Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems...

20
Research Paper Conict Theory, Complexity and Systems Approach Giorgio Gallo* Computer Science and Interdisciplinary Center Sciences for Peace, University of Pisa, Pisa, Italy Since the end of the Cold War, we have been witnessing the emergence of new types of conicts. These are progressively more complex, but are, still too often, conceptualised and approached simplistically, using a linear type of reasoning. Complexity is disre- garded, and the need for systemic thinking is underestimated, not rarely leading to disas- trous results. Feedbacks are most often ignored, and the complex dynamics which make a conict to change over time, following often unpredictable paths, are rarely taken into account. A shift from a precomplexity mindset to a mindset founded in an understanding of complexity is necessary. In the paper, using concrete examples, we will try to show how a systems thinking approach is essential to analyse todays conict, to prevent them, and to act so as to make them develop along non violent constructive paths rather than along violent destructive ones. Copyright © 2012 John Wiley & Sons, Ltd. Keywords conict theory; systemic models; critical systems thinking; complexity INTRODUCTION A conict is a special kind of system whose complexity stems from many different and some- times unrelated elements. On the one side, there are the parties involved in the conict. If it is true that there are cases in which the parties are just two (or even one, in the case of a dilemma), most often the parties are many, with intricate relations between them. More importantly, there are often multiple and diverse objectives. Some may even be hidden, not dened once and for all, and may evolve over time. This is almost always the case in conicts arising between different groups within a country or in international conicts. These are the types of conicts we will be dealing with in this paper. On the other side, each conict does not arise in a vacuum, but in a context, local, regional, or international, a context that may be changing over time and has often unforeseen effects on the conicts structure and parties. Another important fact that is too often disregarded is that a conict does not end simply when violence is stopped or when a satisfactory compromise between the parties is signed. Ending a conict in a real and stable way implies the construction of a lasting peace, which is something daunting and difcult to obtain (Bartolucci and Gallo, 2010). * Correspondence to: Giorgio Gallo, Computer Science, University of Pisa, Largo B. Pontecorvo 3, Pisa, Italy. E-mail: [email protected] A rst draft of this paper has been presented at the conference on Complexity, Uncertainty and Ethics, Delft University of Technology, 14 April 2011. Received 22 November 2011 Accepted 16 July 2012 Copyright © 2012 John Wiley & Sons, Ltd. Systems Research and Behavioral Science Syst. Res. (2012) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/sres.2132

Transcript of Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems...

Page 1: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

■ Research Paper

Conflict Theory, Complexity and SystemsApproach†

Giorgio Gallo*Computer Science and Interdisciplinary Center ‘Sciences for Peace’, University of Pisa, Pisa, Italy

Since the end of the Cold War, we have been witnessing the emergence of new types ofconflicts. These are progressively more complex, but are, still too often, conceptualisedand approached simplistically, using a linear type of reasoning. Complexity is disre-garded, and the need for systemic thinking is underestimated, not rarely leading to disas-trous results. Feedbacks are most often ignored, and the complex dynamics which make aconflict to change over time, following often unpredictable paths, are rarely taken intoaccount. A shift from a precomplexity mindset to a mindset founded in an understandingof complexity is necessary. In the paper, using concrete examples, we will try to show howa systems thinking approach is essential to analyse today’s conflict, to prevent them, andto act so as to make them develop along non violent constructive paths rather than alongviolent destructive ones. Copyright © 2012 John Wiley & Sons, Ltd.

Keywords conflict theory; systemic models; critical systems thinking; complexity

INTRODUCTION

A conflict is a special kind of system whosecomplexity stems from many different and some-times unrelated elements. On the one side, thereare the parties involved in the conflict. If it is truethat there are cases in which the parties are justtwo (or even one, in the case of a dilemma), mostoften the parties are many, with intricate relationsbetween them. More importantly, there are oftenmultiple and diverse objectives. Some may evenbe hidden, not defined once and for all, and

may evolve over time. This is almost always thecase in conflicts arising between different groupswithin a country or in international conflicts.These are the types of conflicts we will be dealingwith in this paper. On the other side, each conflictdoes not arise in a vacuum, but in a context, local,regional, or international, a context that may bechanging over time and has often unforeseeneffects on the conflict’s structure and parties.Another important fact that is too oftendisregarded is that a conflict does not end simplywhen violence is stopped or when a satisfactorycompromise between the parties is signed.Ending a conflict in a real and stable way impliesthe construction of a lasting peace, which issomething daunting and difficult to obtain(Bartolucci and Gallo, 2010).

*Correspondence to: Giorgio Gallo, Computer Science, University ofPisa, Largo B. Pontecorvo 3, Pisa, Italy.E-mail: [email protected]†A first draft of this paper has been presented at the conference onComplexity, Uncertainty and Ethics, Delft University of Technology,14 April 2011.

Received 22 November 2011Accepted 16 July 2012Copyright © 2012 John Wiley & Sons, Ltd.

Systems Research and Behavioral ScienceSyst. Res. (2012)Published online in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/sres.2132

Page 2: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

In spite of all this, too often when a conflict isanalysed or when decisions about an actual orpotential conflict are taken, the kind of reasoningthat is followed is simplistic, linear, to say theleast. Complexity is disregarded, let alone theneed for systemic thinking. That is true both ata level of theoretical analysis and practicaldecision making, as it is shown by Pinzón andMidgley (2000) in their analysis of the theoreticalframeworks which are used to evaluate theresults of a conflict. This is something that hasrelevant practical consequences: in fact, the waya conflict is approached is shaped by the criteriaused to evaluate its possible outcomes. Pinzónand Midgley illustrate, by means of a detailedanalysis, how the evaluation framework thatprevails in some areas of the conflict resolutionliterature, particularly in negotiation and medi-ation theory, is based on a reductionist and quitenarrow conceptual paradigm, and propose a newframework on the basis of a systems approach.

Here, we will try to show how a systemsapproach is essential for a correct understandingof the characteristics and of the dynamics of aconflict and, as a consequence, for the decisionsthat are taken within a conflict. Without asystemic and holistic framework, decisions mayworsen the conflict, resulting in increased andprolonged suffering for the involved populations,and the analysis may lead to poor and misleadingunderstanding of the conflict’s dynamics andperspectives. To make clear this last point, wepresent next two cases, which can be consideredas typical. One has to do with the 2003 Iraq war,the second with an older conflict, operation ‘Peacefor Galilee’, that is the Israeli invasion of Lebanonin 1982.

Iraq War

In 2003, the US and British forces invaded Iraqand, over a 3-week period, succeeded in over-throwing the regime of Saddam Hussein andoccupying the whole country. Triumphantly,President Bush claimed that the invasion of Iraqhad marked the arrival of a new era. The feelingof novelty brought by the American victory iswell expressed by the emphatic words of Max

Boot, an American political analyst. Shortly afterthe end of the military operations, he wrote inForeign Affairs: ‘That the USA and its allies wonanyway and won so quickly must rank as oneof the single achievements in military history.This 3-week campaign will be studied anddebated by historians and military analysts foryears to come’ (Boot, 2003). Actually, not every-body shared such a feeling of enthusiasm.Kenneth N. Waltz, in a letter to the editor ofForeign Affairs, published on the September/October issue of the same year, is sharp inhis judgement: ‘Iraq entered its most recentwar with its military strength at less than halfof its 1991 level. Why then does Boot find itimpressive that the USA and the UK won withabout half the troops, in about half the time,and with about half the casualties of the firstGulf War? In 2001, Iraq’s gross domestic prod-uct (GDP) was about $15 billion and itsdefence expenditure $1.5 billion. US GDP wasabout $10.2 trillion and its defence expenditure$322 billion. For a giant to defeat a pygmyhardly tests a country’s military prowess orvalidates a “new way of war”’ (Waltz, 2003).Waltz challenged the idea that the victorywas something extraordinary and of greatsignificance, but he did not contest the fact thata victory had been obtained. Now, after morethan 9 years, we are in a better position to seehow elusive that victory had been. In Figure 1,the monthly coalition military fatalities are plot-ted from the beginning of the war to the end of2011.1 It can be observed that, in spite of theearly victory proclamation, fatalities havestarted to grow, hitting quite high values forseveral years. Only in December 2007 did theydrop below the level of 40 per month. And in2010, we still had between four and five deathsper month. The behavior of the civilian deathsis similar, but for the scale which is from 10 to30 times higher. The civilian deaths due togunfire, vehicle bombs and suicide attacks today,after the US troops withdrawal, are still of theorder of hundreds per month.2

1 The ‘smoothed casualties’ have been obtained by sliding windowaveraging, with a 5months window.2 See the site Iraq Body Count (http://www.iraqbodycount.org/).

