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Introduction: In recent years, fresh big data ideas and concepts have emerged to address the massive increase in data volumes in several commercial areas. Meanwhile, the phenomenal development of internet use and social media has not only added to the enormous volumes of data available but has also posed new hurdles to traditional data processing methods. For example, the insurance industry is known for being data-driven, as it generates massive volumes of accumulated material, both structured and unstructured, that typical data processing techniques can’t handle.

Purpose: In this study, the authors compare the benefits of big data technologies to the needs for insurance data processing and decision-making. There is also a case study evaluation concentrating on the primary use cases of big data in the insurance business.

Methodology: This chapter examines the essential big data technologies and tools from the insurance industry’s perspective. The study also included an analytical analysis that supported several gains made by insurance companies, such as more efficient processing of large, heterogeneous data sets or better decision-making support. In addition, the study examines in depth the top seven use cases of big data in insurance and justifying their use and adding value. Finally, it also reviewed contemporary big data technologies and tools, concentrating on their key concepts and recommended applications in the insurance business through examples.

Findings: The study has demonstrated the value of implementing big data technologies and tools, which enable the development of powerful new business models, allowing insurance to advance from ‘understand and protect’ to ‘predict and prevent’.

Introduction: China released an action plan in 2015 to foster the growth of big data, demonstrating that big data development has become an essential and inescapable choice for stabilising growth, advancing reform, adapting structures, helping people’s livelihoods, and supporting government modernisation. The rudimentary ecology of the big data sector, combined with a favourable policy climate, creates ideal conditions for developing big data in China. The use of big data, on the other hand, has steadily shifted from a theory to reality, thanks to the explosive increase of data resources and the rise of specialised big data firms. Globally, the insurance industry is undergoing a technological revolution. The internet, mobile networks, social networks, cloud computing, and big data are all examples of digital technologies that progressively influence daily business operations and will usher in a golden era for the insurance industry.

Purpose: This chapter aims to understand the use of big data in the insurance industry innovation and the challenges insurance companies face. This chapter will also offer insight into the big data strategies of insurance companies.

Methodology: This chapter attempts to study literature reviews related to big data and examines the use of big data in the insurance industry. Also, different techniques associated with collecting big data and an assortment of big data sources are analysed in the context of the developing insurance industry.

Findings: This chapter helps us understand how big data innovations are useful for the insurance industry. The present chapter helps us in understanding the challenges faced by insurance companies. This chapter will also offer insight into the big data strategies of insurance companies.

This research aims to explore the potential of big data technology for sustainable management and investigate its impact on tourism. Its goal is to obtain meaningful results related to sustainable tourism to understand better how big data technology plays a role in decision-making by looking at it through the lens of various studies.

A systematic review, which is a qualitative method, was used in this study. The analysis was conducted using secondary data from the Web of Science Core Collections databases.

Big data technology has many economic benefits for businesses, but it also has managerial benefits such as forecasting, decision-making and tracking human and machine behaviour. Furthermore, big data technology offers sustainability benefits such as resource efficiency, preventive quality systems, carbon reduction and environmentally friendly production.

Big data's capabilities enable businesses to make more informed business decisions, improve overall business performance and contribute to achieving various SDGs. Big data, which aids in developing smart and sustainable tourism in the tourism sector, assists tourism managers in making economically, socially and environmentally sound decisions.

This chapter introduces the concept of the Shared Mobility Services Agency for the planning and managing of collective transport services at urban and regional level.

Building on previous work which established the concept of the Flexible Transport Service (FTS) Agency as a single co-ordination centre for different flexible services, this chapter extends the concept to consolidate the role of the Agency as a Shared Mobility Centre, including the integration of different on-demand or New Mobility Services and the co-ordination of different key actors in a co-modal approach. Specific attention is given to the enabling information and communication technology (ICT) architecture and standards and to the actions needed for consolidating the Agency’s role.

Findings indicate the fundamental role of the Public Transport Authority (local or regional) to enable the implementation of the concept. Priorities include: recognizing the Agency as an added value service for the area; supporting possible interaction/synergy among different Dispatch Centres and/or with other paratransit services; and defining a specific set of indicators measuring the quality and quantitative of service that are different from those of the conventional transport service.

In a time when household and public expenditure are under pressure, coupled with rapid technology progress (especially enhanced connectivity) the shared mobility services Agency offers a co-ordinated solution to planning and managing collective transport services, including New Mobility Services (represented by recent solutions like Uber, Sidecar, Lyft and BlaBlaCar) which are not yet integrated with traditional transport services.

Introduction: With the proliferation and amalgamation of technology and the emergence of artificial intelligence and the internet of things, society is now facing a rapid explosion in big data. However, this explosion needs to be handled with care. Ethically managing big data is of great importance. If left unmanageable, it can create a bubble of data waste and not help society achieve human well-being, sustainable economic growth, and development.

