Wicked Problems and Applied Economics - OECD. · PDF fileWICKED PROBLEMS AND APPLIED ECONOMICS...

WICKED PROBLEMS AND APPLIED ECONOMICS

SANDRA S. BATIE

The term “wicked problems” is found inmany disciplines, including public administra-tion, policy science, health education, ecology,forestry, and business administration, but theterm is relatively unknown in applied eco-nomics. Applied economics needs to becomebetter acquainted with wicked problems; theyare pervasive, and they present challenges ifapplied economics is to retain its relevancein today’s world. This paper explores thesechallenges but is necessarily exploratory, aswidespread recognition of the complexity ofwicked problems is leading to new kinds ofresearch, but these research approaches arestill evolving. My basic thesis is that normalscience assumptions and approaches are in-adequate for addressing the complexities ofwicked problems in a policy context, but thatscience, including social science, remains cru-cial for the development of alternative poli-cies. This exploration, therefore, is about boththe characteristics of postnormal science nec-essary to inform alternative policies designedto address wicked problems as well as theirimplications for policy contributions from ap-plied economics. Because many wicked prob-lems involve sustainability issues, I will focusmainly on sustainability problems.

Wicked vs. Tame Problems

Examples of wicked problem issue areas in-clude terrorism, global climate change, nuclearenergy, healthcare, poverty, crime, ecologicalhealth, pandemics, genetically modified food,water resource management, trade liberaliza-tion, the use of stem cells, biofuel production,

Fellows Address.Sandra S. Batie is the Elton R. Smith Chair in Food and Agricul-tural Economics Policy in the Department of Agricultural, Food,and Resource Economics at Michigan State University, East Lans-ing, MI. Her email is [email protected].

Thanks are due to Dave Ervin, Patricia Norris, Christopher Pe-terson, David Schweikhardt, Carol Shennan, Leonard Shabman,and Kurt Stephenson, whose suggestions helped to improve thisarticle.

Fellows Address was presented at the 2008 AAEA annual meet-ing in Orlando, FL. Invited addresses are not subjected to the jour-nal’s standard refereeing process.

nanotechnology, gun control, air quality, sus-tainable development, biodiversity, environ-mental restoration, forest fire management,and animal welfare. Other wicked problemsinclude the locating of not-in-my-backyard(NIMBY) projects (e.g., a freeway or a half-way house); reengineering a food supply chainto address food safety problems; constructingor removing a hydroelectric project; or open-ing of a new mineral mine.

Wicked problems, which are sometimescalled social messes or untamed problems,are dynamically complex, ill-structured, pub-lic problems. The causes and effects of theproblem are extremely difficult to identify andmodel; wicked problems tend to be intractableand elusive because they are influenced bymany dynamic social and political factors aswell as biophysical complexities (Rittel andWebber 1973). Also, most wicked problemsare connected to, or are symptoms of, otherproblems (Carroll et al. 2007). As a result,there is no consensus on what exactly the prob-lem is. Indeed, a wicked problem is not wellunderstood until after formulation of a po-tential solution, and therefore, the problemdefinition tends to change over time. However,because of their complex interdependences,wicked problems are never solved (Conklin2006), but rather they become better or worse(Rittel and Webber 1973).

Wicked problems always occur in a socialcontext, and there can be radically differentviews and understanding of the problem bydifferent stakeholders, with no unique “cor-rect” view (Horn and Weber 2007). Thus,their wicked nature stems not only from theirbiophysical complexity but also from multi-ple stakeholders’ perceptions of them and ofpotential trade-offs associated with problemsolving. Identification of solutions becomes asmuch a social and political process as it is a sci-entific endeavor (Kreuter et al. 2004). Also,wicked problems are characterized as hav-ing high uncertainty associated with them, notonly with outcomes but also with the poten-tial causes and effects underlying the problems.In addition, there are multiple stakeholders’

Amer. J. Agr. Econ. 90 (Number 5, 2008): 1176–1191Copyright 2008 Agricultural and Applied Economics Association

DOI: 10.1111/j.1467-8276.2008.01202.x

Batie Wicked Problems and Applied Economics 1177

Table 1. Summary of Differences Between Tame and Wicked Problems

Characteristic Tame Problem Wicked Problem

1. The problem The clear definition of the problem alsounveils the solution

∗∗∗

No agreement exists about what theproblem is. Each attempt to create asolution changes the problem

∗∗∗The outcome is true of false, successful

or unsuccessful∗∗∗

The solution is not true or false—the endis assessed as “better” or “worse” or“good enough”

∗∗∗The problem does not change over time The problem changes over time

2. The role ofstakeholders

The causes of a problem are determinedprimarily by experts using scientificdata

Many stakeholders are likely to havediffering ideas about what the “real”problem is and what its causes are

3. The “stoppingrule”

The task is completed when the problemis solved

The end is accompanied by stakeholders,political forces, and resourceavailability. There is no definitivesolution

4. Nature of theproblem

Scientific based protocols guide thechoice of solution(s)

∗∗∗

Solution(s) to problem is (are) based on“judgments” of multiple stakeholders

∗∗∗The problem is associated with low

uncertainty as to system componentsand outcomes

∗∗∗

The problem is associated with highuncertainty as to system componentsand outcomes

∗∗∗There are shared values as to the

desirability of the outcomesThere are not shared values with respect

to societal goals

Source: Adapted from Kreuter et al. (2004).

viewpoints with respect to the desirability ofalternative outcomes.

Wicked problems can be contrasted withtame problems. While frequently complex anddifficult, tame problems are those that can beclearly delineated and solved by experts whoproduce workable solutions using the analyt-ical approaches of their disciplines (Kreuteret al. 2004). Examples include landing men onthe moon; determining the specific source of afood contamination outbreak; identifying thecost effectiveness of different crop practices toreduce soil erosion; or determining the costsand benefits of expanding an irrigation project.Tame problems are characterized by clear def-initions of the problems which do not changeovertime. Also, the problem definition revealspotential solutions because of clear cause andeffect mechanisms. Unlike wicked problems,there is little conflict over the desirability ofthese potential solutions. Tame problems canbe addressed primarily by experts with littleor no involvement of stakeholders, and unlikewicked problems, they can be solved.

Table 1 summarizes these differences be-tween wicked and tame problems as beingabout whether there is (1) a common defini-tion of the problem; (2) a direct involvement

of stakeholders in problem definition and anal-ysis; (3) a deterministic “stopping rule”; as wellas (4) the unique nature of the problem.

Challenges Posed by Wicked Problems

Wicked problems pose a dilemma for normalscience activities. Normal science, as defined byThomas Kuhn (1962) in his book The Structureof Scientific Revolutions, is the routine work ofdisciplinary scientists “puzzle solving” in theirparadigm. Normal science research (i.e., con-ventional or mainstream research) adds to thedetails of the established theory but does notchallenge it or test its assumptions.

Historically, normal science has had a closerelationship with the creation of policy alter-natives (Funtowicz and Ravetz 1993; Stokes1997). Since World War II, normal sciencehas been guided by a linear model1 whichis illustrated in figure 1 and can be sum-marized as: “[B]asic research, conducted byscientists that are largely autonomous, is a

1 The linear model of normal science and its relationship withpolicy development can be traced to concepts articulated in Van-nevar Bush’s 1945 report Science—The Endless Frontier (Stokes1997).

1178 Number 5, 2008 Amer. J. Agr. Econ.

Source: Pielke and Byerly (1998).

