From PSScience to digital planning: Steps towards an integrated research and practice agenda for digital planning

Up till now, a widely accepted definition of Digital Planning is missing. Following the Editorial, digital planning is defined as the application of digital technologies and data-driven approaches to enhance efficiency, effectiveness, and inclusivity in planning processes to improve social, economic, and environmental outcomes for a sustainable urban future. It is necessary to clarify the distinction between Digital Planning and two associated terminologies: Planning Support Systems (PSS) and Planning Support Science (PSScience). PSScience and Digital Planning (DP) are envisioned as distinctive but closely interconnected. PSScience acts as the scientific base of the foremost planning practice-oriented Digital Planning. Based on this double-sided distinction and interconnection with PSScience, the relatively new concept of Digital Planning is further elaborated upon, resulting in an integrated research and practice agenda. For both approaches, a quadruple collaboration will be needed between governmental organizations, market parties, societal organizations/individuals, and educational/research institutes.


Introduction
Digitalization in the policy and practice of spatial planning is currently a hot topic, although far from brand-new.The origins of digital transformations in planning can be traced back to the 1960s with the socalled Systems Approach in spatial planning (McLoughlin, 1969).It referred to digital technologies as the means of helping cities become more efficient and equitable.Nevertheless, its focus was on more than just the application of computers perse; more central were the strategic and visionary ways to arrive at a better quality of life in cities (Batty, 2021).
At present, in many realms of the public domain, one can identify the urge for more attention to digitalization within planning.In the United Kingdom, quite recently, a task force for Digital Planning was set up (www.digital4planning.com) to develop better plans for better cities while at the same time engaging in developing a deeper understanding of how cities change in time (Batty & Yang, 2022).In the Netherlands, a comprehensive and impactful digital planning initiative started with the Environment and Planning Act, effective as of January 2024.Together with the increasing digitalization of the planning process, an integration of 28 separate laws into one comprehensive environmental law was established (https://www.government.nl/topics/environment-and-planning-act).In Finland, a transition is ongoing towards an information model-based planning with a principal focus on achieving national-level interoperability of plan data (Nummi et al., 2023).In Australia, like the UK Planning Portal, Singapore's CORENET, the Danish Planning Portal, eDevelopment Scotland, and e-permitting systems in Finland and Ontario, Canada, the digitalization of the planning system is led by the implementation of the New South Wales Planning Portal (Williamson, 2024).These examples show the widespread attention to the digitalization of planning as a recent phenomenon.Furthermore, it underlines that this digitalization has a strong impact not only on the planning outcomes but also on the social (e.g., community of planners) and contextual (e.g., planning practices, information systems) entities of planning.This societal urgency justifies a closer reflection on this digitalization of planning, which scholars increasingly identify as 'Digital Planning' (Lin et al., 2024).
Nevertheless, before we continue on Digital Planning, it should be acknowledged that this process of continuous digitalization in planning and policy-making is identified with a plethora of terms, of which, besides Digital Planning, the concept of Smart (Urban) Governance is the most prominent (Jiang, Pan, et al., 2023).Smart (Urban) Governance is generally envisioned as the intelligent use of ICT to improve decisionmaking through better collaboration among stakeholders, including government and citizens (Pereira et al., 2018).Smart governance is defined as technology-enabled collaboration between citizens and local governments to advance sustainable development (Tomor et al., 2019).From this, it can be seen that Smart (Urban) Governance and Digital Planning have much in common.In contrast, one must also identify that Smart (Urban) Governance is more generally focused on the disciplinary field of urban governance, so policy-making.Digital Planning is inclined to urban and regional planning, a subcategory of policy-making.
Despite this increased focus, a widely accepted definition of Digital Planning is missing.In accordance with Lin et al. (2024), digital planning is defined as "the application of digital technologies and datadriven approaches to enhance efficiency, effectiveness, and inclusivity in planning processes to improve social, economic, and environmental outcomes for a sustainable urban future" (Lin et al., 2024).This is a comprehensive definition with a diversity of broad terminologies.For the sake of clarity relating to the purpose of this paper, digital technologies are envisioned as instruments dedicated to supporting professional planning like Planning Support Systems (PSS), Digital Twins, dedicated Artificial Intelligence (AI), Virtual Reality (VR) and Augmented Reality (AR), dedicated Social Media and apps and games, etcetera.The mentioned data-driven approaches refer to using multiple data sources and advanced techniques for analysis and simulation to support informed decision-making (Geertman & Stillwell, 2020).
It is important to clarify the tangle of associated terminologies here first.We will start by clarifying the distinction between three associated but distinctive terminologies: Planning Support Systems, Planning Support Science and Digital Planning (see also Geertman & Stillwell, 2020).
