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At the doorsteps of the fourth wave of the industrial revolution, it is compulsory to develop a new understanding regarding the future of human labor based on “Industry 4.0” for German manufacturers, and two American concepts: “The Industrial Internet” and “The Internet of Things.” How will the nature of human work be in the digital economy of the forthcoming future? The problem of unemployment and the composition of the labor market, in terms of professional skills, are yet to be waiting for answers. Scientific management is also transforming to answer the emerging requirements of this new era, as “Digital Taylorism” to re-organize work in a techno-centric manner. Accordingly, the aim of this chapter is to examine the nature and the possible opportunities and threats of the digital age and try to develop a digital Taylorism understanding to minimize the negative impacts of digitalism on both individual workers and society in a way that all parts including the manufacturers can fully take the benefit of potential advantages of this new era.

This study aims to explore human–machine interactions in the process of adopting artificial intelligence (AI) based on the principles of Taylorism and digital Taylorism to validate these principles in postmodern management.

The topic has been investigated by means of a case study based on the current experience of Carrozzeria Basile, a body shop born in Turin in 1970.

The Carrozzeria Basile’s approach is rooted in scientific management concepts, and its digital evolution is aimed at centring humans, investigating human–machine interactions and how to take advantage of both of these.

The research contributes to both Taylorism management and the literature on human–machine interactions. A unique case study represents a first step in comprehending the phenomenon but could also represent a limit for the study.

Practical implications refer to the scientific path to facilitate the implementation and adoption of emerging technologies in the organisational process, including employee engagement and continuous employee training.

The research focuses on human–machine interactions in the process of adopting AI in the automation process. Its novelty also relies on the comprehension of the needed path to facilitate these interactions and stimulate a collaborative and positive approach. The study fills the literature gap investigating the interactions between humans and machines beginning with their historical roots, from Taylorism to digital Taylorism, in relation to an empirical scenario.

Massive open online courses (MOOCs), a Taylorist attempt to automate instruction, help make course delivery more efficient, economical and better. As an implementation of Digital Taylorism Implementation (DTI), MOOCs enable individuals to obtain an occupation-oriented education, equipping them with knowledge and skills needed to stay employable. However, learning through online platforms can induce tremendous amounts of technology-related stress in learners such as complexity of platforms and fears of redundancy. Thus, the aim of this paper is to study how student perceptions of DTI and technostress (TS) influence their perceived employability (PE). The role of TS as a mediator between DTI and PE has also been studied.

Stratified sampling technique has been used to obtain data from 305 students from 6 universities. The effect of DTI and TS on PE, and the role of TS as a mediator, has been examined using the partial least squares (PLS) structural equation modelling approach with SMART PLS 4.0. software. Predictive relevance of the model has been studied using PLSPredict.

Results indicate that TS completely mediates the relationship between DTI and PE. The model has medium predictive relevance.

Learning outcomes from Digitally Taylored programs can be improved with certain reforms that bring the human touch to online learning.

This study extends Taylorism literature by linking DTI to PE of students via technostress as a mediator.

What happens when computer software is designed to replace the teacher and the human role is to service the relationship between the software and the learner? Specifically, this paper aims to consider whether or not emotional labour is performed in contexts mediated by technology in the private sector.

The research is a single site, the online tutoring centre, in a large global education company in Europe servicing learners based in companies elsewhere. It is a critical case study with strategic importance for understanding the effects of the transformations to the education work afforded by a work design based on digital Taylorism. Qualitative methods are used, including observation, analysis of tutor/student e‐mail exchanges over a ten‐month period and interviews with key personnel.

It was found that in spite of the drive for standardisation and consistency, online tutors engaged in considerable levels of emotional labour, individualised in its performance along a spectrum.

The work has value in that it extends into new sites the study of digital Taylorism. In finding emotional labour in this critical case, it suggests that emotional labour will be present in less extreme cases.

The article is a useful source of information for practitioners in online learning centres, as well as researchers in the area of recruitment and training of online tutors.

The article provides insights into effects of the recruitment of underqualified people in private learning centres.

The article provides insights into an area of work‐based learning that is under‐investigated to date – i.e. the recruitment and practices of tutors in private learning centres and the role of emotional labour.

The purpose of this paper is to explore parallels between scientific management and the new scientific management to gain insight into applications of machine learning and artificial intelligence (AI) to human resource management and employee assessment.

Analysis of Taylor’s work and its interpretation by scholars is contrasted with modern analysis of human resource analytics to demonstrate conceptual and methodological commonalities between the old and the new forms of scientific management.

