An integrated three-layered foresight framework

1. Introduction

In today’s complex rapid-changing world, trends in various spheres interact in increasingly unpredictable ways so that a single-issue focus is no longer sufficient to deal with emerging threats and opportunities (Habegger, 2010; UNDP GCPSE, 2014). The objective of strategic foresight is to take what we know and project it forward in useful ways (Wayland, 2015). Foresight practitioners are challenged to improve insight into plausible futures by a systematic process of anticipation (Martin, 1995). Plausible developments can be described by means of trends and key uncertainties. Trends describe historical changes up until the present, which can be expected to continue until they bend or break. Key uncertainties relate to emerging developments, which play a role in bending or breaking historical trends such as a possible new technology, a potential public policy issue or a concept, and can develop into a trend in its own right (Lum, 2016).

The expectation of what foresight is able to tell about future developments is influenced by outspoken perceptions of rapid or even exponential change, such as discussed in work of futurists such as Brynjolfsson (2014) and Leonhard (2016) and in literature in the Futures field on “postnormal times” (Sardar, 2010; Sardar and Sweeney, 2016). Awareness of rapid change is also evident in the mindset of decision-makers and policy advisors, as reflected in the extensive literature on methods for dealing with wickedness and deep uncertainty (Walker et al., 2013).

In spite of these views, we argue that not all future developments are equally uncertain. The perceived degree of uncertainty relates to the inertia (or duration) of unfolding trends and our understanding of the broader context in which they take place. This paper proposes an integrated three-layered framework, which represents the first step in a theoretical method for assessing megatrends based on their inertia and mutual interaction and illustrates the application of the method for a practical case study for the Port of Rotterdam. The framework suggests that by systematically analysing well-known trends and key future uncertainties in conjunction at an overarching meta-level, and by placing them in a broader integrated framework of long-term trends, better insight is obtained in the direction of individual trends.

Each layer in the framework refers to a different level of inertia, ranging from long-term trends with a duration of several decades to even longer trends that evolve over centuries. The method is tailored to address issues with a high level of uncertainty as defined as Level 3 uncertainty by Walker et al. (2010), which also recognises Level 4 or deep uncertainty. It is positioned in-between the forecasting and probabilistic forecasting methods that are well suited to deal with Level 1 and Level 2 uncertainty (Armstrong, 2001; West and Harrison, 1999) and the methods directed at addressing deep uncertainty, such as scenarios and adaptive pathways (Volkery and Ribeiro, 2009; Haasnoot et al., 2013).

Level 3 uncertainty, in particular, links to methods for anticipating technological and social change that may either involve empirical observations, theoretical explanations, or ways to envision desirable futures and move towards them. Cyclical theory and empirical data on long economic cycles (i.e. so-called Kondratieff waves) offer an increasingly recognised potential to create a comprehensive empirical view on transformations that we are experiencing today (Wilenius, 2015; Wilenius and Kurki, 2017). They provide clear insights into the primary drivers of unfolding transitions, but in the absence of a theoretical explanation, they offer little insight into the underlying processes of change. De Haan and Rotmans (2018) discuss the state of play regarding our understanding of the way these transitions unfold and propose a theoretical framework for assessing the role of different types of actors in transitions. Another method for addressing Level 3 uncertainty is the three-horizons method that uses a group process to assess three distinct time horizons (i.e. first – present system; second – transition zone; third – future system) with the objective of identifying and creating narratives on possible pathways for organisational transformation towards a desired future (Sharpe et al., 2016; ITC, 2020). Although these methods can be used to address plausible developments, which can be linked to Level 3 uncertainty (Van Dorsser et al., 2018b), they are less specifically directed at reducing epistemic uncertainty by gaining understanding of the context of individual trends and their mutual interaction, which is the purpose of our method.