First, Planning Support Systems (PSS) can be traced back to the 1980s.They can be considered computer-based tools that can be used to support planners (and other stakeholders) in undertaking professional planning-specific activities like scenario-building, forecasting, participation processes, trend analysis, enhanced sustainability, and much more (Batty, 2021;Geertman & Stillwell, 2003;Harris, 1999).These tools encompass the 'Systems' in the PSS abbreviation and change with the growing complexity of reality: from Geographical Information Systems (GIS), land use models, and (Spatial) Decision Support Systems ((S) DSS) towards Digital Twins (DT), Artificial Intelligence (AI), gamification platforms, Virtual/Augmented Reality (VR/AR) applications, big (open) data and smart city platforms, digital data infrastructures, and much more (Geertman, 2015).A recent citation analysis by Daniel and Pettit (2022) revealed that over the past 30 years, the field of PSS has matured into 27 distinct research streams under four main themes.
Second, the Handbook of Planning Support Science (Geertman & Stillwell, 2020) showed how the field of Planning Support Systems research matured over time with a change in focus towards a widening in application orientation, increasing methodological attention and increasing focus on the impact of contextual factors (see Geertman, 2017;Jiang, Geertman, & Witte, 2023).Owing to this maturation, the authors proposed to change the abbreviation PSS into PSScience, referring to Planning Support Science, with a much stronger emphasis on the 'goals of support' instead of on the 'systems of support', the latter which are considered dominantly as the means of support.This also expresses the present user-or demand-driven approach of PSS developments and applications in contrast to the former technologyfocused supply-driven approach.This PSScience as an academic field or domain is engaged in the scientific question of how instruments (including digital technologies like PSS) can best be attuned to the style of governance and to the application at hand, given the specifics of a particular contextual environment, to optimise the goal of support.For instance, Yap et al. (2022)  Third, related but distinguished from PSScience, Digital Planning (DP) is concerned with the planning practice-oriented application of digital technologies and data-driven approaches to enhance efficiency, effectiveness, and inclusivity in planning processes to ultimately improve social, economic, and environmental outcomes for a sustainable urban future.So, Planning Support Science and Digital Planning are interconnected, and one is a prerequisite for the other.Planning Support Science is more scientifically oriented (theoretical, methodological, and contextual), heading for more generalizable statements and outcomes about planning support.Planning Support Science is not so much heading for practical outcomes of digitalization of planning.Instead, it is foremost interested in the preconditions, the underlying assumptions, and the scientific roots of planning support with the help of digitalization, in the end, to bring planning support to the next level of support.It also requires the valuable input of digital planning, where digital planning can provide insights into, for instance, the strong and weak points of certain forms of digital support within particular planning contexts.In return, Digital Planning can be enriched with valuable insights from Planning Support Science.It can practice those insights within certain planning contexts and test the relevancy of its recommendations.In this relationship, Digital Planning is envisioned as more planning practice-oriented and is focused on arriving at factual results in a particular planning practice.It is more application-oriented and continues to build on the outcomes of the scientific PSScience work.
In both approaches, a quadruple collaboration is foreseen between governmental organizations, market parties, societal organizations/individuals, and educational/research institutes.Examples of the growing attention to digitalization in planning practice are provided by Hersperger et al. (2022), who looked into digitalization in land-use planning practices in Switzerland, Austria and Germany, and Christmann and Schinagl (2023), who reflected on the implications of digitalization for 'mundane' urban planning activities.Also, Sabri and Witte (2023), in their Special Issue on digital technologies in urban planning and management, highlight the urgency of addressing the planner's role in dealing with new technologies in the urban realm.
In the remainder of this conceptual paper, we will elaborate on the double-sided distinction and interconnection between Planning Support Science and Digital Planning and its consequences for planning practice.This fits our paper's primary goal to further enhance our understanding of the relatively new concept of digital planning and the questions still open for research and practice.For this, in Section 2, the conceptual framework of Planning Support Science will be presented and elaborated upon.In Sections 3, 4 and 5, the steps will be taken from this conceptual framework of Planning Support Science towards the new concept of Digital Planning.Moreover, based on this in Section 6, an integrated research and practice agenda for Digital Planning will be presented.In Section 7, we will come up with some conclusions and discussions.

Conceptual framework: from planning support science to digital planning
In the previous section, a distinction has been made between Planning Support Science (PSScience) and Digital Planning (DP), which are both also related to their predecessor of Planning Support Systems (PSS).It has been stated that PSScience and DP are distinctive on the one hand, although closely interconnected on the other, in which PSScience is envisioned as the scientific base of the planning practice-oriented Digital Planning.To elaborate further on this distinction and interconnection, we first have to clarify the conceptual framework of Planning Support Science (Fig. 1). 1rom this framework, three distinctive but interrelated notions can be distilled.The first is the role and position of 'Application' in connection to information and communication technologies (ICT) and planning support systems (i.e., 'Instrumentation').The second notion is a consequence of the first one and focuses on the interrelationship between each of the components within the framework.The third notion concerns the role of contextual factors in the framework.
