Industry 4.0 as a ‘sudden change': the relevance of long waves of economic development for the regional level

ABSTRACT

While the rapid proliferation of the Industry 4.0 concept suggests that it brings about major economic change, the concept lacks a socio-economic foundation of change. In this context, the paper raises three questions: First, how sudden does the change brought about by Industry 4.0 occur, and, second, does it make a difference if it is conceived as sudden or not? Using a model of long waves of economic development and the concept of general purpose-technologies it is argued that much of the change brought about by Industry 4.0 is not of a sudden nature but largely represents the roll-out of the prevailing techno-economic paradigm, and that digitalization and artificial intelligence have the potential to trigger of a next long wave. The third question asks for possible implications of the long-wave perspective for adapting to an upcoming paradigm at the regional level. A major conclusion is that policy measures ought to reach beyond traditional innovation and technology-related policies and be implemented in the appropriate phase of a long wave.

KEYWORDS:

• Industry 4.0
• Long waves of economic development
• General purpose-technology
• Artificial Intelligence

1. Introduction

It took only 5 years that the number of hits in Google Scholar that contains the expression ‘Industry 4.0’ (or its German version ‘Industrie 4.0’) in the title of scholarly publications increased from zero to more than 1000 per year. Given the quick proliferation of this expression, it is fair to say that the concept of Industry 4.0 has rather ‘suddenly’ received a prominent place in academia (industry, consultants and politics are fascinated by the concept anyway). Proponents of the concept argue that mankind is at the beginning of a fourth industrial revolution which will bring about fundamental changes to the way how business and production will be done and how our lives will be organized. While it has been made clear that it would take Industry 4.0 some time to revolutionize the economy as a whole, the change it brings about – at least in manufacturing – would be unavoidable and disruptive in nature.

Within this context, this essay tries to answer the following questions:

• First, how ‘sudden’ has the concept Industry 4.0 emerged, how ‘sudden’ is the actual and possible change experienced that it is likely to bring about, and could the perception of ‘suddenness’ of change vary across regions?

• Second, does it make a difference for economic policy if Industry 4.0 is conceived as bringing about a ‘sudden’ change or not?

• Third, what are regional and policy implications of interpreting Industry 4.0 in a long wave model?

These questions will be discussed in a model of long waves of economic development that does not consider technological change as exogenous influence but analyses it in a wider socio-economic context. This distinguishes our approach from the literature on Industry 4.0, that originates from a policy paper about sustaining the competitiveness of the German manufacturing sector with a strong focus on technology and its ramifications with the business sector (Kagermann, Wahlster, and Helbig 2013). Propagators of Industry 4.0 tell a story of successive industrial revolutions¹ in which each revolution stands for itself, and it is claimed that now the time has come for another such revolution. As there is not much of a socio-economic foundation of ‘industrial revolutions’ provided in this story it represents what we call the ‘stand-alone’ perspective of the Industry 4.0 concept.

In contrast to this perspective, we interpret the change that Industry 4.0 brings about in the Perez (2002) model of long waves of economic development. Thereby it is possible to endogenize important aspects of the technological change that is fueled by Industry 4.0, and to analyse the timing of the concept’s emergence, changes that it is likely to bring about, and consequently the ‘suddenness’ of change and the perception of the suddenness of that change. It is argued that while there actually ‘is’ some sudden change and some changes may be ‘perceived’ as sudden, most of the change that is involved with Industry 4.0 can be identified as ‘not-so-sudden’ in nature but as regular phenomena of long-term economic dynamics that is captured by the long wave-concept.

In Section 2 criteria are proposed for conceiving a change as a ‘sudden’ one, and it is analysed if the stand alone-perspective of the Industry 4.0 concept meets these criteria. Section 3 interprets the Industry 4.0 concept in the socio-economic context of the Perez (2002) model, asks if in this waves-setting the criteria for ‘sudden change’ apply to Industry 4.0, and asks how regional differences in the suddenness of change and its perception emerge. Section 4 addresses implications for economic policy that derive from interpreting Industry 4.0 in a long wave-perspective in three policy areas (distribution, stabilization and regional policy). Finally, the paper concludes that the Industry 4.0 concept has not emerged suddenly and that the ‘perception’ of suddenness varies across regions if a long-wave perspective is applied.

