Lessons for developing a planning support system infrastructure: The case of Southern California's Scenario Planning Model

Abstract

Although planning support systems are being more widely adopted by professional planners, there are very few examples of planning support system infrastructures designed to support planning practices on an ongoing basis. This paper reports the result of an exploratory qualitative study of the Southern California Association of Governments' Scenario Planning Model, an innovative new planning support system infrastructure. Interviews with professionals who served as participants in a two-year development process were conducted to explore the six dimensions that theories from the planning support systems, innovation diffusion, and organizational information technology fields suggest are important to understanding the adoption and use of a planning support system infrastructure: user considerations, perceived benefits, technical details, the development process, jurisdiction characteristics, and planning style. Drawing on these interviews, the article proposes seven lessons for the creation of planning support system infrastructures: utilize participatory design, support a variety of planning practices, address indirect costs to users, encourage collaboration among multiple users within each organization, ensure that all stakeholders have appropriate access, be mindful of the framing of new technologies, and embrace their transformational potential. Although the Scenario Planning Model has benefited from California's unique planning mandates, advances in web-based geospatial technologies mean that many regions may draw on these lessons to create similar planning support system infrastructures, which have the potential to improve local and regional planning practices through enhanced information, analysis, and communication.

Keywords

Planning support systems technological frames planning support system infrastructure scenario planning

Introduction

A planning support system (PSS) is defined by Klosterman (1997) as information technology in urban planning that facilitates a process of collective design, and Geertman and Stillwell (2003a) propose a related definition of a PSS as “a subset of geotechnology-related instruments that incorporate a suite of components (theories, data, information, knowledge, methods, tools) that collectively support all or some part of a unique planning task” (p. 6). Since these definitions appeared, a large body of PSS research and practice has emerged, and this term is now used to describe various software programs tailored for planning applications (e.g., Geertman et al., 2015; Geertman and Stillwell, 2003b, 2009; Klosterman and Pettit, 2005). Practitioner use of PSS is also growing due to the popularity of planning approaches that call for the close integration of geoinformation tools into the planning process, such as scenario planning or geodesign (Brail, 2008; Brail and Klosterman, 2001; Holway et al., 2012; Steinitz, 2012).

While significant attention has been paid to developing and applying PSS tools as part of specific projects, there has been much less progress in achieving a lesser known aspect of Klosterman's definition. Specifically, Klosterman (1997) argues that PSS should serve not only as a collection of tools but also as an enduring information infrastructure that facilitates interaction among planners and other stakeholders as they engage in a “continuous and interactive process of analysis, design, and evaluation that constantly integrates new information generated as model-produced analytical results redefine design issues, and the elaboration of design issues generates new demand for analytical information” (p. 51). The literature on digital infrastructures in general, and spatial data infrastructures (SDIs) in particular, provides needed detail to Klosterman's proposal. Boerboom (2010) identifies two ways in which data infrastructures have been defined. Normative definitions typically specify that an SDI is a combination of technologies, policies, and institutional arrangements that provide access to spatial information (e.g., FGDC, 2017). More interpretive definitions of digital infrastructure, such as Star and Ruhleder's (1994), analyze infrastructures from the users' point of view, defining them not primarily as technical objects but instead as practices with informal norms. Drawing on Edwards et al.'s (2007) definition of cyberinfrastructure that links these two strands, we define a PSS infrastructure as the set of organizational practices, technical infrastructure, and social norms that collectively support planning tasks by diverse users on an ongoing basis.

Although there are many examples of SDIs and other forms of digital infrastructure, examples of PSS infrastructures are scarce. After conducting extensive searches of online databases, Boerboom (2010) concluded that no true PSS infrastructures exist. We are aware of only two projects that may have approached a PSS infrastructure. The Sacramento Council of Governments (SACOG) developed and used for several years the web-based I-PLACE³S system to facilitate regional planning and local land-use plans (Condon et al., 2009; McKeever, 2011). However, unlike an infrastructure that is made generally available to a set of users, I-PLACE³S was primarily used by agency staff. Also in California, the web-based tool MarineMap was used by a diverse set of stakeholders to support marine spatial planning activities, but it was taken offline after the associated planning projects ended (Cravens, 2016).

Many reasons have been proposed to explain why individual PSS tools have not been widely adopted, which may also explain why few have matured into such a PSS infrastructure. Drawing on a comparison with travel forecasting computer models—which are widely institutionalized in U.S. metropolitan planning organizations (MPOs)—Brail (2006) observes that unlike PSS, travel models benefit from dedicated funding sources, federal regulatory mandates, and a network of like-minded peers who use shared methods. In contrast, PSSs aim to support planning practices that have limited and fickle funding, lack consistent legal mandates, and use a variety of methods. PSSs are highly diverse, encompassing tools for sketch planning, predicting land-use change, estimating development impacts, and constructing visualizations of alternative proposals (e.g., see the popular and versitile PSS CommunityViz, Walker and Daniels, 2011). Vonk et al.'s (2005) research on PSS adoption in the Netherlands concludes that limited use of PSS was explained by factors, such as usability, cost, and poor suitability for planning tasks. Furthermore, it seems likely that technical reasons also play a role in limited adoption, since most current PSS require access to hardware and technical skills to configure and operate, which are not widely available in professional practice (Hamerlinck, 2011).

Although research has identified many barriers to PSS adoption, proponents have little reliable evidence about their relative importance—or whether they can be overcome at all. For these reasons, Geertman (2017) recently urged PSS researchers to refocus their efforts from studies that document the reasons for this “implementation gap,” to investigations of success stories where PSS are being used. This paper follows Geertman's suggestion by conducting an exploratory study of the early development of a technically innovative PSS infrastructure, the Southern California Association of Governments' (SCAG) Scenario Planning Model (SPM). As described further below, this PSS was developed partly as a result of the state's 2008 adoption of Senate Bill 375 (SB 375), a climate change law.