Figure 1. The linear model of science

resource for applied research. Applied re-search is the source of results useful to prac-tical concerns, including policy development”(Pielke 2007, p. 81). In this model scientificfindings flow into a reservoir that can thenbe drawn on by society to create beneficialtechnologies and outcomes. Basic science isjudged by criteria internal to science, suchas disciplinary standards, whereas applied re-search and development is judged by criteriaexternal to science, such as the potential use-fulness to society. There is also more statusconveyed to those engaged in basic re-search than to those undertaking appli-cations that involve the integration ofscience into decision-making processes (PielkeByerly 1998; Stokes 1997). Many researchinstitutions—universities and agencies—arereflective, supportive, and reinforcing of thislinear model of normal science (Bonnen 1986;Peters 2007; Stokes 1997).

With respect to policies and decision mak-ing, linear, normal science models maintain un-derlying assumptions that scientific progressleads to societal progress (Frodeman andHolbrook 2007) and getting the science rightis necessary to settle political disputes and foreffective policy making to occur (Pielke 2007;Sarewitz 2004). However, as figure 1 illustrates,normal science frequently has a division be-tween those who do the science and those whouse it: “Autonomy is implicit in the [linear]

model, because the reservoir [of scientific find-ings] isolates science from society; scienceassumes no responsibility to apply the knowl-edge it puts into the reservoir, and society doesnot set scientific priorities” (Pielke and Byerly1998, p. 42). This division implies that reduc-ing scientific uncertainty will reduce politicaluncertainty, and reaching a consensus on thescience is a prerequisite for a political consen-sus and for policy action to occur (Vatn andBromley 1994).

These assumptions are tantamount to con-flating the “what is” and the “what if” prod-ucts of science with the “what ought to be”product of politics. They are also quite prob-lematic but tend to be more realistic (1) wherethere is widespread agreement by stakehold-ers as to what are desirable outcomes as wellas (2) where there is low uncertainty surround-ing the system components and outcomes ofalternative course of actions (Pielke 2007).That is, they tend to be more realistic withthe “tamer” problems of society. For examplethe research to develop a vaccine for a seri-ous human disease falls in this tame problemcategory. With most vaccines, there tends to bewidespread agreement that protecting humansfrom the disease is desirable, and there is lowuncertainty about the system components oroutcomes. Thus, for vaccine development theassumptions of the linear model of normal sci-ence are apt.


Normal Science and Applied Economics

To illustrate Pielke’s points, consider appliedeconomics. As with all disciplines, normalscience is applied economists’ “bread and but-ter” work. The American Journal of Agri-cultural Economics showcases normal scienceresearch, most of which tends to follow whatLindbloom (1965) calls the “rational analyticalmethod.” That is, applied economics researchprojects normally follow formal decision logic,and the applied economist is the expert—selecting assumptions and methods, definingsignificance, and using theory (e.g., welfaretheory) as criteria to isolate end states suchas equilibria or optimal outcomes (Stephenson2000). Examples include formal benefit-costanalysis, nonmarket valuation techniques, dy-namic optimization, multiattribute utility anal-ysis, econometric demand modeling, spatialequilibrium modeling, and willingness to payestimations. And for much of applied eco-nomics policy research, “getting the scienceright” can equate with “getting the pricesright.”

Advocates for the rational analytical ap-proach, following the linear model, defend itsuse in policy making as a systematic and ratio-nal way for decision makers to decide betweencompeting ends (Shulock 1999; Stephenson2000). That is, research can be placed in areservoir to be drawn out by policy and de-cision makers as needed. As discussed above,the potential for this research to influencepolicy is higher when the system componentsand outcomes are known and probable out-comes are generally viewed as desirable. Thus,the selection of, say, the least-cost alternativeto reduce (the relatively tame problem of)erosion is more likely to have policy accep-tance than is the identification of the optimalallocation of resources to reduce (the morewicked problem of) perceived global warmingthreats.

The distinction being made is that within apolicy context, there is a difference with “whatis” (and “what if”) types of research and the“what ought to be” types of research as theyaddress tame and wicked problems. “What is”issues, such as “What are the impacts of landuses given the new Energy Act?” and “what if”issues, such as “What would be the impact onthe economy if there was more development ofwind power sources of energy?” are appropri-ate for both tame and wicked problems. Wheresocietal goals are broadly known and accepted,such as in the vaccine research example, re-searchers can proceed with “there ought to be”

types of questions (e.g., there ought to be avaccine) with broad acceptance and support.

The same cannot be said for the “what oughtto be” research with wicked problems. Con-sider water management, where the old west-ern saying of “Whiskey is for drinking andwater is for fighting” highlights water manage-ment’s wicked nature. An example of a “whatought to be” research question is: “What isthe efficient reallocation of water among com-peting interests?” The implicit assumption isthat efficient allocation is a policy goal, butpolicy goals do not emanate from disciplinaryparadigms (Bromley 2008b; Stephenson 2003).As an approach to making policy decisions,“[the] rational analytic approach vests powerand decision-making authority in the hands ofunelected analysts” (Stephenson 2000, p. 11),thereby substituting the researchers’ values ofwhat is considered to be the best outcome forthose of others. Also, the assumption of the lin-ear model that all research will ultimately addvalue to decision making is flawed with wickedproblems. Failure to recognize its inappropri-ate nature for wicked problems may accountfor much of the limited acceptance of such pol-icy research (Batie 2005; Bromley 2008b; Shu-lock 1999). The assumption of “build it andthey will come” is not appropriate; there is noassurance that the supply of knowledge aboutwicked problems (e.g., nature–human interac-tions) will have demanders.

Normal Science and Wicked Problems

Normal science is ill suited for wickedproblems—with their attendant conflict overvalues and high uncertainty about system com-ponents and outcomes. By their nature, wickedproblems cannot be easily categorized intoseparate disciplinary boxes nor can they be di-vided into more manageable parts under theassumption that there are clear and known ca-sual paths (Weber and Khademian 2008). Withwicked problems it is difficult to decide whatfacts to gather without first discussing values;thus, it is necessary not only to have many dis-ciplines involved, but also to have interactionwith those whose resources and cooperationare indispensable for tackling the problem—that is, with stakeholders (Bueren, Klijn, andKoppenjan 2003).

These various actors bring different valuesand perceptions to the policy dialog. For ex-ample, with respect to sustainability of ecosys-tems, environmental ethicists may focus on theintrinsic value of nature; applied economists


may focus on the instrumental value of na-ture; and nonacademics may bring tacit knowl-edge garnered from practical experiences andpersonal values associated with nature andresource use (Norton 2005). Also, manage-ment agencies might consider natural re-sources from the viewpoint of wildlife survival,whereas project agencies might consider nat-ural resources as commodities (Ingram andBradley 2006). Even when dialog occurs andincludes all of the actors, clear solutions rarelyemerge; rather, via negotiation processes areidentified which are judged as better or worse(not right or wrong) in addressing the wickedproblem (Norton 2005).

Why the Concern About Wicked ProblemsNow?

Linear model and normal science were notchallenged as long as society and policy mak-ers felt that they were meeting social needs(Bonnen 1986; Pielke and Byerly 1998; Stokes1997). But over the last several decades, thatsituation has changed. It is no longer widelyassumed that scientific progress leads to soci-etal progress (Frodeman and Holbrook 2007;Peters 2007). The reasons are multiple.

First, our improved understanding of systemconnections as well as recent volatility in nat-ural resource and commodity prices has raisedwidespread concerns about the sustainabilityof many of our current development paths andpractices (Millennium Ecosystem Assessment2005). The complex connections between na-ture and society are seen as vulnerable. Thewarming of the global climate, for example,appears to be threatening the prosperity ofeconomies as well as the functioning of ecosys-tems and the survival of many species. As moresustainability concerns arise, and as technolo-gies appear to produce more risks than theyresolve, many are challenging the post–WorldWar II concept that our science can controlthe risks that it produces (Gallopin et al. 2001;Nowotny, Scott, and Gibbons 2001). Further-more, the aforementioned critics note that sci-ence itself introduces new risks For example,the use of pesticides may reduce pest damagebut may increase the risk of damages to humanhealth (Russell 2001).