2. The ‘stand-alone’ perspective: Industry 4.0 as a ‘sudden’ change

This section develops criteria that have to be met for a change constituting a ‘sudden’ change and analyses if the Industry 4.0 concept meets these criteria. ‘Sudden’ has several meanings (Merriam-Webster, 2018-10-04): something is (a) happening or coming unexpectedly, changing angle or character all at once, (b) made or brought about in a short time, or (c) marked by or manifesting abruptness or haste. Synonyms for sudden are abrupt, unanticipated, unexpected, unforeseen, unlooked-for. In the context of Industry 4.0 meaning (a) could be relevant because the concept claims changing the character of the economy fundamentally within a rather short period, meaning (b) could be relevant because of the quick proliferation of the concept, and meaning (c) could also be relevant in the sense of abruptness of change. In the context of long-term economic development and fundamental technological and economic change (which is claimed to be brought about by Industry 4.0 when considered as a stand-alone concept), we argue that the following four criteria have to be met for a change constituting a ‘sudden’ change.

‘Relevance of change’: First, the impact of change has to be sufficiently strong to impose an impact on doing business and organizing life in virtually all sectors of the economy, all regions, and all realms of society. Otherwise change is not important enough to be considered in the context of long-term structural change and economic development. Proponents of Industry 4.0 as a stand-alone concept claim that it will bring about encompassing change in economy and society:

The continuing convergence of the real and the virtual worlds will be the main driver of innovation and change in all sectors of our economy. The exponentially growing amount of data and the convergence of different affordable technologies that came along with the definite establishment of Information and Communication Technology are transforming all areas of the economy. (Kagermann 2015, emphasis by the author)

Yet, the form and intensity of change will differ across regions because of regionally different circumstances and because of diversities of innovation across sectors that impact the adaptability of the regional economy (O’Gorman and Donnelly 2020).

‘Disruptiveness of change’: Second, the more disruptive a change is, the more likely it will be considered a sudden one. Disruptiveness means that a break is required with institutions, economic structures, habits and other fundamental elements in society which have been well established before over a long period. A major claim of proponents of Industry 4.0 as a stand-alone concept is that it has the potential to bring about not only localized change in some specific markets and industries (‘first order disruption’; see Schuelke-Leech 2018) but that it affects many industries and changes social norms and institutions substantially (‘second order disruption’). Business models, economic structures, institutions and other fundamental elements in society which have been well established for a long time will (have to) undergo major changes and will be felt in all regions (although differently, again). This argument is extensively elaborated in the literature and need not be further extended here.

‘Unexpectedness of change’: Third, a change’s nature is the more sudden the less it is part of an agent’s mindset. If there is no probability known for the occurrence of change and even more so if the set of possible changes is not known, uncertainty about the future increases and (nearly any) change could become considered as ‘sudden’ in its nature. In contrast, if the set of possible changes is known and probabilities can be attached to each of the possible changes then it is less likely that change will be considered as unexpected. Nevertheless, even in such a situation the timing of the actual occurrence of change and the timing of the unfolding of the change requirements may still be unclear ex ante so that change might still come as a ‘surprise’.

If Industry 4.0 is considered as a stand-alone concept, then it claims to be a revolution that requires and ultimately brings about change in all spheres of life – also in those in which change comes largely unexpected. Technological properties, possibilities and implications of Industry 4.0 for individuals and the socio-economic framework are still unclear, and many of the concept’s implications and possibilities are not part of most individuals’ mindsets. While the emergence and proliferation of Industry 4.0 is likely to affect all regions in some way the (un-)expectedness of the concept’s appearance will vary across regions. Firms and the population in regions with a large share of developers and users of Industry 4.0 concepts might be less surprised by the occurrence of change that is brought about by Industry 4.0 compared to regions that need to import these concepts and applications. Summing up, the change brought about by Industry 4.0 can be considered largely a ‘sudden change’ on the dimension of expectedness if it is considered a stand-alone concept.