To start with the first notion, one has to acknowledge that the prime focus within spatial planning, and as a consequence also in Digital Planning, is not with the supportive (technical) instruments but with the (practical) application.In other words, the prime question is not which instruments one will apply in a particular case but rather which problems or challenges one needs to address with the help of the planning activity (see also Jiang et al., 2019).As such, the application at hand is positioned at the top of the conceptual framework to indicate its primacy over the other components and as the starting point of further analysis.Nevertheless, in many cases in practice in which technology plays a prominent role, the starting point and prime focus are put on the role of the instrumentation, leaving the application component to be of secondary importance.See, for instance, the survey results on functionalities of planning support instruments presented by Jiang et al. (2021).Attention is then put mainly on the utility of the instruments, so their functional capabilities (the 'supplies'), instead of their usability, in other words, the question of what the instrumentation can contribute towards the identified application challenge (the 'needs').In contrast, within our conceptual framework, we consider the analysis of the role of the application component to be of prime importance.As such, not the instrumental utility is at prime stake, but foremost, the usability of instrumentation in the light of the identified application challenge. 2he second notion is a consequence of the first one.It has to do with the identification that each of the components within the framework is interrelated and exerts an influence on each of the others.For a further elaboration on this interplay, please refer to Geertman (2016).This interrelatedness implies that the working of each component depends not just on its intrinsic power or value but also on its relationship to the other components.Although these components are all distinguished in the conceptual framework as separate, bi-directional relationships exist between each of the three constituting components.For example, a particular sub-goal of Sustainable and Resilient Urban Futures ('Application'), like the transformation towards renewable energy production and consumption, asks in planning practice for a particular participatory governance setting ('Governance') in which all stakeholders involved are thoughtfully included because the consequences of this transformation will impact directly on their well-being (e.g., windfarm locations, hydrogen hubs, etc.).The associated supporting instruments ('Instrumentation') will have to comply with a range of associated criteria like transparency and visual appeal, showing possibilities instead of just restrictions, etcetera, which can result, for instance, in the application of a map-based design table.This specific instrumentation will affect the governance process, making it possibly more participatory, open-minded, inclusive, etc.A recent illustration is provided by Eilola et al. (2023), who researched the potential of 3D visualizations to support public participation and collaboration in urban and landscape planning.
The third notion concerns contextual factors.This indicates that both the outcomes of planning support and the process -the methodology to arrive at planning support-are determined by their contextual embedding and, therefore, require adaptation when transitioning to another context.Please refer to Geertman (2006Geertman ( , 2013) ) and Jiang, Geertman, & Witte, 2020 for elaboration.These contextual factors refer to factors likely to influence the other components in the framework, like characteristics of the policy process (e.g., time pressure), user characteristics (e.g., familiarity with technology or functional preferences), and political, institutional or cultural contextual factors.These contextual factors impact the appropriateness of a certain infilling of each of the three components and their interrelationships within the conceptual framework.For example, while a participatory planning approach in a democratic Western society might be considered well-fitting to tackle a particular application challenge like social sustainability, this might be entirely inappropriate or counter-productive in a more authoritarian society.So, contextual factors are unmistakably crucial in the proper working of the conceptual framework.
At the centre stage of the conceptual framework, it is envisaged that research, education and practice work together closely within Planning Support Science to attain mutual goals and cooperate to strengthen the scientific outcomes of planning support and bring support for planning practitioners a step closer to reality (Geertman, 2016).
Bringing all the above notions together, one can easily relate the components of Planning Support Science to the definition of Digital Planning as presented earlier.To restate this definition in the components of the conceptual framework as described above, the main purpose of Digital Planning -as the practice-oriented equivalent of the scientificoriented PSScience-is formulated as heading primarily to improve the sustainability of cities ('Application') by making use of digital technologies ('Instrumentation') and by striving for an efficient, effective and inclusive planning process ('Governance'), and planning practice ('Contextual factors').
In the next section, the elaboration and operationalization of Planning Support Science into the concept of Digital Planning are presented along the lines of the three separate components within the conceptual framework and briefly illustrated through examples of recent scientific work.This is despite our acknowledgement that these components interact and contextual factors impact each of them and their interrelations.The following sections discuss what this implies for Digital Planning in real-world practices.

From PSScience towards digital planning: the application component
The first mentioned component in the PSScience conceptual framework refers to the application field, which is the object-oriented goal and which, in Digital Planning, can be referred to as 'Sustainable and Resilient Urban Futures.' Planning is an intrinsically future-oriented activity focused on urban and regional issues, in which the general quest for 'sustainability' is more often than not at the core of the activity (Geertman, 2016;Witte & Hartmann, 2022).In our perspective, 'Sustainable and Resilient Urban Futures' first of all refers to an urban environment in which an appropriate balance is sought between ecological goals ('planet'), economic prosperity ('profit') and social justice ('people') (see also United Nations' Sustainable Development Goals, or the before-mentioned Planner's Triangle by Campbell).This 'sustainable and resilient urban future' is not a fixed end state, nor uniform in place or time.Instead, it consists of dynamic processes, flows of people, traffic, sewage, information, knowledge, etcetera, each with its own pace and dynamics.These will not materialize in a fixed end state but in interacting and continuously changing flows, heading for a more or less sustainable balance.Nor is this 'sustainable balance' itself uniform in place or time.Sustainable solutions in one context are only properly transferable to other contexts with profound adaptations to the specifics of that particular context.