Although SPM implementation is ongoing, it was selected because it fits the definition of a PSS infrastructure. It is intended for use by local jurisdictions to support local and regional planning tasks, including information sharing, reviewing forecasts, and creating land-use plans. The SPM also illustrates a promising technical approach to PSS infrastructure that other regions could follow. This paper presents the results of a case study of the development phase of the SPM, when an advisory committee made up of local stakeholders participated in a two-year development process with SCAG. The case study data sources include interviews with SCAG staff, the consultant, and eight members of an external working group, as well as other case research. This exploratory study seeks to answer the research question: How does a metropolitan region develop a collaborative PSS infrastructure?

The remainder of the paper is organized as follows. The next section describes the theoretical framework that guided the case research. The “Case context and methods” section describes the SPM, case context, and research methods, and the section following this presents the results. The “Lessons for developing a PSS infrastructure” section describes the seven lessons for creating a PSS infrastructure. The final section concludes the paper.

Theory

Because PSS infrastructures are complex information systems, various theoretical perspectives can be applied to them. For this exploratory qualitative study, we developed a theoretical framework that integrates several of the most relevant perspectives. Our starting point is Geertman's (2006) conceptual framework for PSS within planning practice, which usefully places technical considerations—the primary focus of PSS research to date—into a broader perspective. The framework features six elements: (1) the content of the planning issue, (2) characteristics of the users, (3) characteristics of the planning and policy process, (4) the political context, (5) specific characteristics of the geoinformation, knowledge, and instruments, and (6) the dominant planning style and policy model. However, this is primarily a descriptive framework, and it lacks concept specificity and descriptions of relationships between variables. Since the initial specific purpose of the SPM is to share information between organizations, another relevant research area is studies of organizational information sharing. These conclude that the primary motivations for geographic information system (GIS) data sharing include cost savings, improved data availability, and enhanced interorganizational relationships, and that information-sharing activities are often guided by formalized mechanisms, such as legal agreements, policies, and procedures (Nedovic-Budic and Pinto, 2000; Nedovic-Budic et al., 2004). This work does not provide the broader understanding needed for PSS infrastructures, which have many different uses. This section briefly describes three research areas that provide this broader perspective: PSS, diffusion, and organizational information technology (IT).

PSS research

Two areas of PSS research provide insights useful to this study. By definition, planning professionals use a PSS infrastructure at different places and times. Pelzer et al. (2015) propose that the concept of task-technology fit provides a means of understanding how these practitioners perceive the usefulness of PSS given their particular practices. This idea holds that the “matching of the functional capability of available information technology with the activity demands of the task at hand” can explain technology utilization (Dishaw and Strong, 1998). Through four case studies, Pelzer et al. (2015) document examples where practitioners used PSS because they supported specific planning tasks, such as exploring energy use, communicating new locations in a market, and negotiating development rights. Second, researchers have found a relationship between participation in creating a PSS (and related tools) and user acceptance (Goodspeed et al., 2016; Vonk and Ligtenberg, 2010). Therefore, our framework includes not only technical details but also the characteristics of the development process itself.

Diffusion research

Since a PSS infrastructure must be widely adopted by different users to succeed, the study also draws on diffusion research, which investigates how innovations of all types spread in society (Rogers, 2003; Wejnert, 2002). Rogers' (2003) well-known synthesis of research in this field argues that the adoption of innovations can be explained by several characteristics: the perceived characteristics of the innovation itself, the characteristics of the adopters, and the characteristics of the broader social context, such as the social network through which the innovation spreads. According to this theory, the perceived innovation characteristics that influence how rapidly users adopt innovations are simplicity, observability of benefits, relative advantage, and compatibility.

However, this theory may be inadequate to explain the adoption of PSS infrastructures, since their benefits are so varied and uncertain. For example, GIS technologies—which share many technical similarities with PSS—have been widely adopted by municipal governments, even though Innes and Simpson (1993) conclude that GIS rated poorly on Rogers' dimensions. Although diffusion theory is useful in studying the adoption of discrete innovations, Schön (1971: 36) critiques it as inadequate for technologies that require changes to institutions, which he argues require a process of social learning. Therefore, we also look into studies of how IT results in organizational transformation.

Organizational IT

Considering the adoption of GIS technology, Ventura (1995) observed that using the new technology for analysis and decision-making requires changes to organizational incentives and structures. This is true for PSS infrastructures as well. Scholars studying the organizational adoption of information systems have developed alternative approaches that explain why IT may—or may not—result in organizational changes (Robey and Boudreau, 1999). One particularly relevant study from this literature documents the dramatically different ways two adjacent U.S. counties adopted GIS at roughly the same time (Robey and Sahay, 1996). In one county, the introduction of GIS was coordinated by a cross-departmental team, which resulted in greater collaboration and information sharing between departments. In the other, GIS was implemented by a central IT department and resulted in little new learning or information sharing. The concept of technological frames has been proposed to account for situations where similar technologies are used so differently within organizations (Davidson, 2006; Davidson and Pai, 2004; Orlikowski and Gash, 1994). Orlikowski and Gash (1994) define technological frames as

that subset of members' organizational frames that concern the assumptions, expectations, and knowledge they use to understand technology in organizations. This includes not only the nature and role of the technology itself, but the specific conditions, applications, and consequences of that technology in particular contexts. (p. 178)

This view suggests that choices about how to implement technologies depend on these frames.

Study framework

Drawing on these ideas, we developed a theoretical framework to guide the data collection activities, summarized in Figure 1 and Table 1. This framework encompasses all dimensions from Geertman (2006) except planning issue content, since our focus is on PSS infrastructure in general. The framework's six dimensions are:

User characteristics, including the organizational role of participants and the capacity of intended users;

Perceived benefits of the PSS, since they suggest the most relevant PSS performance measures and are an important variable in diffusion theory to explain the adoption of innovations;

Technical details of the PSS, a central focus of PSS research;

Development process, identified in PSS and organizational IT studies;

Jurisdiction characteristics and motivations, which provide the context for the diffusion and adoption of the PSS;

Planning style, which is important in this case: although state law mandates regional scenario planning, local jurisdictions vary widely in their planning practices.

Figure 1.

Theoretical framework of the study.

Table 1.

Primary relationships between framework dimensions and theory categories.

