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The COVID-19 pandemic compelled educational institutions to shift from classroom interactions to electronic learning (e-learning). This study uses eTAM with usability dimensions to examine the use of e-learning for core academic activities during the COVID-19 pandemic. Leveraging the switching value framework, it investigates students’ preference for extending the use of e-learning to extracurricular activities post-pandemic. The study also integrates eTAM and the switching value framework to conceptualize students’ e-learning usage behavior in a synchronous learning environment.

Structural equation modeling was used to test the proposed research framework using a cross-sectional design. Data were collected through a survey conducted at two premier management institutes with broad national representation in India.

The result revealed that emotional cost had a more significant impact on perceived switching value compared to learning, sunk and reduced performance costs. Also, perceived switching value had a stronger influence on e-learning than the eTAM factors. Interestingly, learning support negatively influenced perceived ease of use and usefulness.

The study provides evidence that while eTAM largely explains e-learning usage during the pandemic, perceived switching value significantly influences its extended use post-pandemic. Our study challenges the belief that eTAM factors influence the continuous use of e-learning post-pandemic. The study insights can guide educational institutions, educators and policymakers in expanding the application of e-learning beyond the pandemic.

This study aims to determine whether the relationship between the Muslim community and moneylenders is important even though the practice of moneylenders is clearly forbidden in Islam. This study examines a model consisting of two major theories, namely, the theory of planned behavior (TPB) and marketing theory, and the existence of the religiosity variable as a moderator.

This study uses a structural equation modeling (SEM); SEM was chosen because it has effectiveness in revealing estimates of direct and indirect effects and shows moderating values. Manual questionnaires were distributed to 385 Acehnese who use loan shark services.

The combination of TPB and marketing theory constructs has a significant influence on the intention to use loan shark services. Then, the existence of the word-of-mouth variable significantly mediates the relationship between service and subjective norms and the intention to use loan shark services. In fact, the position of the religiosity variable has a significant negative effect on the intention to use loan shark services, and in terms of the moderating effect, it has been demonstrated that religiosity weakens the relationships between the services provided by loan sharks and the intention to use loan shark services.

This study has several limitations. First, sampling is still limited and can still be expanded. Second, it is difficult to get data and there are people who refuse to be sampled. Third, this study succeeded in capturing the phenomenon of the behavioral intentions of people who have a religious spirit but are still associated with moneylenders.

This research provides material implications for the Aceh Government, especially in managing public funds. Indeed, Aceh is a productive province that has produced policies and regulations that encourage the Sharia economy; it is just that the use of social funds and Islamic philanthropy in Aceh has not been maximized, which has led to the growth of a network of moneylenders. Because of this, Aceh, which has been successful in producing the law for Islamic financial institutions, should also be successful in destroying the moneylender network by synergizing to create alternatives and financial solutions for the community, especially the lower and middle classes.

This research explains that the level of religiosity can dampen and reduce the intention to use loan shark services; therefore, it is important for the community to understand the dangerous impact of using loan shark services and expand the role of community leaders in socializing the idea of lending money to loan sharks.

Due to the lack of studies on the behavior of Muslims using the services of moneylenders, therefore, this study provides new knowledge of the literature on the economic behavior of Muslim communities who continue to use the services of moneylenders. This study develops TPB theory and marketing theory in one model and involves the religiosity variable as a moderator.

This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe₂O₄, CFO) for oil spill removal from seawater surface.

One-pot co-precipitation route was used to synthesize MBCC. The prepared materials were characterized by X-ray diffraction, scanning electron microscopy-energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy. The densities of the prepared materials were also estimated. Crude, diesel engine and gasoline engine oils were used as seawater pollutant models. The gravimetric oil removal (GOR) method was used for removing oil spills from seawater using MBCC as a sorbent material.

The obtained results revealed that the prepared materials (CFO and MBCC) were able to remove the crude oil and its derivatives from the seawater surface. Besides, when the absorbent amount was 0.01 g, the highest GOR values for crude oil (31.96 ± 1.02 g/g) and diesel engine oil (14.83 ± 0.83 g/g) were obtained using MBCC as an absorbent. For gasoline engine oil, the highest GOR (27.84 ± 0.46 g/g) was attained when CFO was used as an absorbent.

Oil spill removal using MBCC derived from cobalt ferrite and HTB. Using tree bark as biomass (eco-friendly, readily available and low-cost) for magnetic biochar preparation also is a promising method for minimizing agricultural solid wastes (e.g. HTB) and obtaining value-added-products.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

The intricate dynamics of ChatGPT adoption among Indian students are discussed while exploring the factors outlined by Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). By assessing these factors, this study aims to unravel their impact on the behavioral intention to use ChatGPT.