For instance, in several Western European countries, relatively successful governmental investments in public transportation have been implemented to counter car congestion and improve overall job accessibility.However, the implementation of the same kind of governmental intervention in the context of the United States would be rather unthinkable, not least given the infringement of private autonomy, the sheer scale and distances, and the primacy of the privately owned car in the American as compared to the Western European continent.Research shows considerable differences across continental contexts related to the organization of their respective transport systems (e.g., Wiegmans et al., 2018).So, distinctive urban contexts show substantial differences in, among others, historical background, pressure on economic prosperity, expectations of social justice, determination to achieve ecological goals, cultural appreciation and institutional settings.For instance, it is difficult to compare the well-operationalized nationwide network of highspeed rail trains in China (Yang et al., 2018) with a hugely hampering high-speed rail network system in Europe without acknowledging political, institutional and administrative differences between these contexts.Nevertheless, 'Sustainable and Resilient Urban Futures' is a complex application field within which a continuous and challenging range of trade-offs has to be made between ecological, economic and social goals, which asks for a precise attunement and dedication to the specifics of a particular context (Geertman, 2016).Therein, one has to acknowledge the need for sufficient flexibility and dedication to the application challenges at hand to become supportive in planning practice.For example, Snel et al.'s work on risk perception and responsibilities concerning flooding showed this need for flexibility and dedication (Snel et al., 2021).It was shown how individuals can and will differ in their perception and interpretation of the problem at hand (a wicked problem like 'flooding'), in their perception of who is responsible for what (personal versus public responsibility), in the role of underlying concepts like 'social justice' and 'fairness', and in what kind of supportive tools are needed to become effective, given the diversity of perceptions.In short, contextualized flexibility and dedication are needed to tackle these wicked application challenges.In this regard, several distinctive analytical concepts have been developed and applied, like a Flow perspective (input-output model of information, goods, water, etc.; e.g., Yang et al., 2018), a Time perspective (distinctive speeds of change in urban systems for travel, land-use, employment, etc.; e.g., Chai et al., 2022) or the Ecological Footprint (ecological impact of activities via resources or waste).Also, planning-specific concepts have been developed, such as the Planner's Triangle (Campbell, 2016), in which trade-offs between economic development, environmental protection, equity, and social justice are foreseen and required.Practice, however, shows the complexity of making trade-offs between sustainability goals.For instance, while particular neighborhoods in American cities (e.g., the Pearl District in Portland) have become much more sustainable in an ecological sense (e.g., the introduction of sidewalks, bike lanes, low-speed streets, trees, terraces, etc.), at the same time, from a notion of social sustainability, it has resulted in increased gentrification and a neighborhood just for the 'happy few'.Another planning-specific concept of relevance is Urban Metabolism (Dijst et al., 2018).In this concept, a range of elements (drivers, constraints, facilitators) like ecology, economic forces, human behavior, material flows, energy, etc., are linked together and interact with each other to arrive at outcomes which show to be more or less preferred from an overall sustainability perspective.
To summarize, out of this short elaboration on the application component in the conceptual framework of Planning Support Science, several implications have shown relevance for the concept of Digital Planning.First, there is a need for a much more encompassing perspective on urban sustainability.The ecological perspective is relevant, as are the economic and social perspectives.Also, the notion of 'spatiality' expressed by Lefebre (1991) is relevant from a spatial planner's point of view (see also Jiang et al., 2019).Second, besides this encompassing perspective, one has to identify a serious need for an integral perspective, in which the mentioned perspectives are connected and especially interconnecting with each other.As the example of urban metabolism shows, complex trade-offs have to be made in this interconnection between ecological, economic, social, and spatial perspectives (Dijst et al., 2018).Third, as seen before, this integral perspective requires sufficient flexibility and dedication to the application challenges to become supportive in planning practice.
In general, it can be stated that all these 'lessons' for Digital Planning are very much in accordance with one of the main outcomes of the research in the Handbook of Planning Support Science (Geertman & Stillwell, 2020) concerning the need for strengthening the knowledge base on the application field of 'Sustainable and Resilient Urban Futures', to become better equipped to perform the planning supportive task.

