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This bibliometric study aims to analyze publication trends, active countries, collaborations, influential citations and thematic evolution in learning analytics (LA) research focused on higher education (HE) during and after the COVID-19 lockdown period.

From the Scopus database, this bibliometric analysis extracts and evaluates 609 scholarly articles on LA in HE starting in 2019. The multidimensional process identifies the scope impacts, advancing the understanding of LA in HE. An analysis of co-citation data uncovers the key influences that have shaped the literature. This study uses the stimulus-organism-response (SOR) theory to suggest future research directions and organizational adaptations to new LA technologies and learner responses to LA-enabled personalized interventions.

Learning analytics are becoming important in the HE environment during and after the COVID-19 lockout. Institutions have used LA to collect socio-technical data from digital platforms, giving them important insights into learning processes and systems. The data gathered through LA has assisted in identifying areas for development, opening the path for improved student success and academic performance evaluation and helping students transition to the workforce.

The study’s concentration on the post-COVID-19 timeframe may lead to paying attention to potential pandemic developments. Nonetheless, the findings provide a thorough picture of LA’s contributions to HE and valuable ideas for future study initiatives. Future research with the SOR framework suggests areas for additional study to maximize LA’s potential in diverse HE situations.

This study adds to the growing corpus of knowledge on learning analytics in HE, especially in light of the COVID-19 lockdown and its aftermath. By using bibliometric analysis, the study provides a complete and evidence-based understanding of how LA has been used to address challenges related to HE. This study uses bibliometric analysis and SOR theory to appraise and map HE learning analytics research. The selected study themes can help scholars, educators and institutions shape their future efforts to improve teaching, learning and support mechanisms through learning analytics.

The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps.

This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC.

This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies.

The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

Goat milk yoghurt differs from cow milk yoghurt in that it has a different casein composition and content, which presents several technical challenges, including consistency with an appropriate flavor.

In this study, the antioxidant potential and phytochemical profiling of the fruits (pineapple and papaya) and vegetable (carrot) extracts was evaluated and the effect of their purees on the quality and stability of stirred goat milk yoghurt (GMY) were investigated. The qualities of stirred GMY with carrot (CrY), pineapple (PaY) and papaya (PpY) purees were assessed against the product without puree (CY).

The carrot puree had the highest moisture, ash contents and pH value. The carrot extract had the highest DPPH radical scavenging activity, while the pineapple extract had the highest total phenolic value (1.59 µg GAE/g) and flavonoids content (0.203 µg CE/g). The scanning of all the puree extracts in GC-MS indicated that 5-hydroxymethylfurfural was a major component. The phytochemical quantification of the extracts through multiple reaction monitoring (MRM) against 16 compounds showed the presence of sinapic acid, cinnamic acid, pthalic acid, ferulic acid, 4-OH-benzoic acid, 3-OH-benzoic acid, p-coumaric acid, caffeic acid and vanillic acid in different quantities. The addition of purees and storage period had a significant (p < 0.05) effect on the moisture, pH, titratable acidity, syneresis, viscosity, color values and sensory properties of the products. In all the samples after 15 days of storage, Streptococcus thermophilus and Lactobacillus bulgaricus counts remained above the recommended level of 106CFU/g. Stirred GMY sample produced with pineapple puree showed a higher syneresis and viscosity, but the CrY sample demonstrated the highest antioxidant activity. The developed formulations remained stable with minimum changes in quality and sensory attribute during refrigerated storage for 10 days.

This study suggests that addition of fruit and vegetable improve the viscosity and sensory perception of the product with minimal use of synthetic flavor and preservatives.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

This study aims to explore the knowledge, attitudes, and experiences of PhD students in India regarding research ethics and institutional review boards (IRBs), assess awareness levels, identify training gaps, examine ethical priorities and understand challenges in the IRB application process.

A quantitative approach was used, and a self-evaluator questionnaire was distributed electronically to PhD students. Data collection occurred between 1 March 1 and 30 March 2024, with analysis conducted using SPSS software.

The study reveals a significant gap in formal training on IRB procedures within PhD programs and challenges in completing IRB applications despite recognising ethical priorities such as informed consent and confidentiality.

This study provides insights into PhD students’ perspectives on research ethics and IRBs in India, highlighting the need for enhanced education and awareness initiatives to promote responsible conduct and safeguard research participants.

This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

Environmental, Social and Governance (ESG) reporting is crucial for organizations, especially in the current era where sustainability holds significant importance. Proper utilization of ESG reporting offers long-term benefits and enhances overall corporate well-being. This study explores fundamental aspects of ESG reporting, elucidating the reporting process, its advantages and requirements. An analysis highlights key impacts on businesses and their influence on consumer behaviour. The disclosure of ESG reporting and its determinants, such as business size and profitability, is discussed. Additionally, the study underscores the role of promoting diversity and inclusion as a Corporate Social Responsibility (CSR) function. Global firms undertake diverse initiatives to advance sustainability. The study emphasizes the triple bottom line theory as a strategy for sustainable development. ESG is recognized as a valuable tool for ensuring sustained growth and development in businesses. The research underscores the imperative for businesses to adopt sustainable measures consistently. Overall, the findings stress the significance of ESG reporting in the contemporary business landscape, linking it to corporate success, responsibility and the pursuit of sustainable practices.

As more and more cities adopt resilient, inclusive and sustainable principles, circular economy (CE) emerges as a critical ally in developing smart cities. The technology-driven environment of smart cities and CE's resource-efficient principles are perfectly compatible, overcoming challenges and highlighting benefits like increased resource efficiency. The integration of CE in smart cities is thoroughly analyzed in this chapter using VOSviewer and RStudio, tracing its history and pointing urban innovators towards a circular future. The categorization of obstacles to CE implementation in smart cities, the provision of knowledge about barriers and the facilitation of methodical solutions constitute a critical focus of research. Additionally, by analyzing pertinent literature, this investigation highlights the importance of integrating the concepts of the CE and the smart cities, illuminating the interdisciplinary nature of this field. This synthesis provides policymakers and planners with the knowledge they can use to advance sustainable urbanization effectively.

It's no longer a secret that a hassle-free life and better human development index are only possible in smart cities with appropriate and efficient deployment of artificial intelligence (AI)-based technologies where the best results of data analysis are being used. Technology is becoming more productive using circular economy while employing all the dimensions of AI where integration of results is being incorporated as an outcome of data analysis received from different segments i.e., Traffic Management, Public Safety, and Movement, Security and surveillance, Waste Management Systems, or the Energy Management, etc. This chapter specifically talks about areas where AI is facing challenges in the implementation and administration of smart cities while covering the intrinsic challenges faced in specialized domains such as Public Sanitation, Virtual Parking Management, Traffic Congestion, Security Surveillance, and many more discussed as case study relating to the functioning of the circular economy. In the last, we have summarized the impact of AI on the CE and its future scope where AI can play a better role in increased productivity, increased efficiency, robust safety and finally economic benefit for long-term stable economic stability, development and inclusive growth.