Chapter 5



The Effect of Competition on Terrorist Group OperationsStephen NemethDepartment of Political Science244 Waters HallKansas State UniversityManhattan, KS 66506snemeth@k-state.edu Abstract: Scholars have long accepted the contention that competition amongst terrorist organizations raises the level of violence used by the competitors (Crenshaw, 1981, 1985, Oots, 1989; Bloom, 2004, 2005; Chenoweth, 2010). This paper discusses this claim and advances another – that competition amongst terrorist organizations creates incentives to use less violence. Using insights from the organizational ecology literature - namely that competition occurs within “species” – I create a variable that assesses intra-species competition. I test both claims using a dataset of domestic terrorism created from the Global Terrorism Dataset for the years 1970-1997. I find support for the hypothesis that competition leads to more terrorism, validating the claims of outbidding theorists. Furthermore, ideologies have differential effects on whether outbidding occurs, with nationalist and religious terrorist groups responding to competition with more terrorism and left-wing organizations responding with less. The idea that competition amongst terrorist organizations results in a number of negative outcomes, such as suicide terrorism, civilian targeting, and extreme violence has become a powerful and persuasive idea in the terrorism literature (Crenshaw, 1981, 1985; Oots, 1989; Bloom, 2005; Chenoweth, 2010). Organizations, vying for the attention of recruits or for the support of wavering adherents, use escalating levels of violence, or “outbidding” as a means to demonstrate their commitment and capability (Bloom, 2005). This violence can also be turned against competing organizations, rendering the states most likely to be fertile grounds for terrorism the most dangerous for terrorist organizations (Oots, 1989). The outcome of this process is likely to have an indelible mark on affected states; competition acts to legitimize more violence, encourage violence against civilians and, in some cases, to encourage the use of suicide terror (Bloom, 2005). Intuitively, this perspective has great appeal. Organizations that can demonstrate their ability through continued and notable violence are advantaged in both recruitment and group maintenance (Crenshaw, 1985; Post et al., 2003). Recruits are drawn to the organizations which have the most selective incentives to offer, with the opportunity to participate in violent activity forming a primary motivation (Crenshaw, 1985). Group cohesion and retention is increased because violence and the number of operations performed help “build morale within the membership through the experience of cooperative operations” (Waugh, 1983: 9). Violence is currency in this perspective – groups that are the most adept in its use ensure their survival, develop into capable adversaries of the state, and become increasingly able to achieve their political goals. At the same time, the argument is one of nuance. For Bloom (2005), the type of violence characterized by outbidding only flourishes and resonates in particular situations. Organizations that engage in suicide terrorism, or excessive levels of violence, in the incorrect environment fail to win public support and potentially endanger the organization. The terrorism literature is replete with accounts of groups miscalculating the amount of violence a populace was willing to accept (see Ross and Gurr, 1989; Cronin, 2006). In such cases, violence has played a negative role in the development of the organization, leading to less recruiting success, reduced public support, and the decline, if not the dissolution, of the group. This paper seeks to address why competition leads to more terrorism in some cases and less in others. Like Bloom (2005), I forward that two factors - government policy and social acceptability – determine whether outbidding actually occurs. In areas where those factors are present competition leads to outbidding. Areas with competition that are absent those factors will not demonstrate outbidding behavior. In fact, competition in such states may actually lead to less terrorism. This insight distinguishes Bloom’s (2005) discussion of outbidding from earlier ones (Crenshaw, 1981, 1985; Oots, 1989). I test this contention using cross-national domestic terrorism data from the Global Terrorism Dataset (GTD) for the years 1970-1997. Second, I test these claims using an improved operational definition of competition. Building upon the organizational ecology literature, I develop a measure of competition that is “species” specific (Lowery and Gray, 1995). This means that competition is restricted to groups of a similar type; in this case, competition is restricted to groups that share a similar ideology. This lets us avoid treating two very different concepts the same way: the absolute number of terrorist organizations and the density of the organizational environment. By constructing an indicator using the latter, we achieve a closer association between measure and reality (Post et al., 2003) The paper is composed as follows: In the next section, I discuss the various ways that competition may affect terrorist organizations. I highlight Bloom’s (2005) theory of outbidding and the factors that make it possible. I follow with a discussion of the relationship between competition and terrorism when those factors are not present and how, in those circumstances, competition may reduce terrorism. The section ends with the discussion of the hypotheses that stem from the theory. In the third section, I discuss the data and coding rules. I emphasize the organizational ecology literature to create a measure of terrorist organizational competition independent of the total number of terrorist organizations that reside within a state. The fourth section presents empirical tests of the hypothesis. The fifth section concludes. THE FACETS OF COMPETITIONWhile outbidding has become the dominant perspective relating competition to terrorism, the possibility exists that competition can also have a negative, rather than a positive effect. One of the most prominent of these alternatives is that of backlash – groups select a target or engage in violence that reduces the support of previously sympathetic population, thus reducing the flow of resources and the ability of the organization to carry out attacks (Ross and Gurr, 1989; Cronin, 2006). At the same time, competition may also lead to a reduction in violence if it leads to cooperation between two terrorist organizations or if it acts to reduce the capacity of the competitors. These alternatives stand in contrast to the outbidding perspective, yet neither these alternatives nor the outbidding perspective have been subject to quantitative analyses (although see Chenoweth, 2010). Before these perspectives are tested, I discuss them in detail below. OutbiddingThe outbidding perspective arises from the realization that dual pressures exist within all terrorist organizations. Terrorist leaders, “must cope with a constant tension between their desires to preserve the organization and the membership’s desire for action” (Crenshaw, 1985: 476). Early theories of outbidding posited that competition solely affected these two factors (Crenshaw, 1985; Oots, 1989). Later theories, notably that of Bloom (2004, 2005), sees competition leading to outbidding when external conditions – the acceptability of violence and government policy - are favorable. The first theory of outbidding