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 3: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

Peace for Galilee

In 1982, the Israeli government wanted to get ridof the Palestinian Liberation Organization (PLO),whose headquarters were then in Lebanon. Themain aim of Sharon, at the time Defence Ministerof Israel, in launching the so called operation‘Peace for Galilee’, a full scale invasion ofLebanon, was to destroy the PLO’s military infra-structure in Lebanon and to undermine it as apolitical organization, so as to weaken itsinfluence on the West Bank Palestinians.3 Thewar was harsh, with heavy losses on both sides.At the end, it ‘had cost Israel 660 deaths, had exa-cerbated its economic difficulties, subverted thenational consensus on security, and tarnishedIsrael’s image abroad’ (Shlaim, 2001, p. 427).Actually, the PLO was dislodged from Beirut,but it did not take too much for it to reorganizein Tunis, and it was only a matter of a few yearsfor the Palestinian front to become hot again withthe start of the first intifada. Furthermore, acompletely unforeseen effect materialized: thebirth of a new and more formidable adversary,the nationalistic Islamist movement Hizballah(Party of God). With Iranian and Syrian support,‘Hitzballah steadily pushed Israel out of Lebanon,first to a security zone along the border in1985, then completely out of Lebanon in 2000. AfterIsrael withdrew, Hizballah remained a threat,supporting Palestinian fighters, launching rocket

attacks, and kidnapping Israel soldiers—actionsthat led to war in 2006’ (Byman, 2011, p. 9). Thislast war has been the only one waged by Israelafter independence when the enemy, throughthe launch of rockets, was capable of strikingtargets deep inside the country. In addition to 121soldiers, 43 Israeli civilians died in this war,whereas 1200, mainly civilians, had been thecasualties on the Lebanese side. The shortcomingsthat have characterized Israel’s counterterrorismoperations, including a disregard for long-termplanning and a failure to recognize the long-termpolitical repercussions of counterterrorism tactics,are analysed in depth by Daniel Byman (2011).

CONFLICT AS A COMPLEX SYSTEM

The two cases presented in the preceding sectionare typical examples of linear and mechanisticthinking. Conflict, instead, is a very complexsystem, with adaptive structures and evolutionarymechanisms. It is a system composed of intercon-nected parts that, as a whole, exhibits propertieswhich cannot easily be understood only by dissect-ing and analysing the properties of the individualcomponents. A deep understanding of conflictsrequires, on the one side, a system thinkingapproach, and, on the other, the confluence ofmany social and scientific disciplines.

Key elements in system thinking, which makeit very different from a linear type of reasoning,are as follows:

Figure 1 Monthly coalition military fatalities in Iraq from March 2003 to December 2011

3 A second objective was to help Bashir Gemayel, the chief of thePhalange, one of the Maronite militias, to become Lebanon’s President,so to arrive to a favourable peace treaty with Lebanon.

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 4: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

• Boundaries definition.• State and activity variables.• Causal loops and feedbacks.• Multiple interconnected subsystems.• Delays.

All these elements, which are typical featuresof a system structure, are present in conflicts,and make them so difficult not only to solve butalso to analyse. All these elements will bepresented in detail, with reference to conflictmodelling, following this section. Instead, the nexttwo sections will deal with two characteristics of asystem which derive from the structural elementsdescribed here. Finally, in the section on ModellingConflicts as Systems, some challenges one cannotescape in conflict modelling are discussed.

System’s Boundaries

‘The boundary concept lies at the heart of systemthinking: because of the fact that everything inthe universe is directly or indirectly connectedto everything else, where the boundaries placedin any analysis becomes crucial’ (Midgley, 2000,pp. 128–29). In fact, systems are not the reality;they are rather social constructs, logical concep-tual constructions, which are the result of theinteraction between our culture, perspectivesand objectives on the one side, and the realityon the other. It is us who define the system and itsboundaries, that is, which variables are to beincluded in the system andwhich are not.4 Consid-ering the boundaries explicitly is a way to bring thecontext into the analysis, which is essential if we areto devise successful resolution strategies for aconflict. Unfortunately this is rarely done, aspointed out by Monty Marshall (1999, p. 5): ‘Mostconflict research and conflict management tech-niques assume some form of systemic closure tosimplify the inquiry and isolate the problemevents or processes from their general systemiccontext (i.e. focus on the opposition and discountexternal influences)’.

The Peace for Galilee case is a typical exampleof poorly chosen boundaries. The boundariesdrawn by Ariel Sharon included only the Israeliarmy/government and the Palestinian leader-ship, which are the main institutional actors. Hedid not fully appreciate how strongly rooted inthe Palestinian population the nationalist feelingsand the consensus toward the PLO were, andhow articulated and strong the Palestinian resis-tance was. Moreover, the complexity and theextreme fragmentation of the Lebanese societywere completely disregarded and so were thesubtleties of its politics. But also, the full implica-tions of the war on the Israeli society wereunderestimated.5

The choice of the boundaries shapes a conflictand has deep effects on how we tackle it. Bound-aries have many dimensions:

• Physical—Land is themost typical case, but thereare also several kinds of resources, such as oil,water, minerals, access to the sea and others.

• Temporal—This dimension is, for example,linked to the question: How far do we haveto go back in defining the conflict? The answerto such a question can determine the way theconflict is shaped. For instance, in the Israeli-Palestinian conflict, we may consider theconflict as having started with the 6-day war(1967), or with the independence declarationof Israel (15 May 1948), or even before. Thechoice has deep consequences, among others,with respect to the refugee issue.

• Symbolic—For instance, the symbolic value ofKosovo for Serbians. Kosovo region has beenat the centre of the Serbian empire until themid-14th century, and still, Serbians regard itas the birthplace of their nation. Without refer-ence to the symbolic aspects, it is impossible tofully understand the Kosovo conflict between1998 and 1999.

• Ethical—Some aspects in a conflict have ethicalimplications that cannot be disregarded. Theethical implications of the boundary choiceare well illustrated by Pinzón and Midgley(2000) with reference to the Colombianguerrilla conflict.

4 Variables, which are left outside of the system, are either not relevantwith respect to our objectives and to our understanding of the system,or are considered as constants, that is, they influence the system’sdynamics, but are not influenced by them.

5 The deep scars left in it by the war are the object of the filmWaltz withBashir.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 5: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

State and Activity Variables

It is well known that after the end of the ColdWar, there has been an increase in the numberof ethnopolitical conflicts. The Minorities at Risk(MAR) project, initiated by Gurr in 1986 (Gurr,1994, 2000), examines and documents the statusof ethnic and religious minority groups in allthe countries of the world over the contemporaryperiod since 1946. The number of minoritygroups that the project has studied has beengrowing during the years: from 227 in 1990 to284 in 2003. One of the objectives of this analysishas been to develop a theoretical framework ofthe causes of ethnopolitical conflicts to explainthese social phenomena through causal mecha-nisms. A system dynamics model based on Gurr’swork (Ackam and Asal, 2005) is given in Figure 2.Analysing this model, we see a certain number

of loops describing the main dynamics in an eth-nic conflict.6 For instance, the rebellion may leadthe Government to try to understand the roots of

the ethnic group’s grievances and to act in orderto lower the discrimination, trying for instanceto reduce the economic differences. That in turnreduces the comparative disadvantage of thegroup and hence the incentives for rebellion.Note that there is a difference between a variablesuch as ‘rebellion’ and a variable such as‘economic differences’. The former has to do withan activity, which can be performed or not,whereas the latter has to do with a structuralaspect of the situation, something that does notcorrespond to a specific action performed by oneof the actors, and hence something that cannotbe set to zero just by a decision. A decision caninstead be taken to stop the conflict, at least inprinciple. The former is what we call an activityvariable, whereas the latter is a state variable.7

Another example of state variable in the ethnoter-rorism model is the ‘salience of ethnic identity’,although it is a state variable, it is different from‘economic differences’, in the sense that it doesnot represent something concrete and easilymeasurable, but refers to the attitudes and thedeep feelings of the people involved. Statevariables are those that define the structural

Figure 2 The dynamics of ethnoterrorism (Ackam and Asal, 2005)

6 In the model, the standard notations used in system dynamics mod-els have been used. An arrow with a ‘+’ sign from variable A to vari-able B means that a variation in the value of A induces a variation inthe same direction in the value of B. On the contrary, a ‘�’ sign indi-cates that a variation in the value of A induces in the value of B a vari-ation in the opposite direction.

