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Purpose: The purpose of the chapter is to highlight the game-changing potential of emerging technologies and how these will change the very face of companies cutting across industries. Our work also aims to highlight the converging point of these technologies and describes how these new-age inventions can be more effective if stakeholders adopt a collaborative approach rather than competing against each other.

Design/Methodology/Approach: Using real-world case studies, the chapter identifies the most significant emerging technologies heralding a new era of efficiency across business categories. This identification has been made based on both secondary data and expert interviews. The opinions of the domain and industry experts have also been included to select six emerging technologies for the analysis.

Findings: Based on secondary and primary data, the chapter has identified the five emerging technologies that are expected to change how businesses are run completely today. The technologies are: (1) Metaverse Platforms, (2) Blockchain Technology, (3) Non-fungible Tokens (NFTs), (4) Decentralised Finance, and (5) Cryptocurrency.

Research Limitations/Implications: By identifying emerging technologies and their application domains, the chapter contributes significantly to both the world of academia and practice. The research has important implications for scholars and practitioners as these stakeholders must prepare themselves to realise the maximum potential of these new-age inventions. Policymakers also need to contribute constructively so that the adoption and implementation of these technologies can be done smoothly and seamlessly.

Originality/Value: The research is unique in the sense that it identifies the most-significant emerging technologies and offers a constructive roadmap for stakeholders to integrate these new inventions into their functional procedures and operational mechanisms effectively and efficiently.

Micro-moments are rationale-rich moments while selections are made, and alternatives fashioned. Such records and trends can provide insights as to what topics and types of content material the customers are looking for. The main agenda to choose this topic is that it is something very minute, yet highly profitable to a firm if done right. This chapter mainly aims to focus on quantitative analysis with the collection of data that revolves around questions which represent consumer behavior and some parts of consumer psychology as well. Google has devised four major moments with regard to online purchase behavior as just browsing, shopping, reviews to positive word of mouth which when measured in the right manner can generate the database of the most profitable target consumer group for a particular organization. This being the major agenda of the research, it will help marketers and the R&D team of any organization to formulate and advertise the right products on the right platform. The objective of this study is to connect consumer behavior and micro-moments for the benefit of marketers. The managerial implications of this study are to reduce the advertising costs by tapping into the right target customers and find a suitable online platform to advertise by understanding the micro-moments of the consumers with the help of some questions via the form of a questionnaire and finally to prove that the relation between measuring these moments of consumers are profitable to determine the purchaser’s mindset hence to achieve profitable conversions.

The emergence of strengths-based management may be the management innovation of our time. Nearly every organization has been introduced to its precepts – for example, the insight that a person or organization will excel only by amplifying strengths, never by simply fixing weaknesses. But in spite of impressive returns, organizations and managers have almost all stopped short of the breakthroughs that are possible. With micro tools largely in place, the future of strengths management is moving increasingly to the macro-management level, as witnessed in the rapid and far-reaching use of large group methods such as the Appreciative Inquiry Summit and its next generation design-thinking summit. Macro means whole and, by definition, unites many improbable opposites – for example, it embraces top down and bottom up simultaneously. It is a prime time source of organizational generativity. But the rules of macro-management are different than any other kind, most certainly micro-management. A decade of research and successful prototyping with single organizations, regions and cities, extended enterprises, industries, and UN-level world summits reveals five “X” factors – a specific set of mutually reinforcing elements of success and organizational generativity – and provides a clear set of guidelines for when and how you can deploy the “whole system in the room” design summit to bring out the best in system collaboration. By analyzing the performance and impacts of six case studies of the “whole system in the room” Appreciative Inquiry design summit, this chapter provides a bird’s eye view of the opportunities, challenges, and exciting new vistas opening up in this the collaborative age – a time when systemic action and macro-management skill are the primary leverage points for game-changing innovation, scalable solutions, and generative organizing. The chapter concludes with a call for more research into the stages of large group dynamics and advances a metaphor from the leadership literature – the spark, the flame, and the torch – to give imagery to the “positive contagion” and “the concentration effect of strengths” that happens during an Appreciative Inquiry Summit where 100s and sometimes 1000s come together interactively and collaboratively to design the future.