sees competition contributing to the collective radicalization of the terrorist organization (Crenshaw, 1985). Groups facing competition from a more extreme competitor typically radicalize and engage in more violence to prevent the defection of members to the competitor organization. The adoption of terrorism by the Official IRA in response to the same decision by the Provisional IRA is indicative of this type of outbidding logic (Crenshaw, 1985; Moloney, 2010). In the Palestinian areas, the adoption of suicide terror by secular groups after its use by fundamentalist organizations may be another example. Secondly, Crenshaw (1985) suggests that outbidding may occur when competition, and the threat of member exit, leads members to fight harder to validate their investment in joining the organization. The decision to join a terrorist group entails a sacrifice and a distinct change in lifestyle; Wolf (1978: 176) depicts the life of a terrorist as one “characterized by the lack of comfort, the absence of expendable income, and the denial of leisure activity and personal privacy”. As a result, the high personal cost endured by members makes activity their only sustenance and identity. Increased action therefore, is a logical result of individuals seeking to ensure their choices to engage in terrorism are justified (Kellen, 1979; Crenshaw, 1985). The failure of the Israeli-Palestinian peace process in the late 1990s and the subsequent rise in suicide terrorism provided the main impetus for the most recent incarnation of the outbidding theory (Bloom, 2005). The increase of the use of suicide terror, and the support groups received for their actions soon created an environment where all groups had to engage in spectacular acts of violence. The logic of this theory is simple and persuasive - “if multiple insurgent groups are competing for public support, bombings will intensify in scope and number as they become both the litmus test of militancy and the way to mobilize greater numbers of people within their community” (Bloom, 2005: 78). This is known to be effective; Jerrold Post and his research team found that nearly 60 percent of members in secular groups and 43 percent of religious group members admitted to joining the most active terrorist organization in their community (2003: 173). This theory does differ from its predecessors. For Bloom (2005), outbidding requires that the environment be able to support a group’s decision to engage in extreme violence. In the case of the Israeli-Palestinian crisis, outbidding was successful because the ongoing conflict, the collapse of the peace process, and the ineffectiveness of the Palestinian Authority created an atmosphere of hopelessness that both spurred the creation of terrorist organizations and legitimated terrorism, particularly suicide terrorism. The newfound acceptability of this tactic became the mark by which all organizations were judged, setting off the cycle of outbidding. Support for suicide terrorism increased quickly after these occurrences, reaching upwards of 85 percent in October 2001 from lows of 24 and 33 percent during the period from 1997 to 1999 (Bloom, 2005: 193). In Sri Lanka, another of Bloom’s (2005) case studies, outbidding arose for largely the same reasons. The Tamil history with the Sri Lankan government had been marked by political futility and communal violence at the hands of the majority Sinhalese. As a result, Tamil quality of life had changed little since Sri Lankan independence. This status quo led to the acceptance of terrorism as a political tactic and, moreover, to the creation of a number of Tamil separatist groups, one of which was the Liberation Tigers of Tamil Eelam (LTTE). As a result, the violence that resulted was similar in origin to the Palestinian territories – groups competed with one another for support within an atmosphere that accepted this kind of violence. Unlike the Palestinian case, the acceptability of terrorism began to wane in Sri Lanka. The LTTE had used violence to great effect; it struck at the Sinhalese, moderate Tamils, and its competitors to become the predominant organization pressing for Tamil separatism. By 2001, the long-running conflict between it and the Sri Lankan government has sapped the will of the organization’s supporters, driving it to negotiations with the government. By the time of Bloom’s analysis, Tamil hopefulness for peace and the end of competition between the various Tamil organizations had largely ruled out the use of suicide terrorism as a tactic. This perspective has led to some quantitative work – most notably that of Chenoweth (2010). In this work, she argues that intergroup competition explains why democracies experience more terrorist activity than non-democracies. She finds support that transnational terrorist incidents and domestic terrorist organizations are more likely to originate in competitive polities. While her analysis does provide some validation of Bloom (2005), it is not a test of terrorist competition per se. Instead, competition between terrorist organizations is subsumed into a larger measure of political competition. States may, in fact, have high levels of terrorist competition while having little political competition. Competition is also assumed to occur across the terrorist group system. The assumption here is that resources and recruits are indifferent about which organization they are directed to as long as they are directed to the most active one. I discuss the potential drawbacks to this approach, particularly in the context of the organizational ecology literature, in the methods section. Competition and ModerationWhile Bloom’s (2005) theory provides an excellent explanation of terrorist competition and its outcomes in those areas which include both components, it is important to consider what the effect of competition may be when either of those two conditions is absent. First, competition may raise the cost of action; civilians see outbidding as escalating savagery rather than meaningful attempts for political change, driving civilians away and increasing the risk of backlash (Ross and Gurr, 1989). Second and relatedly, this cycle of violence may serve as an implicit government counterterror policy. Internecine struggles amongst terrorist organizations may drain groups of resources and recruits, decreasing the efforts needed by incumbent governments for counterterrorism. These considerations may lead to the observation that competition may lead to less, rather than more, violence. The possibility of backlash is a major risk of outbidding in an incorrect environment. Groups have frequently miscalculated the effects of their violence and triggered this response. Cronin (2006) points out the Popular Front for the Liberation of Palestine – General Command (PFLP-GC) and ETA as two groups amongst many that have engendered condemnation for their actions. In the context of outbidding, the Omagh bombing in August 1998 can be seen as a major contemporary instance of backlash occurring from competition –between the Real Irish Republican Army, the perpetrators, and the Provisional Irish Republican Army (Dingley, 2001). The deaths of 29 civilians from the attack, precisely during the Northern Ireland peace process, led to a denunciation of the perpetrators from every political party in Northern Ireland, Ireland, and Great Britain. Moreover, group support from individuals within the United States waned and support for the then-recently signed Good Friday agreement increased (Dingley, 2001). Lastly, competition and