A CONTINGENCY FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING

Yoder: A Contingency Framework for Envlranmental Dedsion-Makhg

A CONTINGENCY FRAMEWORK FOR ENVIRONMENTAL

DECISION=MAKING:

Linking Decisions, Problems, and

Processes 11

Diane E. Yoder School of Policy, Planning and Development University of Southern California

Policy Studies Review, FayWinter 1999 16:3/4

ABSTRACT

This article explores a contingency framework for environmental decision- making. This framework suggests when environmental decision-makers will use certain decision-making processes by arguing that the process used is contingent on the type of environmental problem confronted and the attributes of the decision being made. I examine environmental decision-making @om two points. First, in the policy and organizational behavior literatures, a shortage of decision typologies exists. Thus, the article suggests a general typology of decision-making based on dichotomized categories, e.g., short-term versus long-term decisions, decisions made under certainty versus uncertainty, new versus redressed decisions. Second, I suggest a general classijkation of environmental problems and describe their characteristics. The two typologies are superimposed and predictions made for when certain decision processes will be used. By categorizing decision types and process conditions, one cqn suggest what processes best suit which decisions and offer suggestions for improving policy outcomes.

INTRODUCTION'

his article explores the possibility of a contingency T framework for environmental decision-making. Rather than argue that organizational decision-making is based on one process only, this article suggests that environmental decision-makers will use different decision-making processes contingent on the types of decisions being made and the types of environmental problems confronted. The framework described here identifies potential influential attributes of environmental problems and decision types as routes to decision-process selection. In other words, by categorizing decision types and the conditions of interest of the processes, as well as environmental problems and their attributes, one might predict which processes will be used with which environmental problems.

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Three reasons for exploring environmental decision- making drive this framework. First, the contingency framework proposed here may fill certain gaps in the organizational behavior, policy, and environmental decision-making fields. Next, the framework offers areas of environmental decision-making that may

Yodec A Contingency Framework for Environmental Dedsion-1Malring

be appropriate for future empirical studies, which, once completed, may suggest which decision-making models are appropriate for which problems. Finally, the article may help elucidate environmental decision-making for practitioners who are working to involve multiple stakeholders in the decision-making process, as the article by Bauer and Randolph in this volume highlights.

I begin with a review of eight organizational decision- making models and two concepts, highlighting the historical development of the decision-making literature, the theoretical constructs of the models, and the decision processes of each model. Next, I identify seven attributes of decisions (e.g., time horizon, amount of risk) involved in environmental decisions, which form the basis of a new typology of environmental problems. The typology proposed here is new to the environmental policy literature and is suggested to demonstrate how environmental problems differ from other policy problems and to assist environmental policymakers at all levels classify the types of problems they confront. The article then superimposes the three areas in a contingency fiarnework to suggest when certain decision processes might be used and examines some current decision- making projects vis-a-vis the contingency framework. The proposed framework may help federal, state, and local policymakers, nonprofit groups, and local citizens self-diagnose the nature of environmental problems and facilitate decision- making at all levels.

I3

DECISION-MAKING MODELS AND CONCEPTS

The notion of organizations as decision-making bodies was developed in the 1940s and 1950s by Herbert Simon and others like James March (Morgan, 1 986). Originally, decision-making was modeled on perfect rationality. Simon, however, saw limits to the rational model, which is a prescriptive or normative model, and developed a more descriptive model of bounded rationality. Simon argued that organizations are not perfectly rational due to limited information processing capability, “good enough” decisions

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based on simple rules of thumb, and limited information.* Simon noted that organizations are “institutionalized brains that fragment, routinize, and bound the decision-making process in order to make it manageable” (Morgan, 1986: 8 1).

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From Simon’s work, both directly and indirectly, came other models of the decision-making process. The work of Cyert and March (1 963) and others developed a stream of models and concepts, based on behavioral aspects of decision-making, that focused more on an empirical rather than normative theory. The behavioral model is based on the idea of the organization as a coalition, thus decisions are made based more on bargaining and side payments than on the definition and analysis of preferences and alternatives. That is, organizations consist of factions with agendas. At any given time, the dominant coalition may change, but coalitions obtain their objectives through bargaining and side- payments. Related models include incrementalism (Lindblom, 1959) and the garbage can model (Cohen, March, and Olsen, 1972).

