BMS Research Themes

Smart Industry: Business, Society and People in the 4th industrial revolution

SMart Industry

The fourth industrial revolution is in full swing. Its vision – well-known as "Industry 4.0" or "Smart Industry" – to decentralize production processes into autonomous but interconnected units along global value chains is about to become reality. The overall promise to raise customer satisfaction through individualized products, while at the same time increasing productivity and sustainability will change production and consumption radically. The social and economic implications of Smart Industry go far beyond ‘simple’ technical links which offers opportunities but raises also concerns:

Will we be having a production without humans and how will our society handle the risk of increasing job losses?

Will these new technologies change organizations and how can we create new, appropriate business models?

Will we exploit our natural resources when further increasing production and how can we systematically increase sustainability?

Tackling such questions about the implications of Smart Industry requires a deeper understanding of business and societal interrelations and joint multidisciplinary initiatives. Smart Industry is not only a technological but much more a societal challenge which requires high-tech with a human touch in a responsible and sustainable way. 

As part of a university that carries the motto ‘High Tech, Human Touch’, the Faculty of Behavioural, Management and Social sciences (BMS) of the University of Twente is uniquely positioned to engage in research on the origins, developments and consequences of this transformation of the economy and society. The Faculty consists of various departments that focus on business processes, human resources, information systems, communication sciences, policy studies, sociology, economics and the philosophy of science. Through the combination of these sub-disciplines and its connection to the engineering-oriented faculties of the University of Twente, the faculty of BMS can proactively anticipate and explore different possible scenarios (revolving around critical societal challenges), explain and predict (and teach about) the consequences of smart industry for systems of production, management, and governance. 

The BMS Smart Industry Working Group has developed a research roadmap focused on the implications of Smart Industry  to business, society and people. The full roadmap containing the systematic bibliographic research is available here. Below you can find a short summary of the roadmap.

Research Roadmap (in short)

Domain challenges

The fourth industrial revolution, also known as Smart Industry (the Netherlands), Industry 4.0 (Germany) and Advanced Manufacturing (United States), is in full swing. The vision of decentralized business processes consisting of autonomous yet interconnected units along global value chains is about to become reality. The use of cyber-physical production systems holds the potential of raising customer satisfaction through individualized products, while increasing productivity and resource efficiency. Currently, industry and research are working closely in field labs and smart factories to develop these cyber-physical production systems through digital applications, smart machinery, sensor technology, intelligent robots, and manufacturing concepts for globally interconnected value chains.

Along with the new digital technologies and the bright vision regarding their potential business and sustainability benefits outlined above, many concerns and worries also arise about their implications for individuals and society as a whole. Will we be having a production without humans and how will our society handle the risk of increasing job losses? Are large IT companies controlling our data? Will we deplete our natural resources even more as result of an increased and more efficient production? Will companies ever mange implement circular business models in a structural way? How do we avoid increasing the technology gap between the global north and the global south? These questions reveal that the 4th industrial revolution is not only a technological but also a societal challenge that requires a responsible “human touch” approach for understanding and controlling the driving forces behind the “high-tech”. Furthermore, since most I4.0 technologies are still in the phase of innovation triggers or have just reached the peak of inflated expectations, their societal and environmental benefits need not just to be declared but also to be proven in the years to come.

BMS Smart industry research roadmap model

All industrial revolutions started with the development of new technologies in support of production, which allowed for efficiency gains. Subsequently, firms had to adopt them, and adapt their business models, since they would not be able to withstand more efficient competitors. Gradually, society also had to change as result of the adoption of such new technologies on a large scale, and of the impact new business models had on economy at a macro level. This had important consequences for people, as they had to adjust to a new way of working, of being educated and of living, in order for them to be able to respond to the needs of a more modern economy and society. We observe the exact same pattern emerging now in the context of the 4th industrial revolution. Therefore, we followed this line of reasoning to structure our Smart Industry Roadmap Model (see figure below). Each of the focal areas is further divided into several sub-areas that reflect both the research interests of BMS researchers, and the information we collected on I4.0-related industry needs. Next each of the sub-areas is described.

