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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.

Today humanity is facing a time period, in which the speed and rate of change in different fields are faced. The rapid and effective change in the technological, economic, military, social and cultural fields all over the world in recent years has had important results in many topics such as informatics, interactive communication, production, data production and sharing and forms of consumption and perception. Changes and developments at very high speeds and rates affect the personal life, social life and work life in a deep manner, especially after the 1980s, paving the way for many concepts such as globalization, Industry 4.0, digitalization, new economy, new world order and digital transformation age to be the leading variables in every field of social sciences.

Production, consumption and communication forms at the global level are becoming more and more in depth and predicting the future is becoming more and more difficult and valuable. Understanding, analyzing and predicting the future for national and international companies and organizations directly and indirectly affect all economic, military and political variables. At this point, competition stands out as one of the most critical concepts for survival and growth for profit-oriented companies.

Based on this, the topics and contents selected in this study were created to cover the field of management and strategy. Indeed, in this study, the concept of organizational agility is explored theoretically from a historical perspective on the concept of Industry 4.0 and especially emphasized the dimensions and components of agility used in today’s world.

Within the scope of this study, the aim is to define and present the general framework of the Industry 4.0 and agile firms, which aim to combine the conceptual and theoretical infrastructure with the implementation of the agile firms within the field. In this respect, the study defines the situation coming from the past together with the world of today in the relationship of the technological and economical dimensions of globalization with the digitalization and latest theoretical view for the agile firm’s structure and management. On the other hand; in this study, the possible effects of the recent COVID-19 pandemic crisis on the management of organizations are interpreted in the context of Industry 4.0 and agile companies. This aim will provide a foresight for the future periods, with the conclusions added with the theory of senism, which present the dominant value of the study.

The digital transformation calls for new thinking about sociotechnical systems design (STSD) because it has enabled new kinds of work systems to proliferate. We identify a new class of sociotechnical system, called the Platform-STS (P-STS), which complements the existing Industrial- and Knowledge-STSs. The P-STS has distinctive characteristics compared to the other classes because it reaches directly into ecosystems and is, therefore, “distributed,” and because it is governed through market mechanisms rather than hierarchy or clan mechanisms. We introduce a new design principle, redundancy of connectivity, to ground design thinking about the P-STS. We demonstrate why fundamental STSD principles need to be reconfigured, suggest how they might do so, and conclude that socioecological designs and interventions may need to supplant sociotechnical ones.

This chapter develops a framework for classifying approaches to conceptualizing and measuring implementation of innovations. It first develops a typology that distinguishes rollout, modification, programmatic and transformation conceptualizations of implementation. The implications of each conceptualization for measurement of implementation are discussed. Following this a classification scheme for implementation measures is presented that distinguishes measures on the basis of their: (a) criterion for success of the implementation; (b) innovation unit; (c) source of data; (d) measurement scale; and (e) level of analysis. Issues related to various measurement choices are discussed along with recommendations for future research and development in the measurement of implementation.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.