In addition, Pfeffer and Salancik (1974) argued that decision-making is based on power and coalitions. That is, power is the basis of decision-making, particularly in resource allocation. A related idea is one of escalation of commitment (Staw, 1976), which is not considered a full-fledged model, but is an important addition to the decision-making literature. This deals with the continued support of a bad policy decision to save face and protect a power dynamic. Work on these models can be seen in a kind of progression from the rational model to behavioral deviations to specific behavioral models. For example, the politics model is, in one sense, a continuation of the behavioral deviations from rationality. Also, some concepts or processes may be applicable to both models (e.g., escalation of commitment).

This article’s focus on organizational decision-making deviates from traditional decision thought, which argues that the process chosen is based on individual factors like context,

Yoda: AContZngencgFramewakfor Environmental Decision-Making

psychological conditioning, and experience of the decision- maker@) involved. The reason for the organizational focus is that most environmental policy is made by organizations. While individuals make decisions that affect their particular environmental role, most policy-making is done at the organizational level.

The following eight models and two concepts are the primary ones used in decision-making and recognized in the organizational behavior, public administration, and public policy literatures.

The Rational Model

March and Simon (1958) were some of the first organizational researchers to describe the rational model for organizations, which was derived from classical economics. This model involves four steps. First a unitary and discrete objective or goal for the decision and all available means for achieving that goal are specified. Next, the alternatives are thoroughly analyzed and the consequences or values for each alternative are quantitatively and qualitatively explained. Then, the alternative, based on the consequences set out in step two, are rank ordered. Finally, the alternative that maximizes utility or has the most benefits given the goal is chosen. The key here is to maximize utility or to decide on the alternative that provides the best possible return (Lein, 1997).

The model is straightforward in theory and has predictive value; in reality, however, decisions rarely get made that way. Problems lie in the assumptions of the model. It is rare that a unitary, discrete goal can be identified. Also, knowing the full set of alternatives and the consequences of those alternatives is a rare luxury for decision-makers. As well, it is unusual that the full set of alternatives can be rank-ordered. Thus, using the rational model often impedes the decision-making processes and organizational functionality. Harrison (1 993) adds that the rational

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model assumes that numeric values can be assigned to various preferences and outcomes, and when it cannot, that preference or outcome should be disregarded.

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Bounded Rationality Model

The limits of the rational model led Simon and his colleagues to a derivative of that model. Simon argued that at best, rationality is bounded in decision-making. Often, organizations have more than one goal and they do not consider the full set of alternatives or consequences. More important, however, is the idea that alternatives are chosen on the basis of familiarity; that is, alternatives chosen are those similar to past alternatives, those that are easy to identify, or those that can be made on the available information. Simon also argued that full information comes with information costs and because of this, more uncertainty exists than the model assumes. March (1978) also argued that objectives and preferences are not always known or consistent. In fact, he argued that decisions get made more randomly due to the inconsistency in goals and alternatives. March and others continued Simon’s work on bounded rationality, developing variations, including limited rationality, selected rationality, contextual rationality, process rationality, and posterior rationality.

An important extension of the bounded rationality model is that of satisficing identified by Simon. This process is based on the idea that maximized utility is ignored even in the bounded rationality model. Thus, instead of evaluating alternatives with maximization in mind, an alternative that satisfzes is chosen after a shortened search for and analysis of alternatives, and minimum expectations guide that choice. Lein (1 997) explains the model as that used when due to time, resources, or individual constraints, the alternative with the highest value may not be available to decision-makers. Thus, the goal becomes that of satisfying basic objectives or values and hoping to improve the outcome with subsequent decisions.

Yodec A Contingency Framework for Environmental Decision-Making

Another variation of bounded rationality is that of credibility logic (Coursey, 1992). This model argues that information is less important than theprocess of how we decide. That is, the highest quality data or information that is closest to perfect may be ignored or discounted as the decision is subjectively evaluated. Information, credibility, and logic are weighted differently as decision-making relies on stories and colorful, personalized pieces of information, rather than statistics. Sometimes information external to the decision-making process is used. In other words, credibility often suppresses the search for arguments and counter arguments.

