension have positive effect on the perceived usefulness of eWOM. Perceived usefulness has positive influence on the information adoption of eWOM, which in turn predicts the young consumers’ purchase intentions.

The present study strengthens and advances the existing literature on tourism, social media and marketing by offering an extension to the IAM. The proposed extended model of IAM is verified and applied effectively in the context of eWOM for travel social networking sites.

Practitioners and marketers of travel social networking sites can improve the usability and effectiveness of eWOM to attract more young consumers.

The study contributes to the extension of IAM by adding information quantity and emotive word comprehension. This research validated the significant roles of eWOM argument quality and source credibility in predicting the information usefulness of eWOM.

This research aims to investigate the influence of electronic word-of-mouth (eWOM) on the diffusion rate of innovation in the context of entrepreneurial firms in emerging markets. It examines a comprehensive model for the effect of eWOM dimensions (including Content, Intensity, Positive Valence and Negative Valence) on the diffusion of innovations. Thus, it provides new insights on how entrepreneurial firms can use eWOM as a communication tool to facilitate the diffusion rate of innovations in emerging markets.

A quantitative approach was adopted, consisting of 215 responses from Jordan. Data were analysed using Linear regression analysis tools.

A significant relationship exists between eWOM dimensions (Content, Intensity, Positive Valence and Negative Valence) and the Diffusion Rate of Innovations. In emerging markets, eWOM content highlights critical information regarding consumers’ sentiments towards new products (including features, price, design), which consumers use in judging innovations. Especially when there is a high volume of eWOM about a new product, consumers are likely to gain reassurances regarding their purchase decisions. Specifically, the valence of eWOM (including reviews, complaints and suggestions) generate adoption/risk-aversion attitudes towards new products. Consequently, entrepreneurial firms must carefully analyse eWOM regarding their products and integrate them into their marketing strategy. 10;

This research extends the eWOM literature by developing a comprehensive model for the effect of eWOM dimensions on the diffusion of innovations. Additionally, it sheds new light on the effect of eWOM valence on consumers’ attitudes towards innovations. Finally, it provides significant theoretical and managerial implications and future research direction to deepen our understanding of the effect of eWOM on entrepreneurial firms.

The purpose of this study is to delve into the intricate terrain of assimilating sustainability practices into digital accounting and finance, centring on the transformative dynamics introduced by artificial intelligence (AI)-enabled FinTech. The primary objective is to scrutinize critical lacunae in existing literature, exploring how organizations can meticulously construct comprehensive sustainability frameworks. Simultaneously, the study investigates the protracted repercussions of AI-enabled FinTech on the enduring sustainability paradigms.

Executing a systematic literature review, the research engaged in the meticulous identification and assessment of a voluminous pool of 1,158 articles. Using a judicious two-phase strategy, the scrutiny distilled a mere 64 pertinent articles, subjecting them to rigorous evaluation encompassing methodologies, contributions and overall quality. The Fuzzy Delphi method was used to elicit expert opinions and facilitate consensus-building, leveraging fuzzy logic to accommodate uncertainties in the data.

The review navigates the convoluted impact of AI across diverse sectors, accentuating its transformative imprint on realms such as health care, finance and transportation. Specifically, in the financial domain, the discerning eye of AI-enabled FinTech optimizes investment portfolios, augments risk assessment, propels financial inclusion and streamlines the intricate landscape of sustainability reporting. The study meticulously pinpoints research gaps encompassing investment optimization, risk management, financial inclusion, sustainability reporting and ethical considerations within the intricate milieu of AI-enabled FinTech. This research contributes to the existing body of knowledge by synthesizing intricate thematic strands, discerning overarching trends and spotlighting critical voids in the synthesis of sustainability practices and AI-enabled FinTech. The findings resonate with far-reaching implications, emphasizing the exigency of comprehensive investigations into the longitudinal sustainability ramifications instigated by AI-enabled FinTech.

The study underscores the imperative of crafting robust ethical frameworks for the equitable and transparent deployment of AI solutions within the intricate landscape of FinTech. Moreover, this research stands poised to shape organizational strategies, inform regulatory frameworks and guide investment decisions, thereby catalyzing the cultivation of conscientious and sustainable financial practices.

This study aims to examine the main factors influencing customer meta-banking (metaverse banking) adoption intention based on the unified theory of acceptance and use of technology (UTAUT) model.

In this study, the PLS-SEM modelling technique was used to analyse the quantitative data collected from a total of 407 participants who were purposefully chosen.

The findings revealed that performance expectation, effort expectancy, facilitating conditions and hedonic motivation have significant positive effects on customers’ perception of the value associated with adopting the metaverse. However, the effect of social influence was found to be statistically insignificant. The results further emphasised that technostress is an obstacle that negatively influences the perceived value. Lastly, perceived value is found to be a key facilitator of adoption intention as it shows a positive effect on it.

This study stands at the forefront of research on banking customers’ adoption intention of meta-banking. Going beyond the investigation of adoption intention, the research also critically assesses the applicability of UTAUT in the context of meta-banking. The results demonstrate that UTAUT is a viable theoretical framework for examining the dynamics of meta-banking. In particular, the findings indicate that UTAUT model provides a reliable lens for comprehending the intricacies of meta-banking adoption.

Corrosion is a major concern for many industries that use metals as structural or functional materials, and the use of corrosion inhibitors is a widely accepted strategy to protect metals from deterioration in corrosive environments. Moreover, the toxic nature, non-biodegradability and price of most conventional corrosion inhibitors have encouraged the application of greener and more sustainable options, with natural and synthetic drugs being major actors. Hence, this paper aims to stress the capability of natural and synthetic drugs as manageable and sustainable, environmentally friendly solutions to the problem of metal corrosion.

In this review, the recent developments in the use of natural and synthetic drugs as corrosion inhibitors are explored in detail to highlight the key advancements and drawbacks towards the advantageous utilization of drugs as corrosion inhibitors.

Corrosion is a critical issue in numerous modern applications, and conventional strategies of corrosion inhibition include the use of toxic and environmentally harmful chemicals. As greener alternatives, natural compounds like plant extracts, essential oils and biopolymers, as well as synthetic drugs, are highlighted in this review. In addition, the advantages and disadvantages of these compounds, as well as their effectiveness in preventing corrosion, are discussed in the review.

This survey stresses on the most recent abilities of natural and synthetic drugs as viable and sustainable, environmentally friendly solutions to the problem of metal corrosion, thus expanding the general knowledge of green corrosion inhibitors.