Purpose: This chapter aims to understand different perspectives of big data. One philosophy of big data is defined by its volume and versatility, with an annual increase of 40% per annum. The other view represents its capability in dealing with multiple global issues fuelling innovation. This chapter will also offer insight into various ways to deal with societal problems, provide solutions to achieve economic growth, and aid vulnerable sections via sustainable development goals (SDGs).

Methodology: This chapter attempts to lay out a review of literature related to big data. It examines the implication that the big data pool potentially influences ideas and policies to achieve SDGs. Also, different techniques associated with collecting big data and an assortment of significant data sources are analysed in the context of achieving sustainable economic development and growth.

Findings: This chapter presents a list of challenges linked with big data analytics in governance and achievement of SDG. Different ways to deal with the challenges in using big data will also be addressed.

The improvement of the agri-food supply chain sustainability plays pivotal role in the planet’s survival and in overcoming of climate disasters. Digital technologies that support the collection of Big Data produced along the agri-food supply chain (SC) emerge as powerful tools to accelerate the ecological transition of the sector. Digital technologies can support the implementation of circular business models by sharing data across the SC, monitoring in real time the materials flow, automatizing some agricultural practices and improving the decision-making through the development of decision support systems. Despite the relevance of these arguments, there is a lack of shared frameworks and guidelines for the effective development of a “data-driven circular economy” in the agri-food SC. In this scenario, this chapter examines how scholars investigate data-oriented strategies to accelerate the ecological transition and the adoption of circular economy (CE) models in the agri-food sector (AFS). To this end, a systematic literature review (SLR) was performed. Twenty-nine papers were selected following a rigorous sampling process. Both bibliometric and descriptive results are provided in the first part of this chapter. According to the analytical framework developed, the selected papers were examined in light of the “reduce, reuse and recycle” (3R) paradigm. Moreover, an additional R was retrieved from the systematic review (i.e., redesign), broadening the analytical perspective. The results indicate that scholars have predominantly provided theoretical contributions concerning the role of digital technologies and big data for the agri-food circular transition from a macro-perspective. The findings are useful for policy-makers and managers, who can promote and implement the big data-oriented approach to facilitate the circular transition. Limitations and future research directions are also provided.

This chapter discusses some of the internationalisation (e.g. mergers and acquisitions, networks and strategic alliances) of household names into Africa – especially in the aftermath two simultaneous events – that is, the African Continental Free Trade Area and British exit from the European Union (Brexit) with or without a trade deal. This chapter also touches upon the need for inter-functional integration in driving forward Africa’s creative industries – notably the intersections between entrepreneurship and innovation within which business models in digital publishing and software development, as well as localisation of animation and games in Africa have been seen.

Introduction: With the accelerated process of building metropolitans, more and more people tend to live in cities. So, to deal with this, the need has arisen to make smart everything that we have around us even when we arrived at the term of the smart city. All of this produces data we call big data that is generated by citizens.

Aim: So, cloud computing is the main idea implementation which we can use ineffective from all of these services which we call smart. And taking into account all of this, in this literature review, we have used different techniques to extract the most relevant papers on our topic. Mainly, we focus on smart cities and their taxonomy of it such as smart homes, smart buildings, traffic monitoring, security and emergencies, and so on. For a smart city, we discussed different proposed system architectures which represent the real work of researchers.

Results: In this way, we mention services that are offered and have the base services cloud services. Also, the articles we used are extracted and analysed from the most powerful and relevant databases such as IEEE, ACM, Elsevier, Science Direct, and so on. In total, we take 88 papers, and from all of these papers we have extracted 53 with different methods. This Systematic Literature Review presents building and using smart cities inside of cloud computing services.

Conclusion: However, a different implementation idea to do better life for all of us is by converting our lifestyle into a new form of living. The only form of implementation is by digitalising and implementing everything around us which means making every service in one place, where you can have access from anywhere, anytime. So, the smart city is the future.

Originality/value: This systematic literature review contributes to everyone who expresses interest to implement and provides additional evidence for existing studies in smart city patterns which used cloud services. Researchers offer various implementation forms of different models and express the impact of cloud services, especially for placements, where there are more people populated. Also, this study identifies a major weakness in existing smart city implementation by using cloud services, which have identified the main obstacles now and it needs to reanalyse the form of implementation for more complex systems in the future.

Since 2007, the cloud computing term had been introduced to the information technology (IT) dictionary. The theme is attracting growing interest from both the IT world and the business players, who need to enhance information systems agility, reduced costs, or even less dependence on internal IT teams when they are judged too slow. However, the fact that cloud computing, as presented by providers, increases the agility, is unclear. Business Managers; IT professional, and academics are querying about relationship between cloud computing and IT agility. This chapter aims to answer two major concerns: Factors that influence cloud computing adoption in medium and large organizations, and the cloud computing role to improve the agility of information systems. This chapter argues that cloud computing impacts Information System (IS) performance by organizational capabilities (agility). One of the primary motivations of this chapter is the lack of fieldwork when considering how cloud computing improves the information systems’ agility.