Planning Practice and Research

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Planning Practice and Research

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Gaining insight in the development potential of station areas: A decade of node-place modelling in The Netherlands

To cite this Article: Peek, Gert-Joost, Bertolini, Luca and De Jonge, Hans , 'Gaining insight in the development potential of station areas: A decade of node-place modelling in The Netherlands', Planning Practice and Research, 21:4, 443 - 462 To link to this article: DOI: 10.1080/02697450701296247 URL: http://dx.doi.org/10.1080/02697450701296247

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Planning, Practice & Research, Vol. 21, No. 4, pp. 443 – 462, November 2006

ARTICLE

Gaining Insight in the Development Potential of Station Areas: A Decade of Node-Place Modelling in The Netherlands GERT-JOOST PEEK, LUCA BERTOLINI & HANS DE JONGE

Introduction In cities around the world the integration of transport and land use development at stations is high on the agenda, whether under the label of ‘Transit Oriented Development’ (TOD) as in North America, or merely as redevelopment of and around railway stations as in Europe and elsewhere (Bertolini & Spit, 1998; Cervero, 1998; van den Berg & Pol, 1998; Cervero, 2004; Dittmar & Ohland, 2004; Dunphy et al., 2005). Four sets of factors contribute to determining this upsurge of station area related urban projects. First and foremost are mounting concerns about the sustainability of ‘sprawling’ and ‘car-dependent’ urbanization patterns. The integrated development of railway networks and land around the nodes of those networks is seen as a way towards a more public transport and non-motorized modes oriented, concentrated urbanization pattern. The arguments are not just environmental (reduction of pollution, greenhouse emissions, land consumption etc.). Many local governments and citizens see this shift also as a badly needed mobility alternative for metropolises rapidly approaching, or already experiencing, traffic gridlock. A second set of factors triggering station area projects is of the new development opportunities provided by transport innovations such as the expansion of high speed railway systems (particularly in Europe and Asia) and light rail systems (as most notably in North America and Western Europe). These development opportunities are further compounded by the generalized transfer of distribution and manufacturing activities away from station areas and towards Gert-Joost Peek, Real Estate & Housing, Faculty of Architecture, Delft University of Technology, PO Box 5043, 2600 GA Delft, The Netherlands. Email: [email protected]; Luca Bertolini, AMIDSt, University of Amsterdam, Nieuwe Prinsengracht 130, 1018 VZ, Amsterdam, The Netherlands. Email: [email protected]; Hans de Jonge, Real Estate & Housing, Faculty of Architecture, Delft University of Technology, PO Box 5043, 2600 GA, Delft, The Netherlands. Email: [email protected] ISSN 0269-7459 print/1360-0583 online/06/040443–20 Ó 2006 Taylor & Francis DOI: 10.1080/02697450701296247

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Gert-Joost Peek et al. more peripheral locations or new, dedicated freight interchanges. Third, there is a wish to boost the competitive position of cities as places to live, work and consume through new large-scale urban projects. Many of these projects typically show a dense mix of office, retail, leisure and housing located around stations. High-speed railway station areas in European cities have been in particular, the theatre of such initiatives in recent years. Fourth and last is the ongoing privatization process or at least a move towards greater market orientation of transport companies. One of the consequences is that transport infrastructure and service providers are increasingly looking for ways to recapture the accessibility premium they help to create. Characteristically this implies development of commercial activities within stations and redevelopment of land above or around stations. Many Asian cities have a long tradition in this respect, but the trend has been expanding in Western Europe and North America as well. For all its potential, the integration of transport and urban development at station areas is also a very complex planning challenge. Station areas are, ambivalently, both nodes and places (Bertolini, 1996): nodes of networks, and places in the city. Station areas are (or may become) important ‘nodes’ in both transport and non-transport (e.g. business, consumption) networks. On the other hand, station areas also identify a ‘place’, a both permanently and temporarily inhabited area of the city, a dense and diverse conglomeration of uses and forms accumulated through time, which may or may not share in the life of the node. Accordingly, a multifarious array of both node- and place-based actors crowd station area redevelopment processes. The local government and the railway company are two characteristic ones. Depending on the local context, also other actors will have a decisive role. These include different levels of the public administration, different transportation companies and market actors: developers, investors, end-users. Furthermore, and particularly at station locations set in dense, historically stratified urban districts, local residents and businesses may also have a significant stake. The objectives of this heterogeneous array of actors are often conflicting and at best uncoordinated. They may range from transforming the station area into a smooth transfer machine for passengers, to a vibrant business centre for the city; and from becoming a node connecting all transportation networks of different scale levels, to a new kind of market square delivering opportunities for all sorts of human interaction. The shared base of these often high expectations is the idea of synergy between the node and place features of the station area. The term synergy derives from the Greek ‘synergos’ and indicates collaboration in order to reach a common objective or achievement. Synergy makes the whole more than the sum of its parts, and it can be defined as the added value of coherence as result of collaboration. Insight into the characteristics of the complex, node-place dynamics of station area development, and the opportunities for and threats to synergy between node and place developments seems a necessary precondition for effective action. For this purpose, since the second half of the 1990s a number of so-called node-place models have been developed in The Netherlands. In this article we will discuss some significant examples. The focus will not so much be on the details of the individual models, but rather on the underlying concepts and their evolution. The aim is twofold. First and more in general, we want to show what the possibilities 444