‘Perception of change’: Fourth, for a change to be considered a sudden one it is required that it is also ‘perceived’ as a sudden change. Therefore, the perception of change will largely depend on the communication of information about it, and on the willingness and ability of the population to adapt to change. The announcement or forecast of change which is likely to come about confronts individuals with uncertainty and at least implicitly requires them to change their habits, lifestyles, ways of earning income and doing business. On the one hand, given a high degree of firms’ and individuals’ adaptability to change this could be considered as a business opportunity or as an opportunity to improving one’s wellbeing. But, on the other hand, as change requirements might be substantial and costly, the proper timing of response is not clear in advance, less well adaptable individuals and those who are less willing to adapt might assume (or hope) that the personal impact of such change might materialize only in the distant future. But not responding to change requirements just delays the necessity to adapt; change requirements will pile up, and ultimately change can be perceived as a sudden phenomenon although it had been forecasted long time before. As adaptability and willingness to adapt is likely to vary across regions (Hu and Hassink 2016), the perception of change might differ across regions.

Perception patterns might be reinforced if change is assumed to be unavoidable – proponents of Industry 4.0 argue that it ‘will come inevitably, whether we want it or not’ (Drath and Horch 2014, 58). Using branded patterns of argumentation under the label Industry 4.0 has facilitated the concept’s reception in the general public, in business and in academia. The label has become so convincing and powerful because it suggests that a new era is going to arrive which has had only three predecessors in history (three former ‘technological revolutions’), because it reduces complexity, because it merges a broad variety of topics into one single label, and because the change that it brings about is claimed to be ‘unavoidable’.

In conclusion, from a ‘stand-alone’ view Industry 4.0 meets the four criteria of ‘suddenness’. Yet, this view is silent about the causation of that revolution: a few descriptive references to Schumpeterian-type innovation and/or superficial references to Kondratieff waves are not sufficient for providing a sound theoretical foundation for telling the story of a ‘revolution’. This view considers industrial revolutions merely as phenomena which just happen to happen from time to time: a revolution is going to happen right now because the appropriate technologies are available right now, and because these technologies are more economic than the existing technologies. While this may not be wrong it tells only part of the story: A more thorough socio-economic framework is required for explaining the emergence of such revolutions, why such a revolution is going to occur right now and thereby giving an answer to the question if this is occurring suddenly.

3. A long wave-perspective: the not-so-sudden appearance of (much of) Industry 4.0

After having discussed Industry 4.0 as a stand-alone concept now it will be interpreted within the Perez (2002) model of technology-driven long waves of economic development. The general analysis of the four criteria developed in the preceding section (relevance, disruptiveness, unexpectedness and perception of change) will be extended to a regional perspective in the final sub-section. Long waves are triggered by general purpose technologies (GPT) that have the capacity to profoundly transform the economy and that ultimately establish a new ‘techno-economic paradigm’ (TEP) (Perez 1983). The dynamics in the model is driven by ‘real economy’ entrepreneurs and financial investors, and economic development is the result of an interplay of technological, economic, political and social influences. A technology qualifies as a GPT if it has an impact on all aspects of the economy and society, and if it causes innovation and structural change in nearly all sectors of the economy. The change it brings about means more than just using a new technology, but it means establishing a new best-practice model of organizing business and the economy according to the properties of the new GPT. The label ‘industrial revolution’ suggests that the proponents of Industry 4.0 assume the concept to constitute a GPT.

A TEP runs through several phases of a long wave (Perez 2002): it starts with the upcoming phase and the ‘Frenzy’ phase (together forming the ‘installation phase’ of a new TEP), and ends with the synergy phase and the maturity phase (forming together the ‘deployment phase’ of a new TEP). Installation and deployment phases are connected by a period of transition (‘turning point’) that is particularly important from a policy perspective. The current fifth long wave of economic development has been triggered by new (=digital) information and communication technologies (ICTs); at the begin of the 2020s it is in its deployment phase. In order to scrutinize the ‘suddenness’ of change that is likely to be triggered by industry 4.0 the concept will be interpreted in a long wave context based on the four criteria of ‘suddenness’ of change.

3.1. Relevance and disruptiveness of change

For clarifying if Industry 4.0 meets the ‘relevance’ criterion for constituting a sudden change also from a long-wave perspective, the results of two recent systematic surveys of the academic literature are referred to. First, Liao et al. (2017) found 10 meaningful noun phrases which are commonly recognized terms that are associated with Industry 4.0. These are Cyber Physical Systems, Smart Factories, Industrial Revolutions, Internet of Things, Production Systems, Industrial Internet, Manufacturing Systems, Smart Manufacturing, Production Processes and Cyber Physical Production Systems. Second, according to a bibliometric search by Trotta and Garengo (2018) research on Industry 4.0 addresses Big Data Analytics, Cloud Services, 3D-Printing, Cyber Security, Autonomous Robots, Internet of Things, Augmented Reality, Simulation, and Horizontal and Vertical Integration.