Process or Bureaucratic Model

Based on Allison (1 971), this model splits decisions into subparts and then routinizes or proceduralizes them. Decisions are best seen as the outputs of the organization and less as deliberated choices. Thus, decisions get made based on routines and previous experiences, rather than consideration of preferences, alternatives, and outcomes. In difficult or uncertain decisions, decision-makers may opt to rely on standard operating procedures. Lein (1997) refers to this model as the “organizational model” and notes that decision-makers will make their choices based on preordained policies or decision guidelines (i.e., process) to reduce uncertainty.

Incrementalism

Lindblom’s incremental model (1959) is based on a negotiation process. Decisions are made through bargaining done by various participants, each trying to improve some salient aspect of the organization without any definitive or best solution in this “muddling through” process. Rather than deviate from the status quo, decisions are decomposed into small parts or little steps and choices are made sequentially (Pennings, 1983). What is interesting here is that goals do not necessarily predate potential solutions. That is, an alternative may establish a new goal thus policy emerges

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Policy Studies Review, FaWWiitex 1999 16:3/4

as goals and solutions. Furthermore, goals and solutions are closely intertwined.

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Garbage Can Model

This model is characterized by organized anarchy (Cohen, March, and Olsen, 1972). The organized anarchy is based on “problematic preferences, unclear technology, and fluid participation” (p. 1). The goals do not have any bearing on the decisions made in this process, in which problems are multiple and have many possible solutions. Decisions get made at decision points (e.g., annual budget) in the process. This model mixes these elements randomly and spits out a decision randomly. Gortner, Mahler, and Nicholson (1 989) go so far as to call it a “nondecision- making” model.

Politics Model

The politics model is based on political influence or power as the primary basis for decisions (Pfeffer and Salancik, 1974; Pfeffer, 198 1). Lein .( 1997) refers to this model as one of group interaction. This process for decision-making is one in which conflict is present and no clear solution exists. Rather, conflicting coalitions (e.g., in Pfeffer and Salancik’s study, university subunits vying for resources) base decisions on bargaining and on relative political strength. Here, power is a “structural phenomenon” and when decisions get made as to who will get what and how and when they will get it, decisions are made based on power (Pfeffer, 198 1). In addition, consistent, overarching goals or objectives do not drive decision-making. Nor are preferences of any one coalition or of the organization evident, due to the bargaining nature of the process. Again, the optimal solutions may give way to acceptable solutions that satisfl the conflicting coalitions as best as possible.

Accountability Logic

This politically related concept argues that “people are, in a fundamental sense, politicians who need to achieve and

Y& A Contingency Framework for Environmental Decision-Making

maintain the good will of the constituencies to whom they are accountable” (Tetlock, 1985: 325). Accountability is defined as a necessary part of organizing society, as the regularity mechanism founded on norms, social processes, and rules. Tetlock argues that people will seek approval or status due to (a) the drive to protect or build one’s social image, (b) the drive to protect or enhance one’s self-image, and (c) the drive to maintain the respect of others via resource procurement. Thus, people will make decisions that others are likely to approve of or accept without going through the exhaustive search for and calculation of preferences. As well, people will make “predecisions” based on identifying the most defensible solution possible.

Escalation of Commitment

This concept argues that decision-making gets “entrapped” in specific policy options, and that the escalation of commitment to a given option, whether or not a better one exists, is associated with the negative consequences of that decision (Staw, 1976; Staw and Ross, 1978). Decision-makers, feeling responsible for the negative outcomes of the decision, will escalate their commitment (both emotional and physical/material) to the decision, risking further negative outcomes. That is, decision-makers will process information differently and will allocate more resources on programs with negative consequences when they feel responsible for those consequences. The classic example of this is the decision- making process in becoming involved in the Vietnam War.

In spite of the models and concepts that have been developed, some critics suggest that organizational decision- making may not even exist (Peter J. Robertson, personal communication, Nov. 1994). The organization itself does not have a brain that makes decisions; it is the people within the organization-individually or within groups-who make the decisions. As Robertson argues, the deviations from perfect rationality, then, result from the deviations on the individual’s part combined with deviations in the aggregate. To focus on decision-

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making at the organizational level, then, one must look at the types of decisions that get made in organizations. That is, what organizational-level decisions get made and what process is used in making them? To speak to organizational decision-making by process alone leaves some uncertainty and doubt as to which process is used and why. To use decision types to predict the decision process at work, as the proposed contingency framework does, may allow a more complete understanding of organizational decision-making.