7 Sometimes, activity variables are called flows, and state variables arecalled stocks or levels.

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 6: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

aspects of the conflict. Analysing such structure,we can understand which state variables need tobe changed to get to a sustainable solution of theconflict, and in which direction the change isneeded. But, the only way to obtain the changeis through the activity variables.

There are interesting analogies with one of theclassical and most known conflict paradigms,that is Galtung’s ABC triangle, depicted inFigure 3, where A stands for Attitudes, B forBehaviour and C for Contradiction (Galtung,1996). According to the ABC triangle, a conflictis defined by three main elements, the contradic-tion, which is the concrete object of the conflict,the behavior of the different actors, and theirdeep feelings, the attitudes. A conflict cannot besolved, or better transformed to becomeconstructive instead of destructive, unless wetackle all the three components at the same time.It is interesting to see that, in our systemicparadigm, attitudes are essentially state variables(e.g. ‘salience of ethnic identity’ in our example),whereas behaviors are essentially activities (e.g.‘rebellion’). Less direct is the interpretation ofthe third component, contradiction; usually, itrefers to something that can be represented as aset of state variables (‘economic differences’ inAckam & Asal’s model is one of the componentsof the contradiction).

The systems paradigm and the ABC one areclearly different, the former being dynamicwhereas the latter is quite static, but they arecomplementary. The ABC paradigm may providethe broad framework within which the conflict isanalysed, the boundaries are chosen, the mainvariables and the relations among them aredefined, and eventually, the model is built.

Causal Loops and Feedbacks

Causal loops and feedback are typical of complexsystems and are at the basis of the difficulty todevise the right actions to bring a conflict to asolution. For instance, in the model of Figure 2,we can find different such loops. As an example,‘rebellion’ of ethnic groups brings the governmentto respond with repressive actions, but those same

repressive actions have the effect of exacerbatingthe ‘comparative disadvantage of ethnic groups’,which in turn props up the ‘incentives forrebellion’ and, through the ‘group capacity forrebellion’, the rebellion is strengthened. Thereare also negative feedback cycles: as examples,the repression and hitting the leadership of theminorities may reduce their capacity of planningand implementing effective actions against thegovernment.8 If this negative cycle is dominantthen the repression will be successful (at leastin the short term); otherwise, it will fuelthe violence.

An interesting analysis of the repression–rebellioncycle is contained in a paper by Kress andSzechtman (2009). Their model, based on a setof differential equations, is focused on the roleof intelligence in counterinsurgency operations.In insurgency situations, governmental forcesare confronted by relatively small guerrillagroups dispersed in the general population. Foreffective counterinsurgency operations, goodintelligence is required. In fact, poor intelligencenot only makes easy for the rebels to escapeunharmed and continue violent actions, butcollateral damage caused to the population frompoor targeting may generate resentment againstthe government and create popular support forthe insurgency. Here, the cycle derives from thefact that intelligence effectiveness can be consid-ered an increasing function of the strength of thegovernmental forces deployed, but also of thesize of the insurgency forces: the more the insur-gents are, the easier it is to get information aboutthem and to locate them. A high effectiveness of

Figure 3 Galtung’s ABC paradigm

8 This has been, for instance, the case of the 1936–1939 Arab revolt inPalestine. The result of the British repression was that ‘the communityin Palestine remained in effect leaderless. The British had effectivelydestroyed the nationalist notables’ (Pappe, 2004, p. 107).

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 7: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

the intelligence implies higher insurgent losses,and hence, a reduction in the insurgency forces.This, in turn, makes it more difficult to get reli-able information on them. Eventually, the effectis an increase in the civil losses due to counterin-surgency operations, an increase in popularsupport for the insurgents andmore new recruitsfor them. The authors conclude that it is almostimpossible to eradicate insurgency by force only;soft actions such as civil support and psycho-logical operations that affect the attitude of thepopulation may be needed too.Completely different is the insurgency warfare

model developed by Coyle (1985). A portion ofthis model is represented in Figure 4.Here, reference is made to a widely used tactic

in counterinsurgency operations in peasant areas,consisting in assuring military protection tothe villages and/or gathering the peasants inlarge protected villages, with the stated objectiveto protect them, but also of controlling themand severing possible collaborations with the

insurgents.9 According to Coyle, the model sug-gests that the effective loops for the Governmentare those of Protection and Supply Control.Weakening the insurgents via military actionsmakes the village protection more effective, hencereducing the transfer of allegiance (Transfer rate)of the population from the Government to theinsurgents (Protection Loop). Similarly, a moreeffective protection reduces the insurgents’ abilityto obtain supplies and new recruits, so furtherweakening them (SupplyControl Loop). A key roleis played in the model by the link from ‘Insurgentstrength’ to ‘Transfer rate’. Its sign can be eitherpositive or negative, depending on several factors.For instance, a widely shared perception of thegoodness of the insurgents’ cause may make thesign positive, so that an increase in their strengthhas the effect to increase the transfer of allegianceto the insurgents. On the contrary, the recourse toterrorism and a brutal behavior may weaken the

9 Tactics of this type have beenwidely used in Asia and in Latin America.

Figure 4 Government response in Coyle’s insurgency model

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 8: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

insurgents’ appeal, making the sign negative.According to the sign of this link, the Compulsionand the Logistic loops may be either reinforcing ordecaying.

Another self-reinforcing cycle in repressionpolicies has been studied by Kaplan et al. (2006),with reference to the Israeli–Palestinian conflict.Self-reinforcing loops are also described by Galloand Marzano (2009) in the context of the analysisof structurally asymmetric conflicts, with appli-cations to the Israeli–Palestinian case.

Multiple and Multiply-InterconnectedComponents

Systems are made of subsystems and, at the sametime, they are subsystems of larger and morecomplex systems. The problem is that too often,when facing a conflict or a situation of instability,which can develop into an armed conflict, thecomplexity is disregarded, at least until the situ-ation is so deteriorated that sustainable peacehas became almost unattainable.

The recent Afghanistan war is a typical case.‘By 1 May 2003, the combination of the successin Afghanistan and the apparent military victoryin Iraq meant that President Bush could deliverhis “Mission Accomplished” speech on the flightdeck of the USS Abraham Lincoln. . . . [T]herewas a confidence in Washington that the AfghanWar was over, that the Taliban would notre-emerge and that European allies would bearthe brunt of reconstruction and development’(Rogers, 2011). An important result that thevictory would have made reachable ‘was thatby maintaining a substantial military presencein Iraq and Afghanistan, and controlling thePersian Gulf and Arabian Sea through the USNavy’s Fifth Fleet, Iran would be thoroughlyconstrained. Given that Iran was seen as the mostserious of all threats to US interests in the region,this would be a hugely positive outcome’(Rogers, 2011). Today, after 9 years from thatday, the war is still going on, and the perspectivesafter the eventual withdraw of the US soldiersare far from clear. The reality proved to be farmore complex that it was expected.