Therefore, Industry 4.0 comprises a broad range of technologies that do not only have an impact in a single industry or small group of industries in which the technology initially emerged but on the economy as whole. Regions that are strong in Industry 4.0 applications will feel the economic impact more directly than regions with less Industry 4.0 penetration. The latter ones tend to become vulnerable to advances in digitalization that occurs in more developed regions and, therefore, will feel the impact indirectly as their competitiveness tends to deteriorate (Hickie 2020). By implication, the relevance criterion for Industry 4.0 constituting a sudden change in economic development can be regarded as fulfilled.

If Industry 4.0 meets the criterion of being ‘disruptive’ within a long wave-perspective depends on whether it qualifies as a GPT: does Industry 4.0 have the power to create a new techno-economic paradigm that changes the ways how business and social life is organized? Two caveats need to be considered: first, not all technological and organizational change taking place currently is related to Industry 4.0. Second, many changes that involve elements of Industry 4.0 are not of a disruptive nature but improve efficiency or performance within existing business models. While the former caveat is self-explanatory the latter one needs some explanation that is based both on theoretical considerations and on empirical observation.

Within the Perez’ long-wave model of economic development many Industry 4.0 applications represent the deployment phase of the fifth wave that has been coined by the emergence and proliferation of ICT. In the deployment phase the existing ICT-based TEP is rolled out to ever more firms and branches, particularly in the manufacturing sector (Scherrer 2019). This argument is supported by Drath and Horch (2014, 58) – two proponents of the Industry 4.0 concept – who observe that Industry 4.0 is similar to the ICT penetration of ‘the consumer world, which was confronted with the internet in the early 1990s’. In the same vein, Ibarra, Ganzarain, and Igarta (2018, 4) posit in a review essay on Industry 4.0 that ‘(t)he increasing fusion of industrial production and ICT has brought the so-called Industry 4.0 into the manufacturing world’ and thus support the idea that (much of) Industry 4.0 is concerned with the roll-out of the ICT-based TEP. Xu, Xu, and Li (2018, 2942) emphasize a different aspect of this roll-out process in the manufacturing sector and declare that ‘Industry 4.0 focuses more on the end-to-end digitization and the integration of digital industrial ecosystems by seeking completely integrated solutions.’

Empirical analyses and case studies of the impact of Industry 4.0 applications are also supportive to the view that many applications represent the roll-out of the ICT-based TEP. E.g. Gaddi, Garibaldo, and Garbellini (2020) find in an in-depth analysis of case studies on Industry 4.0 use in Italian manufacturing firms that these applications were only in few cases disruptive in nature. This finding is confirmed by several in-depth case studies on the experience of internationally operating firms that are headquartered in southern Germany and Austria and operate in the manufacturing and service industries.² Two large manufacturers of metal working equipment and a leading manufacturer of industry automation systems report that the adoption of Industry 4.0 applications has not changed their business models. A leading manufacturer of specialized equipment in the health sector has not felt pressure to change its business model, too. Most of its products are complex and need much explanation, and product support has been mostly provided by independent specialized distributors. As the firm relies on the distributors it only recently has established a web-shop in cooperation with the distributors for selling standardized goods to the final customer. But again, this does not mean disruption but change that occurs within the existing ICT paradigm.

Regarding the service industries, a major provider of specialized business to business logistics and transport services has not experienced fundamental change of the sector’s business model, too. Instead, it is claimed that a significant increase in productivity could be easily achieved if business partners were ready to implement rather simple business procedures based on conventional ICT. A supplier of advanced building services who operates in the business to consumer segment has experienced that building technologies and information technology converge. While ICT has changed the composition of equipment and services provided by the firm the basic business model in the sector has not changed. Finally, a leading provider of real estate services reports that it has started digitizing its huge stock of information and that this process is going to take much more time and effort than expected. It is not yet clear if this process would have a disruptive impact on the firm’s business model.