outbidding may be damaging because it works to inadvertently advance the state’s agenda rather than the terrorists’ goals. In Sri Lanka and Turkey, the government either funded a favored terrorist organization or turned a blind eye to intergroup violence in the hopes that the organizations would eliminate, or greatly weaken, each other (Bloom, 2005). The extent to which groups may be concerned with this problem is unknown. However, the decision of the PKK and Turkish Hezbollah to abandon intergroup conflict in favor of jointly fighting the government may indicate that groups have some realization of the dangers of conflict with one another (Bloom, 2005). These concerns all contribute to a number of mechanisms which may lead to competition causing less violence. Groups may first simply try to avoid backlash by changing the nature and number of their attacks. This is especially evident if we consider the level of public support as relatively fixed; each increase of an additional organization reduces each group’s potential allocation of support. Given the assumption that using outbidding violence results in a net gain of organizational support for the organization, the use of this strategy in competitive situations ultimately results in each group gaining a pool of supporters that does not compensate for the loss of members. Instead, this should lead to the formation of coalitions - a rare occurrence (Crenshaw, 1985; Oots, 1989) - or the moderation of violence. An additional explanation for why competition may lead to less violence may lie in the work of Lewis Coser (1956). He argued that external conflict can result in cohesion within groups or the creation of coalitions, or at least elements of cooperation, amongst different groups. In terms of this analysis, the increased attention brought to groups by competition can lead to elements of coordination, or even cooperation, between the competitors. Bloom (2005) noted that both the Kurdish Workers’ Party (PKK) and Turkish Hezbollah, when confronted with government attention, abandoned outbidding to adopt a campaign of violence directed against the Turkish government. Brym and Araj (2008: 493-495) note that Israeli action had even pushed both Hamas and Fatah into situations of tactical cooperation. In both cases, the number of terrorist events perpetrated by these groups was lower after coordination than they were prior.The two perspectives regarding terrorist group competition provide contrasting hypotheses about their effect on group operations. They are presented as follows:Hypothesis 1: Groups in competitive and favorable environments will commit more terrorist acts than groups in non-competitive and non-favorable environments.Hypothesis 2: Groups in competitive and favorable environments will commit less terrorist acts than groups in non-competitive and non-favorable environments. DATA AND METHODSIn order to analyze the relationships discussed here, I use the Global Terrorism Dataset (GTD) from the National Consortium for the Study of Terrorism and Responses to Terrorism (START) at the University of Maryland. The dataset includes 81,800 acts of domestic and international terrorism occurring in 180 states spanning the years 1970-2007. The GTD provides a remarkably flexible platform for two reasons. The first is that its definition of terrorism is quite broad, referring to terrorism as “the threatened or actual use of illegal force and violence to attain a political, economic, religious, or social goal through fear, coercion, or intimidation” (LaFree and Dugan, 2007: ii). The definition, absent references to targets and referring to a variety of goals and mechanisms, allows researchers to create their own definitions and circumvents the contentious issue of having to use an established definition of terrorism (Schmid and Jongman, 1988; Hoffman, 1998; Silke 2004). Second, the GTD contains a wide variety of perpetrators of terrorist violence. Well-defined organizations such as Hamas, Al-Qaeda, and the Tupamaros are included along with actors such as political parties, student protesters, and rebels. This also provides flexibility by allowing researchers to focus on interests ranging from crime to social movements. Since the analyses regard the effects of competition on group behavior, I use the group-state/year as the unit of analysis. This distinction, rather than group-year, accounts for the behavior of the same group in different states, such as Karen National Union in Myanmar versus its branch in Thailand. The repressive environment in Myanmar is likely to exert a different effect on group behavior than the somewhat more permissive environment in Thailand. Second, this also accounts for differing levels of competition within the same state. A state may have a competitive atmosphere regarding left-wing groups, but a relatively monopolistic environment regarding groups on the right. Accounting for competition as a state-wide phenomenon is likely to eclipse the effect of the substantial range of terrorist ideologies that are contained within a state. This distinction and ideological competition are discussed in more detail below. I also restrict my analyses to cases of domestic terrorism. This is important not only because domestic terror is more prevalent than international terrorism (Rosendorff and Sandler, 2005), but because analyses that focus solely on international terrorism or combine the two may lead to incorrect conclusions because they will be biased towards large states and certain highly capable groups (Abadie, 2006). In terms of competition, international and domestic groups are likely to face different pressures. Groups operating domestically have to rely on resources within the country – meaning that their practices are likely to be heavily driven by their public support. This means that factors such as competition, as well as the acceptability of violence and government policy, are likely to show a direct impact on the amount of terrorism a group perpetrates. An international group, on the other hand, does not face the same pressure. Instead, the international group can circumvent factors at the target state and go back to its home base to get the needed resources. Competition, then, should have very little to do with international group behavior; in fact, Siqueira and Sandler (2006) state that groups with outside sponsors, particularly international groups, are likely to face little restraints on the type of violence they use. I create this distinguishing coding rule by noting the attack location and perpetrating group in the GTD. This is then compared to the available group record in the START Center’s Terrorist Organizational Profiles (TOPS) database. If the location of the attack in the GTD coincides with a known operating area for the terrorist organization in the TOPs data, the event is marked as domestic terror. The process of distinguishing international from domestic terror is illustrated in Figure 1. [Figure 1 Here]The final dataset contains 31,364 acts of domestic terror perpetrated by 459 terrorist organizations. This number is comprised of 429 individual groups plus 30 “franchises”. These attacks are then aggregated by group-state/year to create a dataset of 2,131 group-state/years with terrorist attacks. Using the start and end-dates of terrorist activity from the TOPS database, I fill in all non-terror years (years the group was active but not engaged in terrorist attacks) with zeros. The final dataset that results includes 8,217 group-state/years. Dependent VariableThe dependent