Framework dimensions	Geertman (2006)	PSS	Innovation diffusion	Organizational IT
User considerations	✓	✓	✓	✓
Perceived benefits		✓	✓
Technical details	✓	✓
Development process		✓		✓
Jurisdiction characteristics and motivations	✓		✓	✓
Planning style	✓			✓

PSS: planning support system; IT, information technology.

Case context and methods

This section introduces the SPM, provides case context, and then discusses the qualitative data collection and analysis methods used.

Case context and scenario planning model description

SCAG (2016) describes the SPM as “a comprehensive web-based land use sketch planning tool for scenario development, modeling, and data organization developed to support a collaborative and seamless local and regional plan development process.” SCAG is a regional organization responsible for a variety of state- and federally regulated planning activities for the metropolitan region centered on Los Angeles. This region includes six counties and 191 municipalities, encompasses about 9.8 million hectares of land, and in 2015 had an estimated population of 18.8 million, or 48% of the population of California (SCAG, 2015). The development of the SPM was motivated by SB 375, which mandated that MPOs in California develop and adopt, every four years, integrated regional land use and transportation scenarios. These scenarios (termed Sustainable Communities Strategies or SCS) must demonstrate how the interaction of land uses and transportation investments can achieve MPO-level greenhouse gas emission reduction targets for light-duty vehicles. Since these plans incorporate a Regional Transportation Plan (RTP), which the federal government already requires, they are known as an RTP/SCS. While zoning authority remains at the local level, SB 375 mandates the creation of regional land-use scenarios that may differ from local plans and zoning rules (Barbour and Deakin, 2012). California also has a unique planning mandate, the Regional Housing Needs Assessment (RHNA), where regional organizations (including SCAG) establish targets for local jurisdictions for new construction housing for all income groups under local zoning (Calavita and Grimes, 1998). The RHNA provides an important incentive to municipalities to ensure that regional databases are accurate, since these targets are set based on an analysis of current conditions in each jurisdiction.

SCAG has divided SPM development into two phases. The first phase resulted in a data management interface to facilitate local jurisdiction review and input of land-use information for regional planning. The second phase will involve the deployment of scenario development and analysis functionality. As part of the first phase, SCAG formed a working group with 35 members to provide input to the consultants, and several working group members served as pilot testing sites. This study focused on the development process for the data management functionality, although the various functionalities will be closely linked in the final PSS. SCAG plans to distribute the SPM Data Management features to all 197 jurisdictions in fall 2017 to facilitate the local review and input process for the 2020 RTP/SCS.

During this phase of the SPM's development, the working group members provided input on the data management functionality of the SPM. The topical scope of the data contained in the SPM is illustrated in Figure 2, and the tool's interface is shown in Figure 3. The primary purpose of the data management functions is to allow local planners to establish and maintain a spatial database that records, for each parcel in the jurisdiction, the existing and general plan land use. Users can also view forecasted population and employment used for regional planning for their jurisdictions and transportation analysis zones (TAZs). Users can access the SPM on any Internet-connected computer running the Google Chrome browser. As shown in Figure 3, upon logging in, users see a list of available data layers (labeled 1) and a map window (labeled 2) where selected layers are displayed. These layers fall into three groups: (1) base map options, (2) layers with some editable fields for existing and planned land uses, TAZs, and the jurisdiction boundary, and (3) layers providing additional relevant information for land-use planning (shown in Figure 3). Above the map is the “Explore” window (labeled 3), which is used to display attribute queries, and the scenario manager functionality. Finally, the edit window (labeled 4) allows users to view and update the land-use information for each scenario planning zone (SPZ).

Figure 2.

SPM data categories. Source: reproduced with permission from SCAG (2016).

Figure 3.

SPM data management interface. Source: reproduced with permission from SCAG (2016).

The scenario functionality was not the focus of the first phase of development, but the working group members learned about it during their activities. This feature allows users to view preloaded future land-use scenarios created by SCAG for regional planning purposes, as well as create their own land-use scenarios. The SPM presents different indicators to facilitate the comparison of alternative scenarios. Currently, these are water consumption, energy consumption, local fiscal impact, and vehicle miles traveled. In the future, SCAG plans to add modules to conduct analysis of land consumption and public health outcomes.

Methods

The primary data collection method was semi-structured interviews of eight participants in the SPM working group, who represent diverse types of intended SPM users, and an interview with the consultant. Additional case background information came from conversations with SCAG staff, project materials, and attending a working group meeting. The members of the SPM working group were targeted as the primary study participants, since they represent the diverse types of intended users of the SPM, and they developed knowledge of the tool by participating in PSS development and pilot testing. Interview questions probed topics from the theoretical framework (Table 2). Since SCAG staff did not agree to share the full list of working group members, study participants were recruited through (a) an invitation relayed by SCAG staff to the full membership, (b) invitations sent to members identified at an in-person meeting attended by the researcher on Monday, February 8, 2015, and (c) suggestions provided by existing participants. Telephone interviews took place between June and August 2016. Of the participants invited, all but two agreed to participate; in one case, the staff member declined to participate in the study, and in the other, a different staff member from the same jurisdiction who was more involved in the project was interviewed. As Table 3 shows, study participants included planners and planning consultants to jurisdictions of varying sizes, as well as individuals affiliated with two large counties. The participants' experience with GIS ranged from not at all experienced to very experienced, but none had previous PSS experience. After the interviews were transcribed, they were imported into the NVivo analysis software, where we coded the interviews according to a set of codes defined by the theoretical framework and the related theories described above, adding some inductive codes to identify new issues raised in the interviews. To conduct the analysis, the researchers systematically reviewed and summarized the comments tagged for each framework dimension.

Table 2.

Semi-structured interview protocol.

Interview question	Framework topic
What is your role at the municipality or organization where you work?	User characteristics
What are the policy motivations for your municipality to be engaged in advising the design of the SPM?	Jurisdiction characteristics and motivations
What is/was your role on the SPM Working Group?	Development process
Describe the level of input or feedback you had on the tool's analysis topics, assumptions, and scope.	Technical details
What do you think the most important benefit(s) of the SPM will be?	Perceived benefits
Who will be the most likely user(s) of the SPM within your municipality or organization, and what is their current capacity to use it?	User characteristics
What do you see as the primary barriers for tool adoption?	Various
What do you think the impact of the SPM will be on the way your municipality or organization conducts planning?	Planning style

Table 3.

Study participants.

Participant no.	Position	Organization type	Jurisdiction population
1	Associate planner	Municipality	<50,000
2	Planning director	Municipality	<50,000
3	Consultant	County	2–3 million
4	Consultant	County	3–4 million
5	GIS analyst/planner	Municipality	300,000–400,000
6	Planner	Municipality	300,000–400,000
7	Consultant	Municipality	50,000–100,000
8	Senior planner	Municipality	200,000–300,000
9	SCAG technical consultant	Private Consultant	N/A

Results

This section discusses major themes arising in the interviews according to the theoretical framework dimensions.

User characteristics

We spoke with participants who hold various roles within municipalities, related public sector organizations, and the private sector. One interviewee works as a private sector consultant, five are municipal planners (either at the city or county level), and one is involved in demographic analysis. Most interviewees working for jurisdictions believed that their planning departments would be the main users of the SPM, though several also predicted that usage could cross departments and present opportunities for collaboration. Participant 3 observed that “there is a fairly defined division of labor [between departments], but I think (the SPM) could be valuable to folks in transportation and public health and some of the other departments.” Many participants stressed the importance of user training for SPM success. Participant 9 argued that SCAG should be prepared for “hand-holding” and active engagement with users to overcome initial barriers. Working group members also provided detailed comments on a draft SPM user manual. SCAG staff members plan to conduct training activities as part of the fall 2017 roll-out; therefore, training activities were not included in the case research.

Perceived benefits

Most interviewees envisioned the SPM as an opportunity to ensure greater consistency between local and regional data sets. SCAG collects and compiles data from member municipalities in order to create forecasts and regional plans, but many of our conversations touched on past inaccuracies in SCAG data sets, and the need to ensure more accuracy between jurisdictions' data and the information held by SCAG. Participant 9 described how the SPM will aid SCAG in collecting data from 197 jurisdictions.

For jurisdictions, the SPM holds the potential to more easily rectify errors in the data layers describing existing land uses and zoning and view SCAG's TAZ-level forecasts. Participant 7 stressed the importance of having an opportunity to catch and correct these errors early in the planning process:

In past RTP/SCS cycles, we have caught significant errors from our review of SCAG data sets. Our concern, with each new data set, is whether such errors continue to be there. We want to make sure we spend the time early on to correct the database, before the growth projections evolve into a full-blown approved data set.

Participant 6, a city planner, believed that the ability to review and directly correct data inaccuracies to ensure quality data for regional planning would be the primary motivation for municipalities to use the tool, not local planning activities.

In addition, several interviewees were optimistic that the nature of the SPM would expand technical capabilities for many jurisdictions, especially those with limited existing capacity. Because the SPM is web-based and does not require GIS software or skills, it may allow more jurisdictions to easily access and work with spatial data. Participant 7, employed at a smaller city that has GIS capability, pointed out that the tool does not pose many of the typical barriers a municipality might face in using GIS:

What I appreciate about the SPM is that regardless of whether or not a jurisdiction has GIS capabilities, staffing, or money to purchase the GIS software, the SPM does offer a free and a web-based tool where any local jurisdiction can compile all of this land-use information.

Technical details

The primary technical considerations raised by the participants concerned how information was represented in the SPM. Several interviewees mentioned concerns about whether the data structure of the tool was suitable for local planning. Participant 7 recalled a key adjustment to an early version of the SPM, to switch to a new spatial unit from an arbitrary grid as the basic resolution for land-use planning:

I felt, from a planning perspective, this arbitrary, square, 5½ acre grid had no relationship to databases and to planning. It doesn't make planning sense. I told them, from my perspective, the only way you can accurately do this is if you get down to a parcel level, because the jurisdiction will understand the geography of a parcel.

Because of this and other feedback, SCAG decided to create a new geography for its regional planning activities, the scenario planning zone (SPZ), which was constructed by grouping similar parcels.

Another technical consideration arising from local and regional differences is the ability to represent the complex structure of local land-use regulations. One desired feature, which came up in four of the eight interviews, was the ability to represent overlay zones or secondary land-use codes. The SPM tool uses a standard set of regional land-use classifications, and the SPM did not originally allow users to assign multiple land-use classifications to the same parcel. Because of this feedback, SCAG has modified the SPM to allow users to designate a secondary land-use category. According to Participant 4, this issue may arise if “you have a utility corridor that's also used as open space for a trail. To be able to annotate that is critical.”

Development process

The SPM working group members provided comments about the PSS development process. Two cities acted as test sites, working with a pilot version of the software to provide feedback to SCAG based on their experiences. Our participants from these jurisdictions offered specific instances of feedback or conversations about how to improve the SPM. Another described a “translation” process that aimed to link SCAG's zoning definitions with those of individual jurisdictions. Participant 6 argued that the diversity of the working group was a strength: “What's been helpful about the working group is that we do have all types of users involved with it. You know you have people who are concerned about public health to local representatives like myself.” Other members of the working group felt they had not been consulted as extensively. Participant 3 provided minimal feedback, but he believed the test sites were more active. Participant 1 recalled,

the conversations were predominantly used by the larger jurisdictions in the SCAG region, and I was pretty uncertain to what exactly the role of a city the size of [our city] would be in the working group. I felt our input was nonexistent.

Jurisdiction characteristics and motivations

The SCAG region is very large and diverse, and the resulting variations will influence the implementation of the SPM. Several interviewees felt that jurisdictions with little vacant land may see less need for the scenario analysis functionality but noted that it may provide a regional perspective. For example, Participant 7 noted that

[our city], for all intents and purposes, is a built-out community. But there are areas outside [our city] that are undergoing extensive redevelopment and new development … . [We] want to make sure that if a neighboring jurisdiction reports that a proposed project would or would not impact certain intersections in our city, that it's based on the most current and up-to-date growth forecasts.