The method proposed in this paper uses desk research to analyse three layers of trends. The first layer concerns relevant megatrends with a duration of a few decades; the second layer concerns the long wave in economic life that has a duration of about 50 years and is closely linked to transitional processes taking place today; and the third layer concerns the gradual movement of trends that have already existed for over a 100 years. This system of trends is expected to provide sharper insight into the overall development of the world system, allowing trends to be placed in a broader perspective to reduce epistemic uncertainty and improve foresight. Based on a detailed description of the trends and key uncertainties and their mutual interaction in the integrated framework, narratives can be developed to prepare for future change. The use of narratives is similar to the approach in the three horizons method, but the proposed framework aims to provide a sharper view by considering the mutual interaction and inertia of trends.

The framework was developed while carrying out a case study for the Port of Rotterdam (PoR) in The Netherlands (Van Dorsser et al., 2018a). Reference to the case study is only made occasionally in the first part of the paper because the objective is to present a new theoretical framework and method as an integrated foresight approach. The discussion on the practical use of the method for assessing real-world policy issues as illustrated by the case study follows at the end of the paper.

The paper proceeds as follows. Section 2 presents the framework and describes the four steps of the integrated foresight method. Sections 3-6 discuss the application of the steps in practice, whereas Sections 7-9 illustrate the method by presenting a case study for the Port of Rotterdam. Section 10 summarises the main conclusions and elaborates on the further development and potential use of the proposed method in practice.

2. The proposed foresight method

The foresight method proposed in this paper is based on an integrated three-layered framework for improving foresight by systematically analysing aggregated long-term trends (or megatrends) with a different level of inertia in an integrated way at the overarching meta-level. Oxford Living Dictionaries (2018) refers to meta-level as “A level or degree (of understanding, existence, etc.) which is higher and often more abstract than those levels at which a subject, etc., is normally understood or treated”. The meta-level approach leads to insights in the broader context of individual trends.

The theoretical framework is presented in Figure 1. Each layer relates to trends with a different level of inertia. The top layer consists of trends with duration over 100 years. These highly aggregated trends usually follow a long-term transition path and are relatively certain. They can be assumed to continue for a few more decades, justifying mindful extrapolation. The second layer consists of the so-called Kondratieff waves or K-waves. K-waves refer to an about 50-years lasting cyclical movement in the world economy that is observed since the start of industrialisation a few hundred years ago. Empirical evidence reveals a firm link between the main drivers of the K-waves and the pervasive economic, technological and social developments taking place. Though the precise timing of K-waves is hard to predict, the cyclical pattern of the K-wave movement is clear, as are its main drivers. This layer offers relatively clear insight into the dynamics of our world and the direction of technology and socio-economic trends. The third and the least aggregated layer consist of a plurality of megatrends with a considerable impact and an expected duration of a few decades. These megatrends often relate to emerging technologies, such as 3D-printing and autonomous driving. They are well recognised and widely discussed in various media.

Analysing trends with different inertia creates awareness of the degree of uncertainty at each layer. The real added value of the proposed approach, however, lies in the interaction between distinct layers. Each layer adds insight into the movement of the adjacent layer(s). The century-long trends signal the issues that trigger the main focus and direction of the next K-wave. The movement (or regularity) of K-waves provides a rough indication for the timing and relevance of newly developing megatrends and their driving forces. The identified megatrends confirm the direction of the pervasive socio-techno-economic drivers of the K-waves. And finally, the K-waves indicate that some century-long trends may reach the maturity stage of their S-curve and act as a slow steering force on the century-long trends. By placing trends in a broader perspective, insights obtained in the individual layers improve understanding of the direction of trends in the adjacent layers and adds insight into the evolution of individual trends. This approach could, in theory, provide additional insight into the inertia and direction of long-term trends, aiming at sharper foresight for better decision-making. Professional foresight practitioners may have already developed similar insights over time by studying trends and applying existing foresight methods, but decision-makers often lack this experience. Therefore, we propose an integrated foresight method based on the three-layered framework in Figure 1, which consists of the following steps.