variable used in this analysis is a yearly count of the number of domestic terror attacks committed by each individual terrorist organization. Attacks are included in the dataset if they are intentional, involve a use of violence or a threatened use of violence, and the actors are sub-national (START, 2009: 4-5). Attacks must also fulfill two of three additional criteria for inclusion: the act must be directed towards a political, economic, religious, or social goal, there must be evidence of an intent to coerce, and the action must be outside of the realm of legitimate military activities (START, 2009: 4-5). Lastly, to reduce bias that may result from overemphasizing capable organizations, I follow Maoz (2007) and include failed acts of terrorism. Independent VariableTo assess the effects of group competition, I use the inverse of the Herfindahl-Hirschman Index (HHI) as my main independent variable (Herfindahl, 1950; Hirschman, 1945). The HHI was originally conceived as a way to assess the concentration of firms in a marketplace. Used in this capacity, it has since its inception become a central component in economic analyses; both the Justice Department and the Federal Reserve use it to evaluate the market impact of potential mergers (Hannan, 1997; Rhodes, 1993). One of the advantages of this measure, as opposed to other means of determining competition, is that it provides a measure that is invariant to the number of competitors. For example, there may be several firms in a market that create a particular good, yet the market share of one may create an environment where little competition actually exists. Similarly, the presence of several terrorist groups may not indicate a truly competitive environment, especially if one is clearly more capable and more noteworthy than the rest. The ability of the HHI to account for this potential asymmetry is widely touted as one of the strengths of the measure (Calkins, 1983). The HHI is calculated as: i=1NSi2Where Si is the market share of firm i and N is the number of firms in the market. To determine the number of firms in the market, I adopt the concept of “competitive exclusion” from the organizational ecology literature (Lowery and Gray, 1995). This states that competition is a function of the resources that one draws from: groups will only compete with other groups that draw on the same resource (Lowery and Gray, 1995). For Lowery and Gray’s (1995), this meant competition amongst interest groups occur within similar advocacy markets. Farm advocacy groups are distinct from business groups and, as such, are only likely to face competition from other farm groups. As a result, their analysis focuses on “species-guilds” – “sets of organizations representing related interests” (1995: 9). I conceptualize the same for terrorist organizations: each state has a certain number of ideological “markets” in which recruits and resources are sought and competition is bounded. Communist terrorist organization should face competition from groups with similar ideological goals, not dissimilar ones. Secessionists have their needs best served from a nationalist, rather than a religious, organization. Post et al. (2003: 173) notes terrorist recruitment occurring within these lines: “individuals from strictly religious Islamic backgrounds were more likely to join Islamist groups, while those who did not have a religious background might join either a secular or religious group.” Using this insight, I use the RAND Corporation’s End of Terror dataset (Jones and Libicki, 2008) to classify each state as having four potential ideological “markets” - nationalist, religious, left-wing, and right-wing. To determine the number of “firms” in each of these “markets”, I sum for each state/year the number of other groups that exist within each of the four ideological categories. Market share is then determined by the percent of attacks committed per state/year by each group within each market. This best corresponds to the insight that members stay in and recruits join the most active organizations (Crenshaw, 1985; Oots, 1989; Post et al., 2003). These two values are used to calculate the HHI for each ideological category for every state-year. The use of the inverse of the HHI follows Taagepara and Shugart (1989) and allows for a more readily interpretable variable – scores near 1 indicate a condition of monopoly while higher scores indicate competitive environments. If the outbidding argument is correct, high values of this variable will be associated with more total attacks. If the moderation perspective is correct, low values will be associated with more attacks. [Figure 2 Here]Figure 2 plots the average level of organizational competition for the ten states with the highest number of domestic terrorist attacks. Bars of one unit length indicate a condition of monopoly while longer bars indicate progressively more competitive environments. The colors indicate terrorist ideology as determined by the RAND End of Terror Dataset (Jones and Libicki, 2008). The results from the chart appear to accord with our understanding of terrorism. Colombia appears to offer an extremely competitive environment for left-wing groups while France and the UK offer competitive arenas for nationalist terror organizations. It is also interesting to note that high number of uncontested categories; most of the top victimized states are characterized by relatively monopolistic ideological categories. This finding, with the three caveats mentioned above, contrasts with Bloom’s (2005) outbidding theory. The three exceptions accord well with our understanding of terrorism in those states. The high score for left-wing groups in Colombia indicate an environment where the success of organizations such as the Revolutionary Armed Forces of Colombia (FARC) and the National Liberation Army (ELN) gave rise to smaller organizations such as the Guevarista Revolutionary Army and the Popular Liberation Army. In France and the UK, the high level of competition occurs due to groups engaged in struggles for Basque, Corsican, and Northern Ireland separatism. Figure 3 plots the average level of competition by regime type over the time period of the GTD dataset. These are calculated from the Polity IV dataset using the Polity2 measure (Marshall et al., 2009). States with Polity2 scores at 6 and above are coded as democratic and those below 6 are coded as autocratic. Figure 4 plots competition by regime type using a trichotomous classification between autocracy, anocracy, and democracy. The coding rule for democracy and autocracy remain the same. The middle categorization, anocracy, is coded by Polity2 scores ranging from -5 and 5. [Figures 3 and 4 Here]Results indicate that democratic states are more competitive than their autocratic counterparts (t=3.92, p<.01) and, using the trichotomous classification of regime type, more competitive than either autocracies or anocracies (F=9.00, p<.01). While the underrepresentation of terrorist groups in autocracies is a problem for analysis (Drakos and Gofas, 2006), the difference in the number of groups between the regime types provides support for Eubank and Weinberg’s (1994, 1998) findings that democracies are more likely to harbor terrorist groups than autocracies. Further, this echoes Chenoweth’s (2010) research linking the emergence of terrorist organizations in democracies to high levels of intergroup competition. Because outbidding theory is a contextual one – depending on the “domestic politics of the minority group and the state counter-terror