Evolving communication networks create expanding opportunities to measure real-time economic activity, such as social behavior or performance of production equipment. This chapter explores how to deploy instruments to measure, adjust, and analyze business activities, and how to commercialize the resulting data through internal or external channels. By contributing to a better understanding of the drivers of business performance, data can help improve and innovate new products and services, and potentially generate additional revenue streams.

When used adequately, technology-enabled measurement can help researchers and practitioners better assess various constructs and phenomena of interest and hence better understand, predict, and influence them in order to address social and behavioral issues. This article examines key issues and experiences in Singapore associated with digital transformation and data society, including challenges and opportunities in technology-enabled measurement that may be applicable as well in other cities and countries. Using Singapore’s digitization transformation journey to apply technology systematically and extensively to improve the lives of its people as an example, critical issues of contexts, changes, and collaborations in research, policy, and practice involving technology-enabled measurement of psychological constructs and processes are discussed.

Recognizing the pervasive influence of modern digital technologies, this chapter argues for the supremacy of strategy work in terms of giving shape and effect to the associated agenda for strategic, organizational and technological change. The chapter focuses on the theory and practice of action research as a Mode 2 approach to knowledge production as managers co-inquire into the practice of strategizing. The discussion speaks directly to the practice of action research in government organizations, of enhancing strategy work and its related outcomes, and the broader outcomes of co-inquiry. The chapter affirms the central role of action research in knowledge production and emphasizes how the practice of action research is itself being transformed by enabling digital technologies during the current COVID-19 pandemic. The contention throughout is that good practice informs research and good research informs practice.

“Patient support” is a concept far broader than the traditional offer of a phone number for a counselor and handing her a pamphlet. It encompasses optimal clinical management, as well as an organizational structure for the whole service to optimize patient experience. We first summarize supporting women over 40 during the COVID pandemic, followed by providing key steps of an individualized clinical management strategy, and the requirements of patient support structures. However, unlike previous publications, this chapter does not end by simply outlining what is desirable. It proceeds to a number of practical steps that fertility services can follow, using the framework of “patient experience architecture” to build suitable structured pathways. Furthermore, it explores the path of digital transformation in an effort to reduce cost and improve consistency delivering core professional values in every interaction. At the end of the chapter there is a short list of useful reading.

One essential activity that organisations must review as they capitalise on digital technologies' potential is their existing business processes. Put simply, they must examine 'how things are done around here' and, in doing so, identify if there is any way of improving these activities. In this chapter, I seek to offer an account of delivering a module on 'Innovation, Creativity and Critical Thinking' to final year students of a BA Honours Degree in Insurance Practice. This programme, which commenced in 2016,is Ireland's first apprenticeship towards awarding a level 8 honours degree. The three-year, work-based training programme combines digital academic learning with on-the-job learning, allowing students to acquire various skills. This chapter will demonstrate how students can practically apply techniques learnt in their online class to industry, bridging the theory-practice gap by adopting a learning-by-doing approach to business process re-engineering (BPR).

Digital transformation in higher education institutions is a point of no return. Both students and faculty members must embrace the change and understand their roles in the process of innovation in learning and teaching. The Covid-19 pandemic has been a recent catalyst of this academic process, but digital innovation is not a recent phenomenon in this area. Many institutions in recent years have been investing and learning how to offer the right content to their students. In this chapter, we discuss some of the aspects learned, based on the authors’ experience and the findings of qualitative research conducted with eight higher education institutions that have different levels of digital proficiency and maturity, and all devoted to building digital capabilities. The findings revealed what we call the “success factors” that may help other institutions in their journey to digital transformation.

This chapter explores the digitalisation of higher education in the era of the Fourth Industrial Revolution (4IR), where technology is used to support teaching and learning. This conceptual chapter contends that technology uptake and use by institutions of higher learning has been inevitable in the recent past due to a number of factors, with the latest being the COVID-19 global pandemic. Central to the argument of the chapter is the fact that technology is pertinent for the transformation of teaching and learning. However, in some developing countries, especially those of Africa, digitalisation, noble as it is, has resulted in undesirable consequences. Many citizens of the developing countries have been affected by the dark side of technology uptake, which has brought with it social exclusion and digital divide. As much as they need technology for teaching and learning, findings are that factors such as lack of access to internet, shortage of equipment and lack of skills, among others, have proved to be barriers to effective online teaching and learning. The chapter is guided by van Dijk’s Resources and Appropriation Theory.

This chapter aims to present the connection between the digital transformation of Higher Education Institutions (HEI) and personalization in relations to students throughout their life-cycle from prospectus to graduation. Personalized communication, the adoption of emerging technologies to support along with personalized learning, are the new focus in many HEI strategies. Digital technologies offer opportunities that facilitate blended, online, and mobile learning. Nonetheless, the implementation of real data-driven personalization is still at its initial stage, therefore relatively little attention is paid to the impact of personalization on the awarding of academic degrees, the value of diplomas and certificates. This chapter presents personalization at various stages of the student's life cycle, from the initial recruitment and on-boarding through the time of acquiring knowledge and qualifications to ideas related to lifelong learning and “student for life”. The opportunities and challenges that personalization creates for the certification process in higher education were also considered.

The past few years have seen a rapid global scramble of governments developing strategic plans for Artificial Intelligence (AI). We focus in this chapter on four of the largest global economies and what their AI plans mean for higher education. Since 2016, China, the EU, the US, and the UK have all published strategic plans for AI (Fa, 2017; Hall and Pesenti, 2017; USA Government, 2019; European Commission, 2020). These plans’ speed appears to indicate a matter of urgency and a sense of high governmental priority. This chapter discusses how these plans differ, what we might look out for and the likely developments ahead for higher education. Higher education is of central importance to meet the coming AI economy’s demands, and embracing AI is broadly considered a transformative existential requirement for many universities’ survival (Aoun, 2017). How governments and their higher learning institutions are planning this transformation is of the utmost importance to us all.

HEIs are nowadays subject to different disrupting events of a varying and transformative nature. Aside from the emergence of EdTechs, the COVID-19 pandemic has brought about the forced digitalization of most traditional higher education institutions (HEIs). In this context, a born-digital university is subject to the increasing dual pressure of traditional universities shifting their learning offers and competition from the new emerging EdTech players. This chapter provides an analysis of the competitive situation of HEIs and the envisaged business model changes required for a born-digital university to tackle this increasing competitive challenge in a context of ongoing digital transformation. It adopts a business approach for higher education, placing the student (as the main client) at the centre of the analysis. The starting point is the identification of the dimensions of student preferences in their choice of higher education provider with a view to analysing the position of the main types of competitors in higher education -traditional, face-to-face universities, and EdTechs- and to ultimately propose a matrix of required business model changes for a born-digital university.

Today, during the fourth industrial revolution, law firms are navigating in a somewhat changing landscape. Traditional legal practice and the ways of doing business in providing legal services is under pressure to change. The pressure comes from other law firms and increasingly self-sufficient in-house counsels who are gradually handling more and more legal matters internally. Companies and their in-house counsels are demanding more specialized services and alternative pricing structures other than the traditional practice of billing by the hour. This demand is one consequence of the fourth industrialization that includes the evolution of various forms of digitization, automation, machine learning, AI, and other technologies. As any other business, law firms are not exempt from the effects of such technologies. If anything, law firms will experience significant disruptive effects on how they do business and the types of services they provide. This is mostly due to the impact of emerging technologies on changing business models, as well as the content of the demand and needs of clients, in ways that were unthinkable twenty years ago.