From PSScience towards digital planning: the governance component
The second mentioned component in the PSScience conceptual framework refers to the governance field of 'Spatial Planning'.In general, spatial planning refers to a governance field by the public sector, which, in collaboration with the private sector and civil society, influences the organization of space and place and the activities of people at various spatial or policy scales.This governance field has undergone substantial changes in the past decades, significantly impacting the supporting role of information, knowledge, and instruments.For a historical-theoretical elaboration, please refer to Geertman (1996).Up till the 1970s and 1980s, spatial planning was foremost a rational governmental activity performed by well-educated planning experts.Based on extensive scientific research and personal creativity, they drew up a blueprint for the foreseen future end-state of an area to be implemented accordingly.An optimistic belief in the malleability of society and its spatial organization is the basis of this approach.In the 1980s and 1990s, due to fundamental changes in society (e.g., democratisation; financial crisis), this optimistic belief turned around to recognising a range of uncertainties and acknowledging the overall complexity of spatial planning activities, dealing with so-called 'wicked problems' (Rittel & Webber, 1973).This resulted in a 'Communicative Turn' in planning from expert-oriented blueprint planning to process-oriented collaborative planning, accompanied by a recognition of the normativity of the planning activity.This turn is sometimes referred to as a transition from instrumental to communicative rationality (Habermas, 1984).Since then, spatial planning has no longer been envisioned as a solely governmental expert-oriented activity.Instead, it should incorporate opinions of a much wider diversity of actors from other governmental organizations, private parties, non-governmental organizations, and civil society (van Bueren, 2015).
Consequently, it is acknowledged that knowledge is no longer an absolute and unified truth but is socially constructed.This resulted in recognising distinctive forms of knowledge in the policy field of spatial planning: scientific versus lay or experiential, explicit versus implicit, etcetera (e.g., Healey, 2008).One of the biggest challenges was finding the best ways to harvest relevant knowledge from distinctive stakeholders (e.g., through participatory, communicative or collaborative planning) and appropriately integrating these different knowledge types (Rydin, 2007).
Besides these more practice-oriented planning challenges, one can identify some fundamental challenges within current planning practice that require a solution.One is the procedural and foremost short-term orientation of present-day planning (e.g., Böhme, 2023).The other concerns the current dominance of participatory planning as a kind of 'One Size Fits All' governance style.
First, it is generally acknowledged that spatial planning in its current state has become somewhat procedural and short-term oriented.As we have seen, before World War II in Western societies, spatial planning foremost had a substantive focus: the planner, as a substantive expert, is responsible for the design of a complete neighborhood, including houses, street patterns, greens, facilities, etcetera.With the emergence of the rational decision-making model in the 1950s/1960s and the communicative/participatory planning style from the 1980s onwards, this substantive focus was redeemed to be more procedural.However, in light of present-day sustainability goals, there is an urgent need for a close linkage between procedural and substantive focus.For a theoretical justification for bridging this substantive-procedural dichotomy, please refer to our previous research in Hartmann and Geertman (2016) and Witte et al. (2021), where we argue in favor of an integrated approach out of a need to implement both foci in collaboration to arrive at proper materializations in practice.This plea can also be (partly) found in Fainstein's proposition for a Just City Theory (Fainstein, 2011).
Furthermore, with the transformation of the rational decisionmaking model into a communicative/participatory planning style, the horizon of the planning activity has also become remarkably short.In light of sustainability goals, however, there is an urgent need to consider the long-term consequences of present-day decisions.This is a plea for future-oriented research ('Futuring') and a closer connection between short-term decisions and long-term perspectives.For further justification, please refer to one of our previous studies (Pelzer et al., 2015), where we plea for more attention to future-oriented research, not at least because this offers a context for present-day decisions and in that offers the possibility to anticipate on ongoing and future expected developments.
The second fundamental challenge within current planning practice that asks for a solution is the apparent dominance of participatory planning.In present-day Western society, participatory planning seems like a 'One Size Fits All' governance style that dominates over the power of expertise of professional experts, including planners.This dominance can be associated with the earlier-mentioned transformation of the comprehensive-rational decision-making model into the communicative/participatory planning style.Although, in some instances, the opinions of those directly involved are indispensable or at least very helpful and valuable from the perspective of the democratic legitimacy of planning interventions, experts are equally needed to arrive at proper solutions in other instances.Proper spatial planning needs a sufficient balance between the contribution of experts and lay people, in which sometimes the one and sometimes the other should be in the lead.Please see Rydin and Tate (2016) for a theoretical elaboration on this balance.For a more planning practice-oriented elaboration on how to deal with this balance between experts and laypeople, please refer to one of our previous studies (Staffans et al., 2020).Therein, the set-up of 'goals', 'visions', and 'plans' were considered interrelated discussion points in interactive design sessions, positioned within a so-called Big Room where we investigated how short-term decisions and long-term perspectives could be connected.The proper balance between the contribution of experts and lay people at distinctive moments in the planning process was at stake here, too.For another example of how short-term and long-term planning can be interrelated in which experts and lay people contribute, please refer to a translation for strategic spatial planning of Latour's Actor-Network Theory (Rydin & Tate, 2016).