strategies and responses to insurgent violence” (Bloom 2005: 79) – I include a variable assessing the “environment” that each state provides a terrorist organization. This variable is drawn from Mullins and Young (forthcoming), who argue that states and societies that legitimize and rationalize the use of violence may be more likely to be a victim of terrorism. This occurs as a result of a spillover process – groups model and adopt the state’s use of violence to its own interactions with others. This measure is drawn from four distinct indicators – two which capture state violence against its people, a third that measures citizen violence, and a final measure of state involvement in war. The first measures whether or not a state used capital punishment in a given year while the second captures the state’s use of extrajudicial killings through the Political Terror Scale (Gibney and Dalton, 1996). The third component assesses citizen violence by using the number of homicides per 100,000 people as drawn from the World Health Organization. The final element simply measures state participation in an interstate or intrastate war as measured by the Correlates of War project. Because the four components were found to load on a single factor - this analysis, like the later analyses in Mullins and Young (forthcoming), will use a single variable – culture of violence – to conduct the analyses. The temporal range of this variable reduces the subsequent analyses to the 1970-1997 period. To best assess this relationship, I create an interaction term between the concentration score and the culture of violence variable. While some information can be gained from the coefficients on interaction terms, I follow Brambor et al.’s (2006) suggestion to visually analyze interaction terms. To do this, I use Boehmke’s (2006) Grinter data utility. Control Variables I consider a number of control variables that may have an impact on group activity. I first consider the state’s ability to exert control over its population and territory. A weak central authority creates gaps in state control that allow insurgency to flourish and allows groups to divert resources from organizational security to the conduct of international terror (Takeyh and Gvosdev, 2002; Lai, 2007). For domestic terrorist organizations, a weak central government should operate in both of these ways; groups can operate unencumbered by state repression and they can dedicate more of their resources to attacks within the state. I assess state control by using a variable indicating a state’s relative political capacity (RPC) (Arbetman and Johnson, 2008). This variable was originally used in Organski and Kugler (1980) to measure the ability of states to wage war independent of the absolute size of their resource base. At the domestic level, similar measures of resource extraction have been associated with a decrease in internal violence (Benson and Kugler, 1998). This variable is roughly calculated as the ratio of the total value of actual state extractions relative to the potential value of all state extractions (Arbetman and Johnson, 2008). I anticipate that increased state control will be associated with fewer attacks. A second control variable I include is the state’s regime type. The impact of regime type has been thoroughly debated in previous research, resulting in three schools of thought. The first argues that the liberal characteristics of democracies, such as respect for civil liberties, freedom of the press, and rights of due process reduce operational costs for terrorist groups and allow them to recruit new members and plan attacks with minimal interference from the government (Crenshaw, 1981; Hamilton and Hamilton, 1983; Schmid, 1992). A second argues that democracies face reduced risks from terrorism because there are many ways, such as voting, demonstrations, or the formation of political parties to effect change without the need for violence (Eubank and Weinberg, 1994; Eyerman, 1998). Lastly, the third argues that the components of democracy have differential effects on terrorism; characteristics like political efficacy and electoral participation help to reduce terrorism while constraints of executive power increase the probability of terrorism (Li, 2005). For this, I use regime type data from POLITY IV. I divide this score into three parts and exclude autocracy as the baseline category. A number of other control variables are used in this analysis. Civil war should have a positive effect on all three of our dependent variables. Governments engaged in civil wars should be less able to maintain control over their territory, reducing their ability to combat terrorism and allowing for groups to devote more resources towards terrorist violence. At the level of the populace, civil war can sway unaligned moderates to support terrorist organizations increasing their vitality and longevity (Kalyvas, 2004). Data for this comes from the UCDP/PRIO Armed Conflict Dataset (Gleditsch et al., 2001). Larger populations are also likely to have an effect on terrorist group operations. Large populations provide organizations with a larger base to recruit from, a broader pool to draw resources from, and a more difficult environment for a state to monitor. All of these characteristics should contribute to more active organizations. The values for the population variable are taken from Gleditsch (2002). This variable is logged to reflect the decreasing benefit to terrorist groups given larger populations. Lastly, I account for economic development as a final control variable. While economic discontent has been linked to a variety of political outcomes, research on the role of economics on terrorism has found little support for a direct effect (Krueger and Maleckova, 2003; Abadie, 2006; Piazza, 2006). Rather, support and recruitment for terrorism seem to occur more often amongst the educated and employed than the poor (Krueger and Maleckova, 2003; Bueno de Mesquita, 2005). At the same time, wealthier states that are able to provide adequate social welfare policies are less likely to have popular support for terrorism and to experience terrorism on their soil (Burgoon, 2006). This is unclear at the level of the group; organizations in low-wealth countries may produce less terrorism because it is difficult to assemble enough recruits who meet a group’s qualifications. As the wealth of a state increases, groups may produce more terrorism. At the highest levels of state wealth, the production of terrorism may taper off as qualified recruits exist but support for terrorism is low. I account for this by including the logged term of per capita GDP. Data for this variable comes from Gleditsch (2002). Because the hypotheses relate to terrorist group activity, as measured by number of attacks, I use an event count model. Poisson models are not appropriate in this case, as they assume that the data are independent and homogenous; it is likely that targeting is not independent as groups that have gained experience with it are more likely to use it in the future (Jackson et al., 2005). Instead, given that the number of total attacks is dependent and is over-dispersed, I employ a negative binomial model (Long, 1997; Cameron and Trivedi, 1998). I lagged the independent variables to account for endogeneity. Lastly, I also include robust standard errors clustered by group to address any potential problems with heteroskedasticity and serial correlation (Greene, 2002). RESULTS[Table 1 Here] Table 1 presents the results from our test of competition