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Inclusive innovation in tourism sector: Gap analysis through impact assessment
The travel and tourism industry is a major catalyst for global economic growth. Inclusivity and equity are indeed significant challenges faced by the service sector. The present study attempts to analyze the attributes of achieving true inclusivity and equity. This requires addressing systemic barriers and biases that can perpetuate unequal opportunities and outcomes towards building a pro-active tourism community. The chapter identifies the inequities already in place as well as untapped prospects for inclusive innovation in the tourism industry by performing an extensive gap analysis and impact assessment. A comprehensive and multi-faceted approach in practicing inclusiveness in the tourism sector demands an innovative pedagogy and unconventional business practices. The chapter highlights the bigger picture of inclusive innovation in tourism, which clarifies how business, society, and technology interact. A smart tourism approach with an integrated technological effort and socially-driven innovation builds the competency of the destinations. The study aims to assess the existing level of inclusion in tourism innovation, which determines significant representational and access gaps while assessing the potential economic and cultural effects of introducing more inclusive practices. As we navigate complex global challenges, from social inequality to environmental sustainability, inclusive innovation offers a path forward. The implications indicated in this chapter benefits the stakeholders with socially driven inclusive innovation. Towards inclusive innovation, equity takes center stage. An inclusive setting ensures collaboration and co-creation and integrating people from diverse backgrounds, including entrepreneurs, researchers, policymakers, and community members. Socially engaged stakeholders are aligned with inclusive innovation with insights and experiences, resulting in high relevance and sustainable orientation, thereby fostering growth and development. 2024 Nova Science Publishers, Inc. All rights reserved. -
Tourism business management and competitiveness: Intervention of inclusive practices and community based approach towards community empowerment
The travel, tourism, and hospitality industry is a rapidly evolving sector that contributes to the global economy effectively. Effective business management is crucial for success in this industry, as it requires a delicate balance of customer satisfaction, financial sustainability, and responsible practices. In this chapter, we delve into the key aspects of business management in the tourism industry and explore strategies for achieving sustainable growth and success. This chapter explores a multistakeholder perspective in examining the various facets of business engagement in an inclusive setting. The chapter is iterative, with a focus on the crisis management strategies adopted by the tourism business, to tackle the challenges that stakeholders face in a crisis situation. The study also examines case-lets from the hospitality operators. The chapter primarily endorses business management with coping strategies in a crisis management scenario to equip the stakeholders during disasterprone situations. Towards building a competitive and empowered community, a competency framework is proposed for speedy crisis management responses. The implications indicate the role of destinations, over internal strategies and strategy formulation. Paradoxical dilemmas towards inclusive engagement is clarified with dynamics to understand stakeholder engagement in the leisure industry with strategic and tactical perspectives adopted by a good destination governance. The allied and supplementary tourism industry practitioners in the hospitality sector portray business management and success in business through empowered communities with a tactical and strategic outlook. This indeed can reposition and rebrand tourism in the "New Normal" examined through case lets to address the success of inclusive engagement for community self-sufficiency and empowered teams. 2024 Nova Science Publishers, Inc. All rights reserved. -
Harnessing digital innovation for inclusive tourism: Role of emerging technologies in creating accessibility and equity
The rapid advancement of digital technologies has ushered in a new era for the tourism industry, presenting unprecedented opportunities to enhance inclusivity, accessibility, and equity in travel experiences. This study investigates the transformative potential of emerging technologies in fostering a more inclusive tourism landscape. Specifically, it examines how selected digital innovations such as artificial intelligence (AI), augmented and virtual reality (AR/VR), mobile applications, and wearable devices are shaping the accessibility and equity of tourism for diverse populations. This chapter begins with a comprehensive literature review, highlighting current trends, challenges, and existing studies on inclusive practices in the tourism sector. The paper delves into a detailed analysis of each emerging technology, showcasing successful integration examples from real-world cases. It evaluates the benefits and potential challenges of adopting these