• Step 1: Identify megatrends and key uncertainties with a duration and potential impact of at least one or two decades and categorise these trends by theme.

• Step 2: Filter out trends with a duration of at least one century because these can be expected to remain relatively stable over the next few decades.

• Step 3: Analyse the dynamic behaviour of about 50-year lasting economic cycle (i.e. the K-wave) and its primary drivers.

• Step 4: Assess the linkage between the layers and integrate all three layers into a broader meta-framework such that the context of the individual trends stands out.

The existence of a clear framework for analysing trends enhances the options for decision-making under Level 3 uncertainty, as the traditional approach for dealing with increased future uncertainty is to shift from forecasting (i.e. method for dealing with Levels 1 and 2 uncertainty) to assessing a range of scenarios (i.e. Level 4 when considering possible scenarios). Scenarios are well suited to anticipate possible changes, but commercial plans that are designed to accommodate a broad set of requirements presented by innumerable scenarios require high investments and risk becoming non-competitive. In a commercial environment, the challenge is not just to envision developments with a possible effect on the business, but more importantly, to assess which of them are plausible, given a thorough understanding of the underlying system. To stay competitive in a commercial environment, one does not have the luxury to invest in plans that are robust under numerous possible developments. Instead, one has to focus on the more plausible developments, which can be identified on the basis of a comprehensive understanding of the system, as obtained from the proposed framework.

To develop strategic insight and use this to prepare the business (or another relevant policy domain) for upcoming threats and to seize future opportunities, the following additional steps can be taken.

• Step 5: Conduct a thorough strengths, weaknesses opportunities, and threats (SWOT) analysis starting with the identification of threats and opportunities using insight from the three-layered framework, followed by an assessment of the strengths and weaknesses related to these threats and opportunities.

• Step 6: Create a limited set of “trend-based narratives” over the future development of the policy domain (e.g. the business) considering the recognised relevant external threats and opportunities (e.g. described by plausible storyline scenarios) in combination with the strengths and weaknesses of the organisation.

• Step 7: Elaborate on the trend-based narratives to create a broader vision and strategy for the development of the business, or another relevant policy domain.

A narrative is a story written or told, usually in great detail. Well-defined trend-based narratives are useful for creating a collective or shared view over the future and identifying threats and business opportunities, which is a stepping stone towards realising a vision and strategy.

The following four sections provide a general discussion of the four steps in the three-layered foresight method, in which the description of the trends and key uncertainties is based on our interpretation of available sources and intended to illustrate the kind of insights that could be obtained from applying the framework. The subsequent sections discuss the practical application of the method in support of decision-making for an actual case study for the Port of Rotterdam.

3. Step 1: identifying relevant megatrends

Step 1 involves the systematic screening of megatrends and key uncertainties relevant to the subject under consideration, neglecting the inertia of these trends. Megatrends are named after Naisbitt (1982). They can be distinguished from normal trends by their time horizon, reach and intensity of impact. Megatrends can be observed over the decades; impact comprehensively on all regions; and impact powerfully and extensively on all actors (Z-Punkt GmbH, 2020). Key uncertainties are defined as uncertainties that are considered plausible and likely to have a major impact on the system under consideration in case they appear (such as e.g. the development of nuclear fission power or the event of war). Because numerous trends and key uncertainties exist, a well-structured approach is required to filter out relevant ones.

Step 1 starts with identifying overarching themes related to the issue at hand for which the well-known STEEP classification is suggested, as commonly applied in the UK (Habegger, 2010). STEEP stands for Societal, Technological, Economical, Environmental and Policy. Following a suggestion of Watson (2013), extra letters may be added to tailor the method, such as an extra E for Energy, and extra E for Employment, an extra P for Population and an extra I for Identity, turning STEEP into STEEEEPPI. Whether such additions are useful is case-specific. For example, an extra E was added for Energy in the mentioned case study for the Port of Rotterdam as the port is a major player in handling energy products.

