How does decision making work?

Section 3.1 focused on various aspects of transport PPPP making, revolving around its processes and arising conflicts. The specific decision making situation was said to potentially give raise to certain acting strategies, which in turn was said to potentially enable identification of situation specific indicators.

This section provides for some theoretical underpinnings of different decision making situations. In this context, the focus is on a few basic decision making models that can help to explain why and how a specific situation (as outlined in the previous section) may arise. Models introduced include the rational model, the bounded rational model and the garbage-can model of decision making (following Posas and Fischer, 2008). In addition to these three basic models that are able to explain the acting strategy identified in section 3.1, political aspects of decision making are also discussed, referring to the political or coalition approach to decision making. Finally, reflecting on the recent mainstream planning debates (see e.g. Elling, 2008) communicative planning theory is also outlined.

3.2.1. Rational model of decision making

In the rational model, decision making is a rational, linear process, which will produce rational outcomes. It is used to explain microeconomic behaviour and is the accepted model in many disciplines up to the present. The steps in rational decision making (which are similar to the stages of the traditional ‘policy cycle’; see Figure 9 on page 90) can be described as follows (Brooks, 2003, p. 36):

1 identifying a problem that requires a decision;

2 gathering information and materials that will help solve that problem;

3 generating potential solutions to the problem; and

4 making a rational choice, selecting the best solution, and then implementing it.

This is a logical normative model, and the main difficulties with it lie not with the model’s process, but rather with its underlying assumptions. Thus, the model implies that a person will:

“always make a rational decision based on the ability to evaluate all the alternatives and effectively calculate the potential success of each alternative (Brooks, 2003, p. 36).”

In addition, it suggests that the decision is being made in a stable, slow-moving environment and that the decision maker has ample of time to gather all the information, reflect on all the alternatives, and reach a rational solution. This implies that there would also be ample of space and time to identify appropriate indicators that may be used at the different stages of the policy cycle. The main function of indicators (see section 1.2) would therefore be to inform decision making. Indicators therefore fulfil an important role and can potentially effectively influence outcomes. In practice, routine decisions where consent on norms and values is high and uncertainties are low may nearly follow this

rational process (Butler, 1991). However, many decisions, particularly at higher tiers (see Figure 6 and Figure 7) face more pressures and unknowns than this model’s assumptions allow for.

3.2.2. Bounded rational model

In 1959, Simon introduced the concept of bounded rationality to address the rational model’s potential weaknesses and incongruence with many decision making contexts, which are not benefiting from unlimited time and perfect information, i.e. referring to Figure 6 and Figure 7, decisions at higher tiers that are marked by greater uncertainty and less consensus on norms and values.

Bounded rationality is not based on an alternative concrete normative process, similarly to a rational process. Rather, it suggests that a rational process does not realistically describe real decision making in many situations.

However, there have been attempts to model bounded rationality. These models are at time highly complex (e.g. computer models). Rubinstein (1998) proposed to model bounded rationality by explicitly specifying decision-making procedures. These vary, depending on the specific context of application.

The bounded rational model has been shown to be much more consistent with the way e.g. managers of enterprises behave (Brooks, 2003), in that they are faced by time pressure and imperfect information which causes them to find a solution that will ‘satisfy’ rather than what might have been the best one.

While the rational model can be said to still have some relevance for more routine decisions (i.e. referring to Figure 6, decisions with a high consensus on values and knowledge), the bounded rational model is more appropriate for unfamiliar, non-routine, and potentially contentious issues (Butler, 1991). Its six explicit assumptions are listed in Table 14. Here, indicators would be identified on an ad-hoc basis, depending on how the decision process pans out, probably with no direct link to specific goals and targets. Whether certain indicators could be consistently used is rather questionable.

Table 14. Features accepted in the bounded rational model

• Managers respond to problems rather than going out of their way to find them.

• Cognitive limits exist in the search process (human mind is limited in comprehension of problem).

• Time pressures frequently apply (decisions have to be made with incomplete information).

• Disjointed and incremental decision making often occurs, not a smooth continuous rational process.

• Intuition and judgment may have to be the basis for making a decision rather than computation.

• Satisfying (satisfactory and ‘will do’) solutions rather than optimal solutions are arrived at.

Source: adapted from Butler (1991, p. 47)

3.2.3. Garbage can model

Cohen, March and Olsen’s (1972) ‘garbage can model’ is different from the two rationality based models just discussed, in that it is not a sequence of steps that start with a problem and end in a solution. Rather than steps, this model proposes four independent streams (problems, solutions, participants, and choice opportunities). An organisation acts as a ‘garbage can’ in which these streams flow. A decision will be made when problems and solutions can be connected during a time when there are choice ‘opportunities’ (to be made by individuals). This model is more random and likely to be relevant to organisations operating in a volatile business environment (Brooks, 2003).

Butler (1991) notes that organisations following this model exhibit several features, including:

− ambiguity in the decision process;

− difficult to determine cause and effect relationships; and

− fluid participation (i.e. turnover of participants).

While not particularly efficient in organisations (Butler, 1991), the garbage can model can represent an apt description of public policy making (Kingdon, 1995), convergence of problem, policy, and politics. In this context, indicators are likely to mainly fulfil a generic measurement function (see section 1.2.1). To what extent indicators can fulfil an effective role is rather questionable.