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DECISION TYPES AND AITRIBUTES

Although decision-making models are described in various bodies of Qterature (e.g., organizational behavior, public policy, public administration), finding a single typology of decisions or a description of the kinds of decisions organizations make is fairly difficult. Some theorists have broadly classified decisions. For example, in one study, Kraemer and Perry (1 983)3 identified three types of decisions governmental agencies make: operational, programming/management, development/planning. Operational decisions are the simple, small, day-to-day decisions that get made independently based on singular objectives. Programming and management decisions are those that are permanent, have multiple objectives, interrelated factors, and are steps in a process of trying to achieve some overarching goal. Development and planning decisions are those that involve the future of the organization, determining objectives, alternatives, and the long-range vision for the organizations. In another example, Cyert and March (1992) defined three decision types for business firms: output decisions, price decisions, and internal resource allocation decisions. Such general categories, however, only partially inform the array of decisions made in an organization.

Due to the shortage of decision typing in the decision- making literature4 and the streamlined categorizing of decisions mentioned above, it might be more useful to concentrate on the attributes of individual decisions and their consequences, for which

Yodm A Contingency Framework for Environmental Decision-Making

one can identify at least seven general attributes. These are derived from the contexts of the decisions, the consequences of the decisions, and the type of problems confronted. The first two attributes concern the crux of policymaking, i.e., information, without which decisions would be little more than guesses. The amount of reliable information regarding the problem under decision or the consequences of alternatives accessible to decision- makers, i.e., the level of uncertainty in a decision situation, is a key attribute. Uncertainty not only encompasses the tangible information available for any given problem, it also may be affected by the ability of decision-makers to acquire, understand, and integrate information. Furthermore, borrowing from New Institutional Economics, a related decision attribute may be based on the balance of information held by various people involved directly or indirectly in the decision-making process (i.e., information asymmetry). Closely related to uncertainty is the attribute of risk, which involves the likelihood that some adverse consequence will materialize from a policy decision. Although several forms of risk assessment have been developed, exact measurement is elusive because of the probabilities involved.

Related to the consequences of the decision made, another decision attribute is the time horizon of its effects. At a basic level, one can identify short- and long-term decisions. Lein (1 997) expands this idea noting that precise or discrete classifications of time effects may be elusive due to the “snowball” effect of the ramifications of decisions, or what policy analysts and economists term decision “externalities.” Thus, Lein proposes three time dimensions: acute, chronic, or synergistic/cumulative. The former is a decision effect that immediately materializes, while a chronic effect is one with an extended time horizon. Synergistic/cumulative effects are those that may not appear until the decision effect is viewed within a broader and interrelated social, political, or environmental context. Related to time, Lein (1 997) also suggests that decisions have spatial dimensions in which the decision effects have some geographic boundaries. He identifies three such spatial dimensions: (a) microscale, which has clear and specific spatial

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Policy Studies %view, Palvwinter 1999 16:3/4

effects; (b) macroscale, which has broad and general effects; and (c) mesoscale for problems that fall somewhere between the two.

Finally, from an organizational operation standpoint, decisions may be operational or strategic. That is, decisions may deal with routine or repeated implementation issues or may be one-time strategic decisions that affect a discrete situation. Similarly, decisions may be new or redressed; the decision may confront a new problem or may revisit a problem for which prior decisions must be reviewed. These seven attributes present a starting point for matching decision types with decision-making models. Other decision attributes may exist; certainly a more complex framework for decision attributes than that suggested here should be pursued.

ENVIRONMENTAL PROBLEMS

22 Addressing environmental problems poses a challenge for decision makers because of the problem attributes mentioned above. While many social regulatory problems share these general problem attributes, this author argues that the scope and effect of risk, uncertainty, and information asymmetry make environmental problems different. Many environmental problems involve high levels of risk, which complicate decision-making because of measurement difficulties. This is due to various quantitative and qualitative methodologies for assessing risk probabilities, both of which may be affected by subjective and value-laden cognitive processes, as well as sociopolitical and cultural factors, gender, ethnicity, and other phenomena (Slovic, 1997). Discovering some measurement of risk offers only a partial picture of cause-and- effect reactions in the environment, leaving a large amount of uncertainty in policy analysis. This uncertainty vexes decision- makers, who are stymied by a lack of information and unassigned property rights in defining the problems and assigning solutions. For example, global warming is an atmospheric problem, yet property rights are not assigned to the atmosphere. As such, externalities exist and leave policy-makers with a vague set of

Yoda: A Contingency Framework for Enviionmental Decision-Making

parameters/physical boundaries within which to address the problem.