Node-Place Modelling of Stations in The Netherlands are of a node-place approach to station area planning. Second, we want to show how understanding of the changing needs of those involved in actual station area development practice is a crucial condition for effectiveness of the approach and has influenced its evolution. In the following section we will introduce the original node-place model. In the successive sections, we will respectively discuss examples of applications of the model, extensions and modifications, station area typologies, interpretations of the model, and validations. We will begin each section by identifying the central aim of the exercise, we will then briefly describe its content, and conclude by assessing if it achieved its aim and what are possible explanations for this. In the overall conclusions, we will discuss the worth of the approach, the scope for improvements, and the relevance for contexts other than The Netherlands. The Node-Place Model Many models discussed in this article are related with the node-place model proposed by Bertolini (1999). The basic assumption underlying Bertolini’s nodeplace model is that improving transport provision in a station location (or its nodevalue) will, because of improved accessibility, create conditions favourable to the further intensification and diversification of activities there. In its turn, intensification and diversification of activities in a station location (or increase in its place-value) will, because of growth in the demand for connections, create conditions favourable to the further development of infrastructure there. The emphasis on ‘conditions’ is important, as it implies a distinction between the existing of a development potential, and its actual realization, which will by and large depend on other than transport and land use features. Realization of the potential may or may not occur, and development can take different directions. Five ideal-typical situations can be distinguished in the model (Figure 1). Along the middle line are ‘balanced’ locations, where node and place values are equally strong. At the top of the line are areas ‘under stress’. Here the intensity and diversity of both mobility flows and urban activities is maximal. This indicates that the potential for land use development is highest (strong node) and that it has been realized (strong place). The same can be said about the potential for transport development. However, these are also locations where the great concentrations of flows and activities mean that there is an equally great chance of conflicts between multiple claims on the limited space and that further development might become increasingly problematic. Many central stations fall in this category. At the bottom of the middle line is a third ideal-typical situation, represented by the ‘dependent’ locations. The struggle for space is minimal here, but the demand for transportation services from area residents, workers and other users and the demand for urban activities from travellers are both so low that supply can be held in place only by the intervention of other factors (such as peculiarities in the topography of the area or in the morphology of the transportation networks, external subsidies etc.). Small-town stations often fall in this category. Finally, two ‘unbalanced’ situations can be identified. On one side—at the top left of the diagram—are the ‘unbalanced nodes’, areas where transportation supply is relatively much more developed than urban activities (think of a newly opened stations on the urban fringe). On the 445


Gert-Joost Peek et al.

FIGURE 1. The node-place model.

other side—at the bottom right of the diagram—are the ‘unbalanced places’, where the opposite is true (think at an historic, relatively difficult to access city centre). The latter two are particularly interesting station area-types. It can be assumed that they will show a strong tendency to move towards a more balanced state. However, and this is crucial, this could always happen in two radically different ways. An ‘unbalanced node’ could either increase its place-value (for instance by attracting new property development) or decrease its node-value (perhaps through reduction in the level of transportation services). A reverse reasoning can be applied to an ‘unbalanced place’: either the level of connection will be increased or a lower density and possibly qualitatively different functional mix will be developed. Applications As an example of application of the node-place model we consider the exercise described in van Bakel (2001; see Figure 2). The analysis was carried out for the Delta Metropolis, an independent association promoting policy integration at the scale of the Randstad, the highly urbanized West of The Netherlands (Groenemeijer & Van Bakel, 2001). The example is not just interesting as a concretization of the node-place model, but also as an example of the sort of policy issues it might help address. In the upper left graph, 96 (potential) transportation nodes in the Randstad are positioned based on their present (base year 2000) node (vertical) and place 446


Node-Place Modelling of Stations in The Netherlands

FIGURE 2. Application of node-place model for the Delta Metropolis (van Bakel, 2001, pp. 30 – 32).

(horizontal) value. The node value is a measure for the accessibility of the locations and is determined by the type of connections by rail (from high speed train to tram) and road (from highway to local road) and the number of directions connected. The place value is a measure for the intensity of the activities at the location. Adding up the total of inhabitants and jobs within a radius of three kilometres of the node and dividing this by thousand calculate it. In the upper right graph the same 96 locations are positioned based on their potential (base year 2030) node (vertical) and present place (horizontal) value. The potential node value is based on the implementation of all planned governmental investments in infrastructure. Next, the lower left graph shows the space available for development of the 60 most promising locations based on planning and environmental restrictions. The radius of the circles relates to the comparative amount of available space. Finally, in the lower right graph the potential node value (vertical) of these 60 locations is placed against the potential place value (horizontal). The latter is measured by the possible number of inhabitants and jobs based on the space available at the location. The analysis shows that a lot of 447