3.2.4. Political or coalition approach to decision making

Whilst the three basic decision making models introduced above underpin the various possible PPPP making situations introduced in section 3.1, this paragraph briefly deals with what has been described as the political or coalition approach to decision making. This may provide for a useful additional explanation for how transport PPPP making may happen. It also hints at the necessity to be cautious when approaching transport PPPP making in an overly rational way. Subsequently, three related models are introduced; (a) the political or coalition model; (b) the contingency model and (c) the contingent institutional model.

(a) The political or coalition model of organisational decision making was put forward by Cyert and March in 1963. In it, the process of organisational decision making is portrayed as

“involving shifting coalitions of interests and temporary alliances of decision makers who can, for the purposes of a decision, come together and sufficiently submerge their differences to make a decision” (Butler, 1991, p. 51).

A coalition may be formed for just one decision, though some quid pro quo and bargaining is likely to be involved. This kind of decision making has been known to occur in government contexts.

Figure 8. Contingency model of organisational decision making

Source: Butler (1991, p. 59), adapted from Thompson and Tuden (1959)

(b) The contingency model of organisational decision making, developed by Thompson and Tuden (1959), charts the decision making models in terms of means and ends uncertainty (uncertainty about how and why to take a course of action). It positions the three theoretical models discussed above in relation to one another, and adds a ‘coalition’ dimension. Furthermore, it suggests the type of organisational context for which they might be appropriate (Figure 8).

Here, ends uncertainty can be seen as being equivalent with certainty on values and means uncertainty with certainty of methods. This complements the suggestions coming out of Figure 6 and Figure 7. This model can be connected with those introduced in section 3.1 regarding a communication based acting strategy for different decision tiers.

(c) In the third model, the contingent institutional model of organisation, Butler (1991) links the institutional model of organisation (consisting of context, structure and ideology) to the decision models. He sees decisions in terms of their interactions with the areas of context, structure, and ideology in a given organisational context. The variables associated with each aspect are shown in Table 15.

Table 15. Variables associated with three aspects of organisation

Fuzzy v Crisp Complex v Simple Robust v Focused Implicit v Formal

Expert v Local Differentiated v Demarcated

Interactive v Parametric Active v Analytic Collective v Individualistic Decentralized v Centralized

Supportive v Punitive Symbolic v Literal

Unique v Comparable Open v Concentrated Ambiguous v Clear

Variable v Stable Disparate v Agreed Heterogeneous v Homogeneous

Independent v Autonomous

Plural v Singular Tolerant v Particular

Moral v Efficiency

Source: Butler (1991, p. 255)

While the exact meaning of some of these terms may not be apparent without further reading, they suffice to illustrate Butler’s observation that there is a constant tension between these dialectical aspects in an organisation. These variables also fuel a tension between inner loop learning (pushing an organisation towards efficiency) and outer loop learning (which helps it adapt).

In this context, Butler (1991, p. 255) explains that the

“phenomenon appears in organizations when short term expediency leads organizations to tighten up structures, with apparent immediate return achieved through greater efficiency, centralization, and the like, but leads the organization into a vicious circle of decline as the ability to adapt to future exigencies decreases.”

In crisp decision making situations, indicators are likely to fulfil a decision making function, informing actors on the best outcomes. The fuzzier a decision making situation the more likely the role of indicators will be limited to generic measurement.

3.2.5. Communicative planning

Since about the mid 1990s, communicative planning has been widely promoted as the way to reach decisions in societies that are increasingly marked by fragmentation and individual lifestyles (see e.g. Healey, 1996; Innes, 1998). In this context, societal problems were said to have become too complex to be solely managed by the ‘classical’ model of representative democracy (Innes, 1995). Based on observations that planners are not often able ‘to deliver unbiased, professional advice and analysis to elected officials and the public, who in turn make the decisions’ (Innes, 1998), but instead spend a lot of their time communicating with various stakeholders and actors, communicative planning is widely seen as an alternative approach to the rational model, introduced in section 3.2.1. In communicative planning, the function of indicators is likely to be reduced to generic measurement for informing actors, rather than for making decisions.

The concept is based on Habermas’ notion of communicative rationality, arguing that people inevitably searches for and accepts rational arguments in open and fair debates. The ensuing idea is that policy, plan and programme making should develop as an arena for conversation among equals in what has been called an ‘ideal speech situation’ which, in turn, should lead to consensus decisions. Several principles underlie the concept of communicative rationality.

These are shown in Table 16.

Whilst communicative rationality is likely to be able provide some good guidance in unstructured or fuzzy situations, it is doubtful whether it is equally useful in situations, which are structured and crisp (see Figure 6 and Figure 8).

In this context, the underlying assumption that communicative spaces could be created that are free of power has been criticised as being unrealistic in many decision making situations (Tewdwr-Jones and Allmendinger, 1998).

Table 16. Principles of communicative rationality as a process of deliberation

− Individuals representing all important interests must be at the table

− All the stakeholders must be fully and equally informed and able to represent their interests

− All must be equally empowered in the discussion

− Power differences from other contexts must not influence who can speak or who is listened to

− The discussion must be carried out in terms of good reasons, so that the power of a good argument is the important dynamic

− The discussion must allow all claims and assumptions to be questioned

− Within the process, it must be possible for participants to assess the speakers’

claims in terms of four tests

• Speakers must speak sincerely and honestly

• They must be in a legitimate position to say what they do, with credentials or experience to back them up

• They must speak comprehensively (jargon and technical language communicates poorly)

• They must be factually accurate

− The group should seek consensus

3.3. Towards the development of a