The third distinguishing characteristic is information asymmetry. In addition to the lack of certain information in environmental problems, a lack of complete information plagues policymakers, who must often rely on scientific experts for information on environmental problems. As well, differences in the amount of information various decision-makers (e.g., scientists, bureaucrats) may have create discrepancies and misguided priorities, complicating decision-making. The classic example of this discrepancy is that of Superfimd, which continues to be the most expensive environmental program-nearly $2 billion in 1998-and yet is fraught with discrepancies; scientists view hazardous waste removal and storage as a low-risk problem, while the public views it as a high-risk problem.

23 To begin to address these complexities, I propose a typology of environmental problems, based on the very characteristics that make environmental problems different. Such a typology, which does not exist in the environmental policy literature, allows for making decisions and policy in ways contingent on the types of problems being confronted. That is, the different problem types allow policymakers to use different plans for addressing problems with different solutions contingent on the various types of problems and attendant characteristics present in each environmental problem confronted. A caveat is in order: This typology is still exploratory in form. Although some problems may not fit neatly into one category, if a preponderance of problem attributes is found in one category, then the problem should be classified as such, even though one or two attributes may fall into another classification.

Most environmental problems can be classified as one of three types-crises, symbolic causes, and scientific/technical problems-based on attributes discussed above. In some cases, problems may be borderline between two categories and the

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ultimate classification of the problem would depend on how analysts define the p r ~ b l e m . ~ Crises are those environmental problems that are clear, concrete, and immediate environmental incidents from which people feel a direct or indirect impact, such as Love Canal, Three-Mile Island, and the Exxon Valdez Oil spill. Crises also may be continual, such as repeated sewage spills in California’s Santa Monica Bay. Human management-or mismanagement-of environmental and natural resources usually creates crises. The level of risk will usually be medium to high, although uncertainty and information asymmetry will usually be low to medium. The time horizon is usually more acute and the spatial effects of the crisis may be microscale, although a few crises may be mesoscale. If the crisis has long-term effects, like some oilspills, then uncertainty and information asymmetry may increase over time. Operations decisions made about crises are usually new and strategic decisions, although in the case of an on- going crisis like sewage spills, the decision may be of a redressed nature.

Symbolic causes are sentimental causes that have a clear face or image attached, such as wolf reintroduction, dolphin protection, and ancient forest preservation. The public may not feel a direct impact from the problem, but they will likely see the effects. Such problems usually result fiom egregious environmental abuses of species or natural resources against which the public will rally. Low-to-medium uncertainty, information asymmetry, and risk are involved: and the time horizon is usually chronic or synergistic/cumulative. The spatial horizon of a symbolic cause is usually microscale or mesoscale. New or strategic decisions may be made, as might operational or redressed ones.

The third problem is the scientijWtechnica1 problem, which is more abstract and not widely understood. Scientific/ technical problems require a more technical understanding of a less visible cause-and-effect relationship with no clear symbol or “face” attached. Scientific communities or “epistemic communitie~”~ usually bring them to the attention of policy-makers and the public, as was the case concerning the depletion of the

Yoder: A Contin%ency Framework for Environmental Decision-Malring

Ozone layer and the ensuing negotiation of the Montreal Protocol.8 The communities may include ad hoc scientific partnerships of colleges and universities, professional societies, and science academies.

Examples of such problems include global warming, Ozone depletion, air pollution, and organic toxins in food. Such problems are usually high in uncertainty, information asymmetry, and risk, and may be chronic or synergistic/cumulative. The spatial effect may be mesoscale or macroscale. Operation decisions made for scientific/technical problems will usually be new and strategic, although the possibility of redressed decisions is high in a problem that is not easily or quickly solved. This third type of problem is distinguished from the first two in that the latter is not easily understood by nor broadly promoted by the public. This categorization is also reminiscent of Carmines and Stimson’s (1989) dichotomy of public problems as being easy (e.g., clear, concrete, understandable) versus hard (e.g., abstract, not concrete, not widely understood) issues. The symbolic causes and crises would usually be the “easy” problems, and the scientific/technical problems would be considered the “hard” problems.

