The DSS and Its Possible Applications

  • Rosalba D’Onofrio
  • Massimo Sargolini
  • Michele Talia
Chapter
Part of the The Urban Book Series book series (UBS)

Abstract

Acting amid uncertainty is a perennial situation in territorial planning, having always dealt with the inevitable relativity of assessments and choices regarding settlement transformations (Camagni and Lombardo 1999). Today, however, the complexity of territorial government when facing insecurity on different scales characterizes the historical period in which we live and requires a rethinking of the ways of carrying out territorial government activities that must deal with a continuous evolution situation. This not only requires rapidity and a capacity for updating and deciding between different options but also the willingness to address a multitude of new actors that have recently entered the decision-making process.

Acting amid uncertainty is a perennial situation in territorial planning, having always dealt with the inevitable relativity of assessments and choices regarding settlement transformations (Camagni and Lombardo 1999). Today, however, the complexity of territorial government when facing insecurity on different scales characterizes the historical period in which we live and requires a rethinking of the ways of carrying out territorial government activities that must deal with a continuous evolution situation. This not only requires rapidity and a capacity for updating and deciding between different options but also the willingness to address a multitude of new actors that have recently entered the decision-making process.

To reuse an appropriate definition by Ulrich Beck (1986), we can say that the systematic crisis triggered by the terrorist attacks of 11 September 2001 and the failure of Lehman Brothers Holdings Inc. in 2007 have definitively immersed the world in a “global risk society”. As a consequence, the strongly perturbed season we are experiencing starting at least from these dramatic events tends to be increasingly characterized by spreading awareness that resounding changes continue to come, although the direction of these changes is destined to remain almost always undetermined.1

The environmental and territorial changes underway and the consequent criticalities for which the territorial government should respond in a timely manner can be traced to some main categories:
  • The absence of updated cognitive frameworks related to the current changes, with criticalities particularly evident in the case of climate change

  • The lack of a full awareness of the negative consequences that public policies can produce on territorial and landscape systems

  • Insufficient consideration of the negative effects related to land consumption (which in turn lead to other effects/impacts such as compromising air quality or weakening drainage capacity, etc.)

  • An inability to carefully monitor the territorial and social imbalances determined by the urbanization process

  • The difficulty of making a rigorous, updated account of resource waste associated with new lifestyles and the consumption that results from it

  • A tendency to underestimate growing inequalities in the distribution of wealth and access to urban services

  • The weakness of public policies in considering the growing dissatisfaction of citizens about the widespread quality of the landscape, the quality of life, and the services that the city is capable of guaranteeing

In addressing such marked criticalities, of which landscape degradation is only the most evident manifestation of the current crisis in this development model, it is rather probable that the theory of decision-making, at least in its most traditional form, can be rather ineffective. In fact, until recently, it was represented as a framework of knowledge and related methodologies capable of making a careful decision starting with the comparison of different alternatives and considering the possible consequences. By virtue of this formulation, the decision moved within a “context of stability” in which each choice led to a determined consequence and received, according to the case, full legitimacy or explicit confutation. Today, this problem/decision/action sequence has changed profoundly, if not only because a single decision-maker can be subject to multiple problems and concurring options and a single problem can be perceived in different ways by different decision-makers. It follows that we are no longer faced with a linear decision-making sequence but a cyclic learning path; the subject follows an iterative path leading from the problem to solutions, which in turn preclude new questions and possible further problems.