technologies, especially in enhancing accessibility for travelers with disabilities. The examination addresses physical, sensory, and cognitive accessibility barriers, providing insights into how technology reshapes travel experiences for diverse individuals. This chapter delves into the role of emerging digital innovations in fostering equity within the tourism sector. By facilitating cross-cultural connections and enhancing access to tech-driven travel experiences, these technologies contribute to a more inclusive landscape. The study scrutinizes socioeconomic dimensions, shedding light on the holistic impact of tech integration. While acknowledging challenges and ethical concerns, responsible technology deployment is endorsed to counterbalance drawbacks and bridge the digital divide, enabling marginalized communities to leverage the benefits of this digital transformation. The implications of this study are relevant for businesses, policymakers, and tourism stakeholders. The chapter concludes by providing practical recommendations for the responsible incorporation of emerging technologies and emphasizing the long-term sustainability of inclusive digital innovations. By shedding light on the transformative potential of these technologies and outlining guidelines for their application, this research contributes to the evolution of a more accessible, equitable, and inclusive tourism industry. 2024 Nova Science Publishers, Inc. All rights reserved. -
AN ANALYSIS OF PERCEPTION AND AWARENESS OF UNDERGRADUATE YOUTH TOWARDS CYBERCRIME
The perception of a situation or reality determines how one responds and awareness is the first step towards understanding, knowing or recognizing it. The majority of the public and the police may be familiar with the phrase cybercrime, but all of the mare fully informed ofthe nature and scope of these crimes, as well as of the cybercriminals and cyber victims, which has an impact on how they see these issues. This studys main goal was to examine the perception and awareness of cybercrime among undergraduate youth studying in BBA or BCA courses. In this study, we discovered that young peoples responses to cybercrime mostly depend on their perceptions of it and their awareness level. To accomplish the studys objective, a thorough examination of existing literature was undertaken. Primary data of200 students were collected through Google Forms. Percentile analysis, correlation analysis and t-test are done to test the hypotheses. The results of this study may help college administrators better comprehend the mind set of todays youth as they develop laws and policies aimed at reducing cybercrime among students. The results of this study show that the youngsters surveyed have high levels of awareness and a good perception. 2024 Kiran Joshi and Priyanka Kaushik. -
Edge, IIoT with AI: Transforming industrial engineering and minimising security threat
[No abstract available] -
Elevating industries: Cloud computing's impact on industry-integrated IoT
[No abstract available] -
Insights into thyroid disease: Harnessing machine learning for analysis and classification of multi-label medical data
Thyroid disease refers to a wide range of disorders that occur due to dysfunction of the thyroid gland, a small gland located at the base of the neck that produces thyroid hormones. Through the analysis of this comprehensive dataset, we aim to utilize machine learning (ML) techniques for the analysis and classification of thyroid data. Employing ML techniques for thyroid classification has the potential to improve diagnostic accuracy, facilitate timelier interventions, lower expenses, optimize doctor time, and foster a more personalized approach to thyroid care. The objective of this research was to conduct multiclassification, encompassing the broadest array of classes for the target variable. To address the imbalances within the dataset, we employed the Synthetic Oversampling Technique (SMOTE) as a resampling method. Specifically, classes with a minimum of 10 samples were retained, resulting in the inclusion of 19 out of the total 34 classes in the dataset. The importance of SMOTE in addressing class imbalance is examined in this chapter, with an emphasis on how it may be used to enhance classifier model performance. Moreover, we conducted a comparative analysis of Classification Models, including Random Forest, K-Nearest Neighbor, Decision Tree, SVM, Gradient Boosting, Multinomial Naive Bayes, and Logistic Regression, to assess their accuracies. Following the resampling of the dataset, the highest accuracy of 99.99% was achieved with the gradient booster. Additionally, this research incorporated the association rule technique to uncover meaningful relationships within the dataset. 2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved. -
Artificial Intelligence in Green Transportation: A Conceptual Review
[No abstract available] -
Longitudinal study on noncommunicable diseases using machine learning
