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This paper aims to identify the factors affecting the adoption of plastic money and mobile wallets by comparing rural and urban perspectives. For this, the study uses a unified theory of acceptance and use of technology (UTAUT3) model with additional variables, perceived value and perceived risk, to predict use behavior.

This research incorporates two cross-sectional surveys, Study R, which includes 417 rural respondents and Study U, which includes 431 urban respondents, regarding plastic money and mobile wallet adoption. This paper used the Statistical Package for Social Science and partial least squares-structural equation modeling for data analysis.

Both studies showed that performance expectancy, social influence and hedonic motivation substantially influence behavioral intention and use behavior. In contrast, effort expectancy has an insignificant influence in rural (Study R) and urban (Study U). In addition, personal innovativeness and perceived value positively influence, whereas perceived risk negatively influences behavioral intention and use behavior in both studies. However, facilitating conditions had a positive effect in Study U, but it had a negative effect on behavioral intention and use behavior in Study R.

This research lays a practical foundation for governments, policymakers and marketers to encourage a phygital payment service that explicitly addresses the rural and urban context. In addition, the findings of this paper also help regulatory authorities develop effective strategies and campaigns to encourage the sustainable development of countries.

This paper attempts to address the gap in the prevailing literature by investigating the role of geographical differences in the technology adoption system, especially in emerging nations like India, where these studies are missing. The adoption differences between rural and urban areas, along with the insightful findings by the authors, help to highlight the unique aspects of the context. As one of the pioneering studies, this research tests the UTAUT3 model, incorporating two additional constructs, to provide a comprehensive framework for using plastic money and mobile wallets – valuable for both researchers and practitioners.

This paper aims to develop a real-time pothole detection system to improve mapping, localization and path planning, reducing vehicle instability and accident risks. Efficient mapping, accurate localization and optimal path planning stand as prerequisites to realizing accident-free navigation. Despite their significance, existing literature often overlooks the real-time detection of potholes, which poses a considerable risk, particularly during nighttime operations. Potholes contribute to vehicle imbalance, trajectory tracking errors, abrupt braking, wheel skidding, jerking and steering overshoot, all of which can lead to accidents.

Unmanned vehicles constitute a critical domain within robotics research, necessitating reliable autonomous navigation for their optimal functioning. This research paper addresses the gap in current methodologies by leveraging a Convolutional Neural Network (CNN)-based approach to detect potholes, facilitating the generation of an efficient environmental map. Furthermore, a hybrid solution is proposed, integrating an improved Ant Colony Optimization (ACO) algorithm with modified Bezier techniques, complementing the CNN approach for accident-free and time-efficient unmanned vehicle navigation. The conventional Bezier technique is enhanced by incorporating new control points near sharp turns, mitigating rapid trajectory convergence and ensuring collision-free paths.

The hybrid solution, combining CNN with path smoothing techniques, is rigorously tested in various real-time scenarios. Experimental results demonstrate that the proposed technique achieves a 100% reduction in collisions in favorable conditions, a 4.5% decrease in path length, a 100% reduction in sharp turns and a significant 23.31% reduction in total time lag compared to state-of-the-art techniques such as conventional ACO, ACO+ Bezier and ACO+ midpoint Bezier, Improved ACO, hybrid ACO+ A*.

The proposed technique provides a proficient solution in the field of unmanned vehicles for accident-free time efficient navigation in an unstructured environment.

For smooth running of business affairs, there needs to be a coordination among manufacturer, collector and retailer in forward and reverse supply chain. This paper handles the problem of making pricing, collecting and percentage sharing decisions in a closed-loop supply chain. The purpose of this paper is to examine the effect of responsibility sharing percentage on the profits of a manufacturer, a retailer and a collector. The paper further aims to understand the mutual interactions among decision variables and profit functions. It also determines the optimal selling price, optimal time, wholesale price, sharing percentage and optimal return rate in such a manner that the profit function is maximized.

The authors presented a three-echelon model consisting of a manufacturer, a retailer and a collector in the closed-loop supply chain and optimized the profits of each supply chain member. The authors introduced SRR models for the remanufacturing by providing some percentage of physical and financial support to the collector. Optimization techniques have been applied to obtain optimal solutions. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the model.

This study stresses on profitable value retrieval from returned products, and it discusses how responsibility sharing can improve profitability and reduce the workload of an individual. In total, three main results are found. First, sharing and coordination among chain members can improve collector’s profit. Second, supply chain performance may also improve over time. Third, the profit of each member of the supply chain increases with an increase in sharing percentage up to a certain limit. So, the manufacturer can share the responsibility of the collector under a fixed limit.

The main limitation of this model is that there is no difference between manufactured and remanufactured products. There are many correlated issues that need to be further investigated. The future study in this direction may include multi-retailer, stochastic demand patterns.

It is directly utilized by supply chain industries in which coordination among chain members is still needed to maximize profits. This information enables the manufacturer to assist the collector financially or physically for the proper management of the three-layer supply chain. The present work will form a guideline to choose the appropriate parameter(s) and mathematical technique(s) in different situations for remanufacturable products.

