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This study aims to investigate the mechanical properties of sustainable recycled polypropylene (rPP) composite materials integrated with spherical silicon carbide (SiC) particles.

A representative volume element (RVE) analysis is employed to predict the Young’s modulus of rPP filled with spherical-shaped SiC at varying volume percentages (i.e. 10, 20 and 30%).

The investigation reveals that the highest values of Young’s modulus, tensile strength, flexural strength and mode 1 frequency are observed for the 30% rPP/SiC samples, exhibiting increases of 115, 116, 62 and 15%, respectively, compared to pure rPP. Fractography analysis confirms the ductile nature of pure rPP and the brittle behavior of the 30% rPP/SiC composite. Moreover, the RVE method predicts Young’s modulus more accurate than micromechanical models, aligning closely with experimental results. Additionally, results from ANSYS simulation tests show tensile strength, flexural strength and frequency within a 10% error range when compared to experimental data.

This study contributes to the field by demonstrating the mechanical enhancements achievable through the incorporation of sustainable materials like rPP/SiC, thereby promoting environmentally friendly engineering solutions.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

Fueled by the rapid growth of internet, steganography has emerged as one of the promising techniques in the communication system to obscure the data. Steganography is defined as the process of concealing the data or message within media files without affecting the perception of the image. Media files, like audio, video, image, etc., are utilized to embed the message. Nowadays, steganography is also used to transmit the medical information or diagnostic reports. The paper aims to discuss these issues.

In this paper, the novel wavelet transform-based steganographic method is proposed for secure data communication using OFDM system. The embedding and extraction process in the proposed steganography method exploits the wavelet transform. Initially, the cost matrix is estimated by the following three aspects: pixel intensity, edge transformation and wavelet transform. The cost estimation matrix provides the location of the cover image where the message is to be entrenched. Then, the wavelet transform is utilized to embed the message into the cover image according to the cost value. Subsequently, in the extraction process, the wavelet transform is applied to the embedded image to retrieve the message efficiently. Finally, in order to transfer the secret information over the channel, the newly developed wavelet-based steganographic method is employed for the OFDM system.

The experimental results are evaluated and performance is analyzed using PSNR and MSE parameters and then compared with existing systems. Thus, the outcome of our wavelet transform steganographic method achieves the PSNR of 71.5 dB which ensures the high imperceptibility of the image. Then, the outcome of the OFDM-based proposed steganographic method attains the higher PSNR of 71.07 dB that proves the confidentiality of the message.

In the authors’ previous work, the embedding and extraction process was done based on the cost estimation matrix. To enhance the security throughout the communication system, the novel wavelet-based embedding and extraction process is applied to the OFDM system in this paper. The idea behind this method is to attain a higher imperceptibility and robustness of the image.

The present study aims to investigate the effect of environmental reporting on the financial performance of banks in India.

The study is based on the secondary data. The sample includes the banks listed in the NSE Nifty Bank Index from 2016–2017 to 2020–2021. The environmental reporting data was obtained through the content analysis technique. The financial data was collected from the CMIE Prowess database. Panel regression analysis was used to analyse the data.

The findings indicate a negative significant influence of environmental reporting on the ROA and ROE of banks. On the other hand, environmental reporting does not significantly influence the EPS of banking institutions.

To the best of the authors’ knowledge, this study is the first to contribute to the scarce literature on the influence of environmental reporting on financial performance, pertinently in the context of a developing nation's banking sector.

This study aims to identify factors affecting Generation Z (Gen-Z)’s online learning (OL) behavioural intention (BI) using the extended technology acceptance model by investigating gender differences in the BI of Indian students to adopt OL.

The proposed model was tested on 284 students from a higher education institution (HEI) in Gujarat, India, using the partial least square–structural equation modelling. Further, the subgroup analysis was conducted using Statistical Package for Social Sciences (SPSS) to determine male and female OL adoption variances.

Based on the research findings, all the constructs positively influence the BI of Gen-Z to adopt OL, except the influence of information technology infrastructure (INF) on perceived usefulness (PU). However, no substantial difference was observed in the BI adoption of OL amongst males and females. Also, when gender was kept as a moderator between computer self-efficacy (CSE) and PU, and INF and perceived ease of use (PEU), no substantial difference was observed in the OL of Gen-Z.