Gert-Joost Peek et al. locations in the Randstad have the potential for developing into a more balanced situation by raising their place value. With help of the model, the Delta Metropolis association wanted to explore the implications of current spatial development concepts for the Randstad, and especially show the worth of a Randstad-wide view on these concepts. In particular, the application was meant to help select the most promising locations for urban development aimed at exploiting up-and-coming investments in infrastructure. In the end, however, the exercise did not have a direct impact on decision making. The biggest obstacle, according to the Delta Metropolis association, was that the cross-sector, Randstad-wide view underlying the approach sharply contrasted with the high administrative fragmentation. When the previously described exercise was carried out, a window of opportunity for more integration seemed to open, and the Delta Metropolis association hoped to exploit it. However, the window closed shortly after, and remains closed to this day (personal communication with Delta Metropolis representative L. Groenemeijer, 2006). Extensions and Specifications Different applications of the node-place model led to different ways of measuring the node and place value, and sometimes led to more fundamental changes. We discuss two examples. The first example is an extension of the model by Meijers (2000; Meijers et al., 2002), which was commissioned by NOVEM, an agency of the Dutch Ministry of Economic Affairs. The aim was providing recommendations for a national policy on transportation nodes, with a focus on sustainable mobility impacts. The second example is an elaboration of implications for real estate values by van der Krabben and van Rooden of Buck Consultants International (2003), which was commissioned by Connekt, a public – private innovation network for traffic and transport. The aim of this second example was providing a model by which the potential for real estate developments at transportation nodes could be predicted. Meijers (2000) provides an overview of node-place models until then and adds a third dimension: the ‘interaction’ value of the station area. This third value is seen partly as a derivate of the node and place values, and partly as an independent variable, related to the level of ‘urbanity’ of the area. The complementarities of activities and functions in the area are largely responsible for this ‘urbanity’. Meijers (pp. 53 – 54) distinguishes three types of complementarities: 1. Temporal complementarities, as result of the concentration of activities with matching temporal schedules; 2. Functional complementarities, as result of the concentration of functionally matching activities; 3. Location complementarities, as result of complementary transportation functions. Meijers concludes that a national transportation node policy should be aimed at creating locations that are nodes in physical, as well as spatial-functional and 448


Node-Place Modelling of Stations in The Netherlands social and institutional networks. More specifically, he stresses the importance of considering the transportation node as a potential meeting place. This particular point has since become widely accepted as fro instance documented by the current National Spatial Planning Strategy. This states that ‘In the national urban networks, the creation of easily accessible, attractive city centres with a variety of functions and public facilities is crucially important. . . . It is particularly important to develop [these] city centres around infrastructure nodes’ (Ministry of Housing, Spatial Planning and the Environment, 2006, p. 9). The aim of Buck Consultants International (2003) was converting the original node-place model into a model for predicting the effect of an improvement of accessibility on the value of real estate (offices). The node value is measured by the potential accessibility of the location based on proximity of types of road infrastructure, rail connections and frequencies and distance to an airport. The place value is measured by the product of the real estate value, expressed by the market rent divided by the yield, and the present and potential real estate programme. The authors assume there is an optimal balance between the node value and the place value. Figure 3 shows this optimum as a parabolic curved line because it is expected that the influence of raising the node value will decrease along with increase in the level of the place value. In Figure 3 two ways of getting to a new optimum on a higher level are shown. On the left hand investments in infrastructure have led to a higher node value of a location A: A1 to A2. This leads to a potential higher place value: A2 to A3. The position of location A in the real estate market could, however, prevent it reaching the new optimum A3. On the right hand investments in real estate have led to a higher place value of a location B: B1 to B2. This leads to a potential higher node value: B2 to B3. Planning policy or environmental restrictions, could, however, prevent the location reaching the new optimum B3. Due to the limited data-set the model was based on it was not possible to generate reliable estimates of the effect of improvement of accessibility on the value of real estate. However, the results were encouraging enough for the challenge being taken up by a new study based on a much larger data set (Debrezion Andom, 2006). In statistical terms the results of this latter exercise are promising (i.e. significant

FIGURE 3. Operationalization of the node-place model by Buck Consultants International (2003, pp. 17 – 19).