Gallopin and his colleagues (2001) note thatwhat is at stake is not an admission of par-tial ignorance but rather the significance tobe attached to the inability of science to exer-cise mastery over eventual outcomes. The ear-lier protection that provided science with the

now questioned belief that more knowledgewill reduce uncertainties, increase capacity forcontrol of nature, and permit the remedyingof past mistakes is stripped away—along withthe “ideological privilege” that gave presump-tive preference to the intended outcomes ofscientific research while discounting any unin-tended side effects.

Second, wicked problems do not fit the lin-ear model of science, which has smoothedover its wicked, rough edges with abstractingassumptions.2 In ecosystem sustainability de-bates, for example, many question the assump-tions that there are simple linear causes andeffects of problems; science can control nature;the past is a good predictor of the future; orthere are equilibrium conditions to which nat-ural systems will return following disturbances.For sustainability issues, the alternate assump-tions are that there is nonlinearity and un-predictability to system components; sciencecannot control the negative and cumulative ef-fects of technologies on nature and society; andthere are thresholds (e.g., tipping points) thatcan cause irreversible outcomes.

Thus, while normal science assumptionsmight have fitted well with earlier conserva-tion practices of the progressive conservationperiod—when natural resources were viewedas commodities and there was considerablepublic consensus about the goals of resourcemanagement—that fit is no longer the case.Now, these assumptions are challenged in theage of environmentalism because ecosystemsare assumed to provide many functions andservices, including life support, and when thereis considerable public conflict about which ser-vices are the most valuable and about howto practice environmental management (Batie,Shabman, and Kramer 1986; McCool andGuthrie 2001).

As a consequence, there is increasing dis-satisfaction with curiosity-driven, disciplinary-based science. Criticisms abound with the“stove-piped” or the “silo” nature of the disci-plinary approach for addressing wicked prob-lems. As the old saying goes: “The worldhas problems, while universities have depart-ments.” It is becoming more evident that

2 An example in applied economics would be the assumptionthat Pareto-irrelevant externalities (i.e., where there are no fur-ther gains from trade) should not be addressed by environmentalpolicies (Bromley 2008a,b). As Bromley notes, labeling an exter-nality as Pareto irrelevant implies that all costs of the status quo fallon the victims, who probably desire regulation to change that situ-ation regardless of their ability to pay. Similarly, Norgaard (2002)argues that environmental problems are thought of as market fail-ures when they more accurately could be considered to be evidenceof the applicable limits of the market model.


normal science is inadequate in resolvingwicked problems with their attendant conflictsover whose values will prevail in deciding (a)what future is desirable; (b) what trade-offsare worth making; and (c) who bears the costsor gains the benefits of decisions (Weber andKhademian 2008). When values are in conflictand when outcomes are of high consequence,but uncertain, or where there is significantscientific disagreement,3 scientific experts arenot allowed to dictate preferred policies (Fearet al. 2006). Indeed, if normal science is usedto address wicked problems, the frequent re-sult is controversy and gridlock (Pielke 2007;Sarewitz 2004). The decision of whose valuescount is made in the political world, not in theworld of science (Bromley 1997).

Third, globalization has also challenged themonopoly of the western science’s arbitrationof what constitutes valid knowledge. Withinpolicy discussion, there is broader acceptanceof the experience of practitioners as tacit(e.g., silent) knowledge; there is more focuson unique local situations that contextualizeknowledge, and there is inclusion of alterna-tive knowledge as well as hybrid knowledgewhich combines various types of knowledge.The distinct boundaries between science andnonscience are dissolving to be replaced witha wider framework of sources of knowledge toinform policy (Nowotny, Scott, and Gibbons2001).

Fourth, these challenges to normal scienceare enabled and reinforced by new ways ofcommunicating among stakeholders that pro-vide civil society low-cost access to a wealthof data and information as well as low costs topolitical organizing (Hawken 2007). Currently,for example, food companies are strugglingwith how to meet some consumers’ demandsfor more sustainability attributes in their prod-ucts and processes; they know that even smallgroups of consumers can effectively organizeand communicate their concerns to others viathe Internet4 and impact company revenues,but the companies struggle to determine whatthey should do to profitably address the wickedproblem of sustainability.

3 For a good discussion of types of conflict in science in policy-making context, see Lord (1979).

4 The uncertainties surrounding wicked problems can easily leadto the “scientization” of politics, where there is a selective use of sci-entific findings to support particular political positions, and wheresome scientists may become issue advocates (Pielke 2000; Sarewitz2004). Sarewitz explores how to avoid such scientization via suchmeans as articulating value positions from the beginning of a con-troversy. Scientization of politics further confuses the distinctionbetween “is” and “ought” types of policy research and underminesthe legitimacy of scientists in policy.

Addressing Wicked Problems

Society is changing what it is asking of sci-ence; as a result, the role of science in deci-sion making is becoming quite complex (Pielke2007). Addressing wicked problems in a policycontext requires both use-driven science thatrecognizes and addresses uncertainties andmeaningful engagement of stakeholders in de-cision making that propels knowledge intoaction. While science can offer new ways ofthinking or catalyze new technologies, onlychanges in policies and management lead toaction (Ingram and Bradley 2006). The latterrequires engagement of stakeholders.

There is a large and growing literature aboutvarious approaches to postnormal science thataddresses uncertainties (e.g., Funtowicz andRavetz 1993; Nowotny, Scott, and Gibbons2001). An example is the field of ecologi-cal economics (Funtowicz and Ravetz 1994),which has its own transdisciplinary journal andfocuses on the human/nature nexus, frequentlyin a policy context. Ecological economics has apluralistic but scientific approach to the studyof environmental problems and policy solu-tions. It is characterized by systems perspec-tives and appropriate physical, biological, andsocial contexts as well as a focus on long-termenvironmental sustainability.

Another postnormal science example iscomplexity economics, some of which traces itsroots to the Sante Fe Institute’s exploration ofrelationships between economics and physics.Complexity economics is highly mathemati-cal and statistical, and it focuses on complexadaptive systems in pursuit of “real world” rel-evancy. The core components of complexitydynamic models include the psychology of theeconomic agents, the process of learning, adap-tion to a changing environment, and coevolu-tion processes. Complexity economics stressesnonlinearities, disequilibria, and path depen-dences5 (Colander 2000). Both ecological eco-nomics and complexity economics emphasizepostnormal science and assumptions but donot necessarily address engagement or policyapplications.

Another postnormal science is that of sus-tainability science. It is highly integrated and

5 As Brock and Colander (2000) write with respect to complex-ity economics, “Complexity . . . takes away the reference point for[economic] theory’s defense of the market. In the complexity vi-sion there is not proof that the market solves problems. There isnot unambiguous way of stating what is and what is not an exter-nality and there is no guarantee that the market leads to the mostdesirable equilibrium” (p. 82).


multidisciplinary; it has a direct focus onwicked problems (e.g., sustainable develop-ment) and includes engagement with stake-holders through such institutions as boundaryorganizations. Therefore, sustainability sci-ence is a good example to illustrate how sci-ence can address wicked problems in a policycontext.

Sustainability Science

Sustainability science has emerged in the lasttwo decades; it is defined by the problemsthat it addresses rather than the disciplinesinvolved. It seeks to inform and facilitate asocietal transition toward sustainable devel-opment (Clark 2007). It is integrative in thatit is committed to bridging the communitiesengaged in promoting environmental conser-vation, human health, and economic develop-ment. It includes research knowledge from thenatural, social, and engineering sciences withinsights from the humanities. It also incorpo-rates knowledge from those who move knowl-edge to action (Clark 2006). Thus, sustainabil-ity science needs to be engaged, since it isstakeholders who will help frame the problem,determine goals, and implement the desiredchange.

Thus, sustainability science, while still evolv-ing, has become an integrated, multidisci-plinary use-driven science that seeks to (1)analyze and predict the behavior, at multiplescales, of complex self-organizing systems; (2)identify and characterize the irreversible im-pacts of interacting stresses on such systems;and (3) assess the roles of people in the func-tioning of such systems (Cochran 2000). Cen-tral questions include the following: How candynamic interactions be better incorporated

Producers

Scientific Community(e.g. Sustainability

Science)

Users

Policy Makers

Resource Managers

The Public

TechnologyDevelopers& Adopters

BoundaryOrganization

Dual Accountability

Non-Partisan

Co-creationof New Knowledge

User-Driven Science

Safe Harbor

Explicit Knowledge Tacit Knowledge

Source: Clark and Holliday (2006)

Figure 2. Boundary organizations: Linking knowledge withaction

into emerging models and conceptualizationsthat integrate the Earth system, social de-velopment, and sustainability? What systemsof incentive structures can most effectivelyimprove social capacity to guide interactionsbetween nature and society toward more sus-tainable trajectories? (Bolin et al. 2000).

Engagement Using Boundary Organizations

Effective engagement of stakeholders is chal-lenging (Jacobs, Garfin, and Lenart 2005; Mc-Dowell 2001). While there are resources thathelp to guide critical engagement, and exten-sion faculty have been pursuing such engage-ment for decades, there remains more to learn(Fear et al. 2006).

One approach to critical engagement is theuse of a boundary organization, which is abridging institution which links suppliers andusers of knowledge and recognizes the im-portance of location-specific contexts (Ruttanet al. 1994). As defined by Ingram and Bradley(2006): “Boundary organizations are situatedbetween different social and organizationalworlds, such as science and policy. Accordingto advocates, boundary organizations succeedwhen three conditions are met. First, they mustprovide incentives to produce boundary ob-jects, such as decisions or products that reflectthe input of different perspectives. Second,they involve participation from actors acrossboundaries. Third, they have lines of account-ability to the various organizations spanned[by the boundary organization] (Guston 2001).Adaptive and inclusive management practicesare essential to the functioning of boundaryorganizations.”

Figure 2 presents a figure of a boundary or-ganization: on the left side is science and on the


right side are users of science. The boundaryorganization is used to link scientific knowl-edge (in this example sustainable science re-search) to the users. The arrow goes both waysbecause boundary organizations link thosewho have explicit knowledge, such as faculty,with those potential users of knowledge—suchas resource managers, civil society, or policymakers—who have tacit knowledge garneredfrom experience.6 Thus, a boundary organiza-tion by combining tacit and explicit knowledgecan co-create new, transformational knowl-edge and shared understanding which may becritical to the innovation in the policy process(Conklin 2006; Guston 2001; Peterson 2008).7This cocreation process, by allowing partici-pants to critically reflect on each other’s views,enables participants to reflect not only on theirown preferences and viewpoints but also onhow they might be changed (White 1994).

Boundary organizations can function to rec-oncile supply and demand of existing knowl-edge; cocreate new knowledge; translate, ne-gotiate, and communicate among the multipleparties on both sides of the science–use nexus;make transparent tacit assumptions and val-ues embedded in models, paradigms, and asser-tions; identify uncertainties; seek alternativeframing of problems; build hybrids (objectssuch as indicators or maps that contain bothscience and policy information); and build ca-pacity to link knowledge to action (Miller1999). In addition, boundary organizations canprovide process accountability and “safe har-bor” to all parties when there is serious conflictby functioning in a nonpartisan manner.

To illustrate how a boundary organizationcan function, consider the Arizona Water In-stitute (AWI).8 As Ingram and Bradley (2006)note, water management disputes are not nor-mally solved by the revealing of a scientificfinding; rather, they emerge from negotiatedconsensus with water users and water man-agers. Thus, in addressing water managementissues, the AWI combines the expertise of

6 Explicit knowledge is that which is codified, rational, separablefrom context, and thus transmittable by formal means such as text-books or manual. Tacit knowledge is context specific and informalarising from experience and practice (Peterson 2008).

7 See Peterson (2008) for a discussion as to how this frameworkof the cocreation of transformational knowledge can be applied tosupply chain and network performance management.

8 For an excellent discussion of the history and use of anotherboundary organization, the California Bay Delta Authority, seeIngram and Bradley (2006). Jacobs, Garfin, and Lenart (2005) alsoprovide a discussion of a climate-themed boundary organization inArizona. Another boundary organization called Oregon Solutionsis at Portland State University (http://www.orsolutions.org).

Arizona’s water managers with over 400 waterresearchers at three Arizona universities; theInstitute’s mission is to support water resourcemanagement and technology development inreal-world applications. The program includesstakeholder engagement and use-driven sci-ence in support of water management objec-tives as well as intermediaries who translateand connect science to users.

One method used is the formulating of sce-narios of alternative water futures. Scenariowork enhances integration across themes andserves as a mechanism for interdisciplinarywork that engages stakeholders. With dynamicscenario development, alternative futures areidentified (sometimes with forecast models),and then the analysis works backward in timeto identify crucial pathways that avoid unde-sirable outcomes or result in desirable ones.9What is a desirable future is arrived at througha negotiated process among stakeholders.

The role of science is fundamental as a con-vening focus for AWI partnerships betweenfaculty and water managers. In the languageof boundary organizations, science can be a“boundary object” but only if a better under-standing of physical and socioeconomic condi-tions is desirable from all parties’ perspectives.

An illuminating outcome of AWI’s ap-proach is how engagement can change theidentification and framing of problems. Priorto engagement of stakeholders in a sciencecenter associated with the AWI, faculty an-ticipated that the critical questions to be an-swered by water management research mightbe: (1) What are the costs and benefits of ri-parian preservation/restoration? and (2) Whatkinds of water markets and banking are feasi-ble? Once the project commenced, it was de-termined that these were not key questions forwater managers. Questions that emerged af-ter discourse with managers were largely re-lated to climate change and drought (Jacobs2008). Sharing viewpoints and knowledge wentboth ways. For example, the faculty foundthat stakeholders did not always distinguishbetween important concepts such as weatherand climate, nor between risk and uncertainty(Jacobs, Garfin, and Lenart 2005).

Linking insights and knowledge to action is alarge challenge (Ingram and Bradley 2006; Ja-cobs, Garfin, and Lenart 2005; Stephenson andShabman 2007); achieving and implementing a

9 Analogue scenarios are those which use similar situations(sometimes from the past) that shed light on future conditions(Jacobs, Garfin, and Lenart 2005).


negotiated consensus on which actions will beundertaken is a complicated process that takestime and resources (Jacob, Garfin, and Lenart.2005). And as the scale of a problem expandsto include regional, national, or global phe-nomena, the challenges become even larger(witness the Doha rounds in World Trade Or-ganization negotiations!). However, the endresult of using a well-functioning boundaryorganization can be a product that is dis-tinctly different and more broadly acceptedthan would have emerged from either the re-searchers or the stakeholders if they operatedindependently (Ingram and Bradley 2006).

Engagement Methods

There are many engagement methods andtechniques that can enhance engagement andlink researchers with users. One technique isdiscourse10 enabled by computer-aided dis-pute resolution models; another is the explo-ration of alternative policies as experimentalcase studies using adaptive management.

Discourse between stakeholders and re-searches can be added with computer-aideddispute resolution (Stephenson and Shab-man 2007). These decision aids provide anapproach to resource management decisionmaking which engages stakeholders in a mean-ingful manner and manages (but does notavoid) conflict. The technical relationships ofthe model (traditionally the domain of model-ers with the support of scientists) are jointlyconstructed with stakeholders. The involve-ment of stakeholders provides another way toverify technical relationships, level the techni-cal playing field over diverse stakeholder in-terests, and build trust in science. The factthat there is some mechanism for collabora-tive model development sets computer-aideddispute resolution apart from the decision sup-port literature which builds “user-friendly”models.

Computer-aided dispute resolution modelshave no single disciplinary focus, but they sup-port negotiation among various stakeholdersusing computer simulation models. Their ob-jective is not to simplify the range of choice,but rather they are used to separate argumentsabout “what is” from “what should be” across

10 White (1994), in an article entitled “Policy Analysis as Dis-course,” discusses three types of discourse: analytic, critical, andpersuasive. Analytical discourse draws on multiple theories anddata sources; critical discourse emphasizes critical reflection andlinks evidence to value discussion; and persuasive discourse focuseson the roles of ideas and persuasion by policy entrepreneurs.

a broad range of potential choices. That is, themodels are in service of decision making, andthey are neither substitutes for the decision,nor the means of deciding. They are not deci-sion models designed to maximize some goal;rather, they are used to fashion mutual under-standing through discourse and are based onthe premise that decision making is an itera-tive process with learning taking place as stake-holder preferences are developed or discov-ered when confronting choices (Stephensonand Shabman 2007). Stephenson and Shabman(2007) note that effective models are those thatare credible, understandable, and useful to thedecision participants and which avoid hidingor embedding those value judgments in themodel that should instead be the appropriatedomain of the discourse and collaborative ne-gotiations.

Using policies as experiments (e.g., pilotprograms) can be another way to addresswicked problems. Consider environmentalmanagement of agricultural lands. Becausesystem responses (including social systems re-sponses) are fraught with uncertainties andsignificant unknowns (e.g., lags, thresholds,cultural influences) as well as confounding in-fluences of spatial and temporal fluctuationsand variability (e.g., climate changes, land usechanges), no research can predict with cer-tainty the results of large landscape changes onthe environment or agricultural sector (Shen-nan 2008). Thus, there is a strong argument thatpolicies should be viewed as experiments; ba-sically they provide “learning by doing” butwith extensive monitoring of environmentaloutcomes that then provides information foradaptive management (Watzin 2007). As illus-trated in figure 3, adaptive management in-volves feedback loops.

In adaptive management when policy is im-plemented (frequently with experiments built

Research & Analysis

Policy & Rule Development

Monitor

Evaluate

Revised Goals

New technology

New information

Monitoring data

Goals Information Technology Existing Data

Adaptive Management

Source: Batie and Rose (2006).

Figure 3. Adaptive management


High

Low

HighLow Value Conflict

Wicked Problems Engaged Sustainability Science Adaptive Management

Tame Problems Normal Science Conv. Env. Mgt.

Uncertainty

Figure 4. Wicked versus tame problems

into the policy design a priori), the results aremonitored using key indicators as identifiedby stakeholders. These results are comparedto the overarching goal(s) of the stakeholder-identified goals of the policy. If monitoring in-dicates that the goals are not being met, thenadditional research and stakeholder involve-ment is undertaken, and policy or goal ad-justments are made. Adaptive managementusually includes a close relationship betweenscientific research, managers, and local usersof resources (Ingram and Bradley 2006;Norton 2005).

Figure 4 illustrates the differences, whenaddressing tame and wicked problems, be-tween normal and postnormal science (e.g.,engaged sustainability science) as well asthe differences between conventional environ-mental management and adaptive manage-ment. Conventional environmental manage-ment refers to such issues as the cost-effectiveplacement of riparian buffers and can be con-trasted with adaptive management issues suchas changes in whole watersheds to improve thesurvival of endangered migrating salmon.

Implications for Applied Economics

Should applied economics play a role in ad-dressing wicked problems? There is little doubtthat most wicked problems include issues ofhigh consequence to society. The role thatshould be played by applied economics, how-ever, depends on the nature of the subject mat-ter boundary placed on the discipline. Yet, toexclude wicked problems risks the relevancyof applied economics.

The good news for those who view wickedproblems as appropriate work for appliedeconomics is that the integration of science

into decision-making processes has expandedthe roles for the social sciences. These demandsfor integrated, use-driven science are reflectedin funders’ requests for proposals (Moll andZander 2006). Consider the National ScienceFoundation (NSF). At one time NSF’s re-quests for proposals emphasized disciplinary-expanding, curiosity-driven basic research andarguably favored the biophysical sciences. In-creasingly, the requests are for integrated,use-driven, multidisciplinary scholarship thatincludes social sciences. The NSF now listssocial impact as a criterion for selection ofprojects along with scientific excellence andintellectual merit (Pielke 2007); if grant pro-posals fail to address the connection betweenthe proposed research and its broader ef-fects on society, they are returned withouta review (Frodeman and Holbrook 2007).The Cooperative State Research, Extension,and Education Service (CSREES) of theU.S. Department of Agriculture, which man-ages the National Research Initiative, nowrequests specific proposals directed at per-ceived societal goals, such as small farmprosperity, that integrate many disciplines’research, outreach to and inclusion of stake-holders, and education. The committees ofthe National Academy of Science’s NationalResearch Council now include practitioners,private businesspersons, nongovernmental or-ganization representatives as well as scien-tists.11 Many federal regulations now requireparticipation of both the general public and

11 While it is not always obvious that those projects which excelat integration and engagement are always selected (Frodeman andHolbrook 2007), the trend is clear as to what is wanted. Presumably,the selection criteria will mature overtime to show even greaterpreference to excellent projects that are accountable to societalgoals.


Tame Problems

Number of Publications

Wicked Problems

Complexity

2008

2012

Figure 5. Shifting applied economics researchtoward wicked problems

agencies on federal projects; integrated as-sessments12 are part of many federal pro-grams (e.g., the U.S. Global Climate ChangeResearch Program); and there are increasingcongressional demands for greater account-ability of federal science budgets to benefit so-ciety (Jacobs, Garfin, and Lenart 2005; Pielkeand Byerly 1998; Shabman 2000; Stephenson2000).

It is important to note that addressingwicked problems does not equate with aban-doning normal science. Instead, it is an ar-gument to allocate more of the discipline’sresources to wicked problems. Consider figure5,13 where the number of publications is usedto proxy the discipline’s attention to societalproblems. Assume that the curve labeled 2008represents applied economists’ current atten-tion to tame and wicked problems. The shapeof the curve reflects the large volume of ap-plied economics articles that are about testingof theoretical propositions or disciplinary andmethod puzzle solving but which have little orno policy application as well as articles address-ing tame problems. Also included are thosearticles which address wicked problems butreduce them to their reductionist componentsin a manner that inappropriately substitutes ananalyst’s decision for stakeholder-negotiateddecisions. In contrast, there is a paucity ofarticles which appropriately address wicked

12 Integrated assessment is a formal approach to provide compre-hensive analysis of existing biophysical and social scientific infor-mation in the context of policy. Stakeholders (e.g., citizens, industryrepresentatives, scientists, and policy makers) define and evaluatepolicy options for wicked problems.

13 Thanks are due to Carol Shennan, Professor of EnvironmentalStudies at University of California, Santa Cruz, who suggested thisfigure.

problems and their complexities. The argu-ment for more appropriate attention to wickedproblems is an argument that the professionshould shift the curve upward and to the right(e.g., to the one labeled 2012).

Many of the same tools and concepts used inaddressing tame problems will be used in ad-dressing wicked ones. Normal science can beused to address the “what is” and “what if”components of both wicked and tame prob-lems. For example, participants in a negotiatedprocess may want an applied economics anal-ysis of, say, trade-offs associated with the se-lection of one policy alternative over another,so that the participants can decide what trade-offs are worth making, or they may desire acost analysis for the implementation of alterna-tive policies (Stephenson 2003). However, thevalue of such analysis is likely to be enhanced ifit is undertaken after an exploration of valuesunderlying the dispute are made transparent iftheir implications for society are explored andif suitable goals are identified (Sarewitz 2004).

On the other hand, the necessity for thecocreation of knowledge to address wickedproblems challenges many of the assumptionsof mainstream neoclassical economics, suchas the argument that preferences and ratio-nal choice guide market choices, that the mar-ket is a mechanism for making social choices,that prices (market and nonmarket) equatewith valuation, and that economic valuationscan be mapped into what is socially preferredso that analysts can weigh competing alterna-tives and select the outcome that yields thehighest societal benefits (Bromley 1997, 2006,2008b; Funtowicz and Ravetz 1994; Shabmanand Stephenson 2000; Stephenson 2000, 2003;Vatn and Bromley 1994).

Wicked problem analysis provides new op-portunities for alternative methodologies, suchas behavioral economics, Austrian economics,or original institutional economics. Consider,for example, the contributions to wicked prob-lems that can be made from the methodol-ogy of original institutional economics—withits emphasis on processes as to how decisionsare made via political negotiation approachesand how people behave under alternative in-stitutions. Since addressing wicked problemsinvolves improving negotiation processes(Norton 2005; Sarewitz 2004), original institu-tional economics has much to offer.

Other challenges associated with the cocre-ation of knowledge can emanate from dif-fering disciplines’ worldviews. For example,applied economists tend to have a greater faith


in innovation in the face of scarcity so that,say, environmental scarcity can be successfullyovercome; many ecologists do not share thatoptimistic worldview (Norgaard 2002; Sare-witz 2004). Stakeholders, too, bring worldviewsthat can be in conflict with each other and withdisciplines. Since there is much uncertaintyabout “facts,” and therefore many competingalternative “futures” are supported by avail-able knowledge, conflicts are inevitable. De-fusing these conflicts will require that appliedeconomists abandon any prescriptive certitudeand disciplinary hubris they might have andengage in respectful discourse (Bromley 2006;Johnson 2007; Klamer 2007).

What Is Needed?

The types of skills that are needed to un-dertake such postnormal science activitiesare neither well taught in applied economicsgraduate programs, nor do they appear tobe rewarded well in our research institutions.Necessary skills not only include the abilityto respect and understand many perspectivesand viewpoints but also skills in communica-tion and translational science to translate ex-isting scientific findings into a form suitable forpractical applications (Batie and Rose 2006).There needs to be more study of and famil-iarity with the methods of effective engage-ment which would include the development ofmanagement and leadership skills that are ableto incorporate and integrate the knowledge,skills, resources, and perspectives from manyactors (Ingram and Bradley 2006). There needsto be a willingness and ability to understandthe social and historical contexts surroundingpolicy formulation as well as how decisions areactually made (Batie 2005; Jacobs, Garfin, andLenart 2005).

There also needs to be more researchdirected toward both understanding and fa-cilitating collective decision making; actualpreferences and preference formation; andidentification of which held values are subjectto change and which are core values whichare not easily altered (Sabatier 1988). This re-search would need to involve other disciplinesincluding psychology, decision science, and so-ciology.

More fundamentally, however, there is aneed to understand that the role of the appliedeconomist changes with the shift from tameto wicked problems. In applied economics,this change involves moving from a “pure”

analyst to that of the honest broker14 whosejob is not to narrow the range of policy choicesto the optimal one but rather to expand therange of choice (Pielke 2007). To do the honestbroker role well, applied economists need tobetter understand the values and assumptionsembedded in their particular methodologicalapproach. They need to practice transparencyin deliberative processes while maintaining sci-entific credibility.

All of these needed skills suggest that alter-native methodologies and the history of eco-nomic thought should be taught in our grad-uate training and included in professional’scontinuing self-education. In a recent reviewof conversations with economic graduate stu-dents throughout the nation, Klamer (2007)lamented: “Particularly worrisome is the per-ception of this cohort of graduate studentsconcerning the science of economics. . . . Incontrast to their counterparts in the eighties,they do not question the scientific approachthat they are learning and they do not won-der about alternatives. Modeling continues tobe the way they go” (p. 230). He continues:“This cohort appears to be mindless, or at leastresourceless, when it comes to reflections onthe nature of their science. They have no lit-erature to fall back on. Even the text of Mil-ton Friedman appears to have dropped fromtheir reading lists. (Needless to say, economicmethodology has no place in the curriculum.)Apparently they are taught to do what theyare doing without giving much thought as tothe ‘how so’ and ‘why questions’” (p. 231).As postnormal science evolves, Klamer’s re-marks about why economics as a discipline isat risk are worth consideration as well by ap-plied economists. To paraphrase Klamer, howwill applied economists fare in the company ofother scholars who are so much more awareof developments in the new thinking aboutscience?

Barriers to Remodeling

The barriers to such a remodeling of the ap-plied economics discipline appear to be large.

14 In an earlier work, Batie (2005) refers to this role as a scienceadvocate (i.e., honest broker) who understands that to be effectivethere needs to be a commitment to learning about the art andcraft of policy analysis: “Policy relevancy requires that the scienceadvocate understand the policy in question, the issues of concern,and the institutions and stakeholders involved in the decision(s).This requirement suggests a considerable amount of effort by theanalyst in understanding the history of the issues surrounding thepolicy, the motivation of the actors involved, and the policy processitself” (p. 128).


Our research institutions are not designed toreward engaged, integrated, multidisciplinaryscience activities well, although that may beslowly changing. However, many of the poorlyaligned incentives or the research institutionsare derivatives of the discipline’s own view-point that there is no reason to change;15

wicked problems can either be effectivelyaddressed using the same methods and ap-proaches as tame problems; or they are notan appropriate subject for the field. Other ap-plied economists appear to be so constrainedby their focus on end states such as optimiza-tion that they cannot constructively contributeto negotiated decision-making processes es-sential to effectively addressing wicked prob-lems. Further, following the status relationshipset forth within the linear model, many inthe discipline continue to devalue engagementscholarship. Still, others may adopt a rationalanalytical method for policy analysis, evenwhen doubting the utility or validity of the ap-proach, because they perceive that it meets thedisciplinary and institutional standards for ob-jective science (Brunner 1991), whereas post-normal science draws on such a variety ofmethods and methodologies that are perceivedto be more difficult to defend as well as to un-dertake. Therefore, not only do research insti-tutions’ incentives need to be realigned, so dothe discipline’s.

Until realignment happens, postnormal sci-ence scholarship and engagement of wickedproblems will probably remain the task of asmall set of applied economists who are willingto take on these wicked problems regardless oftheir colleagues’ or institution’s approval. Butwhat are the consequences? One may well bethat those prospective graduate students whosee a value in applied economics addressingsociety’s wicked problems may eschew appliedeconomics for schools of public policy and de-cision science which provide education appro-priate to their concerns. And this outcome isonly one of the many ways that applied eco-nomics will suffer if it is labeled as irrelevantdue to neglect of wicked problems or becausewicked problems were treated as if they weretame.

15 This attitude that there is no reason to change may have beenreinforced with the last several decades’ dominance of “free mar-ket” politics. The recent economic crisis may end that dominanceas more regulation is imposed on markets.

Conclusion

There are many who believe that there is arenegotiation underway of the contract of so-ciety with science (Clark 2006; Frodeman andHolbrook 2007; Moll and Zander 2006; Shab-man 2000; Sarewitz 2004; Stokes 1997); butthere is little evidence that applied economicsis fully cognizant of this renegotiation. Thisrenegotiation provides opportunities and risksto the discipline.

Increasingly, the linear concept—in whichmore science leads to less uncertainty whichleads to improved decisions—is viewed asflawed with respect to wicked problems. Thus,for applied economics, as well as other sci-ences, what is needed are new ways of thinkingabout the conduct of science; validating sci-entific contributions; developing institutionsto facilitate engaged science–stakeholder pro-cesses (Sarewitz 2004); and embedding waysof thinking and methods into graduate edu-cation. The challenges are great, but so is thepotential payoff. The important questions forapplied economists to address are:

1. How does applied economics find its rolein addressing wicked problems?

2. How does applied economics institution-alize processes (including graduate educa-tion) that are relevant to successfully ful-filling those roles?

3. How does applied economics survive andthrive if more resources are allocated toaddress wicked problems?

The alternative question also remains:

How does applied economics survive,thrive, and maintain relevancy if it neglectswicked problems?

References

Batie, S.S. 2005. “The Demand for Economic PolicyAnalysis: Is Anyone Listening?” Agricultureand Resource Economics Review 34(2):123–30.

Batie, S.S., and J.B. Rose. 2006. “Environmental Is-sues and Water Resources.” Paper presentedat National Agricultural Research, Extension,Education, and Economics (NAREEE) boardmeeting, Washington, DC, 25 October.

Batie, S.S., L.A. Shabman, and R.A. Kramer. 1986.“U.S. Agricultural and Natural Resource Pol-icy.” In C.F. Runge, ed. The Future of the NorthAmerican Granary: Politics, Economics andResource Constraints in American Agriculture.


Ames, IA: Iowa State University Press, pp.132–38.

Bolin, B., W. Clark, R. Corell, N. Dickson,S. Faucheux, G. Gallopın, A. Gruebler, M.Hall, B. Huntley, J. Jager, C. Jaeger, N. Jodha, R.Kasperson, R. Kates, I. Lowe, A. Mabogunje,P. Matson, J. McCarthy, H. Mooney, B.Moore, T. O’Riordan, J. Schellnhuber, and U.Svedin. 2000. “Core Questions of Science andTechnology for Sustainability.” Available athttp://sustsci.aaas.org/content.html?contentid=776 (accessed June 12, 2008).

Bonnen, J.T. 1986. “A Century of Science in Agri-culture: Lessons for Science Policy.” AmericanJournal of Agricultural Economics 68(5):1065–80.

Brock, W.A., and D. Colander. 2000. “Complexityand Policy.” In D. Colander, ed. The Complex-ity Vision and the Teaching of Economics. Chel-tenham, UK: Edward Elgar, pp. 73–96.

Bromley, D.W. 2008a. “Institutional Economics asVolitional Pragmatism.” In S.S. Batie and N.Mercuro, eds. Alternative Institutional Struc-tures: Evolution and Impact. New York: Rout-ledge, pp. 91–112.

——. 1997. “Rethinking Markets.” American Jour-nal of Agricultural Economics 79(5):1383–93.

——. 2006. Sufficient Reason: Volitional Pragma-tism and the Meaning of Economic Institutions.Princeton, NJ: Princeton University Press.

——. 2008b. “The Emergence and Evolution ofEnvironmental and Natural Resource Eco-nomics.” In J. Wu, P.W. Barkley, and B.A.Weber, eds. Frontiers in Resource and RuralEconomics: Human-Nature, Rural-Urban In-terdependencies. Washington DC: Resourcesfor the Future, pp. 11–28.

Brunner, R. 1991. “The Policy Movement as a PolicyProblem.” Policy Sciences 24:65–98.

Bueren, E.M., E.H. Klijn, and J.F.M. Koppen-jan. 2003. “Dealing with Wicked Problems inNetworks: Analyzing an Environmental De-bate from a Network Perspective.” Journal ofPublic Administration Research and Theory13(2):193–212.

Bush, V. 1945. Science—The Endless Frontier.Washington DC: Government Printing Office.

Carroll, M.S., K.A. Blatner, P.J. Cohn, and T. Mor-gan. 2007. “Managing Fire Danger in the Forestof the US Inland Northwest: A Classic ‘WickedProblem’ in Public Land Policy.” Journal ofForestry 105(5):239–44.

Clark, W. 2006. “Sustainability Science: A Room ofIts Own.” Proceedings of the National Academyof Sciences in the United States of America(PNAS) 104:1737–38.

——. 2007. “Sustainability Science: An Emerging

Interdisciplinary Frontier.” The Rachel Car-son Distinguished Lecture Series. East Lansing:Michigan State University.

Clark, W., and L. Holliday (Rapporteurs). 2006.“Linking Knowledge with Action for Sustain-able Development: The Role of Program Man-agement.” Workshop Summary, Roundtableon Science and Technology for SustainabilityPolicy and Global Affairs. National Re-search Council of the National Academies.Washington DC: National AcademiesPress.

Cochran, S. 2000. “Sustainability Science: State-ment of the Friibergh Workshop on Sustain-ability Science.” Friibergh Manor, Orsunds-bro Sweden, 11–14 October. Available athttp://ksgnotes1.harvard.edu/BCSIA/sust.nsf/pubs/pub3/$File/FW statement.pdf (accessedJune 18, 2008).

Colander, D. ed. 2000. Complexity and the History ofEconomic Thought: Perspective on the Historyof Economic Thought. New York: Routledge.

Conklin, J.E. 2006. Dialog Mapping: BuildingShared Understanding of Wicked Problems.Napa, CA: CogNexus Institute.

Fear, F.A., C.L. Rosaen, R.J. Bawden, and P.G.Foster-Fishman. 2006. Coming to Critical En-gagement: An Autoethnographic Exploration.Lanham, MD: University Press of America.

Frodeman, R., and J.B. Holbrook. 2007. “Sciences’Social Effects.” Issues in Science and Technol-ogy 23(3):28–30.

Funtowicz, S.O., and J.R. Ravetz. 1993. “Science forthe Post-normal Age.” Futures 25(7:)739–55.

——. 1994. “The Worth of a Songbird: EcologicalEconomics and Post-normal Science.” Ecolog-ical Economics 10:197–207.

Gallopin, G.C., S. Funtowicz, M. O’Conner, andJ. Ravetz. 2001. “Science for the Twenty-FirstCentury: From Social Contract to the Scien-tific Core.” International Social Science Journal53(168):219–29.

Guston, D.H. 2001. “Boundary Organizations inEnvironmental Policy and Science.” Science,Technology and Human Values 26(4):399–408.

Hawken, P. 2007. Blessed Unrest: How the LargestMovement in the World Came into Being andNo One Saw It Coming. New York: VikingPress.

Horn, R.E., and R.P. Weber. 2007. New Toolsfor Resolving Wicked Problems: Mess Map-ping and Resolution Mapping Processes.Watertown, MA: Strategy Kinetics L.L.C.

