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1 – 10 of over 1000Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Naresh Kumar and Sandeep Lal
It is difficult to argue against the fact that research has focussed on artificial intelligence (AI) and robotisation over the past few decades. Additionally, during the past…
Abstract
It is difficult to argue against the fact that research has focussed on artificial intelligence (AI) and robotisation over the past few decades. Additionally, during the past several years, it has taken off and is now extensively used in numerous businesses across various industries. Most of the time, AI has been associated with some industrial sector process automation. Still, recently, the authors have noticed more positive technology uses, especially in the financial services industry. Due to several factors, the financial sector needs to adopt AI and recognise its potential. The industry has historically been concerned about unpredictability, legislation, stronger cybersecurity, technological limitations and disruption of established lucrative operations.
Never before has there been more discussion about AI due to the advantages it provides to businesses that are providing financial services. That may explain why this change is referred to as the fourth industrial revolution. Both positively and negatively, it is quite disruptive. The effectiveness, accuracy and cost-effectiveness of solutions greatly increase. However, immense power also entails great responsibility.
Precautions and security are more crucial than ever for businesses since the financial sector is changing significantly and quickly. The various benefits and drawbacks of this technology are yet unknown to humans. Although AI was first shown to us in the 1950s, it has recently gained new prominence as processing power, and the available quantity of data has increased dramatically.
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Central theme: The present chapter discusses the integration of data science methods in devising economic policies in different countries with special reference to India.Purpose:…
Abstract
Central theme: The present chapter discusses the integration of data science methods in devising economic policies in different countries with special reference to India.
Purpose: It explains how the policy-making process in countries can be transformed from estimate-based policies to evidence-based policies with the help of techniques such as artificial intelligence (AI), big data, and data analytics. It answers the research question of whether the data science techniques can make the economic policy process efficient or not in developing countries like India.
Research methodology: Data are collected from secondary sources such as government websites, journals, corporate reports, and research databases to conduct this descriptive analysis. Research papers from Scopus/Web of Science (WoS) database are extracted, and exclusion/inclusion criteria are applied for extracting papers relevant to this research.
Findings: The chapter found out various opportunities which India can tap by gaining new insights on critical macroeconomic issues such as unemployment, labour markets, and water crises and would be able to resolve the problems with the help of predictive modelling. The findings exhibit the possibility of building models that could explain how to integrate data science techniques into the policy-making process. It also highlights the challenges that Indian economy is facing in incorporating these techniques in its policy-making process. It states the need to design different evaluation schemes based on information and communication technology (ICT) and data science for different policies, since one methodology does not suit all.
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Seden Doğan and İlayda Zeynep Niyet
Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for…
Abstract
Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.
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Anastasija Nikiforova, Miguel Angel Alor Flores and Miltiadis D. Lytras
Open data are characterized by a number of economic, environmental, technological, innovative, and social benefits. They are seen as a significant contributor to the city’s…
Abstract
Open data are characterized by a number of economic, environmental, technological, innovative, and social benefits. They are seen as a significant contributor to the city’s transformation into smart city. This is all the more so when the society is on the border of Society 5.0, that is, shift from the information society to a super smart society or society of imagination takes place. However, the question constantly asked by open data experts is, what are the key factors to be met and satisfied in order to achieve promised benefits? The current trend of openness suggests that the principle of openness should be followed not only by data but also research, education, software, standard, hardware, etc., it should become a philosophy to be followed at different levels, in different domains. This should ensure greater transparency, eliminating inequalities, promoting, and achieving sustainable development goals (SDGs). Therefore, many agendas (sustainable development strategies, action plans) now have openness as a prerequisite. This chapter deals with concepts of open (government) data and Society 5.0 pointing to their common objectives, providing some success stories of open data use in smart cities or transformation of cities toward smart cities, mapping them to the features of the Society 5.0. We believe that this trend develops a new form of society, which we refer to as “open data-driven society.” It forms a bridge from Society 4.0 to Society 5.0. This chapter attempts to identify the role of openness in promoting human-centric smart society, smart city, and smart living.
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Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Premkumar Chithaluru and Ankita Tiwari
This research focuses on the challenges of establishing a better medical system that can detect and diagnose diseases earlier. Using such cutting-edge health systems, healthcare…
Abstract
This research focuses on the challenges of establishing a better medical system that can detect and diagnose diseases earlier. Using such cutting-edge health systems, healthcare practitioners may quickly and effectively manage patients’ medical issues by providing the appropriate data at the right time about the right people. The advancement of technology has increased the usefulness of devices that routinely analyse health measurements or monitoring time-sensitive health-related data. Medical professionals and patients alike are downloading health-related mobile apps to better track and manage their health. The research evidences how Internet of Things (IoT) technology may be used to support health care.
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N. Padmaja, Rajalakshmi Subramaniam and Sanjay Mohapatra
This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.
Abstract
Purpose
This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.
Design/Methodology/Approach
The author adopts a grounded theory and conceptual approach to endeavour in this exploratory research.
Findings
The outcome shows a significant rise of big data in the tourism sector under three major dimensions, i.e. business, governance and research. And, some exemplary evidence of institutions promoting the use of big data and data science for sustainable tourism has been discussed.
Originality/Value
The conceptualised interlinkage of concepts like IR 4.0, big data, data science and sustainable development provides a valuable knowledge resource to policy-makers, researchers, businesses and students.
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