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Gert-Joost Peek et al. relationships are shown). However, the model has yet to be applied in planning practice. Both these examples show that the original node-place model is open to extension and specification and therefore has potential use within the different fields connected to the multitude of desired futures that actors involved foresee for station areas (Meijers, 2000; Meijers et al., 2002). Meijers shows the value of the node-place model as a theoretical model in the field of social policy by emphasizing the human interaction value, and thereby relating it to the ideal of a station area as modern market square. The research of Buck Consultants International (2003) tries instead to apply the model to the field of real estate development, relating it to the ideal of a station area as business centre. In terms of applicability, the first model served its theoretical purpose by addressing the significance of the transportation node as meeting place, but it did not led to immediate practical results. The second model resulted in further research that is expected to have a direct impact on planning practice. Typologies The idea of using the node-place approach to order a large group of station areas showed very appealing to policy makers as a tool for setting priorities in policy and investments. The Ministry of Housing, Spatial Planning and the Environment and the Ministry of Transport, Public Works and Water Management commissioned a series of researches aimed at the development of a nationwide typology of ‘nodal areas’. Underlying idea was getting insight in the relationships of competition and complementarity between different types of urban nodes, and using such insights to identify policy priorities. We will discuss one of these studies followed by another example of a typology that was developed by the Dutch Railways. The aim of the latter was defining a concern-wide station typology, which combined transportation, real estate and consumer service features of a station and its surroundings, to support company strategy development. In 2000 the consultancy firm Goudappel Coffeng was asked by the Ministry of Transport, Public Works and Water Management to develop a national map of nodal areas in order to clarify the notion of the concept of the transportation node as an urban centre and starting an interdepartmental discussion concerning the need and usefulness of the concept (Goudappel Coffeng, 2000). Based on an earlier study (VHP & Goudappel Coffeng, 1999) the node value was defined by the highest spatial level served by transportation modes connecting the location, e.g. the Northwest European scale for a high-speed train service. Six spatial scales were distinguished, ranging from subcontinental (Northwest Europe; average radius 1000 km), national (300 km), subnational (100 km), regional (30 km), agglomeration (10 km) and urban (3 km). This spatial hierarchy was also used to characterize the place value by estimating the scale on which the activities at the location function, e.g. the Northwest European scale level for an international business district function. Based on this hierarchy, 92 transportation urban nodes in The Netherlands were classified according to the combination of node and place value. 450


Node-Place Modelling of Stations in The Netherlands Critics have remarked that this very hierarchical, top-down approach, while interesting, bears some dangers if its limitations are not well understood. First, it is tempting, but disputable, to use this descriptive classification normatively, in the sense that node and place features of a location should, by definition, be of the same level. The Buck Consultants International (2003) study showed instead that there could be legitimate explanations why node and place of a location are not on the same level, e.g. limitations of markets and of legislation. Also Bertolini (1999) talks about ‘conditions’ for development, rather than a necessary evolution. Second, such a typological inventory is like a snapshot, it does not show changes, but only documents a status quo at a certain moment. The typology was developed within the context of background work for the national policy documents on spatial planning and transport planning then under preparation. The ministries’ original aim was to translate it into a prescriptive framework of how to match spatial and transport interventions. However, this aim proved to be too ambitious, because of the very complexity of this relationship but also, and importantly, because at odd with the ongoing shift toward a more decentralized, bottom-up view of planning in The Netherlands. However, the typology did provide a useful base for debates between the two ministries and eventually helped pinpoint the planning concept of city centre formation around infrastructure nodes in the two documents in a reciprocally consistent way. A characteristic passage from the National Spatial Strategy has been already cited earlier. The Mobility Policy Document states in its turn: ‘during . . . downtown development, optimum utilization of the existing infrastructure and the potential of interfaces in this infrastructure is one of the primary goals. On the other hand, when developing infrastructure, possibilities for . . . creating downtown facilities are also anticipated’ (Ministry of Transport, Public Works and Water Management, 2006, pp. 9 – 10). A second example of typology is the one developed by the Dutch Railways. In the light of the strategic Product-Market Vision 2010/2020 (NS Commercie, 2001) the Dutch Railways were looking for a concern-wide station typology. Up until then each business unit (passengers, station services and real estate) used their own classifications, hampering intraconcern communication and strategy development. A base for a generic classification was found in the differences in micro and macro accessibility of a station. The micro accessibility was defined as the location of the station in relation to the city centre and three classes were distinguished: central, city edge and rural. The macro accessibility was based on the level of the train service: local, express and intercity. Combining these parameters leads to nine possible station types of which six were thought to be relevant in the Dutch context at that time (Holland-Railconsult & NS Commercie, 2001). Table 1 shows the resulting typology. The thus defined typology was applied by assigning all stations to the six types on the basis of 13 criteria that covered nearly all the variables of the classifications used by the business units. Then, on the basis of forecasts of the development of the micro and macro accessibility all the stations were again classified for the year 2010. The typology helped to develop common business strategies for the station locations. In general three basic strategies were put forward: focus on investment in real estate, which applied to type 1 and 2 locations; focus on investment in 451


Gert-Joost Peek et al. TABLE 1. Station typology Micro accessibility Macro accessibility

Centre

City edge

Rural

High Speed Train/Intercity, Express, Local Express, Local

Type 1 Very large station in centre of big city Type 2 Large station in centre of medium large city Type 4 Station in centre of small city/village

–

–

Type 3 Edge station with good accessibility by car Type 5 Station in city neighbourhood

–

Local

Type 6 Station in country side near small city/village

Source: van Hagen (2002, pp. 1511 – 1514).