Ingram H., and B. Bradley. 2006. “Water Sus-tainability: Policy Innovation and Conditionsfor Adaptive Learning.” Paper presented atthe Michigan State University Sustainable


Michigan Endowed Project Academy, Dear-born, MI, 18–19 November.

Jacobs, K.L., G.M. Garfin, and M. Lenart. 2005.“More than Just Talk: Connecting Science andDecision Making.” Environment 47(9):6–22.

Jacobs, K. 2008. “Informing Priorities for Wa-ter Sustainability Research Through DialoguesBetween Decision Makers and Scientists.” Pa-per presented at the Linking Knowledge withAction for Sustainable Development, SacklerColloquium of the National Academy of Sci-ences, Washington DC, April 3–4.

Johnson, M. 2007. “Finding Peace for Economists inUniversities.” Journal of Agricultural and Re-source Economics 32(3):417–24.

Klamer, A. 2007. “Does This Have To Be Our Fu-ture?” In D. Colander, ed. The Making of anEconomist, Redux. Princeton, NJ: PrincetonUniversity Press, pp. 227–28.

Kreuter, M.W., C. De Rosa, E.H. Howze, andG.T. Baldwin. 2004. “Understanding WickedProblems: A Key to Advancing Environmen-tal Health Promotion.” Health, Education, andBehavior 31:441–54.

Kuhn, T.S. 1962. The Structure of Scientific Revolu-tions. Chicago, IL: University of Chicago Press.

Lindbloom, C. 1965. The Intelligence of Democracy:Through Mutual Adjustment. New York: FreePress.

Lord, W.B. 1979. “Conflict in Federal Water Re-source Planning.” Water Resources Bulletin No.5:226–1235.

McCool, S.F., and K. Guthrie. 2001. “Mappingthe Dimensions of Successful Public Partic-ipation in Messy Natural Resources Man-agement Situations.” Society and NaturalResources 14(4):309–23.

McDowell, G.R. 2001. Land-Grant Universities andExtension into the 21st Century: Renegotiatingor Abandoning a Social Contract. Ames: IowaState Press.

Millennium Ecosystem Assessment. 2005. Ecosys-tems and Human Well-Being: Synthesis. Wash-ington DC: Island Press.

Miller, C.A. 1999. “Report of the Workshop onBoundary Organizations in EnvironmentalPolicy and Science.” Bloustein School of Plan-ning and Public Policy, Rutgers University, NewBrunswick, NJ, December 9–10.

Moll, P., and U. Zander. 2006. Managing the In-terface: From Knowledge to Action in GlobalChange and Sustainability Science. In S. Linde-mann and P. Wood, trans. Munich, Germany:German Federal Ministry of Education andResearch.

Norgaard, R.B. 2002. “Optimists, Pessimists, andScience.” Bioscience 52(3):287–92.

Norton, B.G. 2005. Sustainability: A Philosophy ofAdaptive Ecosystem Management. Chicago, IL:University of Chicago Press.

Nowotny, H., P. Scott, and M. Gibbons. 2001. Re-thinking Science: Knowledge and the Public inan Age of Uncertainty. Cambridge, UK: PolityPress.

Peters, S.J. 2007. “Changing the Story About HigherEducation’s Public Purposes and Work: Land-Grants, Liberty, and the Little Country The-ater.” Imagining America, Forseeable FuturesPosition Paper No. 6, University of Michigan,MI.

Peterson, C. 2008. “Transformational Supply Chainsand the ‘Wicked Problem’ of Sustainabil-ity: Aligning Knowledge, Innovating, En-trepreneurship, and Leadership.” Keynoteaddress presented at the International ChainConference, Wageningen, The Netherlands, 29May.

Pielke, R.A., Jr. 2007. The Honest Broker: MakingSense of Science in Policy and Politics. Cam-bridge, UK: Cambridge University Press.

Pielke, R.A., Jr., and R. Byerly, Jr. 1998. “BeyondBasic and Applied.” Physics Today 51(2):42–46.

Porter, T.M. 1995. Trust in Numbers: The Pursuit ofObjectivity in Science and Public Policy. Prince-ton, NJ: Princeton University Press.

Rittel, H., and M. Webber. 1973. “Dilemmas in aGeneral Theory of Planning.” Elsevier PolicySciences 4:155–69.

Russell, E. 2001. War and Nature: Fighting Humansand Insects with Chemicals from World War IIto Silent Spring. Cambridge, UK: CambridgeUniversity Press.

Ruttan, V.W., D.E. Bell, and W.C. Clark. 1994.“Climate-Change and Food Security—Agriculture, Health and EnvironmentalResearch.” Global Environmental Change-Human and Policy Dimensions 4(1):63–77.

Sabatier, P.A. 1988. “An Advocacy CoalitionFramework of Policy Change and the Role ofPolicy Oriented Learning Therein.” Policy Sci-ences 25:237–54.

Sarewitz, D. 2004. “How Science Makes Environ-mental Controversies Worse.” EnvironmentalScience and Policy 7:385–403.

Shabman, L. 2000. “Bargaining, Analysis and Wa-ter Management.” Water Resources Update 71,March.

Shabman, L., and K. Stephenson. 2000. “Environ-mental Valuation and Its Economic Critics.”Journal of Water Resource Planning and Man-agement November/December:382–88.

Shennan, C. 2008. “Biotic Interactions, EcologicalKnowledge and Agriculture.” Philosophical


Transactions of the Royal Society 363:717–39.

Shulock, N. 1999. “The Paradox of Policy Analysis:If It Is Not Used, Why Do We Produce So Muchof It?” Journal of Policy Analysis and Manage-ment 18(2):226–44.

Stephenson, K. 2003. “Environmental Goal Set-ting.” In M.R. Tool and P.D. Bush, eds. Institu-tional Analysis and Economic Policy. Boston,MA: Kluwer, pp. 443–60.

——. 2000. “Taking Nature into Account: Obser-vation About the Changing Role of Analysisand Negotiation in Hydropower Re-licensing.”William and Mary Environmental Law and Pol-icy Review 25:1–26.

Stephenson, K., and L. Shabman. 2007. “Overviewof Computer-Aided Dispute Resolution:Approach and Evaluation.” In K. Stephenson,L. Shabman, S. Langsdale, and H. Cardwell,eds. Computer Aided Dispute Resolution:Proceedings from the CADRe Workshop.Albuquerque, New Mexico. Available at

http://www.svp.iwr.usace.army.mil/docs/SVP-2007-R-06.pdf (accessed July 12, 2008).

Stokes, D.E. 1997. Pasteur’s Quadrant: Basic Sci-ence and Technological Innovation. Washing-ton DC: Brookings Institution Press.

Vatn, A., and D. Bromley. 1994. “Choices with-out Prices and without Apologies.” Journalof Environmental Economics and Management26(2):129–48.

Watzin, M.C. 2007. “The Promise of Adaptive Man-agement.” In M. Schnepf and C. Cox, eds.Managing Agricultural Landscapes for Envi-ronmental Quality. Ankey, IA: Soil and WaterConservation Society, pp. 147–58.

Weber, E.P., and A.M. Khademian. 2008. “WickedProblems, Knowledge Challenges, and Col-laborative Capacity Building in NetworkSettings.” Public Administration Review68(2):334–39.

White, L.G. 1994. “Policy Analysis as Discourse.”Journal of Policy Analysis and Management13(3):506–25.

Wicked Problems and Applied Economics - OECD. · PDF fileWICKED PROBLEMS AND APPLIED ECONOMICS...

Documents

Transcript of Wicked Problems and Applied Economics - OECD. · PDF fileWICKED PROBLEMS AND APPLIED ECONOMICS...