This longitudinal case study thoroughly explores the intricate connection between body mass index (BMI) and four key factors: physical health, psychological well-being, lifestyle choices, and the impact of diet on health. Through the analysis of longitudinal data, notable trends emerge, revealing an increase in risk factors for noncommunicable diseases (NCDs) and unhealthy behaviors over time. This highlights the combined impact of these interconnected factors on health outcomes and the risk of developing NCDs like heart disease, diabetes, and cancer. Leveraging machine learning, the study effectively identifies individuals at elevated risk for NCDs and dispels common health misconceptions, underscoring the significance of holistic wellness approaches. Serving as a beacon for the next generation, this study provides insights that contribute to shaping a healthier future. 2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved. -
Framework based on IoT, AI, and blockchain for smart access to government agricultural schemes
Agriculture plays an important part in most countries, such as India. A survey says that 54.6% of the total labor force of India is engaged in agriculture and its connected activities. The government is announcing many schemes to facilitate agriculture and support farmers. But most of the farmers are from poor families and are not able to reach the government schemes when they are really in need. Also, it is required to observe and measure the inter and intra-field variability in crops to enjoy the complete benefits of government schemes. This can be done with the advancements in the field of the Internet of Things. Information related to the impact of natural calamities on the agricultural field, malfunctions in the machinery used for cropping, yielding level, and health status of crops can be measured using the technology of IoT (Internet of Things) and analyzed using AI (Artificial Intelligence). Blockchain plays a critical role in replacing traditional means of data storage and exchanging agricultural data with a more trustworthy, immutable, transparent, and decentralized approach. By keeping all the transactions related to government schemes in blockchain, the possible crimes in the form of false data by the intermediate dealers acting between the farmers and the government can be addressed. This, in turn, allows useful government schemes to reach the farmer in time. We propose to develop a theoretical model using IoT, AI, and blockchain, which can assist the farmers in benefitting from the appropriate schemes announced by the government in time and achieving precise agriculture. 2024 Bentham Science Publishers. All rights reserved. -
Security and privacy issues in existing biometric systems and solutions
[No abstract available] -
Integrated photonic devices for cancer detection
[No abstract available] -
Narratives of the self: Comments and confessions on Facebook
Narratives are structured around events, which are used to tell a story. The self is perpetually being constructed through narratives of experience. This chapter focuses on the phenomenon of Facebook confession pages and how they contribute to the construction of digital identity. Drawing on insights from my project on the role of Facebook College Confession pages, the chapter examines how these platforms have transformed the way users express and shape their identities. The anonymity provided by these pages allows users to post confessions without revealing their identities, encouraging a form of virtual self-exploration. These confessions, often written by nameless authors, generate a complex and ongoing narrative of identity, shaped by the interaction of multiple voices and viewpoints. The chapter also explores the motivations behind sharing personal confessions, even when the responses may be negative, and how this contributes to the perpetual construction of the digital self. By examining the intersection of public and private spheres in these online spaces, this chapter highlights how the breaking of the public-private divide enables users to create and negotiate their identities in a digital, networked world. The narrative constructed is endless, and the post is not an end in itself. It paves the way for the generation of an endless narrative by multiple authors with multiple viewpoints. This chapter explores the reasons behind sharing such posts on Facebook, even if the comments are negative in tone. It will refer to Anthony Giddens' concept of time-space "distanciation" (Keefer et al., 2019) to show how multiple tellers through their narratives help to build the complex networked identity of a user. The study will also analyse the role played by the breaking of the public-private divide in creating such spaces for the construction of a private self through public voices. 2024 Rimi Nandy. -
Silicon photonic modulators for high-speed applications-a review
[No abstract available] -
Digital platforms for business applications
[No abstract available] -
ASSESSING FIRMS ESG PERFORMANCE USING THE TOPSIS