and terrorist activity. The first model indicates that competition amongst terrorist organizations within their respective ideological niches has a negative and statistically significant effect on the number of terrorist attacks that occur on a yearly basis. The substantive effects confirm this relationship; a one standard deviation increase (.960) in competition yields a nearly 50% decrease in the number of terrorist attacks. Given that the average number of terrorist attacks in the data is 7.94, groups in environments with competition scores one standard deviation above the mean (1.69) – an environment with one additional group – will perpetrate four fewer attacks than it would in a less competitive environment. Unlike Bloom (2005), this initial finding seems to suggest that moderation, rather than outbidding, may be the way that terrorist organizations respond to competition. The controls generally perform as expected. A state’s orientation towards violence is statistically significant and associated with a greater number of terror attacks, echoing Mullins and Young (forthcoming). The effect of democracy is also positive and strongly significant. This may indicate that domestic terror is strongly influenced by the democratic process – issues of representation or legislation may provoke groups to violence. At the same time, this may also reflect the deep divisions in reporting terrorist acts between democracies and autocracies (Drakos and Gofas, 2006). GDP per capita is also shown to be positive and significant. This suggests that groups will be more active in areas where they can get the best recruits. As expected, relative political capacity is negative and significant, indicating that states with greater control over their territories experience less terrorism. This supports research by Fearon and Laitin (2003) and Piazza (2008) who find that higher levels of state capacity are related to decreased levels of both insurgency and terrorism, respectively. Lastly, civil war is significant and in the anticipated direction. This result indicates that, like Kalyvas (2004), we can see domestic terrorism as a tactic used by combatants within civil war. This may also occur because civil conflict allows terrorist groups room to operate with less threat of government repression. Contrary to our expectations, larger populations are associated with groups committing less terrorist acts. In fact, population increases of one standard deviation result in a 45% reduction in group attacks. This result is puzzling; populations accord larger bases for recruitment, greater target selection, a larger audience to intimidate, and greater monitoring difficulties for the government. One potential explanation for the result is that it may be a methodological artifact – population may affect groups of different ideologies in different ways. I conduct analyses disaggregating group type and discuss this point in detail below. The second model in Table 1 incorporates the interaction between group concentration and a state’s acceptance of violence. The interaction effect is positive but not statistically significant. When analyzed visually using the grinter utility (Boehmke, 2006), as shown in Figure 5, a different interpretation emerges. Here, the effect of competition on the number of attacks has a slight positive effect as the state the terrorist group resides in becomes more tolerant of violence - a similar, albeit weaker, finding to that of Bloom (2005). The controls provide comparable results to that of the first model. Table 2 disaggregates the analyses into the four ideological categories used by the Jones and Libicki (2008) data. This may help to address the weak findings presented above. It also helps to clarify whether the effect of outbidding is different across ideological types – an element that is not directly addressed by Bloom (2005). One may anticipate that groups with a religious ideology may be more likely to engage in outbidding regardless of the acceptability of violence because their spiritual mandate trumps any desire to gain widespread public support (Juergensmayer, 2003). Nationalist groups, on the other hand, may be sensitive to outbidding since excessive violence may negatively affect public support, making the attainment of their goals more difficult (Sanchez-Cuenca and de la Calle, 2009). The results indicate that the effects of many of the variables are conditional on group ideology. This is first echoed in the results for competition; 3 out of the 4 models demonstrate that competition in the ideological environment leads to fewer attacks. The lack of a finding in the fourth case - right wing groups may indicate that these types of groups are less sensitive to issues of citizen perception given that they are, in many instances, an arm of state policy and a recipient of state support. The conditional effects are made more evident by visually analyzing the interaction terms in Figure 6. Here, for religious and nationalist terrorist organizations, the marginal effect of competition on domestic terror attacks is shown to increase as the acceptability of violence increases. In other words, religious organizations and their nationalist counterparts respond to competition using outbidding across most states. Left-wing groups do not appear to engage in outbidding. Rather, for those instances where the interaction is significant, competition leads to moderation for left-wing organizations. The interaction for right-wing organizations is not significant, thus I make no claims about the relationship. The control variables also indicate that ideology has a considerable effect on their direction and significance. The state’s culture of violence has a differential effect across the ideologies; religious groups are less likely to perpetrate attacks in more violence-acceptant states while both left and right-wing groups are more likely to. For anocracies, nationalist groups increase their attacks, while left and right-wing groups curtail their activities. In addition, nationalist and left-wing groups are also active in democracies, although the results for left-wing organizations fall outside traditional significance levels. Per capita GDP only has an effect for nationalist groups; nationalist terrorist organizations such as MEND (Movement for the Emancipation of the Niger Delta) and GAM (Free Aceh Movement) have used arguments based on the wealth of the central government to justify their secessionism (Ross, 2004). Relative political capacity decreases the number of nationalist and left-wing attacks while increasing the number of right-wing attacks. Given that this measures a government’s ability, a positive relationship here may denote the inclination of some governments to use right-wing groups as a coercive element of their policy (Mason and Krane, 1989). The civil war variable is positive and significant for religious and nationalist groups. This may indicate that these groups have larger goals, such as regime change, than groups of other ideologies and that a condition of warfare may be the best context to pursue these goals (). Lastly, population is only significant for left-wing organizations. CONCLUSIONWhile theories of outbidding have been central to explanations of terrorist actions for many years, few attempts have been made to subject the theories to empirical testing. This analysis, focusing on group level data, finds a positive relationship between competition and increases in terrorist violence, conditional on a state’s acceptance of violence. As