The following action is to identify relevant megatrends and key uncertainties based on discussions with experts, literature research, internet searches and news articles, which are also standard tools for horizon scanning and emerging issues research (Slaughter, 2009; Miles and Saritas, 2012). A complicating factor at this stage is that it is impossible to be sure that all relevant trends and uncertainties have been included. The risk of omitting important trends should be recognised and, if possible, mitigated by, for instance, involving experts with a different background. The next step requires examining the potential impact of the trends and key uncertainties on the issue at hand, which can also be based on literature research and expert opinions.

The general outline of the method in this paper does not allow for an in-depth discussion of relevant megatrends, though some trends are mentioned in Table I. Elaborate descriptions of identified megatrends and key uncertainties are provided in the mentioned case study.

4. Step 2: century-long trends

Once the overall set of trends and key uncertainties is obtained, Step 2 analyses the trends identified in Step 1 and filters out the trends that have existed for a century or more, making use of corroborating time series. These trends belong to the top layer of the framework. They have low inertia, are relatively stable and likely to head in the same direction for at least few more decades. Acknowledging that the list is not comprehensive, the following century-long trends were identified and assessed in greater detail in the mentioned case study report (Van Dorsser et al., 2018a):

• secularisation and individualisation;

• population growth;

• urbanisation;

• the nature of activities and social power;

• energy and raw material use;

• connectivity and increased data exchange;

• technological progress and economic output;

• climate change and environmental degradation;

• (reducing) transport costs and globalisation; and

• shifts in geopolitical world order.

For each of these trends, we assessed the potential impact on the global trade and transport volumes as well as on the activities undertaken in the port (i.e. the core subject of the case for which the method was developed). These trends are also likely to be relevant to other foresight studies. This section discusses the ten century-long trends, based on our understanding and subjective interpretation of the trends. It provides an illustrative application of the method for future foresight studies. The discussion includes some detailed aspects specific to our case study to illustrate how the century-long trends can be tuned to provide insight into the subject under consideration.

Secularisation and individualisation have an impact on population growth, migration, geo-political stability, populism, nationalism and anti-globalisation. In Christian-rooted countries, it took almost 500 years (starting with Luther’s 95-thesis and the 80 years’ war in the Netherlands) to reach the secular state that these countries have today. In contrast to this slow gradual bottom-up process, Islamic countries such as Iran and Turkey became a secular state almost overnight in an enforced top-down process under influence of the British Empire and Western ideology in the 1920s. Though some people in these countries want to modernise, others still have difficulty with the swiftly enforced change, which backlashed resulting in the ongoing tensions and conflicts in the Middle-East, Africa and South Asia today that also affect the Western world through extremism and terrorism. In analogy with the long secularisation process in Europe, it can be expected that these tensions remain a source of conflict for many generations. The resulting conflicts and acts of terror are, in combination with induced refugee flows, higher birth rates of religious (often Islamic) minorities in Western countries, and declining welfare growth for the bottom 99 per cent of the population, a growing source of populism, nationalism and anti-globalism in the West.

Population growth has a severe impact on the world. Population growth, of which the rate is affected by religiosity, puts a constrain on resource availability, and also affects geopolitical power, poverty and migration. Based on UN DESA (2017) projections, the population is expected to remain growing throughout the twenty-first century in Africa, where it is booming, as well as in the USA through a stable continued growth. Growth is also strong in India where it is expected to peak around 2080. The European population is stabilising and expected to show moderate decline from about 2040 onward. In China, the population is near its expected peak in 2030 and thereafter expected to face substantial decline throughout the century. Russia is already facing a severe continued population decline. Changes in population growth affect the geopolitical power balance, in which India is gaining regional importance over China and Russia, and in which China and Russia are less likely to fully take over the hegemony of the USA. Africa’s growth will, together with climate change induced poverty and starvation, enhance migration towards wealthier regions, fostering populism and the anti-globalisation movement in western countries. For our case study, this likely results in reduced international trade and transport volumes. In addition, aging populations also require fewer material goods and more services, which also reduces transport volumes handled by major seaports.