While evaluating ChatGPT's adoption dynamics, this study analyses the UTAUT2 core factors and perceived benefits. Real-time data from 638 business and management students in India were collected through purposive sampling and a cross-sectional survey. An in-depth examination using IBM SPSS and AMOS revealed the patterns that regulate ChatGPT reception in educational settings.

Habit emerges as a powerful predictor, which aligns with the Habit Loop Theory's cues, routine and rewards. Perceived benefits significantly influence adoption, and traditional factors like performance expectancy and social influence exert no influence. The insignificance of effort expectancy challenges conventional understanding, unveiling novel aspects of student tech adoption.

There is a need for guidelines to ensure fair and responsible use of ChatGPT among students. While ChatGPT presents advantages like task automation and personalized learning, integrating it into the existing education system requires careful planning to harness its benefits effectively.

With the recent introduction of Generative-AI tools, understanding student acceptance and application is essential. This research sheds light on this emerging technology, emphasizing the importance of analyzing technology acceptance for its successful adoption.

This Chapter has tried to explain the role of sustainable development for a healthy future. This Chapter takes a dive into the environment, its past and present form, with special recognition of Indian scenario. It explains how human activities have affected the environment. It explains the major effects that the human activities have on environment, like Global Warming and depletion of rich flora and fauna. It also takes into account various initiatives taken by the government in bringing back the environment to its original form, and a world towards sustainable development. This Chapter also throws light on Global Economy and Indian Economy in particular. It tries to explain why the economic growth should be related to sustainability. This Chapter also talks about Ozone layer and its depletion, about the Chipko Movement in India, bringing back the lost biodiversity of Mangalajodi, Odisha and how India has been active in maintaining sustainable development (Singh, 2023).

This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.

The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.

The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.

The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.

This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.

This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.

The purpose of this study is to detect the effect of some natural cellulosic polymers in their nano forms with the addition of zinc oxide nanoparticles on restoring the lost mechanical strength of degraded papyrus without any harmful effects on the inks.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

The effect of strengthening materials was studied on cellulose and carbon ink, which makes this study closer to reality as the manuscript is the consistent structure of cellulose and inks, whereas most of the literature stated the impact of consolidation materials on the strengthening the cellulosic supports without attention to their impact on inks.

The incompatibility of natural fibers with polymer matrices is one of the key obstacles restricting their use in polymer composites. The interfacial connection between the fibers and the matrix was weak resulting in a lack of mechanical properties in the composites. Chemical treatments are often used to change the surface features of plant fibers, yet these treatments have significant drawbacks such as using substantial amounts of liquid and chemicals. Plasma modification has recently become very popular as a viable option as it is easy, dry, ecologically friendly, time-saving and reduces energy consumption. This paper aims to explore plasma treatment for improving the surface adhesion characteristics of sisal fibers (SFs) without compromising the mechanical attributes of the fiber.

A cold glow discharge plasma (CGDP) modification using N₂ gas at varied power densities of 80 W and 120 W for 0.5 h was conducted to improve the surface morphology and interfacial compatibility of SF. The mechanical characteristics of unmodified and CGDP-modified SF-reinforced epoxy composite (SFREC) were examined as per the American Society for Testing and Materials standards.

The cold glow discharge nitrogen plasma treatment of SF at 120 W (30 min) enhanced the SFREC by nearly 122.75% superior interlaminar shear strength, 71.09% greater flexural strength, 84.22% higher tensile strength and 109.74% higher elongation. The combination of improved surface roughness and more effective lignocellulosic exposure has been responsible for the increase in the mechanical characteristics of treated composites. The development of hydrophobicity in the SF had been induced by CGDP N₂ modification and enhanced the size of crystals and crystalline structure by removing some unwanted constituents of the SF and etching the smooth lignin-rich surface layer of the SF particularly revealed via FTIR and XRD.

Chemical and physical treatments have been identified as the most efficient ways of treating the fiber surface. However, the huge amounts of liquids and chemicals needed in chemical methods and their exorbitant performance in terms of energy expenditure have limited their applicability in the past decades. The use of appropriate cohesion in addition to stimulating the biopolymer texture without changing its bulk polymer properties leads to the formation and establishment of plasma surface treatments that offer a unified, repeatable, cost-effective and environmentally benign replacement.

The authors are sure that this technology will be adopted by the polymer industry, aerospace, automotive and related sectors in the future.