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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.

This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.

The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.

The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.

The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.

The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.

This paper aims to explore the key factors through which an optimum pedagogy mix can be determined towards effective teaching practice and enhanced student learning outcomes in business/management education.

An exploratory research design has been used. A sample of 310 was analyzed using exploratory factor analysis. A structured questionnaire was developed to collect data. It was pre-tested, and essential modifications were made before its final implementation.

The study has presented the idea of pedagogy mix, which refers to a set of most obvious teaching methods/tools suitable to deliver marketing education in a context-bound manner. Eight factors have been identified that help to decide and/or maintain an optimum mix of pedagogies for effective teaching. An adequate “pedagogy mix” would help achieve educational objectives and equip students with the essential competencies.

The study is particularly significant to educators who are in the initial years of their careers. The identified factors help educators decide and/or maintain an optimum mix of pedagogies by offering an understanding of different pedagogies, their strategic relevance and student needs.

An institution's academic philosophy and commitment to the learning outcomes make it excellent or poor. Present institutions have and retain a main focus on preparation for professional careers, and without a perfect blend of pedagogies, it cannot be achieved. An optimum pedagogy mix would facilitate the key learning process and proffer the intricacies of the concerned profession. In this sense, this paper is a significant attempt, particularly in management education and higher education in general, that enables the educators of higher academics to decide and utilize an idyllic blend of pedagogies towards the successful execution of an educational process of higher order and ensuring the holistic student development.

The purpose of this paper is to identify the factors determining students’ attitude toward using newly emerged artificial intelligence (AI) tool, Chat Generative Pre-Trained Transformer (ChatGPT), for educational and learning purpose based on technology acceptance model.

The recommended model was empirically tested with partial least squares structural equation modeling using 375 student survey responses.

The study revealed that students have a favorable view of the instructional use of ChatGPT. Usefulness, social presence and legitimacy of the tool, as well as enjoyment and motivation, contribute to a favorable attitude toward using this tool in a learning environment. However, perceived ease of use was not found to be a significant determinant in the adoption and utilization of ChatGPT by the students.

This research is intended to benefit enterprises, academic institutions and the global community by offering light on how students perceive the ChatGPT service in an educational setting. Furthermore, the application enhances confidence and interest among learners, leading to improved literacy and general awareness. Eventually, the outcome of this research will help AI developers to improve their product and service delivery, as well as benefit regulators in regulating the usage of AI-based bots.

Due to its novelty, the current research on AI-based ChatGPT usage in the education sector is rather restricted. This study provides the adoption aspects of ChatGPT, a new AI-based technology for students, thereby contributing significantly to the existing research on the adoption of advanced education technologies. In addition, the literature lacks research on the adoption of ChatGPT by students for educational purposes; this study addresses this gap by identifying adoption determinants of ChatGPT in education.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.

This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security).

The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t-tests.

The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences.

Previous studies have looked into impulse buying in its generic sense and not through the “types” of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour.

This study delves into 17th-century colonial port cities – Madras, Bombay, and Calcutta – examining the impact of British imperialism on urban sustainability and heritage conservation. It explores historical development, spatial organization, and connectivity.

This study intricately explores the interplay among urban sustainability, morphology, and heritage conservation using space syntax analysis. It focuses on examining White and Black Town dispersion during British imperialism.

The investigation reveals varying degrees of dispersion of White and Black Towns, with Calcutta exhibiting the most consistent distribution among the three cities. These findings underscore the profound influence of British imperialism on the spatial organization of colonial port cities, offering valuable insights into their historical evolution and layout.

While this study provides valuable insights, it is limited by its focus on the colonial period and the specific cities of Madras, Bombay, and Calcutta. The findings may not be directly generalizable to other contexts or time periods. Additionally, the study’s reliance on historical data sources may present data accuracy and completeness challenges.

This study contributes to understanding colonial port cities, guiding sustainable urban development, heritage preservation, and equitable resource access for global sustainability. By focusing on the historical impact of British imperialism, the research provides original insights into the spatial dynamics of these cities, contributing to the broader discourse on urban sustainability and heritage conservation.

Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this study aims to explore the factors influencing educators’ acceptance and utilization of chat generative pretrained transformer (ChatGPT) in the context of higher educational institutions. This study additionally examines the moderating influence of trust on the association between intention and adoption of ChatGPT.

A structured questionnaire was disseminated to 1,214 educators following the purposive sampling method. The hypothesized relationships between the extended UTAUT model constructs and ChatGPT adoption were examined using structural equation modeling.

The results of this study indicate positive impact of ChatGPT adoption and its use behavior (UB) among educators. Performance expectancy, effort expectancy, hedonic motivation, facilitating conditions and habit have a positive impact on behavior intention to use this tool among educators in higher education institutions, However, the educators intend to use ChatGPT in a personal capacity and are negatively influenced by the social groups. Moreover, behavior intention to adopt ChatGPT has a larger effect on the UB due to the higher involvement of trust.

This research adds to the literature on technology adoption by emphasizing the significance of trust in the adoption of emerging technologies, such as big language models. This study’s findings have implications for ChatGPT technology developers, legislators and academics considering the implementation of ChatGPT for teaching and research.

This research investigates ChatGPT adoption among higher education educators using the UTAUT model. It emphasizes the role of trust in adoption, highlights key adoption factors and reveals a paradox: educators are personally inclined to use ChatGPT but hesitant due to negative social influence. This study's novelty lies in its focus on trust and its implications for developers, legislators and educators, offering valuable insights for integrating ChatGPT in education.

The purpose of this study to identify and optimize the machining of polyvinyl butyral (PVB) material for industrial uses. The research is based on input machining parameters of rotary ultrasonic machining for better understand the output response surface roughness (SR) property of polyvinyl butyral (PVB) by using the Taguchi approach. The grey relational grade analysis (GRG) is also implemented to resolve the complex interrelationship of SR data for optimization and predicting and validate the results.

In experimental work, the input parameters, namely, concentration, abrasives, power rate, grit size, tool material and hydrofluoric (HF) acid has been selected. The experiment’s design was created using MINITAB Software; the L27 orthogonal array was selected for the experimentation. SR was examined with the GRG technique for process optimization. On the other hand, for single parameter optimization analysis of variance (ANOVA) has been used.

ANOVA optimization technique gives the best result on concentration (40%) of abrasive (Al2O3+SiC+B4C), power rate (40%), grit size (600), HF acid (1.5%) and tool material (D2 alloy) are the optimal parameters to provide the slightest degree of SR. GRG optimization of multi-response parameter setting: 40% concentration, SiC+B4C mixed abrasive slurry, 40% of power rating, 280 grit size, 0.5% HF acid and high-speed tool steel tool material gives better results. The SR of PVB glass material improved by 20% after grey relational analysis.

There are several practical applications in a variety of material processing sectors, including metallurgy, machinery, electronics and transportation. These real-world applications have produced substantial and discernible economic benefits.

The analytical and optimization results will be used in the various material processing sectors, including metallurgy, machinery, electronics and transportation.

The ANOVA and grey theory approaches offer the reader a primary picture of the machining research and process parameter optimization. Combined abrasive slurry of Al₂O3+SiC+B₄C with a high power-rating exhibits lower SR. Similarly, grit size is vital; larger grits produce better SR. Ra – 0. 611 m is the lowest SR value at the hole found in trial 25 after the experimentation.