This chapter examines Unilever's transformation in sustainability and corporate social responsibility (CSR) over the past decade. It tracks the author's involvement with an internal team that studied Unilever's world “outside in” and “inside out” through the engagement of over 100 organizational leaders to awaken the company for change. The case reports how Unilever embraced a “vitality mission” to align its strategies and organization around sustainability and CSR and infuse social and environmental content into its corporate and product brands. Among the innovations described are certification of the sources of sustainable fish and tea, Dove's inner-beauty campaign, and several “bottom of the pyramid” efforts. Particular attention is given to the makeover of its high-growth Asian business. The transformation is examined as a “catalytic” approach to change and discussed with reference to theories of complex adaptive systems. This raises theoretical questions about the role of top-down versus more communal leadership, the importance of mission versus vision in guiding change, and the relevance of emotive and psycho-spiritual versus more programmatic interventions in the rearchitecture of an organization as it progresses on sustainability and CSR.

Social media platforms, along with networked devices and applications, enable their user base to produce, access and circulate large volumes of data. On the one hand, this development contains an empowering potential for users, who can make otherwise obscured aspects of social life visible, and coordinate social action in accordance. Yet the preceding activities in turn render these users visible to governments as well as the multinational companies that operate these services. Between these two visions lie more nuanced accounts of individuals coordinating via social data for reactionary purposes, as well as policing and intelligence agencies struggling with the affordances of big data.

This chapter considers how individual users as well as police agencies respectively actualise the supposedly revolutionary and repressive potentials associated with big data. It briefly considers the broader social context in which ‘big data’ is situated, which includes the hardware, software, individuals and cultural values that render big data meaningful and useful. Then, in contrast to polarising visions of the social impact of big data, it considers two sets of practices that speak to a more ambivalent potentiality. First, recent examples suggest a kind of crowd-sourced vigilantism, where individuals rely on ubiquitous data and devices in order to reproduce law and order politics. Second, police agencies in various branches of European governments report a sense of obligation to turn to social data as a source of intelligence and evidence, yet attempts to do so are complicated by both practical and procedural challenges. A combination of case studies and in-depth interviews offers a grounded understanding of big data in practice, in contrast to commonly held visions of these technologies.

First, big data is only ever meaningful in use. While they may be contained in databases in remote locations, big data do not exist in a social vacuum. Their impact cannot be fully understood in the context of newly assembled configurations or ‘game-changing’ discourses. Instead, they are only knowable in the context of existing practices. These practices can initially be the sole remit of public discourse shaped by journalists, tech-evangelists and even academics. Yet embodied individual and institutional practices also emerge, and this may contradict or at least complicate discursive assertions. Secondly, the range of devices and practices that make up big data are engaged in a bilateral relation with these practices. They may be a platform to further reproduce relations of information exchange and power relations. Yet they may also reconfigure these relations.

This research is limited to a sample of respondents based in the European Union, and based at a particular stage of big data and social media monitoring uptake. Subsequent research should look at how this uptake is occurring elsewhere, along with the medium to long-term implications of big data monitoring. Finally, subsequent research should consider how citizens and other social actors are coping with these emerging practices.

This chapter considers practices associated with big data monitoring and draws from cross-national empirical data. It stands in contrast to overly optimistic as well as well as totalising accounts of the social costs and consequences of big data. For these reasons, this chapter will be of value to scholars in internet studies, as well as privacy advocates and policymakers who are responsive to big data developments.

Introduction: Big data is that disruptive force that affects businesses, industries, and the economy. In 2021, insurance analytics will include more than simply analysing statistics. According to current trends, new insurance big data analytics (BDA) methods will enable firms to do more with their data. The insurance business has traditionally been conservative, but adopting new technology is no longer only a current trend; it must be competitive. Big data technologies aid in processing a huge amount of data, improve workflow efficiency, and lower operating costs.

Purpose: Some of the most recent developments in big data for insurance and how insurers may use the information to stay ahead of their competitors are discussed in this chapter. This chapter’s prime purpose is to analyse how artificial intelligence (AI), blockchain, and mobile technology change the outlook and working of the insurance sector.