Environment, social and governance (ESG) criteria are a quantum of a companys performance in the environmental, social and governance aspects. A companys worth may be determined not only by its earnings but also by its knowledge and sensitivity towards its stakeholders and society. The study aims to rank the companies and determine which company is superior based on ESG criteria. The authors employed the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in this study. The companies are ranked with this standardized method comprehending which company is the best taking into consideration the various environmental, social and governance factors. The authors have evaluated four companies in the electric utilities and IPPs industry. The results of the study rank these four companies on the basis of ESG criteria. Interestingly, the rankings calculated for ESG criteria are identical to the rankings calculated by a well-known ESG rating agency. To the best of authors knowledge, this work is among the first to use the TOPSIS method to find rankings of the companies on the basis on ESG criteria. The work provides practical implications regarding convenient to use when finding ESG rankings for companies. This might be the most effective way for investors or other parties to learn which firm is the greatest for sustainable investing. 2025 by Palak Rathi, Ankit Nyati, Rushina Singhi and Anubha Srivastava. -
IoT networks: Integrated learning for privacy-preserving machine learning
Financial fraud is a persistent problem for consumers and financial institutions worldwide. It loses billions of dollars annually. Consequently, a strong fraud detection system (FDS) is essential to minimizing damage to financial institutions as well as clients. One common technique for spotting fraud is to use machine learning algorithms, which analyze large volumes of data to help with pattern detection and future prediction. It is difficult for a centralized FDS to detect fraud trends when these problems are coupled. To train a fraud detection model, this work presents a framework for federated learning, a machine-learning environment in which several entities collaborate to solve a machine-learning problem under the guidance of a central server or service provider. Also, the chapter examines how combined learning can be used to protect privacy in machine learning in Internet of Things systems. It focuses on four main calculations: federated averaging (FedAvg), secure aggregation, holomorphic encryption-based federated learning, and differential privacy in combined learning. Extensive experiments were carried out to evaluate these computations in terms of proving accuracy, conserving protection, and computing efficiency. The findings are shown in the results, with FedAvg achieving the highest accuracy of 92.5% and secure conglomeration demonstrating competitive precision levels of 91.8%. Calculations for differential privacy and holomorphic encryption demonstrated strong security conservation with very little data leakage and security parameters of 2.5 and 1.0, respectively. With little communication overhead and the ability to alter accuracy and conserve protection, secure aggregation emerged as a potential configuration. The computational productivity assessments revealed that secure accumulation produced little communication overhead despite its strong security conservation, which makes it suitable for IoT scenarios with limited resources. By using this tactic, financial institutions may avoid sharing datasets and benefit from a shared model that has seen more fraud than any one bank has on its own. Thus, the sensitive data of the user is protected. The results of the chapter indicate that the federated model (federated averaging) may be as good as or better than the central model (multi-layer perceptron) in detecting financial fraud. This chapter adds to the growing conversation around mixed learning in the Internet of Things by providing insights into the trade-offs between accuracy, security, and efficacy and by laying the groundwork for future developments in privacy-preserving machine learning standards. 2025 selection and editorial matter, Ahmed A. Elngar, Diego Oliva and Valentina E. Balas. All rights reserved. -
Role of ICT in harnessing poverty reduction: An empirical study using an ARDL approach
The catalytic role of Information and Communication Technology (ICT) in poverty reduction has been examined in this chapter, in line with the United Nation's first Sustainable Development Goal (SDG-1). This study focuses on the impact of ICT variables such as individuals using the internet, population covered by a mobile-cellular network, mobile-cellular telephone subscriptions, and international bandwidth usage, on poverty alleviation using relevant data covering countries worldwide from 2010 to 2022. Employing the Auto Regressive Distributed Lag (ARDL) method, the study examines both short-run dynamics and long-run effects of ICT interventions towards achieving SDG-1. Results reveal a stronger relationship between internet usage and poverty reduction, alongside a counterintuitive finding showing a negative coefficient for international bandwidth usage. The findings of the study emphasize the pivotal role of internet usage and international bandwidth usage in poverty mitigation. Further, as evidenced by data findings, any immediate changes in the ICT indicators such as international bandwidth usage, population covered by a mobile network, mobile telephone subscriptions may not affect the poverty levels in the short term. The results of the study posit the policymakers to acknowledge the impact of internet usage in alleviating poverty among the world countries. The study reckons that improvement of internet infrastructure and enhancement of digital literacy initiatives via increased internet usage has the potential to harness poverty reduction. 2025 A. Jose Anand and Saravanan Krishnan. All rights reserved.