In summary, out of this elaboration on the governance component in the conceptual framework of Planning Support Science, several implications of relevance for Digital Planning can be taken.First, it should be acknowledged that knowledge is no longer an absolute and unified truth but is socially constructed.This should result in recognition of the value of distinctive forms of knowledge in planning: scientific versus lay experiential; explicit versus implicit.Appropriate harvesting and integrating these distinctive knowledge types can be considered a considerable challenge within Digital Planning (see Geertman, 1996).Second, the present-day procedural and foremost short-term orientation of planning asks within Digital Planning for a transformation into one in which there is a close linkage of procedural and substantive focus in the light of sustainability goals (Hartmann & Geertman, 2016;Witte et al., 2021).This is a plea for a closer association and collaboration between 'research' and 'design'.Moreover, this is a plea for more future-oriented research and a closer connection between short-term decisions and longterm perspectives within Digital Planning (Pelzer et al., 2015).Third is a plea within Digital Planning to dedicate the appropriate planning style to the application challenge instead of accepting the dominance of the participatory planning style.Several alternative planning styles can be more appropriate given the application and specific planning circumstances (Geertman, 2016).Pan et al. (2022) also stressed this point more recently and called for a more inclusive and contextualized participatory development process related to PSS.Fourth, an overall recommendation for Digital Planning is to accept inherent uncertainties in planning because most matters are impossible to foresee completely.Flexibility is vital here: anticipate but keep as many options as possible open to the future.This is also in accordance with the renewed attention to the long tradition of scenario planning (e.g., Debnath et al., 2024;Geertman, 1996;Goodspeed, 2020).

From PSScience towards digital planning: the instrumentation component
The third component mentioned in the PSScience conceptual framework refers to its instrumentation, summarized as Informationand Communication Technology (ICT) and Planning Support Systems (PSS).In the introduction, we already defined PSS and noted its origins.In follow-up, one has to acknowledge that computer systems for planning support are known for their long-lasting but not very influential history.In the 1970s, Lee (1973) summarized the fundamental shortcomings ('seven sins') of large-scale models heading for policy support (e.g., black boxes, too comprehensive, too big data hungriness), something that was reconfirmed in a study 20 years later (Lee, 1994).Unsurprisingly, others confirmed the discrepancy between the demand and supply of planning support systems in the same years.Klosterman (1997) noted that 'Instruments for planning support are no better developed now than they were ten years ago', and the godfather of PSS -Harris-stated at the same moment in time that 'planners and designers have remained at best distrustful, or at worst downright antagonistic, towards computer-based models of support' (Harris, 1999).In the follow-up years, Geertman andStillwell (2003, 2009) conducted a range of worldwide PSS studies, and Vonk et al. (2005) identified 74 bottlenecks that appeared to hinder the uptake of support instruments in the policy environment of planning.A decade later, we were able to start showing more positive evidence about this taking-up (te Brommelstroet et al., 2014;Pelzer et al., 2014) nevertheless, for a complete uptake in planning practice, there still appears to be a long way to go (Geertman & Stillwell, 2020).
This substantive delay in uptake concerns some long-lasting controversies on applying technology in planning practice.For some, technology is considered 'the holy grail', while others envision technologies as playing fields for 'nerds'.However, presently, in planning practice, a more nuanced picture of the support function of instruments seems to emerge.First, from a recent inventory on PSS in planning practice, we gradually identified a more favourable opinion on PSS' supportive role in planning (Geertman & Stillwell, 2020).It was shown that PSS have achieved an important position in an increasing diversity of PSS application fields (professionalization).This was confirmed through a questionnaire we performed among 300 CUPUM (Computational Urban Planning and Urban Management) conference participants over the past years (see Jiang, Geertman, & Witte, 2020).It was shown that PSS is increasingly applied in a wide range of policy fields like Transport and Mobility, Housing, and Economic, Social, or Environmental Affairs.Within those policy fields, the emphasis, in particular, was on analyzing and modelling exercises.Second, the previously mentioned inventory on PSS in planning practice (Geertman & Stillwell, 2020) also showed that the sub-fields of PSS, smart city, and big data (analytics) are increasingly integrated.Given the overwhelming attention to developments concerning smart city and big data, this integration can catalyse the application of technology within urban planning.Third, the inventory clearly shows that technology should be handled selectively: sometimes, it will be helpful, and sometimes superfluous or even obstructive.To provide an example of both, in a design workshop in Utrecht in the Netherlands organized in 2015, it appeared that while the research-oriented planners welcomed the functionalities of a MapTable very much, in particular their analytical and visualization utilities; at the same time, the design-oriented planners and designers felt highly restricted in their expressional capabilities with the help of the same MapTable technology (see Pelzer & Geertman, 2014).Fourth, also taken from the mentioned handbook, the earlier identified contextual factors increasingly play an essential role in the scientific and practice-oriented discussions concerning planning support.This is another expression of the maturation of this field of science (Geertman & Stillwell, 2020).Fifth, out of several contributions in the Handbook of Planning Support Science, it appears there is an increasing acknowledgement of the need to consider application, governance, instrumentation and context in an integrated way (Geertman & Stillwell, 2020).This indicates the need for closer collaboration between governmental institutes, market parties, knowledge institutes, and civil society in the fields of PSScience and Digital Planning.