According to most of the participants, their jurisdiction's primary motivation for using the SPM is to ensure data consistency between local and regional data sets, to ensure the accuracy of the resulting regional plans. They saw this consistency as a valuable goal in itself: “If everybody's planning for the same thing, and everybody agrees on it, it makes life a lot easier. Consistency makes life easier. If things are accurate, you're planning for what's going to happen” (Participant 4). In addition, they described a variety of concrete ways that data accuracies or inaccuracies could impact their jurisdictions. These included grant funding—“if your local projects are in [regional forecasts] … you could also qualify for money” (Participant 4); legal risks—“you might have a project … moving forward and someone says ‘wait a minute, the SCS says this and you're proposing more growth and then you're in violation of SB 375” (Participant 3); or ensuring fairness in SCAG's RHNA—“If the growth forecast data is wrong, there is going to be a direct implication on your regional housing needs numbers. If you did not review and accurately correct [the data], it will come to bite you” (Participant 7). Participant 3 summarized the diverse motivations and political considerations local jurisdictions have when engaging in regional planning activities, which provides the backdrop for the information sharing facilitated by the SPM:

There is a certain level of gamesmanship when it comes to developing forecasts for the RTP/SCS. Many jurisdictions want to keep their RHNA allocation low, because they have to rezone land to accommodate their allocation of low-income housing. Some jurisdictions desire higher numbers because they fear that SB375 will limit future growth; others may want to show that higher levels of growth in environmental documents [are] consistent with regional growth, or they want to show their jurisdiction is a growth area to encourage economic development.

Planning style

Federal and state mandates require that SCAG produce an updated RTP/SCS every four years, which guides the Association's analysis and determines its data collection needs. The county and city planners, on the other hand, are involved in more episodic and varied planning activities. Although most of the participants felt the SPM would be useful for updating general plans, they described these as relatively rare activities disconnected from the RTP/SCS cycle. Participants 1 and 2, from a small city, said they felt the SPM would be useful, although they did not know when their city would next update its general plan. Similarly, although Participant 4 recognized the usefulness of the scenario analysis functionality for creating regional land-use scenarios, they felt that creating scenarios placed local planners in an awkward position, since regional planning is not well coordinated with local planning activities:

The planners don't have a lot of authority to go through and create a new vision and submit that to anyone. They have to have it signed off by the city council or the voters, depending on what's going on in the jurisdiction. They can't just willy-nilly create a new scenario and then submit that up to SCAG for the RTP.

The participants also raised several concerns about whether the SPM would be useful for local planning. One planner (Participant 6) said that their city made extensive use of overlay zones, which are not part of the SPM data structure. Also, the SPM currently allows users access only to information for their own jurisdiction. Participant 8 felt that this might be an obstacle for planning areas that fall near municipal boundaries, describing a case where two large redevelopments fell across the street from each other in separate cities. Although they felt the scenario planning functionality might be useful, Participant 8 suggested that the affiliation with SCAG might affect local interest in using the tool:

I know that [our jurisdiction] tends to question a lot of the things that SCAG does. They're fearful of the regional planning […], so there's been a lot of work on our end of trying to explain to our electeds that this tool isn't a bad thing, it's actually going to help your jurisdictions in terms of having accurate data at the parcel level. They're a little more hesitant about the sketch planning tool. They don't want somebody else telling them how to run their city.

Given the interactive, visual nature of the SPM, several participants felt that it would be useful to communicate planning alternatives to multiple stakeholder groups. For example, Participant 4 suggested that it could improve communication in public meetings by lending immediacy to the conversation:

if you're having a bunch of roundtables or workshops with the public for your general plan update. Then the planners would say, okay, let's see what happens if we do these types of things […] and to either convince or show the pros and cons of doing these types of projects or those types of projects. So as a sketch planning tool, I think something like a general plan update would be a useful tool to visualize some of those things.

Participant 8 also mentioned that the tool would be helpful for working directly with developers; planners could more easily convey the benefits or incentives developers could obtain with minor changes to projects, and how the projects would influence the broader neighborhood or city. She also observed that, considering the potential to expand municipal planning capabilities, as described above,

it's giving people a tool they haven't ever had before, where you would have to rely on consultants [or] the developer to go out and work with a consultant, or even the city. If we're planning on doing a large infrastructure project or some kind of community project, we'd be able to evaluate the benefits of changing certain aspects of it through the tool.

However, the SPM is not designed for small-scale analysis within a jurisdiction, so such uses would fall outside of the intended applications.

Lessons for developing a PSS infrastructure

After a roughly two-year development process, SCAG together with a consultant and local jurisdictions has succeeded in creating a PSS infrastructure. The SPM has been used on a pilot basis to access and share planning-related information and will soon be made more widely available to the region's jurisdictions. This section describes seven lessons drawn from this case about developing PSS infrastructure. The lessons are directed to both scholars and professionals working to implement similar technologies, and they respond to the following seven questions about PSS infrastructures:

How should they be created?

What functionality should they contain?

How can their adoption be encouraged?

How should users be recruited from each participating jurisdiction or organization?

Which organizations should be provided access?

How can user misconceptions be avoided?

How can their adoption be used to encourage broader changes within organizations engaged in planning?

Utilize participatory design

SCAG's use of a working group resulted in valuable feedback and a group of knowledgeable and committed early users, as predicted by PSS research. Due to the complexity of creating a PSS and the diversity of local stakeholders, all regions hoping to create a PSS infrastructure should plan a similar participatory design process. Although members of the SPM working group reflected admirable diversity, their reported involvement varied widely, and several felt they were not adequately consulted. The PSS literature can suggest ways to further improve the quality of collaboration, such as design thinking (Goodspeed et al., 2016) or other sociotechnical design methods (Vonk and Ligtenberg, 2010).