The examples demonstrate that the business models of many existing firms have not (yet) undergone a fundamental change – even in firms that are located in economically advanced regions and that operate in a variety of industries and regions. While all firms report that innovation takes place in the markets in which they operate, in no case a disruptive impact on a firm’s business model was found. The lack of reported ‘disruptiveness’ could mean that in many firms and sectors innovation brought about by Industry 4.0 would not be disruptive, or that it is only first-order disruption (Schuelke-Leech 2018) within the currently dominating TEP based on and formed by ICT. Therefore – although in all cases it was unclear if, how and when the firm’s or sector’s business model would be affected by Industry 4.0 in the future – the change brought about so far by innovation based on more intensive use of ICT has not been much of a ‘sudden’ change but has been in accordance with the long-wave pattern of dissemination of the dominant TEP.

3.2. Unexpectedness and perception of change

Regarding the dimension of ‘unexpectedness’, embedding the Industry 4.0 concept into a long wave-model casts also doubts that its appearance marks a ‘sudden’ change. Here the timing and sequencing of the phases of the current ICT-driven long wave is important. When its turning point-phase began in 2001 after the burst of the speculative bubble (‘dot-com Bubble’) economic policy was confronted with two challenges. First, after the huge losses in the stock markets, investors’ confidence needed to be regained in order to stabilize the economy in the short run. Economic policy successfully contained the short-term direct economic impact of the burst of the ICT-driven speculative bubble through expansionary monetary policy (with some delay in Europe). This encouraged investment primarily in financial capital and not in ‘real’ capital giving way to the build-up of another speculative financial bubble that was only indirectly related to the dissemination of the ICT-TEP. Its burst in 2008 marked the end of the turning-point phase of the fifth long wave (Perez 2009).

The second challenge in the turning point phase was that the institutional setting needed to be adapted to the requirements of the new TEP. The legal foundations of the internet had been established early, but it took much longer to deal with problems like standardization, privacy and data protection reflecting the slow progress in adjusting the regulatory frame to the needs of the not-anymore-so-new TEP. Only recently IoT-standards – which are required for rolling out ICT particularly in the manufacturing sector – have been developed, and the General Data Protection Regulation in the European Union became only effective in 2017. Beyond technology policy in a narrow sense, adaptations of existing regulations and new regulations were required in many other policy fields (e.g. labour relations, competition policy, social security system) and changing skill requirements needed to be addressed. Different rates of economic growth across regions suggest that the benefits from the ICT-based TEP in the deployment phase of the fifth long wave have not materialized equally across states and regions. While different regional industry structures and clusters that offer different opportunities for rolling out the ICT-based TEP might play a role, substantial differences in economic dynamics among regions of a similar level of economic development suggest that in many regions an appropriate institutional framework has not been found (yet).

According to the phasing of the long wave-model, the deployment phase of the fifth long wave began in the late 2000s by rolling out its ICT-based TEP over the whole economy (Scherrer 2020) by refining, further developing and adjusting these technologies and combining them with other technologies. As this is exactly what many applications of Industry 4.0 are about, from a long wave perspective this kind of innovation and investment has not come unexpectedly. Therefore, it does not constitute sudden change but is within the expected pattern of the long wave dynamics.

The not-so-sudden appearance of Industry 4.0 notwithstanding, economic agents still might ‘perceive’ change as sudden. Like in the early 1990s when the emergence of the internet caused an ‘unpredictable world of online shops, auctions, internet banking, online brokerage, and video streaming’ in the consumer world (Drath and Horch 2014, 58), Industry 4.0 is producing surprising results, this time primarily originating from the manufacturing sectors. While there are analytical differences between interpreting Industry 4.0 in a long-wave framework versus treating it as a stand-alone concept, there need not be much difference concerning the ‘perception’ of change.

Under the powerful label ‘Industry 4.0’ it has been argued that this concept’s implications are not clear ex ante but, nevertheless, the change brought about will be unavoidable. Such a situation is perceived by individuals and firms to be extremely difficult to control, and it is also difficult to develop appropriate responses at the policy level. Some agents might try to neglect or avoid change as long as possible because they have invested substantially in physical and human capital that might be devaluated as a consequence of the changes to come about. Others might not be sufficiently flexible or mobile for adjusting to the change, or consider themselves not being capable of doing so, or may face other restrictions to accommodating change. At the time when they are actually confronted with change and concrete requirements to change, they might be overwhelmed and feel surprised. Therefore, an individual person may perceive change as ‘sudden’ even if it has been discussed publicly long before it had become effective.