Urbanisation is a direct result of the growing population in most parts of the world, but it is also induced by other trends such as the shift in the nature of activities and social power, and by ongoing connectivity and technological progress through specialisation. With respect to our case study, urbanisation changes living patterns and affects consumption in a way that it reduces demand for material goods (i.e. smaller houses, less cars, less energy demand) and increases the demand for services.

The nature of activities and social power is gradually shifting from agriculture and land ownership in the pre-industrial time (up to about the eighteenth century) to industrial manufacturing, capital and possession of resources (since the Industrial Revolution), to services based on information and knowledge in the post-industrial age from about the year 2000 onwards (Van Wyk, 1984; Spies, 1998). This trend fosters connectivity, urbanisation and individualisation.

Energy and raw material use show a long path along a centuries-long transition curve in which raw material and fossil energy resources are extensively exploited resulting in vastly lower energy returns on energy invested (EROI), down from over 100 in 1930 to below 8 for new discoveries in 1970 and only about 5 for shale oil and 2-4 for tar sands (Murphy and Hall, 2010). Similar trends of declining ore grades are also reported for mining products, which implies that more efforts (costs and energy) are required to mine a tonne of material. Until recently, advancements in mining techniques have been able to offset the increasing costs of fossil fuel and mineral depletion, but this trend seems to have reversed around the year 2000 (also for agricultural products). Further cost reductions on energy are only possible through advancing renewable energy, which is becoming competitive and starting to gain noticeable market share. Cost reductions on material use depend on developing advanced recycling, which is a growing industry.

Connectivity and increased data exchange are an ongoing trend that seems embedded in human nature traced back to ancient times with development of trade routes (both maritime and over land) and the invention of writing. It accelerated with the invention of the printing press in the fifteenth century that triggered the renaissance. Connectivity boosted during the industrial age by the invention of new transport means (e.g. canals, railways, paved roads, air transport), new means of communication (e.g. telegraph, telephone, fax, mobile, social media), computers and new data carries (e.g. pons card, gramophone, magnetic disk, SSD). After the introduction of the internet, computers were swiftly connected to the World Wide Web that is now offering a broad range of services including online booking and online shopping. The following step is to connect all kinds of smart machines to the Internet of Things (IoT), including e.g. air conditioners, fridges, cars, etc. and to make extensive use of sensor technology and big data to improve business operations. Next steps that are being researched today are the development of bionics and the connect of the human brain to the cloud through augmented sensing, ultimately moving towards the creation of cyborgs.

Technological progress is closely related to the supply side of the economy, as technological progress is usually measured in aggregated terms of increasing factor productivity and increasing labour productivity. Labour productivity, and therefore also economic output (per worker), has increased dramatically over the past 200 years as a result of higher education levels, more capital intensive processes and advancing technology levels through an almost exponential growth in research output that cannot be sustained nor be expected to continue to offset the diminishing returns on technology development (Fernald and Jones, 2014). Though not universally agreed on, we conclude that labour productivity in technological forefront countries follows a transition s-curve, for which economic output is eventually bounded by the size of the working age population (Van Dorsser, 2015, 2018a). This view is in line with the conclusion of Gordon (2016) that the growth since the Industrial Revolution is a result of a number of life-altering innovations that cannot be repeated, for which he contends that US productivity growth has already slowed down to a crawl and is likely to further decline.

Climate change and environmental degradation are a direct effect of overexploitation and overconsumption of material goods and fossil energy resources. Climate change affects our global living environment in many harmful ways. Devastating are the negative impacts on food yields, dying of marine ecosystems, extreme weather conditions, floods and the impacts of sea level rise. In combination with environmental degradation, it deteriorates the ecosystems by acting as a driver of food-induced conflicts, starvation and climate-induced migration, especially in combination with rising poverty levels. On the positive side, climate change and environmental degradation stimulate global awareness for sustainability that shifts focus on, e.g. reduction of carbon footprint, renewables and recycling. Specific to our case study, climate change results in melting of polar ice and the creation of new sea routes via the artic that are considerably shorter than existing ones. Moreover, global warming also reduces the frequency of river ice events for inland shipping; increases the downtime of port terminals because of extreme weather events; and causes many other subject-specific impacts.