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CONTINGENCY FRAMEWORK

The primary decision-making models and concepts, preliminary decision attributes, and the three-pronged classification of environmental problems, can be superimposed to present the contingency framework. Table 1 lists the decision-making models and concepts and their conditions of interest. As well, the decision attributes used with a particular model are suggested, and the type of environmental problem that may be addressed using a particular model is presented, with the exception of the purely rational model, which is rarely, if ever, used.

Many of the models are offshoots of each other; in some instances, the decision attributes and the environmental problems that are solved may be similar for related models. Bounded

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rationality and satisficing may be used more in crises and some symbolic causes due to the low-to-medium uncertainty, information asymmetry, and risk involved, as well as the acute or possible chronic time horizon and microscale and mesoscale. Credibility logic may be used in symbolic causes and some scientific/technical problems because is lends itself to decisions of medium-to-high uncertainty, information asymmetry, and risk, as well as chronic or possible cumulative time horizon and mesoscale or macroscale effects. The bureaucratic model, incrementalism, and the garbage can model may be used predominantly in symbolic causes due to the low-to-medium uncertainty, information asymmetry, and risk, and the chronic time horizon and microscale or mesoscale effects. Interestingly, symbolic cause decisions may be of a more operational and redressed nature, adding to the support for the suggested models.

The politics model and accountability logic may be used for scientific/technical problems and some symbolic causes. This is due to the medium-to-high uncertainty, information asymmetry, and risk involved, as well as the chronic and cumulative time horizon and mesoscale or macroscale effects. Such decisions may be mainly strategic and new, although some also may be redressed. Finally, escalation of commitment may permeate all models of decision-making and thus may be used to address all environmental problems. However, it is more likely that escalation would be present in symbolic causes more than in crises or scientific/ technical problems given the low-to-medium uncertainty, information asymmetry, and risk, and acute or possible chronic time horizons and microscale or mesoscale effects.

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IMPLICATIONS

Although the purpose of the contingency framework is predictive, it also may be useful in classifying new types of environmental analysis and decision-making methods as highlighted in this symposium. As in many areas of policy and regulation, researchers have been pushing for more collaborative modes of policy-making.

TABL

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Model

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F

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(Table 1 continued)

Model or Concept

~nditions of Interest D

aision Attnbutcs Environm

entalproblem

Incrementalism

ag

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an

M

odel

politics Mo&

l

Adclm

ability Logic

Escalation of com

mitm

ent

decisionsmadeviakgaining

litUe.&

viationfmm

statusquo 0

participts decide without definitive or best solution

decisions cut into &parts and solved sequentially

@s

and solutions am imertwined

orgaaizedanarchy

solutions may predate prot4ems

gods have little bearing on choices prcblem

s and solutions am multiple

decision points dictate when decisioas get m

ade

groups/coalitionsvieforhuf w

nflinispreseat noclearsolution decisionsm

adeviatqaining

eccountability is primary goal ofdccision-m

skrr decision-m

alas look for external approval scarcb/analysis of preferences is brief predecisions m

ade based on defensible solution#

power is primary basis for decisions

negakiveconsequencesctrivecscalation

Won-m

akcrs pnxm inform

ation diffenntty

decision-maldng is entrapped in policy options

&cision-m

akers feel responsible for negative cutcomes

low to m

edium uncel!ain@

, information aqm

metq, rislr, chronic tim

e horizon; micro O

I meso&;

operational; ndrcssedand som

e new problems

low to m

edium uncertainty, information

asymmetry, rie chronic tim

e horizon; micro

or mesoscale; operational; ndnssedand

some new

problems

medium

to high uncertainty, information asymmeeY. rislr, chronic or p

xsiie

cumulatm

time horizon; m

eso ox de

;

strategic and some opetational; mew and some

rrdrssed problems

medium

to high wm

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ation asym

n&y, ride; chroN

c or possible cum

ulative timc horizoq mew or m

anwcalo;