Support a variety of planning practices

In order to be useful to many users, a PSS infrastructure must support planning practices that vary across jurisdictions and play out at different planning scales. This diversity poses a significant challenge to the development of a shared infrastructure, since the theory of task-technology fit suggests that the PSS infrastructure will require diverse features to be broadly useful (Pelzer et al., 2015). The SPM was designed primarily for information sharing and scenario analysis for regional planning, which resulted in participant concerns about its appropriateness for local planning. No participants described using scenario planning techniques for general plans, and they perceived it to be useful primarily for large-scale new development. In other cases, local participants described a desire for analysis not currently possible within the SPM's scenario analysis functionality, such as estimating the reduction in greenhouse gas emissions due to off-road bike trails (Participant 7).

In addition, even if there was broad interest in constructing local land-use scenarios through the SPM, jurisdictions might want to tailor the land-use scenario inputs and analysis indicators. Participant 8 provided an example of this, describing a desire for a new land-use category within the SPM that would better describe the pattern in their city:

I've been asking for a different category, which would be high-density single family so that we can distinguish rather having the typical, you know, large lot, which is one unit per acre and the smaller lot, which is 4 or 5 units per acre. There needs to be something else, because a lot of our single family development is more dense than multi-families […] there's a lot of misrepresentation of “oh my gosh, single family dwelling, detached, bad, bad, bad,” but we've got a lot of stuff that's higher density than some of the older stuff that exists in the entire region.

One solution to these problems, taken by SACOG in Sacramento, is for SCAG to play a stronger role in local land-use planning, thereby encouraging the adoption of regional methods for local plans. However, our participants described this as unlikely to occur in the SCAG region, given the reluctance of local jurisdictions to collaborate with SCAG in this way. Even if the advanced scenario analysis functionality may never be widely adopted for these reasons, participants described a variety of other ways the SPM will support local planning, such as accessing GIS information, maintaining digital data about local land use, and accessing SCAG's spatially detailed forecasts. Creators of PSS infrastructures should remain open to such unexpected uses, since they widen the pool of potential users.

Address indirect costs to users

Although SCAG is responsible for funding the creation and maintenance of the SPM, SCAG relies on the voluntary participation of resource-limited jurisdictions. Participants described how learning to use the SPM's features and using it to report data were time intensive. Participant 4 said, “the biggest obstacle [to implementing the SPM] is getting jurisdictions interested and then having the higher-up enough authorities sign off on having their staff spend the time to proof this data.” Therefore, the successful implementation of a PSS infrastructure should address these costs by providing a user-friendly interface and streamlined training materials; it may also be necessary to provide some local jurisdictions with funding to offset their expenses.

Encourage collaboration among multiple users within each organization

PSS infrastructures should seek multiple users within each organization to further embed the PSS into the organizational environment and mitigate against adoption setbacks created by employee turnover. Distributed deployments that involve a team result in more effective use of new technologies (Robey and Sahay, 1996). In the case of PSS infrastructures, these users may foster collaboration across multiple departments within each jurisdiction, such as planning, GIS, public health, etc. This approach also provides insurance against employee departures, as described by Participant 3:

Frankly, even in my own agency, I think I'm the only one who knows about it, and I'm here on a part-time basis, right? And I think you'd find those types of situations in other agencies. So here, where I would probably be a prime user of it and I'm kind of a peripheral employee.

In the private sector, the practice of cross-training, or training employees in multiple job functions, has become widespread since it can reduce problems created by the departure of key employees, as well as boosting employee performance and morale (Inc Encyclopedia, 2017).

Give stakeholders appropriate access

Collaborative planning theories argue that effective planning must engage diverse stakeholders in a learning process that extends beyond governmental planners (Healey, 1997; Innes and Booher, 2010; for an overview, see Goodspeed, 2016). Specific to the SPM, the scenario analysis techniques it contains were originally created by pioneering regions striving to break away from conventional planning practices that were resulting in sprawling, unsustainable urban development patterns, such as the well-known Envision Utah or Blueprint Sacramento projects (McKeever, 2011; Matheson, 2011). These projects combined technical analysis with a broad public discussion about how alternative land use and transportation scenarios result in public health, environmental, social, and economic outcomes.

These observations suggest that creators of PSS infrastructures should consider how to make them accessible not only to a wider set of stakeholders but also potentially to the public. Due to the sensitivities of parcel-level information, access to the SPM has thus far been limited to authorized users within SCAG's jurisdictions, and as noted above, users can only work with data for their own jurisdiction. One way the SPM might support collaboration is by providing information to collaborative groups engaged in planning projects at a local or regional scale, an idea described by a study participant above. Another approach, suggested by Guhathakurta (1999) and taken in the case of MarineMap (Cravens, 2016), is to provide stakeholders direct access to the PSS infrastructure itself. However, providing this level of access would require addressing local jurisdictions' concerns about data sensitivity, perhaps through the creation of different types of user accounts with tailored permissions, since local jurisdiction involvement is required for SPM success.

Be mindful of the framing

New technologies, such as PSS infrastructures, must be framed carefully to new users, since “early interpretations of a technology are particularly influential because they are established rapidly as the technology is assimilated into work practices and becomes built into organizational routines. Such embedded understandings and assessments of a technology are particularly difficult to change later” (Orlikowski and Gash, 1994: 182). SCAG's decision to implement the data management functionality first meant that most participants viewed information sharing as the primary purpose of the SPM, even if they were aware of the planned future scenario analysis functionality. As a result of the data management emphasis, many of the working group members were selected due to their involvement and interest in the collection and reporting of data (the focus of Participant 3 and 4's activities). In addition, it subtly set the stage for the stakeholders' overall understanding of the SPM. In the words of Participant 6,

I think SCAG often sees it as local municipalities will want to use SPM for our local planning, but I actually see it in the reverse – that we want to make sure that the data in SPM is correct for local planning so that SCAG can use it for regional planning.

While the working group members developed a comprehensive and sophisticated understanding of the SPM through their participation, the same may not be true when SCAG provides all jurisdictions access to the SPM. In particular, if new users come to think of the SPM primarily as a tool to report data to SCAG, users may ignore the additional functionality it already contains (such as extensive spatial information). They may also be less receptive to future functionalities that do not fit within the initial frame (such as the scenario analysis functionality).