In this perspective, the “decision-making arena” is much more crowded than in the past. In fact, public decision-makers are accompanied by many subjects (experts in different sectors, private businesses, investors, public entities, citizens, trade associations, etc.), which, when participating in the discussion, act as players in the process. Bringing the theory of decision-making alongside the implementation of planning processes, it is possible to highlight a close network of interactions that can be recomposed and summarized into four main activities:
  1. (a)

    Framing the problem and the policies, plans, or projects to be addressed

     
  2. (b)

    Developing a structured, calibrated system of indicators to estimate the effects due to each decision and to motivate the selection of priorities

     
  3. (c)

    Construction/implementation of alternative scenarios in order to recover the integrated worth of the different lines of intervention

     
  4. (d)

    Reformulating the plan’s objectives in light of the changes seen (reframing), with the scope as well as of activating decision-making processes and obtaining profitable interaction between medium- and long-term choices

     

The procedural character of implementing the decision-making “path” in this way within the planning process is seen in the possibility of knowledge being “renewable” and therefore not exhausted when developing a preliminary interpretational protocol. On the contrary, it precludes an iterative use once the decision-support system is fully implemented (Talia 2003).

In applying this decision-making model, one must deal with a high degree of administrative, managerial, economic, social, and environmental complexity and with the need to initiate a path for involvement and mediation among different groups of public and private subjects. The aim is to assess the possible solutions not only in terms of satisfying the predetermined objectives but also in relation to the different impacts that these intervention paradigms can have when interacting more directly with the actors and contexts. Therefore, for example, a process to construct environmental and landscape policies for a determined territory will lead to the definition of a set of actions/reactions/interactions within which different types of logic and interests from the different actors involved are compared. This can generate unintended, even positive, conflicts and effects (Hirschman 1991).

Even before being generated by the juxtaposition of actors involved in the concluding stages of the decision-making process, the conflict can anyway trigger the same means of reading and interpreting a territory, which often highlights a contrast between local and expert knowledge. Combining these two sources of the cognitive process implies the conviction that technical problems are hardly ever disconnected from the social context that generated them. It is likewise appropriate to ensure that most participants in the process are actively involved and contribute to forming collective decisions that, precisely in this way, are legitimate from different points of view.

Due to this modus operandi, there is not only a greater possibility of eliminating conflict and finding effective solutions to the problems but also of increasing citizens’ trust and renewing the credibility of public institutions. Broad involvement can in many cases favour the same applicability and acceptability of assessment procedures in the case of sensitive questions. Allowing citizens to intervene in choosing the sets of indicators used to assess policies and projects, for example, can help local administrations to better define the problems and find adequate solutions. As well, the citizens themselves can better represent their requests following this solicitation. In this particular case, well-structured involvement is even more important when the planning process should be renegotiated and/or reconsidered in view of unexpected events or modifications occurring in the list of priorities stated by the government institutions.

Where inevitable, the conflict should be understood in a proactive and creative key, disconnected from the destructive or paralysing logic that may characterize it (Nel lo 2007). This can be thought of as an open discussion that leads to the development of a territorial project starting from the shared cultural concept of the context. On the one hand, a conflict may generate a discussion and the possibility of bringing the population to questions that pertain more directly to the formulation of resource-management policies. On the other hand, a permanent widespread state of hostility and mistrust may lead to an inability to control local power and, consequently, to the deterioration of management policies with the resulting degradation of resources available to the subjects of the plan (Castro and Nielsen 2003). To avoid this trend, the daily involvement of institutional actors and politics (in the most general sense) is necessary; they should be ready to welcome ideas and the push for proposals from local communities.

The idea supporting this involvement is based on a “win-win” formula according to which each actor participating in the conflict, despite the type of interest he defends or the content of her request, can draw benefits from the conflict itself or, even better, from the negotiating process. The negotiation phase, in fact, aims to reach an agreement among the parties that guarantees advantages and opportunities for all (proponents and opponents) and which motivates actors in the conflict to reason, within a real debate, about the interests in play.

Using formulations from game theory, it is convenient to remember that, to lead to a positive outcome for all participants (or at least most of them), each transaction should translate into a non-zero sum. This means entrusting planning with the task of promoting measures and interventions to produce considerable added value, which could be redistributed during negotiation. This in turn means reaching a compromise, setting aside the initial questions that often generate prejudicial juxtaposition—and therefore conflict—and basing the decision exclusively on the possibility of obtaining advantages that, without an agreement among the parties, would not be obtained.