Hardly mentioned in the Handbook of Planning Support Science (Geertman & Stillwell, 2020) but increasingly prominent in technology discussions is the role of artificial intelligence (AI), which is important in urban planning.In brief, AI can be defined as the machine mimicry of human cognitive traits and actions in learning and problem-solving activities such as communication, reasoning, knowledge, perception, and planning (e.g., Yigitcanlar et al., 2020).Several authors note the growing prominence of AI as a crucial technology to transform and reshape the field of urban planning (Peng et al., 2023).However, it has also been identified that AI utilisation for urban planning is a relatively understudied area of research, particularly regarding the gap between theory and practice (Son et al., 2023).Others, like Wang et al. (2023), focus on the potential of AI for planners that can offer planners, according to them, to gain deeper insights into complex systems (e.g., land uses and transportation) that make up modern cities.This can help them to make more informed decisions about issues in urban planning.Moreover, AI can help address some of the limitations of traditional urban planning methods, such as handling large amounts of geospatial and social data quickly and efficiently in near real-time.Additionally, using traditional methods, AI can help identify patterns and trends that might be difficult or impossible to detect.Other examples of the added value of AI can be found in the assistance of urban planners to provide the best possible and equitable networks for larger traffic management and public transportation (Sanchez et al., 2023).It can help urban designers to respond to and design certain environments, creating more efficient communities.Moreover, AI can predict and analyse air quality within cities, publishing results for pollution levels, fossil fuel particle density, and future levels, where these provide invaluable input for informing urban administrations and policymakers.Despite this wide range of examples of potential benefits of AI in urban planning, there are challenges and concerns to consider.In general, it should be acknowledged that AI theory and practice in urban planning is still in its infancy despite the increasing number of successful and, in many cases, not-so-successful examples (Son et al., 2023).Shortly, it should be acknowledged that the convergence of artificial and human intelligence is crucial to address planning issues adequately and achieve smart and sustainable developments (Son et al., 2023).
In summary, out of our elaboration on the Instrumentation component in the conceptual framework of Planning Support Science, several implications are relevant for Digital Planning.First, technology should be handled selectively, which will sometimes be (very) helpful, while at other times, it will be superfluous or even obstructive (see Pelzer & Geertman, 2014).Second, contextual factors are playing an increasingly vital role in the success of the proper application of instruments in planning practice.Factors like the dominant planning style, the policy model, the content of the planning issue, the user characteristics, the characteristics of the planning and policy process, the political context, and the specific characteristics of information, knowledge and instruments all show to play a decisive role in the support function of planning, both individually and in mutual interaction.For an elaboration, please see Geertman (2006).Therefore, there is a severe need for careful identification of the relevance of each contextual factor in a particular circumstance and its interplay with other factors or components.Empirical research on these contextual factors and their impact is still very scarce.See our research in Jiang, Geertman, & Witte, 2020 for a review and overview.For an empirical study on the role of contextual factors in policy-making, please refer to our research in Tomor et al. (2019) and Tomor and Geertman (2020).Third, the handbook mentioned shows growing acknowledgement that 'the what' -the instrument-and 'the how' to handle the instrument -the methodology-are closely interconnected.In history, one can identify distinctive times when planning has been dominated primarily by methods from either end of a spectrum ranging from purely qualitative methods, like social discourse analysis, to purely quantitative methods, like mathematical modelling.Over time, believers and nonbelievers have sought supremacy in one or the other approach.With the increase in the diversity and availability of data, mixed-method approaches are gaining substantial ground.For an example, see the field of 'Geodesign' (e.g., Pelzer et al., 2015).Therein, both modelling exercises (quantitative), like those adopted for forecasting future trends, and deliberative design approaches (qualitative), like those used for developing future spatial scenarios, are combined to contribute to worthwhile outcomes (see Steinitz, 2017).Therein, the statement made before in relationship to AI within urban planning that it is crucial to acknowledge the convergence of artificial and human intelligence to address planning issues adequately is of general relevance here, too.Fourth, based on all the previous, it appears there is an increasing acknowledgement of the need to consider application, governance, instrumentation and context in an integrated manner, which is a clear indication of the need for close collaboration between governmental institutes, market parties, knowledge institutes, and civil society (Geertman & Stillwell, 2020).As mentioned before, this is an important conclusion for the planning practice-oriented field of Digital Planning, too.

Digital planning: an integrated research and practice agenda
Taking the previous notes together, one can distil an integrated research and practice agenda on Digital Planning.'Integrated', as the field of Digital Planning requires close collaboration between governmental organizations, market parties, societal organizations/individuals, and educational/research institutes.
There is a need for a more encompassing and long-term perspective on urban sustainability, connecting the ecological, economic, social and spatial perspectives.Although these perspectives are distinctive and different, in the end, there is a need for one integral perspective in which divergence is turned around into convergence.As indicated, the implied trade-offs are complex and require sufficient flexibility and dedication to the application challenges.Ultimately, however, this will strengthen our knowledge base in the application field of 'Sustainable and Resilient Urban Futures' and help us better perform the planning supportive task.This also requires handling a diversity of data, information, and knowledge categories, both scientific and lay experiential, as well as explicit and implicit knowledge.To handle these will require appropriate methodologies, both in research and in practice.Research will have to result in more knowledge on how to make appropriate trade-offs with the help of all available knowledge, and gaining insights into future-oriented consequences of short-term decision choices will be a particular challenge.In practice, it will imply increasing attention to a more substantive focus on sustainability goals to compensate for the current dominance of the more procedural focus.In the end, procedural and substantive foci must be handled harmoniously.