From the management point of view, this study delivers the strongest result to remanufacturing companies and for whom effective and efficient coordination among chain members is vital to the overall performance of the supply chain.

There are very few studies that consider the remanufacturing of used products under a fixed time period. The authors considered selling price-sensitive and time-dependent exponentially declining demand. This model is developed by considering all possible help to a collector from manufacturer to collect used products from consumers. This research complements past research by showing coordination among supply chain members within a fixed time horizon.

The growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.

A portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.

The HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.

The framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.

The previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.

The aim of this study is to provide a review of the research studies that took place in the previous years regarding Mangiferin and its potential use in the treatment of various disorders such as diabetes, cardiovascular diseases, cancer and human immunodeficiency virus.

Mangiferin can be easily extracted from the plant at a very low cost to treat some common as well as deadly diseases, which will be a miracle in herbal treatment. In support of this, the recent related articles were considered to understand the bioactive compound “Mangiferin” to treat lifestyle diseases. Various review articles and research papers were collected from international and national journals, and internet sources were also being used to compile the current manuscript.

Mangiferin has been shown to have the potential to mitigate many life style diseases such as diabetes, obesity, hypertension, fatty liver, atherosclerosis, dyslipidemia and diabetes-related end-organ complications such as retinopathy, neuropathy and nephropathy.

In this comprehensive review, this study evaluates Mangiferin and its lifestyle disease-modifying properties for nutraceuticals purposes.

The purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.

A smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.

The main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.

The hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental quality management. This new technology needs a supportive ecosystem, and thus, this paper identifies and models the enablers for adopting 3D printing technology toward a sustainable food supply chain.

The enablers were identified through an extensive literature review and verified by domain experts. The identified enablers were modelled through the hybrid total interpretive structural modelling approach (TISM) and the decision-making trial and evaluation laboratory (DEMATEL) approach.

It emerged that stakeholders need technical know-how about the 3D printing technology, well supported by a legal framework for clear intellectual property rights ownership. Also, the industry players must have focused and clear strategic planning, considering the need for sustainable supply chains. Moreover, required product innovation as per customer needs may enhance the stakeholders' readiness to adopt this technology.

The framework proposed in this research provides managers with a hierarchy and categorization of adoption enablers which will help them adopt 3D food printing technology and improve environmental quality.

This research offers a framework for modelling the enablers for 3D food printing to develop a sustainable food supply chain using the TISM and DEMATEL techniques.

Venue comes from the Latin word meaning ‘come’ (venire). Not only the event's location or venue affect attendance but it can also have an impact on the event's personality. Additionally, the location or venue affects the event's atmosphere and the visitor experience. The most significant benefit of revitalisation or adaptive reuse is its positive impact on the environment as razing buildings is a major source of waste and carbon emissions, by contrast, adaptive reuse reduces waste, saves energy and conserves resources. The persistence of this chapter is to investigate the challenges and opportunities in making adaptive re-use or revitalisation of heritage buildings that includes forts/palace/museums as a venue for any event. For the purpose of achieving the goal, secondary data from 2000 to 2023 have been compiled from more than 50 research articles that have been published in peer-reviewed and University Grant Commission (UGC) journals, books written by various authors, including the authors themselves, other researchers working in the related field of event management, conference proceedings and websites. The authors discovered from their examination of the literature that the significance of the event venue cannot be unheeded. The event's tone sets the stage for possible guest experience influences. One must carefully consider the kind of venues or settings that are available in the destination before conducting any event.

The purpose of this paper is to gain insight into international career motives, repatriation and career success of Indian women in Science and Technology.

In total, 30 semi-structured interviews were conducted with (upper) middle-class Indian women in Science and Technology in Bangalore and New Delhi, India.

Thematic analysis resulted in four themes – International career motives, Theme 1: cross-cultural and scientific exposure; Repatriation reasons and experiences, Theme 2: family reunion, career prospects and readjustment; Career success, Theme 3: international experience; and career growth, Theme 4: social responsibility. Motives for international career mobility of Indian women were: exposure to foreign cultures, international collaboration in science and personal and professional development. Family formation and reunion and career prospects were reasons for repatriation and positively influenced repatriation experiences of Indian women. Readjustment to people and conditions in India impacted their repatriation experiences negatively. The meaning women attribute to career success is grounded in recognition from peers in science, career growth, satisfaction and contribution to science and Indian society.

The sample of Indian female scientists may limit generalization of the findings to global career professionals in other professions from other countries with different socio-cultural and economic contexts.

HR policies that foster international careers of women scientists as well as women's networks in science to share and apply knowledge, and their contribution to the Indian economy and society will enhance global career success of women and strengthen the sustainable competitive position of organizations.

The study provides new insights into motivation for international career mobility and repatriation of women professionals from a developing country and their career success in the home country, and contributes to the development of theoretical frameworks on international career mobility and career success.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.