A decision-support system that expects the involvement of all parties to attenuate conflicts should be able to develop intelligent tools capable of “dealing with knowledge” (Fig. 18.1) and the relationships generated in a multiplayer environment. Recourse to shared indicators for interpreting the territory, policies, and projects moves precisely in this direction, even if the choice of indicators corresponds to uncertain interpretational models that can often lead to discordant interpretations. This does not mean they can be overlooked.
Fig. 18.1

The DSS process

Inconvenient setbacks can arise when using one system of indicators rather than another; promoting decisions without preventive information is like flying blind. Faced with this risk, it is necessary to avoid any rigidity and plan by “learning on the job”. In fact, a complex system suggests the application of procedures imprinted with enhancing experience and pragmatism but leads to errors and failures that can be limited, thanks to learning, which is developed starting from a rigorous cost-benefit assessment for each intervention.

Bossel, a member of the Balaton Group, i.e. an international group of experts that has worked to favour sustainable development since 1981, maintains that organizations that depend on the consensus of their members mostly tend to select long lists of indicators. These lists contain, in extraordinary detail, questions on which they agree while mostly leaving out controversial questions, thus losing the extreme richness of cognitive processes that in many cases are entrusted to the many-sided, varied content of different, if not outright diverging, orientations.

Following the same approach for this research, the choice was made to include not only the indicators of urban quality and the landscape which are entrusted to registering physical parameters and on which there is now reasonable consensus but also indicators of a different nature, based on the subjective perception of phenomena for which it is possible to estimate quality rather than quantity.

If, in fact, it is now certain that physical variables can also contribute to the qualitative definition of a territorial context, it is likewise unquestionable that the same indicators cannot “read” certain factors of quality of life such as harmony, beauty, balance, satisfaction, health, the sense of safety, or well-being. To the many people who usually object that the parameters used to analysed these fundamental questions are neither trustworthy nor replicable, one can respond that this is an error of reduction: no individual judgement will be equal for all, but the judgement of all members in a community will be solid, stable, and repeatable, assuming the same authority as a physical measurement. In addition, the assessments that can be expressed on this apparently unstable basis become dynamic for this reason. They acquire a capacity to adapt and evolve and a sensitivity to changes that measurements related to the physical state of a determined settlement context are not capable of expressing.

The choice made in this research, which is illustrated in detail in Chap.  5, is related to building a system of indicators capable of satisfactorily and synthetically representing the “measure” of quality of life. The construction proceeds via a top-down approach whereby various experts select some indicators suitable for parameterization, as well as a bottom-up approach to integrate and combine the indicators that, on the level of phenomenology of the relevant processes, are deemed by the local community to be important for the quality of life of the urban landscape. In the current state of the research presented in this volume, the relevant investigations regarding these non-formalizable indicators have not been made.

The initial selection (Chap.  5) was followed by a further selection that can be implemented with the contribution of local communities and which will relate to the policies, plans, and projects that were selected by the research group through a specific forum. A sort of combined top-down and bottom-up approach is therefore proposed, which is also capable of embodying a long-term vision of the development model. The active involvement of local communities will be fundamental in responding effectively to the needs of the places, thereby avoiding recourse to external or even self-referential logic.

Up to now, this model has been applied only to the city of Ancona (Italy). However, with the appropriate optimization and recalibration, it can be applied to other medium-sized cities in Europe, constituting valid support to allow public administrations, planners, and local communities to evaluate the impacts of different policies on the quality of life in the city and the quality of the landscape and to optimize the results obtained by its application.

The development of the model was organized into four large fundamental areas (D'Onofrio and Talia 2014):
  1. 1.

    Framing the problem through the selection of policies, plans, and projects expressed by the urban system studied within institutional planning documents, plans, and projects being activated (see Chap.  23).

     
  2. 2.

    Developing a structured, calibrated system of indicators of urban quality, as described in Chap.  2.