At the end of 2009, a study commissioned bythe Pentagon went public. It contained a SystemDynamics model of the nation building effort inAfghanistan. The diagram synthesizing themodel is the one in Figure 5. Comments havebeen more disparate. Some said that the reasonwhy the Americans are not winning is becausethey are too busy at drawing fancy pictures suchas this one. Other praised the fact that SystemDynamics is being used in an effort to grasp thecomplexity of the situation, and surely, the graphshows how everything is connected to every-thing else, and makes evident how difficult andelusive a military victory may be.10 That themodel be really sound and useful in practice isanother matter, and it is hard to say with theinformation at our disposal. What we can say isthat, it appears to fail the simplicity test. We mustnever forget that the ‘whole purpose [of a model]is to simplify reality as a tool for thought and that islost if it is too big’ (Coyle, 2004, p. 34). This ispossibly more important in qualitative than inquantitativemodelling. As stated byWolstenholme(1999), ‘One of themajor problems is that of how toproduce simple, balanced and elegant models at anappropriate level of aggregation in time and spaceto be useful. There is always a tendency to producemodels, which are too detailed and complex and toinsufficiently validate them against the mentalmodels of their creators.’

Delays

Delays are a feature that makes the behavior ofcomplex systems so difficult to predict, inaddition to the intricate pattern of relations andnonlinearities. ‘Delays are pervasive. It takes timeto measure and report information. It takes timeto make decisions. And it takes time for decisionsto affect the state of a system’ (Sterman, 2000,p. 411). Delays may lead to counterintuitivebehaviors or to striking differences betweenshort-term and long-term behaviors.

Two main types of delays are usually consid-ered in the literature on dynamic systems,material

10 ‘When we understand that slide, we’ll have won the war,’ GeneralMcChrystal dryly remarked, accordingly to the New York Times,when he was shown the Power Point containing the diagram.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 9: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

delays and information delays. The former refers toflows of material objects. Take for instance thetime needed to deploy a UN peacekeeping forceon the ground once the decision has been taken.The participating states’ contingents must beassembled, and thereafter transported to the siteof the intervention. All these take time, sometimesmore than expected, with negative consequenceson the mission’s effectiveness. More challengingis the latter type of delay. It has to do not withphysical objects, but rather with communication,perceptions and attitudes. It takes time, for in-stance, for the information coming from a crisisarea to reach the first page of the newspapers orthe headlines of the television news. And it takeslonger time for the governments to reach anagreement on a possible humanitarian interven-tion and for the build-up of the public opinion’sconsensus for it. Information delays may play afundamental role in situations in which manyparties are present, operating independently onefrom the other. The lack of a timely knowledgeof the others’ actions and hence of a correctassessment of their intentions, may lead some of

the actors to take decision leading to catastrophicends. This may explain at least in part the dynam-ics that lead to the outbreak of World War I.

An interesting example of the role of delayscan be found in the system dynamics modelproposed by Choucri et al. (2007) to assess thestability of a state, that is, its capability to avoidthat dissident actions develop into violent rebel-lions and in its own destabilization. Among thekey variables in the model are the resilience ofthe state and the effectiveness and strength ofanti-regime messages. The resilience is a functionof different parameters, such as economicperformance, regime legitimacy, political cap-acity and social capacity. The effectiveness andstrength of anti-regime messaging depends onparameters both subjective (perceived strengthof their content) and objective (availability ofsocial networks and free media). The governmentmay think to weaken the dissident groups byenforcing a tight control on the media and onthe internet based social networks. This policymay work in the short term. But at the same time,it curbs civil liberties, and, as a consequence, it

Figure 5 A dynamic systems model of the Afghanistan conflict (The New York Times, April 26, 2010, retrieved from http://www.nytimes.com/2010/04/27/world/27powerpoint.html?_r=1)

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 10: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

reduces the very legitimacy of the government inthe perception of the population. Because itinvolves a change in attitudes and perceptions,this process takes time. So, its effects will bemanifest with some delay. In the long run, thestrength of the dissident groups may be bolsteredrather than reduced. In system dynamics termin-ology, the process through which the reduction incivil liberties leads to a growing awareness ofillegitimacy within the population can be mod-elled by an exponential delay function.

Peace processes based on confidence buildingmeasures are another typical case where delaysplay a fundamental role. One cannot expect theeffects of confidence building measures to beseen immediately, nor that violence from thedifferent parties ends or is reduced in a linearmonotonic way. Delays are present because whathave to change are not only the behaviors butalso and mainly the attitudes of the parties, andattitudes change quite slowly. One has also toconsider that, in a conflict, behaviors andattitudes of a large number of people areinvolved, not only of few leaders. Misperceptionof the delays may make one of the parties (orpossibly both) to end the process claiming thatit has not produced the expected results andblaming the failure on the bad faith of the other.

EMERGENT PROPERTIES

One of the effects of complexity is that a systemmay present properties that are not easilyderived from the analysis of its parts taken inthemselves, but from the interactions among allits parts. Emergent properties have to do with thesystem considered as a whole: ‘An emergentproperty is one that results from the interactionof a system as a whole rather than from one ortwo of its parts in isolation’ (Midgley, 2000, p. 40).

Emergent properties arise at different levels,from macro to micro. Sometimes, we are not ableto know the structure of the system directly, butthrough the analysis of its emergent properties,we can derive some useful information on it. Aninteresting example has been provided byAlvarez-Ramirez et al. (2010). They analysed thefatalities data in the Iraq War trying to derive

from them an idea of the structure of the differentinsurgent groups. The idea is that the fatalitiespattern over time derives from the way the insur-gency is structured.

The main assumption is that a truly randombehavior implies that there is not a stronglyorganized insurgency. Rather, insurgency groupsare scattered, loosely connected and poorly coor-dinated in their actions. On the contrary, a trend-reinforcing behavior11 implies the presence of awell structured resistance. Paradoxically, this lastcase, although in the immediate, much moreharmful, is preferable. In fact, a well structuredresistance ismore easily countered and dismantled,whereas a loosely organized resistance is less harm-ful in the immediate, but it can endure over timeresulting at the end to be more dangerous.

For their analysis of the time series of the casual-ties, the authors make use of the Hurst exponent, H,which is an index of long-range dependence usedto analyse time series. In quantitative terms, thereare three distinguishable cases:

• 0<H< 0.5: time series with negative auto-correlation, that is, an increase of values willprobably be followed by a decrease and viceversa, leading to wide oscillations;

• 0.5<H< 1: time series with long-termpositive autocorrelation, that is, a sequenceof increasing (decreasing) values in the serieswill probably be followed by an increasing(decreasing) value, leading to a trend-reinforcing behavior;

• H=0.5: indicates that the time series valuesrepresent a true random walk (e.g. the timeseries has no memory of previous values).

Analysing the data of the Iraq war fatalities(both military and civilian) using the Hurst expo-nent, the authors found that five regimes or phasesin the evolution of the war could be identified.After a first regime, characterized by an almost

11 This is the case when the time series presents a long term memory,that is, when there is a positive correlation between an event and theset of the preceding events. This implies that if the time series valueshave been increasing (decreasing) for some time, then chances are thatthey will continue to increase (decrease) in the future. This property iscalled persistence. On the contrary, when the correlation is negativethen when the value goes up we expect it to go down in the next fu-ture. In this case we talk of anti-persistence, a behavior characterizedby wider oscillations than those expected in a pure random walk.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 11: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

constant and relatively high value ofH, typical of aconventional confrontation, a second regimeoccurred in the last months of 2004, with thedynamics of civilian fatalities evolving towarduncorrelated behavior, and the dynamics of mili-tary ones showing increased correlations. This isinterpreted as a situation in which the differentinsurgency groups acted in an erratic and poorlycoordinated manner. The third regime, in the firsttwo quarters of 2005, with increasing and conver-ging correlations of civilian and military fatalities,has been interpreted as the rapid emergence ofa well-organized, although non-centralized, insur-gency structure. The fourth regime, frommid-2005to mid-2007, showed an important correlationdecrement for the military fatalities (although notfor the civil ones). ‘This was related to the clashof two antagonist war structures, namely thetraditional centralized Coalition Army and a non-centralized insurgent army. Finally, the fifthregime, from mid-2007 to date, is characterizedby stable fatality dynamics converging to uncorre-lated behavior’ (Alvarez-Ramirez et al., 2010).Their conclusion is that the insurgency

structure is quite decentralized, with a degree oforganisation and coordination among the differ-ent groups varying over time, with phasescharacterized by a high level of coordinationand phases in which the groups act in a poorlycoordinated manner. The conjecture derivedfrom the analysis of the data is that the insur-gency cells, in each phase, can be represented asthe nodes of a scale-free network, where the edgesrepresent the links between them. A scale-freenetwork is a network in which the probability,P(k), (a node has a degree k, that is connected tok other nodes) decays when k increases accordingto a power law, that is P(k)� k�g (Barabási andAlbert, 1999), where g is a positive coefficientwhich, in most of the studied cases,12 has beenfound to be in the range between 2 and 4. In atypical scale-free network, there is a set of high-degree vertices forming the core of the network,with progressively lower-degree nodes makingup the regions between the core and the

periphery. Although the core nodes are not toofew (much more than in purely random graphs),such networks are fault tolerant, as random re-moval of even a large fraction of nodes impactsthe overall connectedness very little. That doesnot mean that targeted attacks cannot destroyeasily the connectedness, but they require ahighly effective intelligence, which is somethingquite difficult to obtain in the presence of an insur-gency, whose loose structure resembles a scale-freenetwork.

Different types of confrontations/wars inwhich one of the parts’ organization has thestructure of a loosely connected network havebeen studied by Arquilla and Ronfeldt (2001). Atypical case is the one of Al Qaida, whosenetwork structure makes it particularly elusiveand difficult to defeat.

OVERSHOOTING AND COLLAPSE

The behavior of a system may present quitedifferent patterns. In fairly high-stability systems,key variables change continuously over time,adjusting slowly in response to the overalldynamics of the system, with patterns that maybe of either increasing, or decreasing, or in somecases oscillatory type.

Oscillatory behaviors are usually the results ofthreshold phenomena or overshooting. An over-shooting occurs when a system goes beyond itslimits. In stable systems, as a result of overshoot-ing, corrective actions are taken, mainly due tothe many feedback loops the system contains,and the system, possibly after some oscillationsgoes back to its equilibrium state. In some cases,we may have a kind of stable oscillatory behavior,with oscillations around the equilibrium value.13

However, overshooting does not always leadto oscillations, possibly dampened. In somecases, it leads to persistent instability or to apossible collapse of the whole system. Actually,in conflict analysis, we are interested in thoseconditions that make a system break down,

12 Typical cases of scale-free networks that can be found in the litera-ture are the Internet web and the web of citation among scientificpublications.

13 An equilibrium may be either dynamic or stationary. In the formercase, the variable either increases or decreases, whereas in the latter,it remains approximately stable.

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 12: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

losing its stability, that is, we are interested inthreshold phenomena. An example, at leastaccording to some interpretations, is the 1967Six Days War. ‘Nasser did not intend to go towar. [. . .] His threat [the closure of the TiranStraits] was a political move to prove to fellowArabs—the Jordanians, Saudis and Syrians—thathe was still the champion of pan-Arabism andthe most radical Middle East leader. It was anexercise in brinkmanship that went over the brink(emphasis added)’ (Bregman and El-Tahri, 1998,p. 60). ‘Threshold phenomena such as violenceare difficult to study because they represent“breaks” in system rather than uniformities.Violence, whether between persons or organisa-tions, occurs when the “strain” of a system istoo great for its “strength”. The metaphor hereis that violence is like what happens when webreak a piece of chalk. Strength and strain,however, especially in social systems, are sointerwoven historically that it is very difficult toseparate them’ (Boulding, 1977).

Consider now the conflicts that often arisewithin a given society. In all societies, there arestrains, which may arise both from internal andexternal factors.14 Most often, there is equilib-rium between the strains and the resilience oradaptation capability of the society. Problemsarise when the strains overshoot the limitsbeyond which the society is unable to adapt, orthe speed of strain growth outpaces the adapta-tion capability. If that happens, the society mayenter into a phase of instability and eventuallymay collapse. Situations of this type have beenstudied by Wils et al. (1998) by means of a systemdynamics model based on the ‘Lateral Pressure’theory of Choucri and North (1975). An overviewof the model is given in Figure 6. The main idea isthat ‘the roots of conflicts can be traced to aconstellation of needs and wants of populations,given levels of technology and availability ofnatural resources. If resources are limited relativeto population demands and technology levels,the country will expand its behavior outsidenational boundaries’ (Wils et al., 1998). Here, we

will focus on the portion of the model dealingwith domestic instability and conflicts, which isdescribed in Figure 7.15 According to the model,resource scarcity and a low level of technology, inthe presence of a population growth, may lead toincreasing levels of social stress, which, over agiven threshold, may result in instability andpossibly in the onset of domestic conflict.

In the model, the variable ‘internal pressure’represents the stress the society suffers. Theinternal pressure is modelled as an increasingfunction of the population and a decreasing func-tion of both the available resources and thetechnology level of the country. Technology maybe seen as a substitute for resources, and hence,when both are scarce, it becomes increasingly dif-ficult for the society to cope with the demands ofa growing population. In the figure, two maincycles are described. One refers to the adaptationprocesses by which a society is able to cope withthe stress (due the population growth or to theresources’ depletion), reducing its value. Asecond cycle is relative to the fact that the stressmay increase the potential for conflict, eventuallyleading to domestic violence. The effect of a con-flict is again to reduce the stress. The first processis crucial: if adaptation is too slow to balance thestress growth, then the potential for conflict mayincrease until the conflict threshold is exceededwith the onset of a violent conflict. Violence hasthe effect to discharge the stress, but that requirestime, and may lead also to a situation ofprotracted instability.

The model has been implemented16 and runon two groups of countries. The first groupconsists of African countries, which have experi-enced domestic conflicts, high rates of populationgrowth and low levels of technology. The secondincludes some of the wealthier countries inEurope and North America. The results aremixed, with a various degree of consistency withthe historical records. In particular for the Africancountries, the simulation results suggest that ahigh level of internal tension may be a sufficient,but not necessary, cause for conflict. In fact, other

14 Take for instance today’s economic crisis and how it affects not onlythe living conditions in many European countries, but also the atti-tudes and perceptions about the immigrants of large sectors of thepopulations.

15 Delays are not indicated in the figure.16 Some problems concerning the quantification of the main variablesused in the model will be discussed in the next section.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 13: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

factors, not included in the model, may lead toconflicts also in the presence of low levels ofinternal tension.An important question concerns the conditions

that make a society more resilient and morecapable to adapt quickly enough to internal pres-sures. The model we have just described focusesmainly on the interplay of population, resourcesand technology. ‘[A]s population density relativeto resource base rises, societies need to changetheir technological and social base, in general

towards higher levels of complexity and sophi-stication—by devising intensified agriculturalmethods, industries, class differentiation, andsuch. High levels of population density and highlevels of technology can result in internally stablesocieties, if access to resources is assumed;conversely, low population density requires onlylow levels of technology for stability’ (Wils et al.,1998). Thus, to avoid instability, an increase inthe population density requires either a corre-spondent increase in the available resources, oran increase in the society technological level. Ingeneral, it is quite difficult for the resourcesto follow population growth: as noted byHomer-Dixon (1999, p. 42), ‘societies must beable to more social and technical ingenuity toadapt to rising resource scarcity’. This capabilityto adapt to social changes is represented by thevariable Domestic Adaptation. The outbreak of aviolent domestic conflict may be the result eitherof the society incapability to implement theneeded changes or to delays, which make itdifficult for technology change to keep pace withresource scarcity.

The presence of institutions and mechanismsthat allow for non-violent solutions of the

Figure 6 The lateral pressure model

Figure 7 Domestic conflict model

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 14: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

conflicts is fundamental to the stability of a soci-ety. This point has been investigated by Hegreet al. (2001). Making use of quantitative analysis,they show that countries with a low level of dem-ocracy (they call such countries semidemocra-cies) are less apt to absorb the social strains, andmore prone to the outbreak of violent civil con-flicts. ‘Semidemocracies are partly open, yetsomewhat repressive, a combination that invitesprotest, rebellion, and other forms of civil violence.Repression leads to grievances that induce groupsto take action, and openness allows for them to or-ganise and engage in activities against the regime.Such institutional contradictions imply a level ofpolitical incoherence, which is linked to civilconflict’ (Hegre et al., 2001). They claim that, onthe contrary, institutionally consistent democraciesand stark autocracies are equally unlikely toexperience civil war.

The recent uprising in North African countries,known under the name of Arab Spring, providesan interesting example of instability leading toregime collapse. Without the pretence to providea complete explanation of the North Africanevents, we will try to present some elements,which, at least in part, may explain such eventsas a threshold phenomenon. In 2001, the Britishmagazine The Economist published an interestingpaper by Wade (2001), an economist at theLondon School of Economics. Wade starts point-ing to the fact that ‘new evidence suggests thatglobal inequality is worsening rapidly. There aregood reasons to worry about that trend, quiteapart from what it implies about the extent ofworld poverty.’ According to Wade’s analysis,the widening income gap in the world systemmay be inherently destabilising: ‘The result is alot of unemployed and angry young people, towhom new information technologies have giventhe means to threaten the stability of the societies

they live in and even to threaten social stability incountries of the wealthy zone.’

In the analysis, there are some key elementsthat play an important role: inequalities,unemployment, age, and new information tech-nologies. In Table 1, some data relative to Tunisiaand Egypt are given (Blow, 2011). These datadepict societies with a population very young,17

with a high unemployment rate,18 a high levelof inequalities19 and a very high cost of food.20

Many young people, frustrated by unemploy-ment and lack of perspectives, angry because ofthe inequalities, with a potential for mobilisation,are strengthened by the access to modern infor-mation technologies. It is not a case that theNorth African uprisings have been called the‘facebook revolutions’. The situation thesecountries experienced is not far from the one antici-pated by Wade. In addition, both the Tunisian andthe Egyptian regimes did lack strong legitimacy. Ina sense, we may say that they were typical cases ofsemidemocracies; autocratic, but at the same timeallowing some liberties and with a relatively livelycivil society. Completely different is the case ofLibya, a strongly autocratic country without asignificant civil society, and the low penetration ofinternet confirms this fact. It is not a case thatwhereas in Tunisia and Egypt, a nonviolent popu-lar uprising was able to grow in strength andeventually topple the dictators, in Libya, onlythrough an external military intervention has theregime been ousted.

17 Consider that the median age is close to 45 in Germany, around 40 inUK and close to 37 in the USA.18 The unemployment among young people is usually much higherthan the average value.19 The Gini index is the most used inequality index; it goes from 0 to100, and higher values correspond to higher inequalities.20 Consider that the average spending on food for a US household isabout 7%.

Table 1 Social, political and economic indicators for Tunisia and Egypt

Country Median ageUnemployment

rate Gini indexSpending onfood (%) Level of democracya Internet users (%)

Tunisia 29.7 14.0 40.0 35.8 2.8 34.0Egypt 24.0 9.7 34.4 38.3 3.1 21.2aSource: the Economist Intelligence Unit’s ‘Democracy Index 2010’ (Scale of 1 to 10).

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 15: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

The analysis of these cases suggests a way torevise and enhance the internal pressure model.The new model is the one in Figure 8.Here, instead of using directly the variable

‘resources’, we introduce two variables: ‘un-employment’ and ‘inequalities, which in a senseinclude some of the information provided by’resources’. In fact, in a situation of resource scarcitynot compensated by a high level of technology,inequality and unemployment are usually quitehigh. In addition, inequality includes also the senseof injustice, which derives from an uneven wealthdistribution, which is one of the most relevantdrivers for rebellion. The variable ‘median age’ isimportant because a large number of youngpeople, unemployed and without perspectives,represent, as we have seen in 2011 in many coun-tries, both rich and poor, a strong potential forrebellion.21 In this model, technology plays adifferent role than in the preceding one. Here, wehave singled out the information technologies,which have two effects. On the one hand, theywiden the horizons of the people’s knowledge,making more striking and frustrating the distancebetween the expectations and the grim day byday life. On the other hand, they provide tool todiffuse information, to organise demonstrationand to mobilise large portion of the population.Democracy level and GDP per Capita play an

important role in the country’s resilience, that is,its capacity to provide adaptation mechanisms.Democracy provides mechanisms for dissidents toexpress themselves and to try to change peacefullythe society, whereas high levels of GDP allow forwealth redistribution through social welfaremeasures. This last is the way Saudi Arabia rulershave tried to avoid the contagion from the ‘Arabspring’ to reach their country.

MODELLING CONFLICTS AS SYSTEMS

As we have pointed out in the Introduction, thecomplexity of conflicts stems from many differ-ent and sometimes unrelated elements. Usually,a conflict involves many parties, with complex

relations between them, and with multiple anddiverse objectives, some even hidden. The sameparties, which, if we take a snapshot of theconflict at a given point in time, appear to befixed, given once and for all, evolve and changeover time as a consequence of the complex pat-tern of internal and external relations. Jacksonand Nexon (1999) criticise the substantialistapproach which is quite common in the Inter-national Relation theories, in which it ispresumed ‘that entities precede interaction, orthat entities are already entities before they enterinto social relation with other entities. The mostcommon of these presupposed entities is “thestate” [. . .] Other scholars begin with “the indi-vidual” or “the ethnic group”, but the basic onto-logical move is exactly the same—units comefirst, then, like billiard balls in a table, they areput into motion’. In today’s world, in which inter-state wars are almost completely replaced byintrastate ones, conflict’s actors are not given onceand for all, but change, split or recompose, givingrise continuously to new ones. To describe thisnew situation, the term ‘neo-medievalism’ hasbeen introduced. It can be defined ‘as a systemof “overlapping authorities and criss-crossingloyalties,”which eliminate the absolute authorityclaimed and exercised by sovereign states. [. . .]Traces of neo-medievalism can be seen intransnational organisations (both military andeconomic), which command some loyalty, terroristgroups that “privatise” international violence, theregional integration and disintegration of states,and the spread of information technology’ (Winn,2004, p. 3). Examples can be seen in the

Figure 8 Revised domestic conflict model

21 After the Middle East Arab countries, it has been the case of Greece,Spain, UK, Israel, Chile and USA.

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 16: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

disintegration of former Yugoslavia with thebloody ethnic wars that followed, and in the en-demic civil war, which characterises the Demo-cratic Republic of the Congo.

This complexity makes particularly difficultand challenging the task of conceiving and con-structing models of real-life conflicts. We identifyhere three challenges, which make hard andproblematic the task of modelling conflicts: theever changing and evolutionary characteristic ofconflicts, the elusiveness of quantification, andthe personal involvement of those who seek toanalyse—or intervene in—a conflict.

The evolutionary nature of conflicts should makeus particularly cautious when using our (mental)models to analyse (or to take decisions about)them. Reality checks are always needed to besure that the model we have constructed, or justthe model we have in our mind, is still adequateto represent the conflict’s reality. In mathematics,Taylor series expansion can be used to get a goodlinear approximation of a nonlinear functionaround a given point, but only provided we donot move too far away from that point. Similarly,the best model we can build today of a conflictmay provide good insights about the conflict’sevolution in the near future, but its validitycannot be pushed too far ahead in time. Theevolution over time of a conflict is quite unpre-dictable not only because of the necessarilylimited number of variables and relations wecan include in a model but also because of thestochastic nature of the behavior of humanagents. Even if in some cases statistical regular-ities can be found, predictability remains elusive.Sometimes the very actions we take, based onour model, make the conflict change in suchways that a new updated model is needed. Anexample is provided by the Israeli–Palestinianconflict. After the 1967 war, the conflict has beenseen mainly as a border struggle, and Israel’ssettlement policy could be interpreted as a wayto make sure that strategically and economically,relevant portions of West Bank remained withinIsrael’s borders once a final agreement were tobe reached. In fact, as stated by Menachem Klein(2010, p. 4), ‘the quantity of Israeli operationscreated a qualitative change. Israeli settlement ex-pansion and security operations since 2000 have

stripped political negotiations of nearly any valueand have returned the Israeli–Palestinian conflictto its original status—it is once again primarilyan ethnic, rather than a territorial, conflict’. Andan ethnic conflict calls for solution strategies quitedifferent from those applicable in border conflicts.

The problems connected with the elusiveness ofquantification in many real life problems havebeen discussed within the system dynamicscommunity for quite some time. The disciplineof system dynamics (which is at the base of mostof the models discussed so far in the paper) ‘haslong been based on the building of fully specifiedquantitative models of strategic problems in allmanner of domains. Such models were, and are,seen as the essential means by which insightsmight be generated into policies to improvesystem behavior’ (Coyle, 2000). Although quanti-fication remains a cornerstone in system dynam-ics, the idea that qualitative models may be aneffective tool to analyse and understand complexproblems and issues, and to develop robuststrategies for dealing with them, has been onthe fore since the early 1980s (Wolstenholme,1983, 1999; Coyle, 1998, 2000).22 The quantitativeversus qualitative issue is of particular relevancein conflict modelling. With reference to a modelof the Angolan conflict he had developed, Coyle(2000) states that ‘Given the number of uncertain-ties and their immensity, not to mention theplethora of competing parties and interests, it ishard to avoid concluding that quantification’would not even be plausible nonsense; worse,‘it would be verging on science fiction’. Some-thing like that can possibly be said for each ofthe system dynamics models mentioned in thispaper. Based on these, and also on other modelsnot referred to here, we claim that rigorous quali-tative modelling can provide useful insights inthe dynamics of real life conflicts, and may beof great help in decision making, but more, thatin most cases, qualitative modelling is the onlymeaningful option when dealing with conflicts.

An interesting exception among the modelscited in this article is the lateral pressure model

22 A page dedicated to Qualitative System Dynamics can be found inthe website of Jay Forrester (http://jayfor.site.aplus.net/qualsd/index.html).

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 17: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

presented by Wils et al. (1998). It is a modelthat the authors have quantified and run onreal world data, obtaining meaningful results.Nevertheless, also this model does not escapethe quantification difficulty. For instance, thevariable ‘technology’ present in the model is veryhard to operationalise and in any case almostimpossible to quantify. The authors try to goaround this problem by using GDP as a proxy,but that introduces in the model an implicit andunwanted loop. In fact, in the model, technologyinfluences the GNP, which is strongly correlatedto GDP, and for countries, such as Rwanda, oneof the model test beds, almost coincides with it.Easier to define, but not less difficult to quantifyis the variable ‘natural resources’. The authorsstress that their use of resource availability ‘refersto a multi-faceted notion—it consists of land area,quality of land, mineral and fossil-fuel reserves,water quantity and quality, and many otheraspects. [. . .] Unfortunately, of these variables,only total land and the value of mineral reserveswere found in consistent form among global datasources’. At the end, considering also the diffi-culty of combining these two variables, theydecided to use one single variable, the total landavailable for agriculture, as a proxy for naturalresources. That implies, for instance, disregard-ing the combined effects on the quality of theland of climate changes, population growth andoverexploitation, something not irrelevant asshown among others by Diamond (2004). In spiteof this rather strong simplification, as the authorsstate, the ‘study has provided some usefulinsights as to the leverage points in the systemof society demands, resources, and conflicts thatmight lead to a more peaceful future’.A third option between fully qualitative and

quantitative models is represented, among others,by the rebellion–repression model of Kress andSzechtman (2009), which combines intelligence,attrition and popular support for the insurgency.By means of a mathematically rigorous analyt-ical study of the differential equations involved,considering different scenarios and differentpossible values of the main parameters, theyshow ‘why it is almost impossible to eradicateinsurgency by force only’, concluding that ‘softactions such as civil support and psychological

operations, that affect the attitude of the popula-tion, may be needed too. This conclusion is quitegeneral and robust; it does not depend on thespecific parameters of a particular insurgencysituation, but on general assumptions regardingtheir characteristics.’ The works of Muncaster andZinnes (1982, 1990), Zinnes and Muncaster (1984)and of Blank et al. (2008) go along a similardirection, from a methodological point of view.This type of approach can be traced back to theseminal work of Richardson (1935, 1993).

The challenge posed by the personal involvementof those who seek to analyse a conflict, is some-thing the system thinking community has beenaware of since the early times. We know verywell that systems are not the reality. They aresocial constructs, logical conceptual constructions,which depend on our culture and perspectives.This is particularly true in the case of conflicts,where our political and ethical beliefs, and some-times our deep feelings, enter into the picture,and may have a profound effect on the type ofmodel we build, on the boundaries we choose, onthe master variables we select, and on the overallmodel’s structure. Take for instance the alreadycited paper by Pinzón and Midgley (2000). In thispaper, the authors are concerned with theproblem of evaluating the results of differentapproaches to conflict modelling. They discussthe philosophical and ethical implications of alter-native approaches to conflict analysis, stressing theimportance of the holistic/systemic paradigm,which they apply to the Colombian civil war.With reference to this conflict, they show howreductionist approaches, concentrating only onthe active actors on the two sides (Government,guerrilla organisation, . . .), quite often disregardthe population, that is the people who most sufferfrom the conflict, and how that rises relevantethical question. The approach of Ellis (2004) iscompletely different and quite reductionist. Hissystem dynamics model of Colombian civil waris mainly focused on the interactions among theguerrilla organisations, the criminal organisations,the economic base of the Colombian society and itsGovernment. Not only in his model is there noroom for the population and for the social rootsof the armed insurgents, but his approach isstrictly framed within the mainstream western

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 18: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

‘security discourse’. Drug cartels, terrorist cells andinsurgent groups are placed in a single basketwith-out really differentiating among them, their activityis seen as a kind of ‘geopolitical virus’ which may‘destabilise the region and undercut the basis forUS global power’, and reference is made to the ‘ac-tivity of anti-US Islamic groups’, a must in post 09/11 security discourse, even when talking of LatinAmerica.

While in Pinzón and Midgley’s approach awide perspective is adopted in which individualsare seen not only in themselves, ‘but also asmembers of a community, a culture, an epochand, in general, the contexts in which our livesgo by’, and ‘Ethics, which implies concern forthe other ’, is taken as a basic element, in Ellis’there is apparently no place for the people andcommunities involved in the conflict, nor forethical considerations. The only concern is thegeopolitical effects of the conflict. We can findsimilar contrasts in the other studies of systemicmodels of insurgency, repression and guerrillawarfare. Some of them are mainly focused onthe tactical aspects of counter insurgency warfare(Coyle, 1985, 2000). Others are concerned withthe complex dynamics which in a society leadto the birth and growth of rebellion activities(Gurr, 1994, 2000; Ackam and Asal, 2005). Thatreflects the different objectives of the models,but also, more generally, the different cultural,political and ethical perspectives of the authors.

CONCLUSIONS

Conflicts are very complex and defy the lineartype of thinking, which is too often used in theiranalysis and, no less relevant, when decisionsabout them are taken. This is particularly truetoday when conflicts are very often intrastaterather than interstate (see Ramsbotham et al.(2005)), and when the state power is losingground to other powers both at supranational/transnational level and at regional/local level.

In this paper, by means of several examples,we have tried to show how important the roleof systems thinking and modelling may be inconflict analysis. Models are learning tools,

which may effectively help in taking decisionsabout conflicts and in operating to prevent theonset of violence or to reduce it when the conflicthas already started.

We have spent some time on the concept ofemergent property of a system, using an interest-ing example from the Iraq war. The conditionsthat make a system unstable and eventuallycollapse have also been discussed with referenceto domestic conflicts. On this last topic, on thebasis of the experience of the 2011 North Africauprisings, a possible extension and enhancementof the classical Internal Pressure model has beenbriefly sketched. This extension, which is at avery preliminary stage, constitutes the object offuture research. In the last section, some issuesthat make conflict modelling especially criticaland problematic are discussed. They relate tothe evolutionary characteristics of conflicts, therelative merits of qualitative and quantitativemodels, and the problematic neutrality of themodeller.