How intensive a change (and the need to change) is perceived depends i.a. on the choices that economic agents have. In historical perspective innovation activity has been concentrated in metropolitan areas (Hilpert 1992, 2016), meaning that both firms and the population in these regions tend to be exposed to the change brought about by Industry 4.0 from its early stages on. This could make economic agents in metropolitan areas perceive that change as less sudden than in regions that are affected by Industry 4.0 only indirectly or later. In conclusion, the criterion of ‘perception’ for considering change related to Industry 4.0 as sudden change is met only to some degree.

Overall, the provocative conclusion from interpreting Industry 4.0 in a long wave-framework is that the surprise is not that Industry 4.0 as a concept has emerged in the early 2010s but that it did not emerge ‘earlier’ within the fifth long wave. Much of recent innovation activity is still concerned with rolling out the ICT-TEP over more and more sectors of the economy – which is in line with the long wave model. Therefore, from a long wave-perspective the change has not emerged ‘suddenly’, although at the same time some change can still be ‘perceived’ as sudden.

3.3. Industry 4.0 – divergent regional perceptions of disruption in the future?

Both public debate and much of scientific research on Industry 4.0 applications emphasize the productivity increase through automation and robotization and its possibly huge negative impact on employment. While this discussion is relevant, of course, and structural change during the dissemination process of a new technology is enormous, this does not necessarily mean that change is disruptive as long as the productivity impact materializes within existing business models. Thus, it has been argued before that – even in economically advanced regions – many Industry 4.0 applications so far have been representations of the deployment phase of the fifth Kondratieff wave. From a long wave-perspective, in order to qualify as a GPT and, hence, becoming the trigger of a long wave, the changes released by a new GPT need to reach beyond productivity impacts within existing business models and need to affect (nearly) all sectors of the economy. The universal applicability of a GPT to many sectors and the possibility to combine it with many other technologies allows for a large variety of uses in economy and society. Change that is brought about by a new GPT will be considered more likely as a sudden one if a new GPT is of a disruptive nature, and if it is difficult to predict its possible uses and the timing when these uses will eventually become effective.

Regarding Industry 4.0, only those elements that cause ‘disruptive’ changes in virtually ‘all’ economic sectors have the potential to constituting a GPT and acting as a trigger of the sixth Kondratieff wave. The strongest candidates are two elements on which Industry 4.0 builds upon: digitalization and artificial intelligence (AI). This is for two reasons: First, based on the conversion of analogue data and processes into a machine-readable format (‘digitization’) digital technologies can be used that result in new activities or in changes to all kinds of existing activities (‘digitalization’; OECD 2018). Both digitalization and AI have the potential for becoming truly ‘general’ purpose technologies because they are likely to be applicable to all economic sectors and activities, and because they can be combined with many other technologies. Second, applications of digitalization and AI have the potential to disrupt existing business models in many sectors of the economy. In particular the emergence of ‘platform economies’ with marginal cost of production close to zero becomes possible and creates private monopolies (and undermines the role of marginal cost as a fundamental concept of pricing in a market economy). While regions in which the developers and platform firms are headquartered will benefit directly, the long-wave perspective suggests that other regions have the chance to gain indirectly if they succeed to adopt to the new TEP that will emerge. The economic gains are likely to vary across regions and will depend on the regions’ economic structures, and – even more – on their capabilities to adjust both economic structures and the institutional setting.

The ICT industry is likely to continue playing a prominent role as a provider of the infrastructure, and the capabilities and the capacities of internet and mobile communication networks will be further extended and improved (think about IoT and 5G mobile communication). As ICTs’ existence has become undisputed and an infrastructural backbone they will act as an enabler for the formation and dissemination of the next GPT. Regional differences in the quality of this infrastructure will be a key determinant of regions’ potential for economic and social development in the 6th long wave. Empirical evidence of current innovation processes suggests that firms digitize their processes and thus prepare for the next GPT.³ Therefore, as digitalization and AI are likely to act as drivers of a sixth long wave and to have the potential to affect business models in many industries, regional differences of the possible economic impact notwithstanding, the disruptiveness criterion is fulfilled. The timing of these technologies’ emergence is coherent with the long-wave model because the upcoming of a new TEP is expected to happen during the late part of the deployment phase of the still dominant ‘old’ TEP.