Transport costs have been declining over a long period fostering globalisation. Oosterhaven and Rietveld (2003) found that real costs for maritime transport declined by a factor 7.5 from the late eighteenth century to the second half of the twentieth century and have remained relatively stable thereafter, though indicating a slight possible increase. In a similar way, they showed that inland transport costs declined by a factor 5.5 for road transport, and by about a factor 4 for rail transport, over the course of the twentieth century. International sea transport costs are now so low that further reduction is fairly difficult, indicating that an increase is not unlikely. This could also be anticipated from the all-time low in the costs of fossil energy and raw materials around the year 2000 (with renewable fuels for sea transport still requiring a few decades to become cost-effective). This implies that a lower cost of international transport is no longer a key driver for ongoing globalisation.

Shifts in geopolitical world order are subject to low inertia changes, in which China and India were once the leading powers prior to the Industrial Revolution. Following the Dutch Golden age and the Industrial Revolution, the “Western” world gained a dominant position first through the British rulership and later through the supremacy of the USA. However, from the 1960s onward, China built up substantial economic and military power and teamed up cleverly with Russia and other countries to undermine the affectivity of Western-originating institutes such as the UN Safety Council, while creating their own institutes, including the Shanghai Cooperation Organisation (SCO). The shift of power from “West” to “East” can potentially result in an all devastating war, but a shift of power without war could be more likely as:

• Levy and Thompson (2011) showed that the percentage of years in which great powers fought each other has fallen dramatically over the past five centuries; and

• because when analysing advancements in the economic power, one can observe the shift of economic power from the USA to China to lose momentum and start stabilising.

This creates a bipolar world order, with two power blocks being NATO and SCO. The USA still has a steady continued growth of its population, economy and technology base, whereas Russia seems already over the top of its economic power, and China is confronted with an expected decline of population and a long-term slowdown of economic growth (with growth gradually moving towards the lower growth path of developed technological frontier countries). Moreover, India, which is more Western-oriented, has joined the SCO and is gaining economic relevance in the region, acting as a stabilising factor. So, presumably, the world will, for a sustained period, remain caught in a bipolar power balance in which the democratic norms and values of the “West” are sacrificed for a more pragmatic “mind your own business and don’t interfere with our own “domestic” affairs” approach. This also implies that the conflict-solving ability of our world is partly disabled, resulting in more severe impacts of geopolitical conflicts, such as obviously being observed in Syria today. However, in spite of this trend of moving away from global military escalation, future geo-politics remain rather uncertain (especially compared to other trends) and are suggested to remain included as key uncertainty.

There are a few remarks. First, economic growth is subject to both the supply and demand side. Trends with respect to technology development and labour productivity growth relate to the supply side of the economy, but another important trend is evolving at the demand side that relates to increasing wealth and income inequality since the 1970s (now lasting about 50 years). This trend is already and could further reduce economic output in the future (Brueckner and Lederman, 2015). Second, the rise of China as a dominant world power is strictly not a century-long trend, but shifts in global leadership, since the middle ages, seem to appear almost every 100 years (Modelski and Thompson, 1996).

5. Step 3: Kondratieff waves

Step 3 analyses K-waves which are a linking pin between the individual megatrends and the centuries-long lasting trends. They concern a cyclical movement around the centuries-long trend in technology development and per capita economic growth. Cyclical movements have been studied ever since the Industrial Revolution started to cause social crises and many cycles of varying lengths have been identified (De Groot and Franses, 2009). The more commonly reported cycles are:

• 3-5-year inventory cycle of Joseph Kitchin;

• 7-11-year business cycle of Clement Juglar;

• 15-25-year infrastructure swing of Simon Kusnets; and

• 45-60-year long wave of Nikolay Kondratieff.