Embrace the technology's transformational potential

The introduction of new information technologies can be used to reinforce—or transform—existing organizational practices. A PSS infrastructure like the SPM could break down departmental silos and foster new planning practices within jurisdictions. Some participants were already beginning to envision how the SPM could positively transform their work. For example, Participant 8 saw the scenario analysis functionality as a way to add value to jurisdictions' interactions with developers, allowing them to demonstrate how minor changes to proposed projects could better benefit the community. Participant 4 described how utilizing the scenario analysis function within a planning workshop could result in a different, data-rich discussion. Participant 7 described how the SPM could be used to create a new local land-use database without relying on a conventional GIS program. However, these transformative changes may remain unrealized, and the SPM may evolve into only a data-reporting tool. Since the creators of PSS infrastructure lack the resources and capacity to foster these transformative local initiatives themselves, we suggest that they instead create an environment where such innovation is recognized and rewarded. Ultimately, it will be PSS users, acting as change agents within their local organizations, who will be in a position to realize the potential of the new technology.

Conclusion

Twenty years ago, Klosterman (1997) presented an aspirational definition of PSS. He argued that shifts in planning theory should be accompanied by changes to the information technologies used for planning. With the rise of a new conception of planning—as a collaborative process of collective design among stakeholders—he called for the development of an “information infrastructure that facilitates social interaction, interpersonal communication, and community debate” (Klosterman, 1997: 51). Although he believed that GIS would be the heart of this new technology, he foresaw a PSS that would include the full range of structured information and analysis tools needed for planning. In the years since, many advances have been made toward achieving this vision, resulting in an exciting array of software and hardware tools, and a growing body of knowledge about how they can be effectively deployed in planning. However, PSSs have generally taken the form of tools used within specific projects, rather than the general infrastructure shared among diverse stakeholders that Klosterman desired.

Following Geertman's (2017) suggestion that PSS research should focus on success stories, this study investigated an innovative example of a PSS infrastructure that links regional planners and local jurisdictions in the Los Angeles metropolitan region. Drawing on a novel theoretical framework, we conducted interviews with nine members of a SCAG working group, which has worked intensively on the PSS during a two-year development period. As described above, the study confirms the importance of many of the hypothesized factors for the adoption and usefulness of the PSS, including the importance of user participation in creating a PSS, accounting for diverse users and planning styles, and the perceived benefits for users.

The case illustrates that a PSS infrastructure is indeed possible, especially when enabled by an institutional context, such as California's SB 375, which provided funding and a legal mandate to create regional land-use scenarios, necessitating detailed input from jurisdictions. However, even in this case, the interviews contain sobering reminders of the many challenges the SPM faces as SCAG seeks its adoption by 197 jurisdictions. The SPM straddles the worlds of regulated planning activities at the regional scale and the highly diverse planning issues of a vast region. Drawing on these findings and the broader body of research reviewed, we propose seven lessons for the creation of PSS infrastructures. These lessons suggest how the creators of PSS infrastructures can encourage their integration into local planning practices in ways that advance desired transformations, such as empowering jurisdictions with greater access to information, fostering a collaborative approach to planning, and encouraging professional innovation. In light of the rapid improvements to the data and information technologies required for PSS infrastructures, these issues will determine whether they mature into a robust resource that improves planning region wide.

Footnotes

Acknowledgement

The authors would like to thank the study participants for sharing their insights about the project.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this research project was provided by the University of Michigan Office of Research and the Taubman College of Architecture and Urban Planning.

Robert Goodspeed is an Assistant Professor of Urban Planning at the University of Michigan, Taubman College of Architecture and Urban Planning. His teaching and research are in the areas of GIS in urban planning, planning support systems, and scenario planning methods. He holds a BA in History from the University of Michigan, an MCP from the University of Maryland, and a PhD in Urban and Regional Planning from MIT.

Cassie Hackel is a Graduate of the Master's of Urban and Regional Planning Program at the University of Michigan, Taubman College of Architecture and Urban Planning. Her concentration was in Housing, Community and Economic Development, with a particular interest in housing and transit justice. She holds a BA in Urban Studies from Vassar College and has previously worked with the New York City Economic Development Corporation and PLASTARC, Inc.

References

Barbour

Deakin

(2012) Smart growth planning for climate protection. Journal of the American Planning Association 78: 70–86.

Boerboom LGJ (2010) Integrating spatial planning and decision support system infrastructure and spatial data infrastructure. In: GSDI 12 World Conference Singapore, pp. 19–22. Available at: http://gsdiassociation.org/index.php/gsdi-conferences/62-gsdi-conferences.html.

Brail

(2006) Planning support systems evolving: When the rubber hits the road. In: Portugali

(ed.) Complex Artificial Environments, Berlin, Heidelberg: Springer, pp. 307–317. .

Brail

(2008) Planning Support Systems for Cities and Regions, Cambridge, MA: Lincoln Institute of Land Policy.

Brail

Klosterman

(2001) Planning Support Systems: Integrating Geographic Information Systems, Models, and Visualization Tools, Redlands, CA: ESRI Press.

Calavita

Grimes

(1998) Inclusionary housing in California: The experience of two decades. Journal of the American Planning Association 64: 150–169.

Condon P, Cavens D and Miller N (2009) Urban planning tools for climate change mitigation. Policy Focus Report, Cambridge, MA: Lincoln Institute of Land Policy.

Cravens

(2016) Negotiation and decision making with collaborative software: How MarineMap ‘Changed the Game’ in California's Marine Life Protected Act Initiative. Environmental Management 57: 474–497. .

Davidson

(2006) A technological frames perspective on information technology and organizational change. The Journal of Applied Behavioral Science 42: 23–39.

10.

Davidson

Pai

(2004) Making sense of technological frames: Promise, progress, and potential. In: Kaplan

Truex

Wastell

et al. (eds) Information Systems Research: Relevant Theory and Informed Practice, Boston, MA: Springer US, pp. 473–491.

11.

Dishaw

Strong

(1998) Assessing software maintenance tool utilization using task–technology fit and fitness-for-use models. Journal of Software: Evolution and Process 10: 151–179.