4. Policy implications from a long-wave perspective: regional effects of national policies and processes

Whether Industry 4.0 is seen as a stand-alone concept or if it is interpreted within a long wave-model of economic development leads to different conclusions on how ‘sudden’ the change occurs that is going to be brought about by its dissemination. This section discusses if the different perspectives also make a difference for adapting to (not-quite-so-) ‘sudden changes’ emanating from Industry 4.0 by economic policy makers at different levels of government.

From a stand-alone perspective, economic policy for Industry 4.0 is geared towards technological aspects (e.g. supporting Industry 4.0-specific R&D and innovation) and direct implications of technological change on the business sector (e.g. developing an appropriate skill base for developing and implementing the Industry 4.0 concept). While policy initiatives addressing these fields are important, of course, restricting the policy focus to such a narrow perspective entails two shortcomings: First, it tends to bias the perception of what Industry 4.0 is about and what its implications for economic policy are. Second, harvesting the benefits from the proliferation of Industry 4.0 will require actions beyond the scope of these policy fields. The common cause of the two shortcomings of conceiving Industry 4.0 as a stand-alone concept is a lack of a socio-economic explanation of its emergence and of its dissemination across industries and regions. Policy implications of these shortcomings will be illustrated by referring to distribution policy, to macroeconomic policies, and to regional economic policy.

First, the stand-alone perspective of Industry 4.0 does not conceptualize the nexus between the dissemination of a new technology, regulation, and the distribution of income, and it cannot capture, the impact of divergent industrial structures on regions’ economic development potential. The long wave perspective, by contrast, suggests that the distribution of income undergoes systematic influences during the phases of a long wave (Scherrer 2016). In the early phase entrepreneurs start experimenting with the upcoming technology thereby developing the properties of the new TEP. In this phase a policy focus on deregulation can be expected in order to facilitate experimenting with the new technology which, in turn, is conducive for developing new products and services within existing markets, and for creating new markets and activities based on the new technology. Adjustments in taxation – in countries with a multi-level government structure all levels of government are possible actors – are also likely to occur in this phase for providing economic incentives for entrepreneurs and investors to push innovation based on the new technology. By implication, an increasing number of entrepreneurs and investors earn huge profits in short time, while the not successful ones and many of those who do not adapt to the new TEP tend to lose ground. Therefore, inequality both between individuals and regions tends to increase during the Frenzy phase, and the increased inequality tends to be accepted as a consequence of the unfolding of the new TEP. Not surprisingly, values like solidarity are not ‘fashionable’ in this phase, and it is difficult to get topics onto the political agenda that are in a social-democratic tradition (like reducing inequality or re-distributing income). In the deployment phase of the long wave when paradigms mature, inequality constrains purchasing power and restrains demand for goods and services. As reducing inequality would allow to fully capture the potential benefits of the new TEP the issue of income distribution becomes relevant for reaping the full economic benefits from the TEP. Therefore, economic policy and taxation in particular should emphasize the principle of redistribution in this phase (Freeman, 2011). It is important to recognize that the argument for policies that reduce inequality and foster demand does not rest on social policy considerations but is based on economic grounds.

Second, the need for complementary macroeconomic policies that reach beyond mere technology policy and those policies that address the direct impact of new technologies is not conceptualized in the stand-alone perspective of Industry 4.0, too. Embedding the concept into a long wave-model clarifies the importance of this connection. During the turning point phase and in the early deployment phase there is a ‘case for a Keynesian policy of demand’ (Reati and Toporowski 2009, 164ff), and in order to prevent countries to fall into deflationary recessions ‘the IMF and the World Bank should be brought closer to the original Keynesian ideal’ (Freeman, 2011, 23). But after the turning point phase of the current long wave macroeconomic policies have not been conducive to exploiting the economic potentials of the TEP as fiscal policies have been largely procyclical after 2008 (Blanchard and Leigh 2013; Fatas and Summers 2018), and monetary policy has incentivized financial and real estate investment relative to investment in real capital.

Third, while distribution and other macroeconomic policies have indirect implications at the regional level, interpreting Industry 4.0 in a long wave perspective allows also for analysing direct economic implications of the emergence and dissemination of a TEP. Both historical evidence of long waves and the analysis of prior technology developments show that most innovation in cutting-edge technologies has always been concentrated in ‘islands of innovation’ (Hilpert 1992; 2016). Such places exhibit a strong research and development (R&D) base, and about 90% of such islands of innovation in the United States and in Europe known today have a tradition in related, precursor industries (Hilpert 2016). An analysis of European R&D in those technologies that are summarized under the Industry 4.0 label also shows that the comparative advantage is concentrated in few regions (Ciffolilli and Muscio 2018). Innovation-relevant infrastructure tends to be dominated even more than in former long waves by very few firms that are located in such ‘islands’.