Methodology: To achieve our research purpose, we analyse case studies and literature that emphasise how BDA revolutionises the insurance market. For this purpose, various articles and studies on BDA in the insurance market will be selected and studied.

Findings: From the analysis, we find that the use of big data in the insurance business is growing. The development of BDA has proven to be a game-changing technology in insurance, with a slew of benefits. The insurance sector is now grappling with the risks and opportunities that modern technology presents. Big data offers opportunities that every company must avail of. We can safely argue that big data has transformed the insurance sector for the better. The BDA’s consequences have enabled insurers to target clients more accurately. This chapter highlights that new tools and technologies of big data in the insurance market are increasing. AI is emerging as a powerful technology that can alter the entire insurance value stream. The transmission of any type of digital proof for underwriting, including the use of digital health data, might be a blockchain use case (electronic health record (EHR)). As digital forensics becomes easier to include in underwriting, it must expect price and product design changes in the future. In the future, the internet of things (IoT) and AI will combine to automate insurance processes, causing our sector to transform dramatically. We highlight that these technologies transformed insurance practices and revolutionalised the insurance market.

The Appreciative Inquiry (AI) Summit methodology is a powerful organizational development tool for unleashing the generative capacity of human systems. When an AI Summit is executed seamlessly, the design and planning appears almost effortless. As we have learned, however, there are many nuances to this powerful tool and attention to detail is vital to delivering a successful Summit. This chapter offers a practical guide to designing and implementing an AI Summit in any organization. The chapter addresses many of the pragmatic issues that emerge when designing a summit and offers insight on how to best prepare an organization for what needs to happen during pre-summit preparations to ensure a strong focus on desired outcomes and advancing post-summit momentum.

This chapter critically examines how recent government papers and policies have informed and contextualised the new Higher Education and Research Bill (HERB) passed in April 2017. In particular, it concerns itself with the issue of ‘teaching excellence’, through what has been termed the Teaching Excellence Framework (TEF) that has emerged as a key plank of the current government’s policy for future funding of higher education (HE). It will consider the other spurs for reform in HERB, such as the desire to create a culture in HE where teaching has equal status with research, the need to ensure that universities provide better information about their courses and the experiences that they can offer students and the predictable governmental requirement for institutions to give value for money and to be clearly held accountable for any failure to provide a quality service to students. Lastly, there is also a strong emphasis on widening student participation across the sector and ‘levelling the playing field’ so that new providers can set up with the minimum of red tape. It is interesting to note how each of these additional areas for reform is clearly linked to TEF, which, this chapter will argue, will be the key vehicle used to drive them forward.

The purposes of this chapter are to propose definitions of innovation, product innovation, business model innovation, marketing innovation, innovation strategy, and strategic innovation, elaborate on their literature and conceptual underpinnings, and provide an overview of the conceptual domains of innovation, innovation strategy, and strategic innovation.

First, certain definitions of innovation, drawn from literature, are presented. Next, certain definitions that incorporate logically incremental refinements in them are presented. Building on these, definitions of innovation, product innovation, business model innovation, and marketing innovation are proposed.

Innovation is the creation of value by using relevant knowledge and resources for conversion of an idea into a new product, process, or practice, or improvements in an existing product, process, or practice. Innovation strategy is an organization’s relative emphasis on different types of innovations and the associated pattern of resource allocation, in alignment with its strategy at the corporate and business unit levels. Strategic innovation is the creation of value by using relevant knowledge and resources for conversion of an idea into a new product, process, or practice with the potential to have a major transformational effect on the evolution of markets and industries.

Over the past several decades, there has been a sustained and high level of interest in issues relating to innovation among academics in a number of disciplines, business and social entrepreneurs, business practitioners, and policy makers. Books, journal articles, and business magazine articles provide a number of definitions of innovation and specific types of innovation. Multiple definitions of a construct can be problematic in certain respects and beneficial in other respects. A potential upside of multiple definitions of innovation is the prospect of each being a source of ideas for one or more innovations that benefit society, and an impetus for research focusing on specific questions.

Implementation of an idea, value creation, and use of relevant knowledge and resources are used as constituent elements in the proposed definitions of innovation, product innovation, business model innovation, marketing innovation, and strategic innovation.