Therein, the present dominance of participatory planning must be reconsidered.Distinctive contexts ask for appropriate and dedicated planning styles in which alternatives like the Just City Theory or the Actor-Network Theory will also have to be explored in terms of their appropriateness.Ultimately, this will comply well with the quest for flexibility in governance and technology.As indicated, the technology will have to be handled selectively.Empirically testing in distinctive contextual circumstances when and why specific instrumentation works well or not will be a vast but valuable challenge.Different circumstances play a significant role: who are the crucial actors; what are their dominant knowledge categories and experiences; what is the dominant policy setting; which instruments are available and which could be appropriate?The state of each of these contextual factors should be identified in each case, including the consequences of their interplay for the governance, the application, and the instrumentation.We need more appropriate knowledge; empirical research is scarce but highly needed.Mixed methods such as Geodesign can help perform such contextual research, not at least because it lacks inherent dominance of the quantitative over the qualitative methods or vice versa.Finally, to execute such a synthesized research and practice agenda, there is a need for close collaboration between governmental institutes, market parties, knowledge institutes, and civil society.This is an important conclusion for the more scientifically oriented Planning Support Science, but likewise for the more planning practice-oriented field of Digital Planning.

Conclusions and discussion
Digital Planning needs to deal with many challenges to fulfil an important role in planning practice.These challenges concern the proper operationalization of the goal of urban sustainability and the problematic internal trade-offs between its constituting parts: the ecological, economic, social, and spatial perspectives.This will imply handling a huge diversity of data, information and knowledge categories, both scientific and lay experiential, which will require appropriate methodologies in research and practice.For research inter alia, it will imply attention to methods for making trade-offs, future-oriented research ('Futuring'), and ways to build connections between long-term perspectives and short-term decisions.For practice, it will imply renewed attention to the substantive focus on urban sustainability and building connections between the substantive and the procedural foci.A broader perspective on underlying planning theoretical notions than the presentday dominant participatory planning style will be a prerequisite.For supportive instrumentation, this implies that the technology will have to be handled selectively and flexibly, which is very dependent on a range of contextual circumstances.To strengthen our knowledge base on this, the scarce empirical research should be extended, for example, with the help of mixed methods research.Finally, for the proposed synthesized research and practice agenda, there is a need for close collaboration between governmental institutes, market parties, knowledge institutes, and civil society (quadruple helix model).This is an important conclusion for the more scientifically oriented Planning Support Science and likewise for the more planning practice-oriented field of Digital Planning.
Still, these outcomes raise many additional questions and challenges in arriving at an appropriate infilling of the concept of Digital Planning.One of these concerns is the quest for an integral notion of sustainability with its inherent trade-offs.Such an integrated perspective is in sharp contrast to present-day specialization in science.However, both are needed.On the one hand, specialization, in other words, research focus, is needed to make substantial progress in science.On the other hand, collaboration between disciplinary specialists is needed to learn from each other and to become able to formulate answers to complex, interdisciplinary, wicked problems.However, this will imply overcoming disciplinary barriers in terminology, working methods, theoretical perspectives, etcetera, a skill that has to be taught in educational study programs, given that people usually tend to stick to their own -trustedstrand of thinking and working.
A further research challenge relates to the quickly upcoming research field of AI.Increasingly, experimentation concerning AI within urban planning practices, besides conceptual research of its potential and limitations, is occurring.In both instances, real-world AI applications are badly needed to support the proper introduction of AI to urban planning practice.We very much agree with Popelka et al.'s statement (Popelka et al., 2023, p.13), "the real impact of AI in cities is not on the technology but on its implementation in urban planning and design.It is in the plan-making process of cities that AI, e.g., in the form of machine learning, has its major impact".
Another challenge relates to the proposed recommendation of mutual alignment of application, governance and instrumentation.One consequence is the need for integrated educational study programs -of which just a few already exist worldwide -in which technological skills are connected to knowledge of application fields and governance styles.Another consequence is the need for research after the conditions and consequences of this mutual alignment within specific contexts, which will be quite a challenge in its own right.The quest for more attention to contextual factors is generally defendable but will complicate matters, too.For instance, this will stress the uniqueness of matters in planning practice, increasing costs.
Finally, another related challenge is the need for collaboration between different parties like governmental institutes, market parties, knowledge institutes, and civil society.Until now, the practice has shown how difficult it is for these distinctive parties to agree on collaboration goals and desired outcomes.Individual agendas, power structures, and internal dependencies will impact such collaborations and possibly and undoubtedly problematize them.So, some fundamental challenges remain for Digital Planning to become a reality.
recently conducted a review to provide a state-of-the-art of 70 relevant open-source software tools for urban planning, showing the widespread possibilities of open-source applications.