12.

Edwards PN, Jackson SJ, Bowker GC, et al. (2007) Understanding infrastructure: Dynamics, tensions, and design, Report of a Workshop on “History & Theory of Infrastructure: Lesson for New Scientific Cyberinfrastructures”. Available at: https://deepblue.lib.umich.edu/handle/2027.42/49353.

13.

FGDC (2017) Advancement of the National Spatial Data Infrastructure. Available at: https://www.fgdc.gov/nsdi/nsdi.html.

14.

Geertman

(2006) Potentials for planning support: A planning-conceptual approach. Environment and Planning B 33: 863–880.

15.

Geertman

(2017) PSS: Beyond the implementation gap. Transportation Research Part A: Policy and Practice. 104: 70–76.

16.

Geertman

Ferreira

Goodspeed

et al. (2015) Planning Support Systems and Smart Cities, Switzerland: Springer.

17.

Geertman

Stillwell

(2003a) Planning support systems: An introduction. In: Geertman

Stillwell

(eds) Planning support systems in practice, Berlin, Heidelberg: Springer-Verlag, pp. 3–22. .

18.

Geertman

Stillwell

JCH

(2003b) Planning Support Systems in Practice, New York: Springer.

19.

Geertman

Stillwell

JCH

(2009) Planning support systems best practice and new methods, Dordrecht: Springer.

20.

Goodspeed

(2016) The death and life of collaborative planning theory. Urban Planning 1: 1–5.

21.

Goodspeed

Riseng

Wehrly

et al. (2016) Applying design thinking methods to ecosystem management tools: Creating the Great Lakes Aquatic Habitat Explorer. Marine Policy 69: 134–145.

22.

Guhathakurta

(1999) Urban modeling and contemporary planning theory: Is there a common ground? Journal of Planning Education and Research 18: 281–292.

23.

Hamerlinck

(2011) Planning support technology implementation by local governments in the US Mountain West, Department of Geography, University of Colorado Boulder.

24.

Healey

(1997) Collaborative Planning: Shaping Places in Fragmented Societies, Vancouver: UBC Press.

25.

Holway

Gabbe

Hebbert

et al. (2012) Opening access to scenario planning tools. Policy Focus Report, Cambridge, MA: Lincoln Institute of Land Policy.

26.

Inc Encylopedia. (2017) Cross-Training. Available at: https://www.inc.com/encyclopedia/cross-training.html.

27.

Innes

Booher

(2010) Planning with Complexity: An Introduction to Collaborative Rationality for Public Policy, New York: Routledge.

28.

Innes

Simpson

(1993) Implementing GIS for planning lessons from the history of technological innovation. Journal of the American Planning Association 59: 230–236.

29.

Klosterman

(1997) Planning support systems: A new perspective on computer-aided planning. Journal of Planning Education and Research 17: 45–54.

30.

Klosterman

Pettit

(2005) An update on planning support systems. Environment and Planning B: Planning and Design 32: 477–484.

31.

Matheson

Jr (2011) Envision Utah: Building communities on values. In: Montgomery

(ed.) Regional Planning for a Sustainable America, New Brunsick, NJ: Rutgers University Press, pp. 154–167.

32.

McKeever

(2011) Visioning Sacramento. In: Montgomery

(ed.) Regional Planning for a Sustainable America, New Brunswick, NJ: Rutgers University Press, pp. 333–345.

33.

Nedovic-Budic

Pinto

(2000) Information sharing in an interorganizational GIS environment. Environment and Planning B: Planning and Design 27: 455–474.

34.

Nedovic-Budic

Pinto

Warnecke

(2004) GIS database development and exchange: Interaction mechanisms and motivations. Journal of Urban and Regional Information Systems Association 16: 15–29.

35.

Orlikowski

Gash

(1994) Technological frames: Making sense of information technology in organizations. ACM Transactions on Information Systems (TOIS) 12: 174–207.

36.

Pelzer

Arciniegas

Geertman

et al. (2015) Planning support systems and task-technology fit: A comparative case study. Applied Spatial Analysis and Policy 8: 155–175.

37.

Robey

Boudreau

M-C

(1999) Accounting for the contradictory organizational consequences of information technology: Theoretical directions and methodological implications. Information Systems Research 10: 167–185.

38.

Robey

Sahay

(1996) Transforming work through information technology: A comparative case study of geographic information systems in county government. Information Systems Research 7: 93–110.

39.

Rogers

(2003) Diffusion of Innovations, New York, NY: Free Press.

40.

SCAG (2015) 2016 RTP/SCS Demographics & Growth Forecast. Available at: http://scagrtpscs.net/Documents/2016/draft/d2016RTPSCS_DemographicsGrowthForecast.pdf.

41.

SCAG (2016) SCAG Scenario Planning Model. Available at: http://sp.scag.ca.gov/Pages/HomePage.aspx.

42.

Schön

(1971) Beyond the Stable State, New York, NY: Random House.

43.

Star SL and Ruhleder K (1994) Steps towards an ecology of infrastructure: Complex problems in design and access for large-scale collaborative systems. In: Proceedings of the 1994 ACM conference on computer supported cooperative work. Chapel Hill, NC: ACM, pp. 253–264.

44.

Steinitz

(2012) A Framework for Geodesign: Changing Geography by Design, Redlands, CA: Esri.

45.

Ventura

(1995) The use of geographic information systems in local government. Public Administration Review 55: 461–467.

46.

Vonk

Geertman

Schot

(2005) Bottlenecks blocking widespread usage of planning support systems. Environment and Planning A 37: 909–924.

47.

Vonk

Ligtenberg

(2010) Socio-technical PSS development to improve functionality and usability—Sketch planning using a Maptable. Landscape and Urban Planning 94: 166–174.

48.

Walker

Daniels

(2011) The planners guide to CommunityViz: The essential tool for a new generation of planning, Chicago, IL: Planners Press, American Planning Association.

49.

Wejnert

(2002) Integrating models of diffusion of innovations: A conceptual framework. Annual Review of Sociology 28: 297–326.