But the historic evidence of long waves also shows that for being economically successful regions need not necessarily be R&D champions in those technologies that act as a trigger of a wave. This argument can be illustrated with many regions that adjusted their economies in the fourth Kondratieff wave successfully to the then-dominant TEP without having an own manufacturing base (which was the sector where the mass production TEP initially emerged) by applying the principles of mass production to sectors like tourism (Scherrer 2019). In recent times, in the realm of Industry 4.0 there is also the possibility to initiate innovation by ‘crossover’ knowledge transfer among recombinant knowledge constellations (Cooke 2018). Existing regional clusters can support the implementation of Industry 4.0 applications if they are equipped with the adequate knowledge base and some expertise in the technology fields that are crucial for Industry 4.0 (Götz and Jankowska 2017). In particular, clusters can be supportive for generating incremental innovation at the regional level (Hervas-Oliver et al. 2019). The gap between regions with different preparedness to Industry 4.0 can be narrowed if regional agents have experience with R&D, if they have a basic understanding of the new technologies, but most of all if they have a good understanding of the new TEP’s implications and potential for organizing economy and society. This poses challenges for economic policy at all levels of government in policy areas that reach far beyond the traditional scope of technology, innovation and qualification policy.

Therefore, the analysis of Industry 4.0 in a long wave perspective provides a socio-economic foundation to overcome shortcomings of the stand-alone perspective. This is relevant for economic policy as it allows developing strategies for accommodating the changes that Industry 4.0 can bring about by addressing also the broader and more indirect impact of new technologies. As a consequence, interpreting Industry 4.0 in a long wave model can make change appear less ‘sudden’ both for policy makers and other economic agents.

5. Conclusion: the not-so-sudden emergence of Industry 4.0 is perceived differently across regions

Interpreting Industry 4.0 within a long-wave model suggests that so far many of its applications have been representations of the roll-out process of ICT over the manufacturing sector and other sectors of the economy. By referring to four criteria that capture the ‘suddenness’ of change it is shown that much of the change brought about by Industry 4.0 is not of a ‘sudden’ nature but is in line with the long wave-dynamics. Analyses of policy areas that focus on income distribution, on macroeconomic stability and on the regional economy have illustrated that interpreting the Industry 4.0 concept in a long wave model improves the understanding of the concept and of its dissemination.

From a long wave perspective, digitalization and AI (being parts of the Industry 4.0 concept) very likely form the core of the next TEP. Regional differences in economic structures will have an impact on regions’ capabilities to adapt their economies to the requirements of the next TEP. Economic agents and policy makers at national and regional levels need to have a good understanding of the upcoming TEP and the economic potential it provides for appropriately adjusting the institutional framework. It is shown that a range of policy measures that reach beyond the narrow scope of innovation and other policies that are directly related to technology can facilitate adapting to change if they are implemented in the appropriate phases of a long wave. Finally, the long wave-perspective also suggests that, while the emergence of disruptive features of Industry 4.0 – digitalization and artificial intelligence – does not come as a surprise. Nevertheless, actual changes and change requirements that come along with Industry 4.0 might still be ‘perceived’ as ‘sudden’ changes, and the perception of suddenness of change is likely to vary across regions. Further research on the triggers of regional variation of the dissemination of a new TEP could improve our understanding of such regional variations and of causes for the (non-) synchronization of long waves across regions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 This story is nicely summarized in Xu, Xu, and Li (2018, 2942):

The First Industrial Revolution began at the end of the eighteenth century and early nineteenth century, which was represented by the introduction of mechanical manufacturing systems utilizing water and steam power. The Second Industrial Revolution started in the late nineteenth century, symbolized by mass production through the use of electrical energy. The Third Industrial Revolution began in the middle of twentieth century and introduced automation and microelectronic technology into manufacturing … The introduction of cyber-physical systems will be one of the most revolutionary changes in Industry 4.0 which is described as a fourth industrial revolution.

2 The following examples from the manufacturing and service sectors refer to in-depth in-firm studies from South Germany and Austria that were made accessible to the author between 2017 and 2020.

3 See also most of the examples in Section 3.1.