For the proposed framework, the 45-60-year Kondratieff (1926) wave is the most relevant. Kondratieff waves are related to the pervasive drivers of our global society and the world economy (Grübler and Nakićenović, 1991; Ayres, 1990a, 1990b). Their close relationship with the diffusion of new technologies and the development of new infrastructure networks make the K-wave useful for identifying future trends and their inertia (or momentum) (Grübler, 1990). The other cycles are less relevant, though Juglar’s (1862) 7-11-year business cycle provides valuable insight into the movement of the K-waves (Van Duijn, 1983). Schumpeter (1939) already observed strong regularities in the movement of the K-waves and suggested each K-wave to consist of six Juglars. Van Duijn (1977) refined this view and proposed that K-waves need not consist of six Juglars, but can also be composed of five Juglars, at least in cases where no war is following the prosperity period as is frequently the case.

The cyclical pattern of the K-waves can be represented in various ways. The most basic is the one with an upswing period followed by a downswing period. Schumpeter (1939) proposed a sinusoidal four-phase model consisting of four phases: prosperity, recession, depression and recovery. A revised phasing was proposed by Kuznets because the original phasing did not comply with the upward and downward movement of the waves. His revised scheme, also adopted by Van Duijn (1977), differs in that the starting point of the upswing phase is located at the beginning of the prosperity phase, and the starting point of the downswing phase is located at the end of the recession phase.

6. Step 4: interaction between the layers

Step 4 analyses the interaction between the layers in Figure 1 and the insights that the layers offer each other through a better understanding of the broader context at the meta-level.

7. Step 5: SWOT analysis

Based on the integrated framework of trends and key uncertainties developed in the previous sections, we can proceed to apply the framework to develop strategic insight and use these insights to prepare the concerned entity for upcoming threats and opportunities. The first step in this process it to conduct a thorough SWOT analysis. This is illustrated by a case study for the Port of Rotterdam (PoR), which is the largest port in Europe and well connected to the West-European hinterland by means of road, rail and inland waterway transport. A summary of the identified threats and opportunities, as well as the strengths and weaknesses in relation to these threats and opportunities, is presented in Table IV.

The identification of the threats and opportunities has taken place on the basis of the insights gained from the presented framework [and supporting material published in Van Dorsser et al. (2018a)]. Note that Table I already paid attention to the impact of societal megatrends on the transport system and the port environment.

8. Step 6: trend-based narratives

By analysing the strengths and weaknesses of the port in conjunction with the threats and opportunities that were identified on the basis of the three-layered framework, it becomes possible to develop a number of trend-based narratives for various clusters of port activities. For means of illustration, we will now address the narratives on the liquid bulk and chemical, the dry bulk, the container and the offshore construction and recycling sector in the PoR. For these sectors, several threats and opportunities are combined in the narrative, which is logical as multiple trends exert forces on the port environment simultaneously.

9. Step 6: towards a vision and port strategy

These narratives indicate an urgent need for more efficient use of space in the port over the next few decades to seize opportunities and facilitate the development of new activities and port clusters. It is expected that port space will remain scarce over the next 20 years in spite of the recent expansion at the 2nd Maasvlakte. This is because the fossil industry is still expected to require another 20 years before phasing out, while space is already required for new activities that are gradually developing in line with the sustainability driver of the sixth K-wave. From a port perspective, it is desirable to support and facilitate these activities to ensure that the port is ready for the future around the year 2040 when new sustainable activities take over the dominant position of the old fossil industry and begin to scale up.

By matching the existing port infrastructure and the location of activities with the demand for space indicated by the narratives, one can schematise a possible clustering of future activities after the current transition period around the year of 2040. This can be seen in Figure 2.

