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One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.

Rather than organize as traditional firms, many of today’s companies organize as platforms that sit at the nexus of multiple exchange and production relationships. This chapter considers a most basic question of organization in platform contexts: the choice of boundaries. Herein, I investigate how classical economic theories of firm boundaries apply to platform-based organization and empirically study how executives made boundary choices in response to changing market and technical challenges in the early mobile computing industry (the predecessor to today’s smartphones). Rather than a strict or unavoidable tradeoff between “openness-versus-control,” most successful platform owners chose their boundaries in a way to simultaneously open-up to outside developers while maintaining coordination across the entire system.

Purpose: Cryptocurrency technology has improved fast in the social economy and growth. Because cryptocurrency has many good qualities, it is initially employed for Bitcoin transactions.

Methodology: With the advent of Bitcoin, the link between distributed ledger technology (DLT) and the banking market has become stronger and more integrated. As more banking institutions understood the relevance of DLT, they began experimenting with using it in financial activities, such as R3CEV, Hyperledger, and Qiwi.

Findings: Many commercial organisations are beginning to experiment with DLT to reduce transactional costs and boost operational effectiveness, particularly in financial notes, cross-border payments, and asset-backed financing.

Practical Implications: DLT has many potential applications in banking domains in the upcoming years.

Surveillance studies scholars have embraced Foucault's panopticon as a central metaphor in their analysis of online monitoring technologies, despite several architectural incompatibilities between eighteenth and nineteenth century prisons and twenty-first century computer networks. I highlight a number of Internet features that highlight the limits of the electronic panopticon. I examine two trends that have been considerably underestimated by surveillance scholars: (1) the democratization of surveillance, where the distributed structure of the Internet and the availability of observation technologies has blurred the distinction between those who watch and those who are being watched, allowing individuals or marginalized groups to deploy sophisticated surveillance technologies against the state or large corporations; and (2) the resistance strategies that Internet users are adopting to curb the surveillance of their online activities, through blocking moves such as the use of cryptography, or masking moves that are designed to feed meaningless data to monitoring tools. I conclude that these two trends are neglected by a majority of surveillance scholars because of biases that make them dismiss the initiative displayed by ordinary users, assess positive and negative outcomes differently, and confuse what is possible and what is probable.