such, this finding is consistent with those of Bloom (2005). These results become more pronounced when the analysis takes group’s ideologies into account. Religious terrorist groups show the greatest proclivity to outbid followed by nationalist organizations. The positive finding for religious organizations affirms Juergensmeyer’s (2003: 221) observation that “there is no need…to contend with society’s laws and limitations when one is obeying a higher power”. Left-wing organizations respond by reducing their violence – precisely responding to society’s limitations. In addition, this analysis utilized the organizational ecology literature to better operationalize the concept of competition. Previous discussions of outbidding and competition treated competition as boundless – resources and recruits ran towards the most capable organization. Similarly, recruits were drawn to any group, regardless of their ideology or history. Interviews and assessments of terrorist operatives have shown that this is not the case, recruits and resources are very specific about their destination (Post et al., 2002). As such, terrorist organizations can be theorized to operate via the “competitive exclusion” principle – competition only occurs between organizations of a similar type. This then allows us to create measures that take this type of sectoral competition into account.This research also points to the value of considering using the group as the unit of analysis. Work by Asal and Rethemeyer (2008) demonstrate this utility, showing that some organizational attributes have important impacts on organizational lethality while others do not. Here, this choice shows various levels of competition, and thus very disparate levels of violence, can exist within a state. Aggregating the data to use larger units of analysis, like the state, threatens to obscure this valuable heterogeneity. Such a focus, and the utilization of concepts from different fields, may provide more clarity to this complex and menacing phenomena. Figure SEQ Figure \r 1 \* ARABIC 1: Coding Rule & Screening Mechanism -466725147955Step 1. According to TOPs, the FMLN was known to operate solely in El Salvador.00Step 1. According to TOPs, the FMLN was known to operate solely in El Salvador.2733675147955Step 2. These states are not defined as regular operating areas for the FMLN and, thus, are not considered domestic.00Step 2. These states are not defined as regular operating areas for the FMLN and, thus, are not considered domestic.151447523368000121920041275Selected FMLN Attacks 1980-198300Selected FMLN Attacks 1980-1983CaseGroupDateState1Farabundo Marti National Liberation Front (FMLN)1/14/1980El Salvador2FMLN1/24/1980El Salvador266065118110Step 3. As a result, Cases 3 and 10 are not coded as cases of domestic terrorism.00Step 3. As a result, Cases 3 and 10 are not coded as cases of domestic terrorism.3FMLN2/14/1980Guatemala4FMLN9/15/1980El Salvador5FMLN2/4/1981El Salvador6FMLN11/12/1981El Salvador7FMLN4/26/1982El Salvador8FMLN10/18/1982El Salvador9FMLN2/3/1983El Salvador10FMLN8/18/1983United StatesFigure 2: Average Level of Concentration for Top Ten Target States of Domestic Terrorism (1970-1997) Figure 3: Average Level of Terrorist Organization Concentration (Autocracies and Democracies) (1970-1997) Figure 4: Average Level of Terrorist Organization Concentration (Autocracies, Democracies, and Anocracies) (1970-1997) Figure 5: Effect of Competition Conditioned on Acceptability of ViolenceFigure 6: Effect of Competition Conditioned on Acceptability of Violence by Group TypeTable 1: The Effect of Competition on Domestic Terrorist Attacks Model 1%ΔModel 2%ΔCompetition-.714***(.122)-49.6-.770***(.166)-52.3Culture of Violence.752***(.151)124.2.656**(.294)102.1Concentration * Culture.055(.103)Anocracy.019(.391)-.002(.385)Democracy1.25***(.419)247.91.23***(.422)240.7Logged GDP per capita.000***(.000)145.4.000***(.000)148.8RPC-.506*(.261)-23.6-.503*(.261)-23.5Civil War.750**(.310)111.8.764**(.310)114.7Logged Total Population-.379***(.113)-45.3-.383***(.113)-45.7Constant-4.63(1.29)-4.74(1.31)N31113111Log Likelihood-5900.73-5900.12Wald χ295.38***121.11***Note: Robust Standard Errors clustered on group in parentheses. * significant at 0.10, ** significant at 0.05, *** significant at 0.01 (two tailed). All independent variables lagged at t-1. Percentage change calculated as change in 1 standard deviation for continuous variables and unit change for dichotomous variables. Table 2: The Effect of Competition on Total Terrorist Attacks by IdeologyReligious%ΔNationalist%ΔLeft Wing%ΔRight Wing%ΔCompetition -1.69***(.608)-76.4-.824***(.164)-60.5-.526**(.241)-32.0-.321(.330)Culture of Violence -2.03***(.633)-86.7.215(.306).911***(.336)177.21.27**(.616)283.2Con * Culture.994***(.367)591.8.110(.092)-.063(.137)-.527(.458)Anocracy-.284(.662)2.00***(.374)637.1-.840**(.403)-56.8-2.92***(.562)-94.6Democracy -.018(.673)1.84***(.330)529.4.949*(.542)158.4.288(.709)Logged GDP per capita -.000(.000).000***(.000)294.3.000(.000)-.000(.000)RPC-.226(.979)-.847**(.351)-39.5-.857**(.387)-29.8.495**(.228)28.5Civil War 1.62**(.801)403.4.742**(.290)109.9.658(.474).903(.583)Logged Total Population -.374(.266).161(.111)-.647***(.218)-60.5-.264(.385)Constant 6.78(2.57)-1.91(1.41)8.28(2.21)2.67(3.37)N 42213711149169Log Likelihood-498.77-2328.64-2621.95-209.31Wald χ225.46***114.81***107.10***453.13***Note: Robust Standard Errors clustered on state in parentheses. * significant at 0.10, ** significant at 0.05, *** significant at 0.01 (two tailed). All independent variables (other than ideology) lagged at t-1. Percentage change calculated as change in 1 standard deviation for continuous variables and unit change for dichotomous variables. ReferencesAbadie, Alberto. 2006. Poverty, Political Freedom, and the Roots of Terrorism. American Economic Review 96(2): 50-56. Arbetman, Marina and Kristin Johnson (2008) Relative Political Capacity: Empirical and Theoretical Underpinnings. Paper presented at the 49th Annual Convention of the International Studies Association, San Francisco, CA, 26–29 March.Asal, Victor and R. Karl Rethemeyer. 2008. The Nature of the Beast: Organizational Structure and the Lethality of Terrorist Attacks. Journal of Politics 70(2): 437-449.Benson, Michelle and Jacek Kugler. 1998. Power Parity, Democracy, and the Severity of Internal Violence. Journal of Conflict Resolution 42(2): 196-209.Bloom, Mia. 2005. Dying to Kill: The Allure of Suicide Terror. New York: Columbia University Press.Boehmke, Frederick. 2006. “Grinter: A Stata Utility for Graphing the Marginal Effect ofan Interacted Variable in Regression Models.” (January 23, 2010)Brambor, Thomas, William Clark, and Matt Golder. 2006. Understanding InteractionModels: Improving Empirical Analyses. Political Analysis 14(1): 63-82.Brym, Robert and Bader Araj. 2008. Palestinian Suicide Bombing Revisited: A Critique of the Outbidding Thesis. Political Science Quarterly 123(3): 485-500 Bueno de Mesquita, Ethan. 2005. The Quality of Terror. American Journal of Political Science 49(3): 515-530.Bueno de Mesquita, Ethan. 2007. Politics and the Suboptimal Provision of Counterterror. International Organization 61(1): 9-36.Burgoon, Brian. 2006. On Welfare and Terror: Social Welfare Policies and Political-Economic Roots of Terrorism. Journal of Conflict Resolution 50(2): 176-203.Calkins, Stephen. 1983. The New Merger Guidelines and the Herfindahl-Hirschman Index. California Law Review 71(2): 402-429.Cameron, Colin and Pravin Trivedi. 1998. Regression Analysis of Count Data. Oxford: Oxford University Press. Chenoweth, Erica. 