BMS Smart Industry Research Roadmap Model












Smart Industry Technology

As mentioned before, the fourth industrial revolution is fuelled by many different technologies which have a multitude of applications in different areas of society, business, and people. For example, autonomous cyber-physical systems became possible due to advances in the sensor technology and to some extent in the advances in robotics, in order to link the digital to the physical world. For instance, a variety of new transportation devices are available, from small automated guided vehicles in a factory to unmanned cargo aircraft or even robots – unmanned robot-driven cargo vessels. The following are examples of technologies which are driving the fourth industrial revolution (not a complete list):

  • Cyber-physical systems: mainly based on advances in sensor technology, the connection between the physical world and the digital world becomes possible, as physical signals are transformed into data.
  • Digital twinsDevices can have a “digital twin”, which is a technology allowing to represent the physical object as a digital replica of itself. The digital twin will reproduce all key properties, real-time state, components of the physical object. The digital twin can be used, for instance, to run simulations and to analyse the interactions between different systems involved in a process. A digital twin may also incorporate some form of artificial intelligence and ability to learn and make improvement recommendations based on context/sensor data.
  • Blockchain technology: relies on distributed ledger technology, which essentially means that many nodes or even the entire network stores all relevant data, ensuring maximum transparency. A key relevant feature of a blockchain is that many servers along one chain redundantly store all data. Data security and nonrepudiation is increased, because all chain members are able to verify the activities of their peers.
  • 3D printing: with additive layer manufacturing physical objects are designed and produced in a decentral fashion by transferring the digital plans to a 3D printing unit which then creates the physical object.
  • Artificial intelligence and machine learning are actually not new. They have been around for more than four decades. However only now, due to the availability of huge volumes of data it is becoming increasingly critical to develop techniques that can cope with such volumes while is extracting knowledge from data in (quasi) real time and using it to improve the execution and planning of future and in progress business processes. Furthermore, machine learning is increasingly used to improve the abilities of robots and software agents to take decisions and to interact with/learn from humans.
Business: From Integrated supply chains to global supply markets

Smart industry will have a great impact on the types of business models organizations will employ. Many of these changes will be reflected in the way they create value, the type of value they offer to their customers, and the way they interact with other organizations. We consider the following aspects as important business developments relating to Smart industry:

  • Global marketplaces: moving from the traditional supply chains to flexibly configured marketplaces which are more suited to serve a new generation of customers, but also to enable stronger and agile collaborations between organizations. New types of marketplaces can emerge which are centred around a sharing platform / economy in which transactions are done via online marketplaces rather than peer-to-peer.
  • (Mass) customization: this represents the next evolutionary step in the way organizations offer their products to customers. While personalized offerings with some level of customization have become a standard for many industries, with the help of flexible computer-aided and additive manufacturing systems, organizations are able to combine the low cost of mass production with the intricacies of individual customization.
  • Decentralised co-creation networks: refers to a new paradigm in which groups of organizations are no longer organizing themselves with the help of a central entity or control tower, but rather they take part in ecosystems in which functions and responsibilities are distributed. As a result, organizations and cyber-physical systems operating in such ecosystems are expected to function and interact autonomously, while still retaining the same level of coordination, which in some cases manifests itself as emergent behaviour. Additionally, I4.0 facilitates organizations to seamlessly integrate with each other in order to co-create highly customized offerings. It is expected that I4.0 may also lead to completely new business models driven by technological innovations.
  • Life-cycle solutionsorganizations are moving from offering a product to their customers to offering a series of services and solutions to address a specific customer problem/need. This entails that a customer will no longer purchase or own a product, but rather they would pay for the service of using it. For providers of such solutions/services, this means that they need to maintain and update them throughout their whole lifecycle in order to ensure that they remains relevant for their customers.
Society: Impact of Smart Industry on sustainability, policy and regulation, education, and social inclusion

Similarly to business, we expect that Smart industry will also have a great impact on multiple aspects of society ranging from the way organizations and individuals behave in relation to waste, to the education of a future generation of workers, to considering societal needs when developing new technology, and in general, to new policies and regulations. We consider the following aspects as important societal developments relating to Smart industry:

  • Sustainable economy: the production, distribution, trade and consumption of goods in a manner which promotes reduction of waste and efficient use of resources. Organizations can make use of sustainability-driven management systems and big data analytics in order to ensure the achievement of such efficiency objectives and industrial symbiosis, and the development of a circular economy.
  • Policy and regulation: one common aspect for all the Smart industry technologies is that they deal with large amounts of data of organizations and individuals which need to be shared and handled in a responsible, and secure way. Therefore, new policies and regulations need to be developed, together with standardization in areas, such as sustainable production and consumption, and interoperability of systems and organizations within the global value chain.
  • Education 4.0: with the introduction of new technologies, processes and practices, the workforce of the future needs to be educated within a fundamentally new type of education system adequately tailored to I4.0 needs, and focusing on shaping professionals  that master 21st century skills.
  • Social inclusion and ethics: observes and discusses risks of excluding (large) groups of people from the gains of the socio-technical transformation. At the same time, it explores the ways to steer this technological transformation in an inclusive way, which helps to anticipate the risks, and challenges, already at an early stage of the technological development.  
People: The future of learning and work

As it can already be seen from the previous two focal areas (business and society), the role of people as workers and consumers will be heavily impacted by I4.0. Therefore, changes are expected in the way workers are trained, organized, managed and in their interactions with new technology. We consider the following as important I4.0-related workforce developments:

  • Continuous learning and employability: refers to the voluntary and ongoing pursuit of knowledge with the purpose of self-development for personal or professional reasons. It raises the question of how workers are trained in order to prepare them for jobs in Smart industry (on-the-job training vs formal education).
  • Self-management and crowd-working: an organizational structure which reduces/removes the need for direct supervision due to the formation of teams which are empowered and able to work autonomously. At the same time, independent individuals may feel the need or prefer to offer their services on digital platforms in the gig economy.
  • Management of T-shaped talent: the type of human capital needed by organizations in an era of Smart industry is predictably different than before. The nature of work often requires workers to have a different set of skills, acting as T-shaped professionals, who have boundary-crossing competences next to a deeper functional understanding.
  • Technology-enhanced work: one of the distinctive aspects of Smart industry is the way workers are expected to interact with machines. Workers are expected to be enhanced by technology to perform tasks (enabled workers), while others interpret and organize the information provided by technology for decision-making and problem-solving purposes (knowledge engineers).

Maturity of the three focal areas and cross-cutting research

In this section, we provide an assessment of the research maturity of the different areas in the Smart Industry Research Model (see table below). For this purpose, we use a simple maturity model, with the following levels:

  • Maturity 0: No Industry 4.0 specific research on the topic
  • Maturity 1: Investigation and Conceptualisation
  • Maturity 2: Validation and application
  • Maturity 3: Knowledge transfer and valorisation

This is also the final result of this roadmap document. Not only it brings into one picture the Smart Industry Research Model areas and the Smart Industry cross cutting issues, but it also assesses and compares the maturity levels of Smart Industry research from two perspectives (resulting from our investigations so far): the perspective of extant literature (also described in the Roadmap document) and that of BMS research. 

What we can observe is that the research related to the business aspects of the Smart Industry Research Model is relatively mature, with two of the topics (Global marketplaces, and Life-cycle solutions) being at the point of entering the knowledge transfer to industry and valorisation stage. Similarly, in terms of research relating to society, the topic of sustainable economy is also entering the valorisation stage, while the topic of Education seems to not be covered by research, in relation to Smart industry. Unlike the other two focal areas of the Smart Industry Research Model , in the case of “People” (based on English language publications), there is little research in relation to Smart Industry. This is why all People-topics have a maturity of 0 or slightly above 0.

The arrows with a dashed line border represent the maturity of BMS research, which has been assessed based on the results of queries for each topic in the three layers, combined with the large query containing the names of the BMS research staff. The number of documents which have resulted from this search are mapped onto the aforementioned maturity levels, as follows: Maturity 0: Up to 50 documents; Maturity 1: Up to 250 documents; Maturity 2: Up to 500 documents; Maturity 3: More than 500 documents.