strate& and sow

operational; Illew

andsome

redressed problems

low to m

edium uncertainty, inform

ation asymmetry, rislc, acute or possible chronic time horizons; m

ino or mesascalc;

operational or strategic; redressed or new

symbolic cause5

scientific or technical problem

s, some

Eymbolic Q

uls

a

scientific or technical problem

s, some

symbolic cI(uses

symbolic causes, som

e crises and scientific or technical pm

Mans


Partnerships with the scientific community (e.g., policymakers collaborating with science academy and professional society members) are one suggestion for improving environmental decision-making. This author argues that independent, non- governmental scientific entities would be most useful in problems of low to medium risk, uncertainty, and information asymmetry and of micro- or meso-scale, i.e., symbolic causes.

Such partnerships are attractive, but in problems where uncertainty and information asymmetry are present in high amounts, the decisions may still be fragmented and scientifically inconsistent. The reason is that such partnerships would probably make decisions via bargaining, power, credible information, or maybe even in ad hoc form. Thus, the models of incrementalism or credibility logic or the politics or bureaucratic models may drive the decisions made. The influence of scientific experts, however, is not to be diminished. The influence of such partnerships in driving the decisions on scientifichechnical problems has been noted above. However, even with scientific/ technical problems, if the levels or risk, uncertainty, and information asymmetry are high, the chances the independent scientists and policymakers could make decisions in the form of partnerships is unlikely, given that the scientific experts will have a more informed view of the problem at hand.

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Bauer and Randolph highlight another form of collaboration. They argue that environmental decision-making can be improved through collaborative environmental management (CEM), proposing that such an approach to decision-making may represent a broader understanding of stakeholder needs and opinions, may inject normative values in to the decision-making process, and may result in more effective decisions. Such an approach rests on information and power sharing, open communication, and collective accountability. According to the contingency framework, the problems best suited for CED would be symbolic causes. Crises are problems with acute time horizons and of microscale. Thus, the probability that a collaborative team

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could expediently and effectively respond to a crisis is low, especially given that such a collaborative body would probably use the bureaucratic, incremental, or garbage can models of decision-making. Such a body may also lean towards the politics model or escalation of commitment as power and turf conflicts may color the decision process. Or, if a collaborative groups was overly concerned with the decision process, it may lean toward credibility logic and weight information less than the process.

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Because of group dynamics, then, such collaborative partnerships may be appropriate for symbolic causes. Moreover, as Bauer and Randolph explain, the collaborative method relies on trust among stakeholders, collaborative learning, and good information. These CED necessities would probably be difficult to establish in a scientific/technical problem, as epistemic communities mostly champion those problems. For those symbolic causes in which CED is used, Beierle’s evaluation framework (explained later in this symposium) would be useful to understand the effects of collaborative decision-making and may also highlight which decision-making model is used in such collaborative ventures.

Two new approaches to environmental decision-making and analysis are examined by Mathis and Patt. Patt highlights the limits of cost-benefit analysis in environmental decision-making, citing the case of acid rain in Europe. Interestingly, cost-benefit analysis is a tool that often presumes rationality and may be best suited for problems that are low in uncertainty, information asymmetry, and risk, and are of microscale and acute time horizon. As indicated in the contingency framework, the rational model of decision-making is rarely, if ever, used given its conditions of interest and the corresponding decision attributes. As such, an offshoot of rationality, like cost-benefit analysis, may not be useful for scientific/technical problems or symbolic causes. If one expands the assumptions of rationality to the bounded rationality model, then cost-benefit analysis may be useful in crises and in some symbolic causes. As an alternative to cost-benefit analysis,

Y& A C o n t i n g e n c g P f o r Environmental Decision-Making

Patt highlights the “critical loads” Mework . This analytic method is more conducive to scientific/technical problems due to heavy reliance on scientific information and scientific values and the setting of health standards and prioritizing of environmental goals. As such, decision-makers using the critical loads framework will probably lean toward the politics model of decision-making and accountability logic.

Similarly, Mathis describes the integrated assessment model in this volume, which is more conducive to the politics model of decision-making or accountability logic and lends itself to more scientific/technical problems. As Mathis argues, the integrated assessment model is useful in complex environmental problems with chronic or cumulative time horizons and where incomplete and asymmetric information exists (e.g., watershed restoration, climate change).