2010. Democratic Competition and Terrorist Activity. Journal of Politics 72(1): 16-30.Coser, Lewis. 1956. The Functions of Social Conflict. Glencoe: Free Press. Crenshaw, Martha. 1981. The Causes of Terrorism. Comparative Politics 13(4): 379-399. Crenshaw, Martha. 1985. An Organizational Approach to the Analysis of Political Terrorism. Orbis 29(3): 465-489.Cronin, Audrey Kurth. 2006. How al-Qaida Ends: The Decline and Demise of Terrorist Groups. International Security 31(1): 7-48.Dingley, James. 2001. The Bombing of Omagh, 15 August 1998: The Bombers, Their Tactics, Strategy, and Purpose Behind the Incident. Studies in Conflict and Terrorism 24: 451-465.Drakos, Konstantinos and Andreas Gofas. 2006. The Devil You Know but Are Afraid to Face: Underreporting Bias and its Distorting Effects on the Study of Terrorism. Journal of Conflict Resolution 50(5): 714-735.Eubank, William and Leonard Weinberg. 1994. Does Democracy Encourage Terrorism? Terrorism and Political Violence 6(4): 417-443.Eubank, William and Leonard Weinberg. 1998. Terrorism and Democracy: What Recent Events Disclose. Terrorism and Political Violence 10(1): 108-118.Eyerman, Joe. 1998. Terrorism and Democratic States: Soft Targets or Accessible Systems. International Interactions 24(2): 151-170. Fearon, James and David Laitin. 2003. Ethnicity, Insurgency, and Civil War. American Political Science Review 97(1): 75-90.Gibney, Mark, and Matthew Dalton. 1996. The Political Terror Scale. Policy Studies and Developing Nations 4: 73-84. Gleditsch, Nils Petter, Peter Wallenstein, Mikael Eriksson, Margareta Sollenberg, and H?vard Strand. 2001. Armed Conflict, 1946-2001: A New Dataset. Journal of Peace Research 39(5): 615-637. Gleditsch, Kristian. 2002. Expanded Trade and GDP Data. Journal of Conflict Resolution 46(5): 12-24. Greene, William. 2002. Econometric Analysis. 5th ed. Upper Saddle River: PrenticeHall.Hamilton, Lawrence and James Hamilton. 1983. Dynamics of Terrorism. International Studies Quarterly 27(1): 39-54.Hannan, Timothy. 1997. Market Share Inequality, the Number of Competitors and the HHI: An Examination of Bank Pricing. Review of Industrial Organization 12(): 23-35. Herfindahl, Orris. 1950. Concentration in the Steel Industry. Ph.D. Diss., Columbia University.Hirschman, Albert. 1945. National Power and the Structure of Foreign Trade. Berkeley: University of California Press.Hoffman, Bruce. 1998. Inside Terrorism. New York: Columbia University Press.Jackson, Brian, John Baker, Kim Cragin, John Parachini, Horacio Trujillo, and Peter Chalk. 2005. Aptitude for Destruction: Organizational Learning in Terrorist Groups and its Implications for Combating Terrorism. Santa Monica: RAND Corporation Jacobson, Philip. 2001. “Home-Grown Martyrs of the West Bank Reap Deadly Harvest.” Sunday Telegraph, 19 August. Jones, Seth and Martin Libicki. 2008. How Terrorist Groups End: Lessons for Countering al Qa’ida. Santa Monica: RAND Corporation Juergensmeyer, Mark. 2003. Terror in the Mind of God. Berkeley: University ofCalifornia Press.Kalyvas, Stathis. 2004. The Paradox of Terrorism in Civil War. Journal of Ethics 8(1):97-138. Kellen, Konrad. 1979. Terrorists-What are they Like? How Some Terrorists Describe Their World and Actions. Santa Monica: RAND Corporation.Krueger, Alan and Jitka Maleckova. 2003. Education, Poverty, and Terrorism: Is There a Causal Connection? Journal of Economic Perspectives 17(4): 119-144.Kydd, Andrew and Barbara Walter. 2006. The Strategies of Terrorism. InternationalSecurity 31(1): 49-80.LaFree, Gary and Laura Dugan. 2007. GTD1 (1970-1997) Global Terrorism Database Codebook. College Park: START. Lai, Brian. 2007. ‘Draining the Swamp’: An Empirical Examination of the Production of International Terrorism, 1968-1998. Conflict Management and Peace Science 24(4): 297-310. Li, Quan. 2005. Does Democracy Promote or Reduce Transnational Terrorism Incidents? Journal of Conflict Resolution 49(2): 278-297. Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage Publications.Long, J. Scott and Jeremy Freese. 2005. Regression Models for Categorical Outcomes Using Stata. Second Edition. College Station, TX: Stata Press.Lowery, David and Virginia Gray. 1995. The Population Ecology of Gucci Gulch, or the Natural Regulation of Interest Group Numbers in the American States. American Journal of Political Science 39(1): 1-29.Maoz, Zeev. 2007. Evaluating Israel’s Strategy of Low-Intensity Warfare, 1949-2006. Security Studies 16(3): 319-349.Marshall, Monty, Ted Gurr, and Keith Jaggers. 2009. Polity IV Project: Political Regime Characteristics and Transitions, 1800-2009. Center for Systemic Peace.Moloney, Ed. 2010. Voices from the Grave: Two Men’s War in Ireland. New York: PublicAffairs.Mullins, Christopher and Joseph Young. Forthcoming. Cultures of Violence and Acts of Terror: Applying a Legitimation-Habituation Model to Terrorism. Crime & Delinquency Oots, Kent. 1989. Organizational Perspectives on the Formation and Disintegration of Terrorist Groups. Studies in Conflict and Terrorism 12(3): 139-anski, A F K. and Jacek Kugler. 1980. The War Ledger. Chicago: University of Chicago Press.Piazza, James. 2006. Rooted in Poverty?: Terrorism, Poor Economic Development, and Social Cleavages. Terrorism and Political Violence 18(1): 159-177.Piazza, James. 2008. Incubators of Terror: Do Failed and Failing States Promote Transnational Terrorism? International Studies Quarterly 52(3): 469-488.Post, Jerrold, Ehud Sprinzak, and Laurita Denny. 2003. The Terrorists in Their Own Words: Interviews with 35 Incarcerated Middle Eastern Terrorists. Terrorism and Political Violence 15(1): 171-184.Rhoades, Stephen. 1993. The Herfindahl-Hirschman Index. Federal Reserve Bulletin 79: 188-189. Rosendorff, B. Peter and Todd Sandler. 2005. The Political Economy of TransnationalTerrorism. Journal of Conflict Resolution 49(2): 171-182. Ross, Jeffrey and Ted Robert Gurr. 1989. Why Terrorism Subsides: A Comparative Study of Canada and the United States. Comparative Politics 21(4): 405-426.Ross, Michael. 2004. How Do Natural Resources Influence Civil War? Evidence fromThirteen Cases. International Organization 58(1): 35-67.Sanchez-Cuenca,Ignacio and Luis de la Calle. 2009. Domestic Terrorism: The Hidden Side of Political Violence. Annual Review of Political Science 12: 31-49Sandler, Todd, John Tschirhart, and Jon Cauley. 1983. A Theoretical Analysis of Transnational Terrorism. American Political Science Review 77(1): 36-54.Schmid, Alex. 1992. Terrorism and Democracy. Terrorism and Political Violence 4(4): 14-25.Schmid, Alex and Albert Jongman. 1988. Political Terrorism: A Research Guide to the Concepts, Theories, Databases, and Literature. Amsterdam: North Holland. Silke, Andrew. 2004. An Introduction to Research on Terrorism. In Research on Terrorism: Trends, Achievements, and Failures, ed. Andrew Silke. London: Frank Cass.Siquiera, Kevin and Todd Sandler. 2006. Terrorists versus the Government: StrategicInteraction, Support, and Sponsorship. Journal of Conflict Resolution 50(6): 878-898.Taagepera, Rein and Matthew Shugart. 1989. Seats and Votes. New Haven: Yale University Press. Takeyh, Ray and Nikolas Gvosdev. 2002. Do Terrorist Networks Need a Home? The Washington Quarterly 25(3): 97-108.Waugh, William. 1983. The Values in Violence: Organizational and Political Objectives of Terrorist Groups. Conflict Quarterly 3(4): 5-19 Wolf, John. 1978. Organization and Management Practices of Urban Terrorist Groups. Terrorism: An International Journal 1(2): 169-186. ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download