parking facilities applying to types 4, 5 and 6; and a combination of both in the case of type 3 station locations (de Bruyn, 2002; van Hagen & de Bruyn, 2002, pp. 1511 – 1514). All in all, the typology proved to be of great value to both strategy making as market research within the Dutch Railways. For instance, current policies on station access and egress transport modes differ per station type as a result, as do policies on real estate development. The station type is also an important explanatory variable in different sorts of forecasts, and the typology is used for benchmarking exercises. There are two important difference between the two examples discussed previously. In contrast to the static nature of Goudappel Coffeng (2000, commissioned by the Ministry of Transport, Public Works and Water Management), the station typology of the Dutch Railways shows the potential of using a descriptive classification to give insight into changes over a period of time. This feature was deemed essential for application in strategy development. A second difference is that the urban context is treated explicitly. This further shift stems from the insight that a classification merely based on spatial hierarchy does not give as much insight in the potential of a station area as one that is also based on variables depicting the position of the location in its urban context. Following a similar reasoning, in node-place typologies commissioned by the Ministry of Housing, Spatial Planning and the Environment criteria were introduced like type of ‘environment’ (VHP & Goudappel Coffeng, 1999, pp. 41 – 42), type of ‘surroundings’ and type of ‘location’ (Tauw, 2000, p. 15). Interpretations This last group of models is not primarily concerned with the classification and comparison of locations. Instead, these models provide a structured view of the mechanisms relating the different node and place features of station areas. Their aim is to help their (re)development by penetrating the complexity and supporting conceptual reframing by the stakeholders involved. Two models are discussed: the 452


Node-Place Modelling of Stations in The Netherlands Concern synergy model (NS, 1999; Peek, 2000) and the Hourglass model (Brandvan Tuijn et al., 2001; Everaars, 2001; Goudappel Coffeng, 2001). The first model was developed in order to show the ways in which the former business units of the Dutch Railways, dealing with transportation (node), retail and real estate (place), could add value mutually. Two ways of former business units adding value to each other were observed. Firstly by adding to each other’s market potential, and secondly by mutually reinforcing each other’s competitiveness. Figure 4 shows the resulting ‘concern synergy model’. The loops show that the use of the product of one business unit is connected to the demand for the product of another unit. For instance, the real estate developed by the real estate unit will increase the demand for transport and consumption on the station location and so adding to the market potential of the other units. The horizontal arrows show the three ways in which the units can mutually increase each other’s competitiveness. The quality of the product of one unit influences the overall quality of the location. For instance, the market potential of real estate at a station location will be influenced by its accessibility and the unit offering passenger services is able to strongly influence the accessibility. The quality of transfer and the local environment play a similar intermediate role among the business units (NS, 1999, Table 16, pp. 11 – 16; Peek, 2000, pp. 9 – 11). The model showed that the different business units of the Dutch Railways were indeed highly interrelated and pinpointed the areas for extra attention when aiming for concern synergy. How much this insight can be translated into practice is still, however, an open question. Since the model was developed, the corporate structure of the Dutch Railways has turned away from business integration. The present trend is towards an organization with a clear-cut division between transportation and real estate activities. It is hoped that this new structure will still

FIGURE 4. Concern synergy model (NS, 1999, Table 16, p. 13).

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Gert-Joost Peek et al. provide ways of managing the interrelations between the different activities in a way that leads to more concern synergy, but the evidence is not there yet. The second model, known as the ‘hourglass model’, originates from an assignment by the Dutch Railways to Goudappel Coffeng (2001) and was further developed by Everaars (2001). Figure 5 shows the model. On the horizontal axis node (traffic & transportation) and place (space & economy) characteristics are distinguished, while on the vertical axis a distinction is made between potential— the qualities of the location—and use—the actual activities on the location. Next to this, a distinction is made between the location itself or micro level, based on walking distance (some 500 metres or 10 minutes), and its surroundings, or macro level, based on transport connections. Essence of the model is the notion that there are no direct relations between the ‘programme’ and the ‘quality of the accessibility’ of a transportation node, other than Bertolini’s model could suggest (Bertolini, 1999). These quantities are only indirectly related through the ‘quality of the place’ and ‘traffic streams’. Brand-van Tuijn et al. (2001, pp. 1384 – 1385) describes five relations between these four quantities that can be traced back to basic mechanisms informing land use-transportation modelling, dynamic traffic modelling and the reciprocity between functions and quality of the location involved in urban development: 1. Improved accessibility increases the catchment area of potential customers and makes the location a more attractive location; 2. Located functions attract traffic flows that could result in congestion and decreased accessibility; 3. Improved accessibility leads to bigger traffic flows; supply creates its own demand; 4. High real estate values, good quality of buildings and amenities make a location attractive; 5. Traffic makes a location attractive for retail, but could also lead to environmental problems.

FIGURE 5. Hourglass model (Brand-van Tuijn et al., 2001, p. 1384).

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Node-Place Modelling of Stations in The Netherlands Brand-van Tuijn et al. (2001) foresees three applications for the hourglass model. First it helps comparing locations and identifying their development potential. This is shown on the left hand side in Figure 6. Here two locations— Zutphen and The Hague—are compared on their relative weight of the quantities depicted by the quadrants of the model. The Hague scores relatively better on ‘quality of place’, ‘programme’ and ‘traffic flows’, while in Zutphen ‘quality of accessibility’ relatively greatly outperforms other dimensions. It is this first type of application the model owes it name to. On the basis of the analysis, the scope for a more balanced configuration could be assessed. Secondly, the model could serve as a reference for a targeted stakeholder analysis. Based on an analysis of competencies, means and interests of actors involved in the (re)development process they can be positioned within the model. This is shown on the right in Figure 6. This way, actors can be related not only through their roles, but also through the mechanisms that underlie the model. The insight can help structuring debate among them. Thirdly and more in general, the model could serve as a common framework of understanding of the nature of the task facilitating stakeholders’ interaction (Brand-van Tuijn et al., 2001, pp. 1387 – 1388). Goudappel Coffeng used the hourglass model in a study assigned by the ‘City Region of Amsterdam’ (Regionaal Orgaan Amsterdam, 2002), a partnership of 16 municipalities in the region of Amsterdam, in order to develop a regional location policy. The model proved useful for typifying locations, organizations and their reciprocal relationships. In particular, the emphases on an interdisciplinary approach and on the relationships between spatial features and organizations were appreciated. Both were quite new for the context of application. The two models described try to picture the complexity of mechanisms at work within a station and between the station and its surroundings. Furthermore, they try to explicitly incorporate the actors involved in the (re)development process. In the Concern synergy model this is done directly by using the business unit structure as basis and adding direct and indirect market mechanisms, while in the hourglass model transportation land use interaction mechanisms form the basis of the model and the actors are fitted in later.

FIGURE 6. Comparing locations (left) and stakeholder analysis (right) with the hourglass model (TwijnstraGudde, 2003, pp. 46 – 47).

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Gert-Joost Peek et al. Validation With the exception of econometric analyses of the relationship between station area quality and real estate values cited earlier (Debrezion Andom, 2006), there are no examples of explicit empirical validations of the node-place model or of any of its successors. However, there has been an ex-post empirical evaluation of the underlying station area synergy concept. Secondly, an assessment of the worth of working with the models in different organizational contexts should be also seen as a validation, and perhaps a more important one. This is the case because many if not most models did not primarily aim at describing, explaining or predicting station area redevelopment dynamics, but rather at helping structuring a stakeholder discussion around policy options. Let us start with research assessing the station area synergy concept. This research (Vaessens, 2005a, 2005b) shows interesting results. Vaessens evaluated the effects on the stations performance, in terms of number of travellers, customer satisfaction, retail turnover and real estate profits, of different combinations of policy measures. These entail measures directed at improving travel times between, increasing land use densities at, and improving the functional quality of station areas. The research considered developments in 10 station areas spanning the years 1996 – 2004. Vaessens concluded that only a coordinated application of measures aimed at all of the three types of policy measure (travel times, densities, quality) resulted in an increase of all four performance indicators. This was the case for only two stations. This result seems to indicate that the concept of synergy on which node-place models are based has some empirical fundament. Still, further research has to be conducted in order for the concept to achieve wider recognition as a potentially useful planning tool. Other validation evidence comes from the evaluation of the worth of working with the models by the actual stakeholders. Although a systematic, cross-case evaluation has not been done yet, most actors involved view node-place modelling as a promising method, as has been discussed for each model in the previous sections (Bertolini, 1999). Except for Bertolini’s initial model, which was largely an academic exercise, actual station area stakeholders commissioned all models and applications presented in this article. They consider the node-place concept useful because it helps structure the debate between land use and transport actors. This debate is seen as essential for achieving coordinated planning around stations. In particular, the idea of station area synergy appeals to both sorts of actors because it shows the scope for mutual gains. The modelling applications are appreciated because they help give form to an interactive and transdisciplinary planning process. A recent study has confirmed both these points (Peek, 2006). Discussion and Conclusions Two general observations can be made regarding the models discussed in this article. First, all are informed by the idea of synergy between node and place, although many differences can be observed, for instance in the way variables are operationalized. It seems there is no ‘good’ or ‘bad’ way of doing this. Rather, how the variables are operationalized is mostly determined by the stakeholder 456


Node-Place Modelling of Stations in The Netherlands view of the problem. We will illustrate this by means of the differences between the typologies that were developed during the preparation of the National Spatial Strategy. Second, a pattern in the development of node-place modelling can be observed; starting off as merely describing the (re)development dynamics and ending up aiming to facilitate the actual (re)development process. This change of focus involves a fundamental shift of perspective. In the second part of this closing section, we will further characterize this evolution and conclude with some remarks on future challenges. Throughout this discussion we will also point at the practical relevance of the exercise, and, finally, at possible implications for contexts other than The Netherlands. Looking at the content of the models there is a striking difference in the way the node and place value are operationalized. In nearly all cases the node is determined by the potential accessibility using variables describing the quantity and quality of connections. The organization of the transport systems leads to such a hierarchal classification of the nodal aspects. The transportation sector is (as yet) organized in a rather top-down fashion and as a result is more supply driven. National transport policy is implemented on lower scale levels. This makes a hierarchal systematic description most appropriate. The determination of the place aspects is less obvious. A diversity of variables is used. In some models the place component is determined by the actual use, using variables like number of jobs and inhabitants; in others by an indication of the hierarchical position of the functions located within a certain radius from the node. The real-estate oriented model of Buck Consultants International (2003) uses for instance the number of square metres and the rental level to determine this hierarchy. Several typologies make use of yet another approach, that is, qualitative positional measures like the level of urbanity of the surroundings and position in relation to the city centre. This ambiguity seems to derive from the way the markets dealing with land uses are organized. In contrast to the transport markets these markets are organized in a more bottom-up fashion. Even though there are many rules and regulations affecting them, real estate markets operate in a more organic and dynamic way than transport markets. There is here, in other words, a more direct relation between the use of space and price that is paid. This results in more demand-driven markets and a less univocal hierarchy. In the end, synergy between node and place features at a station area is created by interactions between the land use and transportation systems through different spatial markets, for instance the labour market, housing market and the market for mobility. These interactions cover a broad range of dimensions, and of time and spatial scales. As a result of this plurality of processes, there is room for more than one view of the problem, and this makes the problem socially complex. This kind of problems is often referred to as ‘messy’ (Ackoff, 1979) or ‘ill-structured’ (Mitroff & Sagasti, 1973). Which view prevails ‘is dependent on the number of stakeholders involved and the differences between their interests and values’ (Geurts & Joldersma, 2001, p. 308). The consequences for the modelling exercise of these different views of the problem can be illustrated by the differences in the typologies developed during the preparation of the National Planning Strategy. In the typology of the national map of transportation nodes, discussed earlier (Goudappel Coffeng, 2000, 457


Gert-Joost Peek et al. commissioned by the Ministry of Transport, Public Works and Water Management), a hierarchal approach towards the operationalization of both node and place characteristics was used. This corresponds with a hierarchal view on the dynamics of transportation and land use as one would expect from this Ministry. In contrast, in both typologies commissioned by the Ministry of Housing, Spatial Planning and the Environment the place characteristics were operationalized by criteria like type of ‘environment’ (VHP & Goudappel Coffeng, 1999, pp. 41 – 42), type of ‘surroundings’ and type of ‘location’ (Tauw, 2000, p. 15), which do not correspond directly to the spatial hierarchy used for the operationalization of the nodal characteristics. The second general observation is that in the development of node-place modelling we observe a shift in orientation from primarily helping to deal with the analytic complexity towards a stronger attention on the issue of social complexity (Bertolini, 1995; Bertolini, 1999). Bertolini’s conceptualization started as a heuristic tool that later on was applied to analyse regional networks of station areas. At the turn of the millennium, different node-place models were deployed for categorizing nodal areas resulting in typologies. As we have discussed, which criteria were used depended largely on the actors involved. Some typologies and models were also used for gaining insight into future situations. Parallel to these developments stemming from the descriptive and predictive potential of the node-place approach, another development took place in which the model was reinterpreted in order to be more directly employed in actual development processes. Here, the purpose of the model is not so much describing a present or future reality but rather facilitating the process of actually changing this reality into a new one that is closer to the wishes of those involved. In terms of practical aim the orientation shifted from the development of coherent policy for whole networks of areas to the actual (re)development of certain locations. Figure 7 shows the path the development of node-place modelling has taken in The Netherlands in the last decade, from merely describing, via categorizing and predicting towards facilitating. This shift involves a change in object and perspective. The model started as a conceptual model that was used to characterize the development dynamics of networks of station areas. Next, it was used to categorize a limited set of station areas by a limited number of criteria depending on the policy goals involved. Predicting asks for insight in the functioning of transport and land use markets, further broadening the perspective and narrowing

FIGURE 7. The development path of node-place models over the last decade.

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Node-Place Modelling of Stations in The Netherlands the spatial focus to the urban-regional level, as this best corresponds to the scale at which most of these markets function. Finally, facilitating is aimed at the actual development of a specific location taking account of the perspective of all actors involved and in that way being more oriented towards the social complexity of the problem. The change of perspective can be described in terms that Teisman (1992, pp. 32 – 33) used in his discussion of decision processes related to spatial investments. The original model was developed from a positivist value-free standpoint corresponding with Teisman’s unicentric perspective. In this perspective goals are seen as beneficial to the public and realized by hierarchal organized processes. The context of the later models is less value-free. Depending on the actors involved some variables are given priority above others in the process of categorizing and predicting. Finally, actually facilitating the (re)development of an individual location asks for a socially constructivist perspective taking account of the different views of the actors involved. This corresponds with Teisman’s pluricentric perspective in which the process of interweaving the goals of the different actors involved is central and should lead to the realization of their common interest. Facilitating this process asks for models that reduce the complexity by giving insight in the problem and help establishing common ground. Both the models of Peek (2000; NS, 1999) and Brand-van Tuijn et al. (2001) are examples of models primarily aimed at facilitating the process. However, almost all models were commissioned and used for the same purpose, as mentioned in the different sections. For this reason, as argued previously, whether and how they helped enhance coordination between stakeholders and develop integrated strategies should be the main focus of future model validation exercises. This evolution also identifies the current model development challenge. Next to an orientation on synergy between node and place aspects of the station area, the focus of the next generation of node-place models should be on the synergy between the actors involved in the (re)development process. With reference to the introduction of this article, synergy could be defined as the added-value to the actors involved of increased coherence between the node and place characteristics of the location, in its turn resulting from their collaboration. It is this collaboration that makes or breaks the synergy prospects of station areas. The challenge seems to lie in the development of models that focus on the question of how to nourish collaboration in order to develop a station area in such a way that it leads to addedvalue to participants in the process. This is, for instance, the ambition of the ‘Location Synergy Model’ developed by Peek (2004, 2005a, 2005b, 2006). How much of this is of relevance for contexts other than The Netherlands? Let us briefly, and lastly explore this. Haywood’s (2005) characterization of the UK situation will serve as illustrative reference case. Haywood describes the overall, long-standing lack of coordination between urban and railway developments in UK planning practice, despite some good examples in the Greater London Area that got much attention. Privatization of the railways appears to have made the coordination between railway planning and local land use and transport planning even more difficult. Haywood concludes with five recommendations to improve this coordination. Node-place modelling could directly help putting his first and fourth recommendations to work. With reference to his first recommendation, 459


Gert-Joost Peek et al. node-place modelling could help making the ‘national planning policy guidance more prescriptive and more firmly tied to rail accessibility measures’ (p. 92). With reference to his fourth recommendation, node-place modelling could help planners understand the peculiarities of ‘planning around stations’ as ‘this has not been a major feature in the education of most’ (p. 93). More in general, Haywood’s recommendations suggest that the struggle of UK planning practice with station area development can be depicted in terms of Figure 7. More than in The Netherlands, the UK seems to be lacking institutions that control interests in and means for station area development on both levels of the network and the location. Hierarchical relations between institutions with complementary perspectives and geographical spheres of influence seem also to a large extend absent. New coordinating bodies might help, but they may also further complicate the situation, and are difficult to implement in the short term anyway. It might then be perhaps worth exploring an approach that is based on the pluricentric perspective. The challenge of redevelopment initiatives could be conceptualized in terms of finding ways of interweaving the goals of the different actors involved. Node-place modelling could help this effort by providing a tool for penetrating the complexity of the redevelopment dynamics and establishing a common ground for discussion among the stakeholders. In conclusion, the success of node-place models in The Netherlands—and arguably also in other contexts—lies in their ability to capture the synergy opportunities of integrated transport and land use development at station areas. However, their evolution points at the need of more closely relating the analysis to the views of the actors involved and thus more explicitly help structure a discussion aimed at agreeing on a common course of action. References Ackoff, R. L. (1979) The future of operational research is past, Journal of Operational Research Society, 30 pp. 93 – 104. Bertolini, L. (1995) Le citta` del treno: la valorizzazione delle stazioni ferroviarie e delle aree circostanti, PhD Thesis (Turin, Politecnico di Torino). Bertolini, L. (1996) Nodes and places: Complexities of railway station redevelopment, European Planning Studies, 4(3), pp. 331 – 345. Bertolini, L. (1999) Spatial development patterns and public transport: The application of an analytical model in the Netherlands, Planning Practice and Research, 14, pp. 199 – 210. Bertolini, L. & Spit, T. (1998) Cities on Rails: The Redevelopment of Railway Station Areas (London, E. & F. N. Spon). Brand-van Tuijn, H. A., Fanoy, J. A. & Schotanus, B. (2001) Zandlopermodel: uitbreiding van het model van Bertolini, Paper presented at Colloquium Vervoersplanologisch Speurwerk 2001: Wie doet wat?, Amsterdam, 29 – 30 November. Buck Consultants International. (2003) Vastgoedontwikkeling op knooppunten: Het effect van bereikbaarheid verklaard, (Delft, Connekt). Cervero, R. (1998) The Transit Metropolis: A Global Inquiry (Washington, DC: Island Press). Cervero R. (Ed.) (2004) Transit-Oriented Development in the United States: Experiences, Challenges and Prospects, Washington, DC, Transit Cooperative Research Program, Report 102, 2004; with G. Arrington, J. Smith-Heimer, R. Dunphy & others. Debrezion Andom, G. (2006) Railway Impacts on Real Estate Prices (Amsterdam, Tinbergen Institute). De Bruyn, M. (2002) Bepaling stationstypes, Memo (Utrecht, NS Productmanagement, MOA).

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