The analysis demonstrates how the epistemology, ethos and cultural trajectory of scientific management has resulted in a mindset that has influenced the implementation and objectives of the new scientific management with respect to human resources analytics.

This paper offers an alternative to the view that machine learning and AI as applied to work and employees are beneficial and points out why important challenges have been overlooked and how they can be addressed.

Commonalties between Taylorism and the new scientific management have been overlooked so that attempts to gain an understanding of how machine learning is likely to influence work, employees and work organizations are incomplete. This paper provides a new perspective that can be used to address challenges associated with applications of machine learning to work design and employee rights.

The rise of new information and communication technologies forms the cornerstone for the future development of work. The term Industry 4.0 refers to the vision of a fourth industrial revolution that is based on a network of autonomous, self-controlling, self-configuring, knowledge-based, sensor-based and spatially distributed production resources. All in all, different forms of the application of the Industry 4.0 concept can be observed, ranging from autonomous logistic transport systems drawn upon the idea of swarm intelligence to smart knowledge management systems. This paper aims to develop a theoretical framework to analyze different applications of Industry 4.0 on an organizing continuum. The general research questions are: What forms of organizing digitalized work lead to the reproduction of routines, and what forms foster innovation within Industry 4.0? The authors thus analyze the consequences of different forms of organizing work on workers’ perceptions and the results of the working process.

This paper provides case studies for different stages of the organizing continuum in the context of Industry 4.0. The cases and a further analysis of all 295 funded projects are based on the Platform Industry 4.0 Map, which is part of the Industry 4.0 initiative of the German Federal Ministry of Economic Affairs and Energy and the German Federal Ministry of Education and Research. The consequences for people acting in such organizational and digitally supported structures are discussed.

A variety of applications of Industry 4.0 can be found. These applications mainly vary in the dimensions of the degree of formalization, the location of control authority, the location of knowledge and the degree of professionalization. At the right side of the organizing continuum, the digitalization organizes a work environment that supports highly qualified humans. They have broad leeway and a high degree of autonomy to design and create innovative forms of digitalization for tomorrow. At the left side of the organizing continuum, Industry 4.0 structures a work environment with narrow leeway, a low degree of autonomy and a top-down structure of control authority predetermined by digital applications. In this case, employees fill the gaps the machines cannot handle.

As the paper focuses on Industry 4.0 developments in Germany, the comparability with regard to other countries is limited. Moreover, the methodological approach is explorative, and broader quantitative verification is required. Specifically, future research could include quantitative methods to investigate the employees’ perspective on Industry 4.0. A comparison of Industry 4.0 applications in different countries would be another interesting option for further research.

This paper shows that applications of Industry 4.0 are currently at a very early stage of development and momentarily organize more routines than innovations. From a practical point of view, professional vocational and academic training will be a key factor for the successful implementation of digitalization in future. A joint venture of industry and educational institutions could be a suitable way to meet the growing demand for qualified employees from the middle to the right-hand of the organizing continuum in the context of Industry 4.0.

Industry 4.0 is designed by men, and therefore, humans are responsible for whether the future work situation will be perceived as supportive or as an alienated routine. Therefore, designers of Industry 4.0, as well as politicians and scientists, absolutely must take the underlying outcomes of digitalized work into account and must jointly find socially acceptable solutions.

This paper provides a promising avenue for future research on Industry 4.0 by analyzing the underlying organizational structures of digital systems and their consequences for employees. Moreover, the paper shows how Industry 4.0 should be organized to simply reproduce routines or to support innovation.

The term “crowdwork” describes a new form of digital work that is organized and regulated by internet-based platforms. This chapter examines how crowdwork platforms ensure their virtual workforce’s commitment and control its performance despite its high mobility, anonymity, and dispersion. The findings are based on a case study analysis of 15 microtask and macrotask platforms, encompassing 32 interviews with representatives of crowdwork platforms, and crowdworkers, as well as an analysis of the platforms’ homepages and community spaces. The chapter shows that performance control on crowd platforms relies on a combination of direct control, reputation systems, and community building, which have until now been studied in isolation or entirely ignored. Moreover, the findings suggest that while all three elements can be found on both microtask and macrotask platforms, their functionality and purpose differ. Overall, the findings highlight that platforms are no neutral intermediaries but organizations that adopt an active role in structuring the digital labor process and in shaping working conditions. Their managerial structures are coded and objectified into seemingly neutral technological infrastructures, whereby the underlying power relations between capital and labor become obscured.