The study will benefit HEIs and associated government departments from a deeper understanding of Gen-Z’s BI to speed up deployment and consider key elements essential while considering OL.

This article found major determinants of Gen-Z’s BI to adopt the OL in HEI. To the best of the author’s understanding, this is amongst the few studies to explore these ideas in the context of India. The uniqueness of the topic has been brought to light by the fact that “gender” has been employed as a moderator between attitude and BI, INF and PEU, and CSE and PU.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.

Interest in generational research has garnered a lot of attention, as the workplace is seeing multiple generations (i.e., the Silent Generation, Baby Boomers, Gen Xers, and Millennials) working side-by-side for the first time. However, it is unclear how multiple generations of workers interact with each other and affect the workplace. Although there is extant literature on generational differences, some scholars have argued that the effect sizes are small and the differences are not meaningful. The focal aim of this chapter is to present the current state of literature on generational research. We present the relevant conceptualizations and theoretical frameworks that establish generational research. We then review evidence from existing research studies to establish the areas of differences that may exist among the different generations. In our review, we identify the issues arising from generational differences that are relevant to human resource management (HRM) practices, including new workforce entrants, aging workers, the changing nature of work and organizations, and leadership development. We conclude with several directions for future research on modernizing workplace policies and practices, ensuring sustainability in current employment models, facilitating future empirical research, and integrating the effects of globalization in generational research.

Construction waste reduction (CWR) plays a vital role in achieving sustainability in construction. A good CWR practice can result in optimizing material usage, conserving natural resources, limiting environmental pollution, protecting the environment and enhancing human health. In this regard, the purpose of the current study is to identify the most relevant organizational policies that aid in waste reduction and concurrently explores the congruent measures to be adopted during the construction process in the Indian high-rise building sector.

The research findings were obtained through a mixed- method approach. Content analysis was used to identify waste reduction measures (variables) targeting on the two domains of construction – “waste-efficient execution” and “waste – mitigating organizational policies.” Furthermore, the authors explored and documented the key measures from the identified waste reduction measures using the constraint value of the relative importance index. As the next step, the study listed the theoretical hypothesis based on expert interviews and tested the theory through confirmatory factor analysis.

The results revealed that “waste sensitive construction techniques and strategies” as the most significant category under the domain “Execution” with a path coefficient of 0.85. Concurrently, the study has also determined that “control procedures for budget, quality and resources” as the most effective organizational approach in reducing construction waste in the Indian building industry, with a path coefficient of 0.83.

The current research is context-sensitive to the Indian construction sector. It presents the stakeholder’s perspective on construction waste reduction and the relevant measures to be implemented to reduce construction waste in high-rise building projects in India. It can also act as a concordance for decision-makers to further focus on CWR management and aid in formulating policies suitable for the Indian context.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

The purpose of this paper is to evaluate the implications of and assess the economic and sustainable impact of environmentally friendly technological packages introduced into agribusiness players in the centre of chilli-producing regions of Indonesia.

This study used a theory of optimisation in production as a fundamental analysis. Producers are assumed to maximise profit by allocating rational amounts of inputs as the components of technological packages. A combination of qualitative and quantitative methods was used. The rate of technology adoption was evaluated, and agribusiness performance was measured using an economic advantage and technical efficiency. Data were compiled using group discussions and individual surveys.

The packages of technologies improved economic and sustainability performance of agribusiness resulting from efficient use of agrochemicals and water resource, and increase the production. Socio-economic and technical factors influenced performance farmers, as agribusiness players responded positively towards the ecological technology packages.

The sustainability of agribusiness was indicated by the reduction in agrochemical use and by the efficient use of water irrigation. There are other measures of sustainability, which are beyond this study. Additional studies are expected to fill the gap.

Considerable potential exists for broad adoption of these technological packages in Indonesia if they are disseminated effectively and in a close partnership with local extension agencies, farmers’ organisations, local non-governmental organisations and private sectors.

This study provides a realistic representation of a current condition because this is an empirical study conducted at the grass-root level. Sustainability of agribusiness practices was achieved with ecological technological packages.