We have tried to apply several standardsystem thinking tools to the analysis of conflicts.But at the same time, through the different exam-ples presented, we have shown the peculiaritiesthat make conflicts somehow different from othersystems. This raises some interesting and challen-ging questions. For instance, most of the system‘archetypes’ used as modelling tools are derivedfrom management. Are there ‘archetypes’ morecapable of capturing the peculiarities of conflicts?The answer to such a question might be the objectof further research.

ACKNOWLEDGEMENTS

The author is indebted to Steve Shore for his care-ful reading of the paper. His valuable commentsand criticisms have been the occasion for a dee-per analysis and understanding of some of theissues discussed in the paper, and have been ofgreat help in improving its quality. The authorwants also to thank Valentina Bartolucci for themany inspiring discussions on conflict analysisduring the last year when a course on ConflictTheory was jointly taught.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo

Page 19: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

REFERENCES

Ackam BK, Asal V. 2005. The dynamics of ethnicterrorism. Presented at the System DynamicsConference.

Alvarez-Ramirez J, Rodriguez E, Tyrtania L, Urrea-Garcia GR. 2010. Regime-transitions in the 2003–2010 Iraq War: an approach based on correlationsof daily fatalities. Peace Economics, Peace Scienceand Public Policy 16(1), article 11.

Arquilla J, Ronfeldt D. 2001. Networks and Netwars: TheFuture of Terror, Crime, and Militancy (1st edn). RandCorporation.

Barabási A-L, Albert R. 1999. Emergence of scaling inrandom networks. Science 286(5439): 509–512.

Bartolucci V, Gallo G. 2010. Operations research/management science contributions to peace studies.International Transactions in Operational Research 17(4):475–483.

Blank L, Enomoto CE, Gegax D, McGuckin T,Simmons C. 2008. A dynamic model of insurgency:the case of the War in Iraq. Peace Economics, PeaceScience and Public Policy 14(2). Retrieved fromhttp://www.degruyter.com/view/j/peps.2008.14.-issue-2/peps.2008.14.2.1120/peps.2008.14.2.1120.xml

Blow CM. 2011. The kindling of change. The New YorkTimes. Retrieved from http://www.nytimes.com/2011/02/05/opinion/05blow.html?_r=4&ref=char-lesmblow [4 February 2011].

Boot M. 2003. The New American Way of War. ForeignAffairs.

Boulding K. 1977. Twelve friendly quarrels with Johangaltung. Journal of Peace Research 14(1): 75–86.

Bregman A, El-Tahri J. 1998. The Fifty Years War. Israeland the Arabs. Penguin Books.

Byman D. 2011. A High Price: The Triumphs and Failuresof Israeli Counterterrorism. Oxford University Press:USA.

Choucri N, Goldsmith D, Madnick S, Mistree D,Morrison JB, Siegel M. 2007. Using System Dy-namics to Model and Better Understand StateStability (No. 4661–07). MIT Sloan School ofManagement.

Choucri N, North RC. 1975. Nations in Conflict: NationalGrowth and International Violence. Freeman.

Coyle G. 1985. A system description of counter insur-gency warfare. Policy Sciences 18: 55–78.

Coyle G. 1998. The practice of system dynamics: mile-stones, lessons and ideas from 30 years experience.System Dynamics Review 14: 343–365.

Coyle G. 2000. Qualitative and quantitative modellingin system dynamics: some research questions.System Dynamics Review 16: 225–244.

Coyle G. 2004. Practical Strategy: Structured Tools andTechniques. Pearson Education.

Diamond J. 2004. Collapse: How Societies Choose to Fail orSucceed (1st edn). Viking Adult.

Ellis RE. 2004. The impact of instability in Latin andSouth America. Engineering in Medicine and BiologyMagazine, IEEE 23: 187–193.

Gallo G, Marzano A. 2009. The dynamics of asymmet-ric conflicts: the Israeli-Palestinian case. Journal ofConflict Studies 29: 33–49.

Galtung J. 1996. Peace by Peaceful Means. Sage.Gurr TR. 1994. Peoples against states: ethnopolitical

conflict and the changing world system. InternationalStudies Quarterly 38: 347–377.

Gurr TR (ed.). 2000. Peoples Versus States: Minorities atRisk in the New Century. United State Institute forPeace: Washington, DC.

Hegre H, Ellingsen T, Gates S, Gleditsch NP. 2001.Toward a democratic civil peace? democracy,political change, and Civil War, 1816–1992. TheAmerican Political Science Review 95(1): 33–48.

Homer-Dixon TF (ed.). 1999. Environment, Scarcity andConflict. Princeton University Press.

Jackson PT, Nexon DH. 1999. Relations before states:substance, process and the study of world politics.European Journal of International Relations 5(3): 291–332.

Kaplan EH, Mintz A, Mishal S. 2006. Tactical pre-vention of suicide bombings in Israel. Interfaces36: 553–561.

Klein M (ed.). 2010. The Shift. Israel-Palestine from BorderStruggle to Ethnic Conflict. Hurst & Company:London.

Kress M, Szechtman R. 2009. Why defeating insurgen-cies is hard: the effect of intelligence in counterinsur-gency operations – a best-case scenario. OperationsResearch 57(3): 578–585.

Marshall MG. 1999. Third World War. System, Process,and Conflict Dynamics. Rowman & LittlefieldPublishers, Inc.: Oxford.

Midgley G. 2000. Systemic Intervention: Philosophy,Methodology, and Practice. Kluwer Academic.

Muncaster RG, Zinnes DA. 1982. A model of inter-national hostility dynamics and war. Conflict Man-agement and Peace Science 6(2): 19–37.

Muncaster RG, Zinnes DA. 1990. Structure andhostility in international systems. Journal of TheoreticalPolitics 2(1): 31–58.

Pappe I. 2004. A History of Modern Palestine – One Land,Two Peoples. Cambridge University Press.

Pinzón L, Midgley G. 2000. Developing a systemicmodel for the evaluation of conflicts. SystemsResearch and Behavioral Sciences 17: 493–512.

Ramsbotham O, Woodhouse T, Miall H. 2005. Contem-porary Conflict Resolution. Polity: Cambridge.

Richardson LF. 1935. Mathematical psychology of war.Nature 135: 830.

Richardson LF. 1993. The Collected Papers of Lewis FryRichardson: Vol 2 –Quantitative Psychology and Studiesof Conflict. Press Syndicate of the University ofCambridge.

Rogers P. 2011. A War Gone Badly Wrong – The War onTerror Ten Years On. Oxford Research Group.

Syst. Res. RESEARCH PAPER

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Conflict Theory, Complexity and Systems Approach

Page 20: Conflict Theory, Complexity and Systems Approach · Conflict Theory, Complexity and Systems Approach† Giorgio Gallo* Computer Science and Interdisciplinary Center ‘Sciences

Shlaim A. 2001. The Iron Wall: Israel and the Arab World.W.W. Norton.

Sterman JD. 2000. Business Dynamics. System Thinkingand Modeling for a Complex World. McGraw-Hill.

Wade R, 2001, April 26. Winner and losers. The Economist.Waltz KN. 2003. Giants and pygmies. Foreign Affairs,

(September/October 2003). Retrieved from http://www.foreignaffairs.com/articles/59196/kenneth-n-waltz/giants-and-pygmies [1 September 2003].

Wils A, Kamiya M, Choucri N. 1998. Threats to sus-tainability: simulating conflict within and betweennations. System Dynamics Review 14(2–3): 129–162.

Winn N. 2004. New forms of political organisation,community, sovereignty and identity: civil wars,

the new diplomacy and international relations. InNeo-Medievalism and Civil Wars. Frank CassPublishers.

Wolstenholme EF. 1983. The development of systemdynamics as a methodology for system descriptionand qualitative analysis. The Journal of the OperationalResearch Society 34: 569–581.

Wolstenholme EF. 1999. Qualitative vs quantita-tive modelling: the evolving balance. TheJournal of the Operational Research Society 50(4):422–428.

Zinnes DA, Muncaster RG. 1984. The dynamics ofhostile activity and the prediction of war. Journal ofConflict Resolution 28(2): 187–229.

RESEARCH PAPER Syst. Res.

Copyright © 2012 John Wiley & Sons, Ltd. Syst. Res. (2012)DOI: 10.1002/sres.2132

Giorgio Gallo