The sketch is drafted by the authors and does not necessarily represent the viewpoint of the PoR. It is included to illustrate how the proposed method could support decision-making.

10. Conclusions and further discussion

Foresight aims at identifying plausible developments to improve strategic decision-making. However, in today’s complex rapid changing world, where trends in various spheres interact in increasingly unpredictable ways, it is difficult to gain insight into the inertia and expected direction of individual trends. This paper proposes a new integrated three-layered foresight framework and method for assessing various layers of megatrends based on their inertia or duration. The proposed theoretical framework shows that by analysing trends and key uncertainties in conjunction at the meta-level, and by placing them in a broader three-layered framework of megatrends, additional insight is obtained in the inertia and direction of long-term trends, aiming at sharper foresight for better decision-making.

The layers in the framework encompass:

• trends with a duration of over 100 years, which are relatively certain and can usually be assumed to continue for a few more decades;

• the so-called Kondratieff wave, or K-wave that relates to an about 50-years economic cycle and is closely linked to the pervasive economic-, technological- and social drivers of our modern industrialised world; and

• a plurality of megatrends that, on balance, seem to be closely linked to the movement and primary drivers of the K-waves.

The strength of analysing trends in conjunction at three distinct layers of inertia is that one becomes aware of the level of uncertainty at each individual layer. Also, by placing trends in a broader meta-perspective, the insights obtained from individual trends at the specific layers improve our understanding of the overall direction of the trends in the adjacent layers and vice versa.

The scope of this paper is limited to presenting the theoretical framework as a new integrated foresight approach, and illustrating, by means of a case study, that the method has potential to be used in practice. The next step is to investigate the applicability of the framework and method for other applications in practice, teaching and research, and to provide a broader, more detailed and more nuanced assessment of trends and uncertainties.

Although the scope of this paper is essentially intended to present the theoretical framework as a new integrated foresight approach, its use has been illustrated for an actual case study for the Port of Rotterdam, where it was applied to gain insight into relevant trends and key uncertainties and to assess their expected impact on the port. This provided insight into plausible developments and their effect on future port business. The identified trends were “translated” into threats and opportunities for specific port activities while taking into consideration the strength and weaknesses of the port with respect to these activities. The result was a SWOT analysis in which threats and opportunities are based on an integrated framework of trends. Subsequently, a number of trend-based narratives were “distilled” from the SWOT. These narratives address the impact of plausible trends and key uncertainties on existing and potential new business activities. The narratives reflect the expected changes in the port arena and enable the port authority to think strategically and optimise their spatial planning for the development of future proof port industrial clusters.

For some port activities, such as the handling of fossil energy products such as coal and oil, the framework only confirms what is already known, i.e. that major decline in throughput can be expected, but for others, such as container transport, the results are more surprising. New insights in long-term economic growth and reverse globalisation hint at a decline rather than an ongoing increase of future container throughput. Other trends show opportunities for expansion of existing and new port clusters, such as for renewable offshore energy supply facilities; demolition and recycling of ships and offshore supply units; fish farming; and transfer, storage and processing of hydrogen, bio-fuels and bio-chemicals. This implies that the port authority could reserve less space for new container terminals and designate additional space to foster other promising opportunities.

The transitional forces driving these developments are clearly linked with the primary drivers of the K-waves, for which the framework provides insight into the direction that concerns a shift from globalisation to sustainability (and a partial reverse of globalisation from hyper-globalisation back to more sustainable levels of globalisation), and an ongoing trend towards increased levels of connectivity (i.e. a shift from ICT to IoT). This suggests that it is worth considering insights from K-waves in foresight. This is being increasingly acknowledged, but predominantly in relation to individual developments. The foresight method proposed in this paper aims at providing a more generic approach for incorporating K-waves.

Having presented the method, we hope that it will inspire others to apply the method on its own or in combination with other methods. The discussion on the use of the method for the PoR illustrates a practical application of the method on its own. Another suggestion may be to use the method in combination with the three horizons method for identifying the transformational processes.