     
  3. 3.
    Constructing/implementing alternative scenarios by verifying possible development paths and lines of action deriving from the programming tools promoted by the cities or other proposals emerging from the interaction with the public administration through:
    1. (a)

      An evaluation system relying on a mathematical algorithm that simultaneously and contextually assesses different indicators (composed of multiple variables) that can be formally defined and represented. For brevity, we refer to this first part of the output as the Tool.

       
    2. (b)

      An interpretation and assessment system that relies on the active participation of local communities and “interested populations” (European Landscape Convention/ELC 2000, Florence) and uses indicators that cannot be formalized in a mathematical algorithm. For brevity, we refer to this second part of the output as the Forum. The Tool uses indicators that evaluate the environmental performance of the city. The mathematical algorithm within the Tool relates the different indicators (by pairs) in order to identify a range of possible balances among them, which could orient a wide range of different possible scenarios. The indicators selected regard the “environmental performance” of the city, which influences the quality of the urban landscape and the quality of life of city inhabitants. In the Forum, indicators pertaining to the stratified values and symbols of the places, the imagination, and collective identification are “chosen” and “presented” to the stakeholders, local community representatives, and the “interested population”. This second family regards the “performance” of the city and influences the quality of the landscape and of life. They cannot be formalized, and they are not considered by the mathematical algorithm in the Tool. By “going back to go forward”, their use allows points of contact and sets of possible scenarios to be established with the Tool.

       
     
  4. 4.

    Reformulating the objectives and choices made (reframing). This methodological setting, which works by formulating development scenarios in relation to the effects on the quality of life and the landscape, makes clear that the choices made regarding policies and projects expressed by a given territory should not be assimilated in a conclusive act or a current state of equilibrium. Rather, it should be an open process that can be modified based on the behaviour of the actors in play and their changing needs, and it should be ever ready to explore new hypotheses according to that same elasticity that allows us to understand the territory as a continuum, which is also made of juxtapositions and discord. The landscape in this context becomes an opportunity for communication between the population and the territory, where the transition from reading and knowledge of the places to defining the objectives of quality of life is translated into a conscious, shared act that is refined through expert knowledge and the expectations and desires of the local communities.

     

Footnotes

  1. 1.

    An investigation of the possible implications of the advance of the risk society and the effects it has had on the decision-making process is contained in Michele Talia’s contribution to this volume (“Urban-Planning Tactics and Strategies in New Decision-Making Process”), as well as in Beck’s essay cited in the Bibliography.

References

  1. Beck U (1986) Risikogesellschaft: Auf dem Weg in eine andere Moderne. Suhrkamp, Frankfurt am Main (2000, trad. It., La società del rischio: verso una seconda modernità, Carocci, Rome)Google Scholar
  2. Camagni R, Lombardo S (eds) (1999) La città metropolitana: strategie per il governo e la pianificazione. Alinea, FlorenceGoogle Scholar
  3. Castro P, Nielsen E (2003) Natural resource conflict management case studies: an analysis of power, participation and protected areas. Syracuse University and FAOGoogle Scholar
  4. COE, Council of Europe (2000) European Landscape Convention, FlorenceGoogle Scholar
  5. D’Onofrio R, Talia M (2014) Monitoring DSS. In: Sargolini M, Gambino R (eds) Mountain landscapes. A decision support system for the accessibility. LIST, TrentoGoogle Scholar
  6. Hirschman AO (1991) The rhetoric of reaction: perversity, futility, jeopardy. The Belknap Press of Harvard University Press, CambridgeGoogle Scholar
  7. Nel lo O (2007) Aquí, no! La conflictividad territorial de base local. In: Inforgeo, pp 29–36Google Scholar
  8. Talia M (2003) La pianificazione del territorio: conoscenze, politiche procedure e strumenti per il governo delle trasformazioni insediative. Il Sole 24 Ore, MilanGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2018

Authors and Affiliations

  • Rosalba D’Onofrio
    • 1
  • Massimo Sargolini
    • 1
  • Michele Talia
    • 1
  1. 1.School of Architecture and DesignUniversity of CamerinoAscoli PicenoItaly

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