CONCLUSION

Critics may ague that a contingency M e w o r k for decision making defeats the purpose of decision-making research. That is, critics may contend that arguing that organizations select models based on the decisions they make does not further knowledge about a particular model. However, as many decision researchers have shown, no hard-and-fast rule exists as to which process will be used when, or which process is best. Still, individual processes have been identified and documented empirically. Thus, the contingency framework presented here, along with subsequent testing of it, may allow a more complete picture of organizational decision-making. As Allison (1971) argued, one organization will use myriad models; rather than limit the understanding of the organization by pigeonholing it into one process, a contingency framework affords a broader understanding.

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Certainly the ideas explored here are in their formative stage. The attributes of decisions and of environmental problems should be better elucidated. Moreover, the contingency framework

Policy Studies Review, PalyWinter 1999 16:3/4

should be tested to see if the predicted decision processes are used with the suggested problems. Empirical verification of the suggested relationships would extend the literature on decision- making and would further understanding of one of the organizational processes that combine to form the “intelligence system” (Gortner, Mahler, and Nicholson, 1989) of an organization. Finally, such a framework, once empirically validated, may improve environmental decision-making and help environmental decision- makers use not only broader and more integrative decision model, but a problem- and decision-specific one as well.

Given the formative status of such a contingency framework, what potential value would the framework have for environmental decision-makers? Environmental problems run the gambut from local, acute problems of varying degrees of risk to national or even global problems with synergistic effects, chronic time horizons, and large degrees of risk. Furthermore, the amounts of uncertainty and information asymmetry vary from problem-to- problem. These inherent characteristics vex policymakers at all levels, particularly local practitioners or nonprofit and citizen decision makers, who may be comfortable with a particular type of decision-making . Universal, one-size-fits-all decision-making may not solve diverse environmental problems. Therefore, the contingency fiamework will help practitioners, particularly local practitioners with limited knowledge and experience, self-diagnose the nature of the environmental problem they confront and opt for the most appropriate decision-making method to solve it. In addition, practitioners who are evaluating previously made policy decisions may use the framework to identify the original decision- making process used, diagnose its problems, and implement more appropriate decision-making methods to improve policy. Finally, although the framework proposed here focuses on environmental problems, once the attributes of a policy problem are identified,

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they may be superimposed on the decision-making models and attributes identified here to construct a contingency framework for other problems.

ENDNOTES

1. The author would like to thank Peter Robertson, Sheldon Kamieniecki, Elizabeth Graddy, and the journal reviewers and editors for their comments on this article.

2. See March, (1 978) for an excellent history and comparison of rationality and bounded rationality.

3. Kraemer and Perry attempted to match decision-making processes with these broad categories. Their results showed that quantitative techniques were used for operational problems where efficiency is a goal; a mix of qualitative and quantitative methods were used for program design; and qualitative techniques were used in planning or development problems.

4. In searching for decision typologies, the literature on participation, particularly participative decision-making and organizational structure, also were reviewed to no avail.

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5 . For a discussion of the politics of problem definition in policy analysis, see Dery, (1984).

6. Some may argue that the extinction of a given species is high in uncertainty and information asymmetry and may involve high levels of risk. This author would argue that this problem be classified as a biodiversity problem, which is really a scientific/technical problem because no one fully understands intertemporal and interspecies consequences of extinction.

7. The term “epistemic communities” is borrowed from the international relations literature on regime theory (c.f., Haas, 1989).

8. See Benedick’s 1991 account of how scientists were the “driving force” in problem definition and policy making.

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Tetlock, P. E. 1985. “Accountability: The neglected social context judgment and choice,” Research in Organizational Behavior, 7, 297-332. 35 ABOUT THE AUTHOR

Diane E. Yoder is a Ph.D. candidate and instructor in pirhlic policy at the University of Southern California. She teaches irtider.qrudurrte classes on political participation and ethics. Her researcA itticwsts itdude the role of risk in agenda setting, property righis. utid tratisncriiotiul citizenship. Recent publications include “The Miwtiing tind Significance of Citizenship in a Transnational World” (in press), cw-uuthored wid1 Tern? L. Cooper, and “Making Sense of Performanw Metrsurernctit in ihe Nonprofit Sector” (in press), co-authored with Jartics hl. Ferris.

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A CONTINGENCY FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING