Human Trafficking-Terrorism Nexus: When Violent Non-State Actors Engage in the Modern-Day Slavery

Abstract

Why do some militant organizations participate in human trafficking? We investigate this question by introducing a new dataset that records insurgent organizations’ involvement in four types of human trafficking: sexual exploitation, forced recruitment, slavery, and kidnapping. Marrying our data to the BAAD2I population of insurgent organizations, we uncover the organizational attributes related to human trafficking. We find that groups with wide alliance networks and territorial control are more likely to commit human trafficking. Organizations that are losing command of the territory and suffering rank-and-file losses are also more likely to turn to human trafficking. Our study sheds theoretical light on insurgent groups’ involvement in crime. It also contributes to the empirical scholarship on sexual violence by violent groups by studying different forms of human trafficking in both conflict and non-conflict environments. Our paper presents an original dataset and empirical analysis of insurgent groups’ human trafficking patterns.

Keywords

human rights international security terror networks asymmetric conflict terrorism

Introduction

In April 2014, Boko Haram, a jihadist militant organization with the home base in northeastern Nigeria, kidnapped 276 girls from a boarding school in Chibok. The kidnapping raid marked a chilling evolution in Boko Haram’s use of women and girls in its suicide operations in addition to sexual slavery, forced marriages, and domestic servitude (Kenny and Malik 2019; Pearson 2018; Warner and Matfess 2017). The same year the Islamic State of Iraq and Levant (ISIS) made headlines with its appalling campaign of enslavement and human trade endorsed by an official policy on treating the exploited women (Malik 2017). On the other hand, the Al Qaeda branch in Syria (also known as Al-Nusra and Jabhat Fateh al-Sham) operating next to and in competition with ISIS and other insurgent groups in Syria and Iraq, raised its revenue from kidnapping for ransom but has not been known for its participation in the human trade (Fanusie and Entz 2017). Hezbollah, a political and militant Shi’ite Muslim group, has engaged in large-scale drug trafficking and smuggling of a variety of legal and illegal items using increasingly complex smuggling schemes but has stayed away from human trafficking (Fanusie and Entz 2017).

Why do some insurgent groups engage in human trafficking activities?¹ This study systematically examines this question. While the nexus between terrorism, conflict-related sexual violence, and trafficking in human beings is not new, it has only recently been recognized at the highest level by the United Nations Security Council, other UN agencies, and individual governments (Counterterrorism Committee Executive Directorate [CTED] 2018; UNODC 2018; UN Security Council 2016). These studies have advanced our understanding of insurgent groups’ motives and modus operandi, yet, the state of knowledge on human trafficking by insurgents is still dominated by two simplistic views. The first and dominant argument is that human trafficking plays an increasing role in the operations of violent groups. With the reduction in state sponsorship and global efforts at disrupting money-laundering and terrorist financing, insurgent groups have turned to various criminal activities for raising funds in support of their operations (Kloer 2009; Roth and Sever 2007). The cash motives that drive criminal organizations to engage in crime also drive violent groups’ participation in human trade.

The second theme has emerged suggesting that the permissive regional and global environments characterized by high volumes of people displaced or affected by conflict and natural disasters, as well as social and economic maladies that have resulted in significant number of under-employed youth have allowed insurgent and criminal groups to take advantage of the highly lucrative and low risk crime of human trade (Basra, Neumann, and Brunner 2016; Bigio and Vogelstein 2019; Cockayne and Walker 2016; Farley 2018; FATF-APG 2018). Global communications and transportation technologies have facilitated activities of criminal syndicates and insurgent groups, while the government complicity has strengthened the backbone of crime and violence enabled by corruption (Shelley 2010, 2020; Traughber 2007).

This study maintains that neither of these two arguments suffices to explain insurgent groups’ participation in human trafficking. While the spread of permissive environments that support a growing market for human trade has been used to explain the rise in migration, smuggling, and trafficking in persons, these conditions alone are insufficient to account for variation in human trafficking by insurgent groups operating in similar contexts (Haer, Faulkner, and Whitaker 2020). There is also a growing recognition that insurgent groups’ participation in human trafficking serves a “dual purpose” of causing social harm and helping groups to achieve their political objectives (Kenny and Malik 2019; Shelly 2020). This complex incentive structure that extends beyond revenue generation as a reason for human trafficking by insurgent groups makes it challenging to attribute the crime of human trade to a single motive.

Our contention is that the patterns of insurgent groups’ involvement in human trafficking are driven by organizational factors, rather than by country-level attributes. Theorizing the impact of organizational attributes through the concepts of opportunity and motivation, we show that groups’ network embeddedness and territorial control drive their decisions to participate in human trade. Alliances expand opportunity by facilitating operations across borders and in cooperation with similar groups elsewhere. Alliances also permit transfer of skills and personnel, expanding the capabilities of groups. Ties forged among groups that engage in crime permit convergent milieus, whereby both criminal and terrorist groups draw from the same pool of recruits (Basra, Neumann, and Brunner 2016; Kupatadze and Argomaniz 2019). Territorial control expands opportunity by permitting the transport of resources inside insurgent-held territory (Asal, Rethemeyer, and Schoon 2019). It also increases need because maintaining control of a given territory is resource intensive, demanding that group hold the territory against government forces, while also commanding the support of the local populace therein (Cornell and Johnson 2014; Kenney 2007). Territorial control thus increases incentives for revenue-generation, while at the same time improving the capacity to conduct illicit activities.

The appeal of human trafficking to insurgent groups merits a systematic examination for several reasons. First, our understanding of the human trafficking-militancy nexus is based on a number of abhorrent examples of the large-scale exploitation of humans by a handful of insurgent groups, but we lack knowledge about the extent and nature of human trafficking activities by a larger universe of these actors. Second, a systematic analysis of human trafficking by insurgent groups can afford a better understanding of the role of criminal activities in their revenue generation and how fund-raising efforts relate to various aspects of an insurgent organization, including its size, membership, ideology, territorial control, and more (Binetti 2015). Third, a better understanding of human trafficking by insurgent groups may inform more nuanced counterinsurgency and legal approaches aimed at the members of these organizations. Fourth, by shifting focus from the macro conditions to the attributes of groups, we develop a theory of organizational characteristics that animate human trafficking. In doing so, we seek to bridge the gap between two separate strains of scholarship. One segment of existing literature uncovers patterns of human trafficking at the country level. A separate segment adopts a human rights perspective and focuses on the victims of trafficking (Shelley 2010). Both of these literatures are handicapped by the clandestine nature of trafficking and miss the roles that insurgent actors play in the process (Campana and Varese 2016). A comprehensive approach should leverage both strands of the literature by simultaneously accounting for perpetrator characteristics and human rights consequences of specific forms of human trafficking.

Since we are interested in understanding a group-level phenomenon—human trafficking by insurgent groups—we derive explanations of the group behavior from organizational characteristics of terrorist and insurgent groups, such as group size, structure, leadership, and intra- and inter-group relations. We also examine state level factors that prompt and facilitate the involvement of these groups in human trafficking. We test these expectations using an original dataset on human trafficking by insurgent groups coded for this project. The human trafficking data is part of a larger dataset of organizational characteristics of violent non-state actors, the Big Allied and Dangerous (BAAD) 2 dataset (1998-2015) (Asal, Rethemeyer, and Schoon 2018).²

We define human trafficking consistent with the Palermo Protocol to Prevent, Suppress and Punish Trafficking in Persons Especially Women and Children, supplementing the United Nations Convention against Transnational Organized Crime, adopted by General Assembly resolution 55/25 of 15 November 200.

Trafficking in persons’ shall mean the recruitment, transportation, transfer, harboring or receipt of persons, by means of the threat or use of force or other forms of coercion, of abduction, of fraud, of deception, of the abuse of power or of a position of vulnerability or of the giving or receiving of payments or benefits to achieve the consent of a person having control over another person, for the purpose of exploitation. Exploitation shall include, at a minimum, the exploitation of the prostitution of others or other forms of sexual exploitation, forced labor or services, slavery or practices similar to slavery, servitude or the removal of organs. (UN General Assembly 2000)

What Motivates Insurgent Groups’ Involvement in Human Trafficking?

The case studies of human trafficking by insurgent groups have identified a range of underlying motivations and purported justifications for these criminal activities (Kenny and Malik 2019). For analytical purposes, we classify these motivations into two broad categories recognizing that, in practice, insurgent groups’ trafficking activity often serves multiple interrelated uses (Shelley 2020). The first set of motives includes financial incentives of insurgents who integrate human trade into their functions for raising revenue. The second set of motives involves the use of trafficking as a war tactic and recruitment strategy. While the former emphasizes narrower financial incentives, the latter underscores a broader strategic dimension of insurgents who need to legitimize their campaign of violence, attract new members, and win the support of the people in order to sustain the very existence of insurgency (Freeman 2011).

Human Trafficking as a Means of Financing Insurgency

Any insurgent organization needs funds to survive, train and equip its foot soldiers, build an infrastructure for recruitment, planning, and procurement between attacks, and create an enabling environment to sustain its activities. Compared to terrorist cells that can commit violence at lower cost, insurgent groups have higher economic demands (Basra, Neumann, and Brunner 2016). Nevertheless, insurgent groups have been versatile and opportunistic in meeting their financial needs resorting to drug trafficking, smuggling, black market trading, and other criminal activities as money-making mechanisms. When crime promises high yield in revenue at a relative low cost, insurgent groups can be expected to engage in criminal activity. The barriers to entry for human trafficking are relatively low, in part because governments have not standardized prosecution laws for the crime (Shelley 2010; de Brouwer, de Volder, and Paulussen 2020). Compared to other forms of organized crime, human trafficking has an ancillary benefit of providing “monetary flows to terrorist organizations […] through the sale and re-sale of human bodies” (Malik 2017, 2). While other forms of crime that involve the illicit transport of humans are profitable, the human trade makes possible continued profits through the repeated sale of humans (Bowersox 2019).³ The “commodification” of trafficked women and children has been inferred from the measures that insurgents take to protect their value. ISIS, for example, has reportedly forced victims to take birth control to prevent pregnancies and allow for continued re-sale of enslaved women (Kenny and Malik 2019). In addition to ISIS, a number of other well-known insurgent organizations—Al Qaeda, the Haqqani Network, Boko Haram, FARC, among others—have relied on human trafficking for raising revenue (Clarke 2015, 9; Shelley 2010, 2014).

There are, however, obstacles to an insurgent group’s involvement in human trafficking. Although, the physical movement of people is unnecessary for engaging in human trade, reaping the greatest benefits from trafficking may require a sprawling network of operatives in multiple countries or collaboration with criminal networks (Kara 2009, 2011). The nexus of criminals and insurgents is rarely enduring and almost always asymmetric with the stronger party exploiting its strength to coerce the weaker party into collaboration. For criminal cartels, terrorist networks are major competitors; for terrorist groups, crime can be inimical to their self-defined higher causes (Cornell 2009; Dishman 2001). Insurgent groups are invested in cultivating legitimacy because they directly contest the claim to leadership of the regime in power and seek to supplant its rule (Paul, Clarke, and Grill 2010). Not only does commanding public loyalty aid a rebel organization take hold of the territory but it is also essential for its eventual goal of governing the constituency residing on it. It is not surprising, therefore, that insurgent groups involved in prominent criminal activities have tried to legitimize the methods of acquiring funds. Hezbollah, for example, published a fatwa in the mid-1980s to provide a religious justification for distribution and trafficking of drugs (Hernandez 2013). ISIS has justified, elevated, and celebrated slavery and sexual violence as spiritually beneficial and consistent with Islamic theology in its own publications, such as Al Dabiq (Malik 2017).

Human Trafficking as a War Tactic

Historically, belligerent parties have used sexual violence as a tool to punish, terrorize and destroy populations (Crawford 2017; Choi-Fitzpatrick 2016). Modern-day insurgencies (as well as armies) have also employed sexual violence as a tactic to pursue their strategic objectives. In practice, sexual violence and human trafficking have often been intertwined and the boundaries between them so blurred that these crimes have been viewed as both the means and the outcomes of some insurgent groups’ criminal actions (Kenny and Malik 2019). There are several ways through which human trafficking can strategically benefit insurgent groups. First, by terrorizing people with trafficking, slavery, and rape, insurgent groups can destabilize and dislocate communities and undermine societal trust in the government. For example, Boko Haram has used human trafficking and concomitant sexual violence to humiliate the Nigerian state and “destroy the social fabric of society” (Attah 2016, 388). Al-Shabaab deployed human trafficking and sexual violence to terrorize civilians and state structures in Somalia and neighboring countries (de Brower, de Volder, and Paulussen 2020, 14).

Second, the strength of an insurgent group hinges on its ability to provide a sense of identity and belonging to its members and supporters. Sexual violence has been used to reinforce bonds among group members while fostering a sense of strength among those committing acts of violence (Malik 2017). Insurgent groups have been known for using victims of trafficking and sexual exploitation to discipline and reward the rank-and-file (Cohen 2013). By offering prospective and active fighters an opportunity to use human slaves as domestic servants or wives, human trafficking serves as a strategy for recruiting and retaining foot soldiers and a mechanism for rewarding successful combatants (Binetti 2015).

Third, forced pregnancies, marriages and conversions have been used as part of deliberate strategy to expand ideology and insurgency by the militant groups (Kenny and Malik 2019). Lastly, trafficked victims have been deployed in the commission of violent attacks (Warner and Matfess 2017).⁴ Not only have women and children been more likely to avoid detection (due to the widespread perception of women and children being non-violent and non-threatening), but they have also been more expendable and easier to manipulate and coerce, than men, from the group’s standpoint (Warner and Matfess 2017). The employment of women and children in suicide attacks within insurgencies have generated more profound shock than terrorist violence by male counterparts, putting pressure on the governments to respond. The global exposure that these attacks often receive as a corollary of the media attention can be important to violent groups seeking to disseminate their messages worldwide. Lastly, when an insurgent group is capable of not only “importing” the trafficked female suicide bombers but also “exporting” them for committing acts of violence in other states, this sends a powerful message of strength and reach of the terrorist group to both its supporters and targeted societies (Clarke 2015).

Characteristics of insurgent groups as explanations of human trafficking

While the discussed motivations afford a better understanding of insurgent groups’ involvement in human trafficking, the distinction between financial and tactical uses of human trade is murky in practice. The same insurgent groups have resorted to human trafficking based on financial calculus but also for ideological, strategic, and recruitment purposes. Furthermore, the existing explanations leave a critical question about the variation in groups’ preferences unanswered. To put it differently, if all insurgent groups need funds to survival and are motivated to gain strategic advantage over their adversary, why do some insurgent groups partake in human trafficking, but others do not?

Our contention is that an insurgent organization’s preference for human trafficking is shaped through the interaction of its various motives with organizational imperatives of accomplishing their goals. In particular, we consider the impact of the size and structure of insurgent groups, their ideological underpinnings, territorial control, rivalry with other insurgent organizations, embeddedness in the networks of insurgent groups, and involvement in criminal activities on human trafficking by insurgent actors.

First, although all insurgent groups need funds to survive, large organizations require more resources to fund themselves and carry out their operations. Further, smaller groups may lack the organizational capacity necessary for succeeding in risky high-profit criminal activities. These smaller groups can be expected, therefore, to engage in low-profit crimes requiring no or few in-house capabilities in order to generate enough revenue to carry out a specific act of violence. Financing beyond these immediate requirements is neither necessary, nor desirable, as it increases the risk of detection and capture (Hutchinson and O’Malley 2007). In addition to funding, larger groups may be in a greater need for other “members’ incentives” to sustain their loyalty and social cohesion of the group. Others maintain that diminishing manpower incentivizes groups to exploit women and children for armed combat, including for suicide operations (Bloom 2007). Accordingly, we expect groups that are losing members to attempt to compensate by engaging in human trafficking, either to maintain their ranks or morale. Put differently, the loss of manpower animates opportunism, through which groups use trafficking to directly deploy forced recruits, or use sexual enslavement as an enticement to keep and draw fighters (CTED 2018).

H1: Larger insurgent organizations and those that are losing size are more likely to engage in human trafficking.

Another organization feature is the structure of a violent group. Wood (2009) argues that rape is rare in groups with leaders who deem sexual violence to run counter to group interests. Groups with strong leadership can punish transgressors of group norms and may be less predisposed to resort to sexual violence (Wood 2009). While these arguments pertain to the use of rape in armed groups, we can extrapolate that hierarchically organized groups will be less likely to engage in human trafficking. In the loosely-knit decentralized groups, individual cells must rely on their own funding mechanisms. These semi-autonomous factions may be more conducive to criminalization especially in the absence of a strong, ideologically-driven leaders able to unify the terrorist network toward a common strategic objective (Asal, Brinton, and Schoon 2015). Lacking a universal template for behaviors and practices, decentralized and non-hierarchical violent organizations are also more likely to forge ties and collaborate with criminal networks (Dishman 2005).

H2: Non-hierarchical organizations are more likely to engage in human trafficking.

For insurgent groups, brutal tactics run the risk of losing legitimacy in the eyes of the population, which threatens to erode popular sympathy for the group (Tokdemir and Akcinaroglu 2016). By breaking commonly held mores, human trafficking similarly frays support in the general populace for insurgent groups. Loss of popular support is a significant cost for insurgent actors who rely upon public’s loyalty in their battle against the state. However, if some groups hinge on a wider base of support, others target specific out-groups—such as ethnically or religiously dissimilar groups. If these organizations select victims from out-groups, then they may sustain support among their own referent brethren.

Ideological dispositions often correlate with the extent to what insurgent groups engage in indiscriminate and ruthless tactics. Ideologies that present a hard boundary between those who belong and others facilitate indiscriminate violence and are also likely to be permissive of reprehensible acts such as recruitment of minors or enslavement (Asal and Rethemeyer 2008). Ideologies that have a universal appeal are likely to be more discriminate and more vulnerable to losing legitimacy. Leftist and environmentalist ideologies, for example, seek to bring new members into the fold and see individuals as potential converts rather than members of the out group. Religious fundamentalism allows othering by vilifying those outside of the religious group and sometimes even casting them as sub-human (Juergensmeyer 2003). Religious ideologies may portray non-adherents as a legitimate target and justify atrocities against them (Binetti 2015). Ethno-nationalist groups are secular and appeal to an earthly rather than supernatural audience, making it harder for them to legitimate violence on divine grounds. However, these groups also have a strong othering component. Ethnicity provides a convenient metric for selecting targets of violence, where victims can be identified by cultural traits such as linguistic or racial grouping (Bloom 2003). It comes to no surprise, therefore, that insurgent groups involved in human trafficking have targeted representatives of ideologically opposed groups or religions. The insurgent groups’ justification for enslavement, sexual violence, and human trade have often been buttressed by the “othering” rhetoric toward the targeted victims (Kenny and Malik 2019).

H3: Religious and ethnic organizations are more likely to engage in human trafficking.

Insurgent groups that lack territorial control are more likely to turn to civilian targeting in order to compensate for asymmetric weakness against the state actor (Asal, Brinton, and Schoon 2015; Kenney 2007; De La Calle and Sanchez-Cuenca 2015). On the one hand, control over vast swathes of land generates greater demand for resources since organizations must muster more personnel to solidify and maintain command over land. On the other hand, it grants insurgent groups better access to resources and allows them to move personnel and goods within the territories they control without the danger of detection by state forces. Insurgent groups may up the ante in terms of atrocities committed as their territorial control diminishes. When insurgents suffer battlefield losses, including the loss of territory, they may also experience the shortage of new recruits: civilians flee the area of operations and potential members may avoid joining a losing group. These situations may necessitate forceful recruitment, including by means of human trafficking (Haer, Faulkner, and Whitaker 2020).

H4: Limited and diminishing territorial control are associated with higher rates of human trafficking.

From the literature on rebel groups’ violence toward non-combatants we know that violent groups are more likely to use coercion against civilians if they are threatened with the presence of an active rivalry (Metelits 2009). An active rivalry is present if violent organizations compete over the same piece of territory or have competing claims to represent the same referent social group. When a violent group confronts other organizations on its territory, it is forced into a competition for the same pool of resources. Rivalry with other violent organizations compels groups to engage in outbidding, whereby groups opt for more brutal tactics to jockey for control over limited resources (Bloom 2004). Scholars posit that outbidding motives arise in the face of steep competition among groups for the same constituency (Stanton 2019). Groups amplify violence in order to signal their resolve and attract popular support (Bloom 2005; Chenoweth 2010; Conrad and Greene 2015; Kydd and Walter 2006). Outbidding animates groups to not only commit more attacks but also to adopt more brutal tactics. While scholarship has been preoccupied with civilian targeting as a form of brutality, we can generalize these insights to suggest that inter-group rivalry heralds other types of atrocities, such as trafficking in humans.

H5: Organizations facing active rivals are more likely to engage in human trafficking.

Human trafficking requires more logistical infrastructure than episodic crimes that do not require organizational investment (Asal, Rethemeyer, and Schoon 2019). An organization is more likely to have in-house capabilities and connections to criminal groups if it engages in other types of illicit activities. Insurgent groups that raise significant revenue from crime have fewer incentives to restrain abusive behavior, including human trafficking. On the other hand, insurgent groups that lack steady funding tend to rely more on local population to provide financial support. These groups, therefore, have a greater incentive to refrain from abusing civilians (Haer, Faulkner, and Whitaker 2020). Organizations with a history of involvement in the drug trade are particularly well equipped to engage in human trafficking. Drug trafficking has been compared to a kind of “plough” that leaves “burrows” that can be exploited for trafficking in other illicit items, include human trade. Insurgent organizations involved in drug trafficking tend to diversify their activities in order to shield profits from government crackdowns (Shelley 2020).⁵ They can harness the same know-how and skills used to transport drugs across borders and avoid state scrutiny. And, they can use the same drug transport routes for human trade. For example, North African groups have exploited the turmoil in the wake of the Arab Spring to move both drugs and people.

H6: Organizations engaged in drug trafficking are more likely to engage in human trafficking.

Insurgent groups have been known to develop in-house operational capabilities for carrying out successful criminal operations by learning from their criminal counterparts. Alliances with other violent organizations enhance group capabilities and also make it easier for groups to operate across borders (Cornell and Jonsson 2014). Along these lines, previous work finds that network embeddedness augments the probability that violent groups engage in the drug trade and other forms of organized crime (Asal, Brinton, and Schoon 2015; Asal, Rethemeyer, and Schoon 2019). Terrorist groups can and have learned from their terrorist counterparts through training and other contact. Some Boko Haram members, for example, have received their training in the ISIS camps and fought and trained alongside Al Qaeda in Islamic Maghreb. Through these shared experiences of training and combat, members of one group can learn about the benefits of human trafficking to their organization from the trafficking experiences of their counterparts. Working together means greater efficiency whereby violent groups can benefit from the specialized skills of other groups (Shelley and Picarelli 2005). These alliance ties may be particularly beneficial insofar as the network in which the organization is embedded consists of other organizations with experiences with human trafficking. Following the footsteps of Asal, Rethemeyer, and Schoon (2019), we generalize this claim to look at ties with organizations involved in organized crime.

H7: Organizations with larger networks of allies are more likely to engage in human trafficking.

H8: Organizations with ties to criminal networks are also more likely to engage in human trafficking.

Research Design

We present a new dataset on human trafficking coded for a sample of 157 insurgent organizations for 1998 to 2015. We obtained our list of insurgent organizations from the Big Allied and Dangerous Insurgencies (BAAD2I) project. The BAAD2I project defines insurgent organizations as non-state groups engaged in armed combat, which perpetrated at least twenty-five battle-related deaths according to the Uppsala Conflict Data Program (UCDP) and Battle Deaths dataset for the period 1998 to 2012.⁶ The current version of BAAD2I records information on organizational behaviors and traits for 140 insurgent groups that were active from 1998 to 2012. Taking into account that not all organizations are active for the full timespan, the original BAAD2I yields an unbalanced panel of 1,386 group-year observations across 49 states. We then married our human trafficking indicators to the BAAD2I dataset (Asal, Rehemeyer, and Schoon 2019). We also incorporated state-level variables from various meta-databases including the Quality of Government (QoG) project (Dahlberg et al. 2018).

Following the development of a coding scheme, a team of research assistants conducted Lexis Nexis (now NexisUni,) guided news search of insurgent and terrorist organizations. We developed search algorithms and relied on the strings of group names developed and tested by the BAAD2 researchers to scan all available academic and news sources. Each group was analyzed by two researchers and supervised by faculty mentors for consistency in coding.

For the purpose of the study, we created four binary variables. The first is a human trafficking (H_Traff) variable denoting whether or not the group engaged in human trafficking in a given year. The coders relied on the Palermo Protocol’s definition of human trafficking. In light of this definition, the transportation of persons is not required for trafficking to take place. The key element of the definition is exploitation, which is typically sexual or labor (but could also be for organ removal). The use of child soldiers (although regulated by different international instruments) falls within trafficking as well, if they have been compulsorily recruited into the armed forces. H_Traff is the overarching variable that captures four types of human trafficking activities: forced recruitment, sexual exploitation, forced labor, and kidnapping. The kidnapping variable was transferred from the BAAD2 dataset. Forced Recruitment for Armed Combat (Force_recruit) is a dichotomous variable coded “1” for group-years with insurgent groups engaged in forced recruitment and “0” otherwise (“99” if unknown). Sexual exploitation (Sex_exploit) was coded “1” if the organization forcibly recruited individuals by means of false advertisement or propaganda, deception, threat of force, or force and coercion for the purpose of sex servitude, or forced marriages. Slavery is defined as “the total control of one person by another for the purpose of economic [labor] exploitation.” It entails control by violence and denial of all of individual freedom for making money for someone else (Bales 2004, 6).⁷

Substantively, we aimed to identify patterns and process rather than lone incidents. Accordingly, we made sure to code cases of ongoing and repeated human trafficking activity. For instance, a lone incident of abduction would not warrant a “1” coding for kidnapping but endemic and repeated use of abductions toward group aims would.

We also created a modified human trafficking variable. This is narrower in that it takes on the value of “1” if any of the three sub-indicators other than kidnapping were coded “1.” This modified variable is premised on the idea that kidnapping may be a conduit for human trafficking but is a distinct, if related, crime. The Trafficking Protocol of 2000 defines human trafficking by the act, the means, and the purpose. While kidnapping is an act of trafficking in the sense of transporting, transferring, harboring, or receiving persons, the purpose does not always conform to the definition of trafficking as: “exploitation by, inter alia, prostitution of others or other forms of sexual exploitation, forced labor or services, slavery or practices similar to slavery, servitude, or organ removal.” Therefore, some forms of kidnapping may be divorced from the core of human trafficking.

The BAAD2 dataset contains information on a variety of organizational attributes of insurgent groups. The following independent variables are used for testing the hypotheses:

Organizational size. The group size variable is a categorical variable with several categories assigned to numerical ranges of the group’s members (1: 1 to 9 members; 2: 10 to 99 members; 3: 100 to 999 members; 4: 1,000 to 9,999 members; and 5: 10,000+ members).

Change in group size is a dummy variable that we created from the Organizational Size variable. It answers the question, “Has the group’s size decreased compared to the previous year?” If “yes,” we coded the decrease as “1,” and “0” otherwise.

Group leadership is a categorical variable with 0 denoting leaderless organizations with no defined leadership; 1—multiple leaders with independent power; 2—Governing Council united multiple leaders who vote on orders using a governing body; 3—hierarchical leadership consisting of multiple leaders organized as a chain of command; 4—single leader who controls the entire organization.

Organizational Ideology: Ideology refers to the guiding principles of the group. Insurgent groups belong to at least one ideological category with the possibility of multiple designations (i.e., ethnic separatist). In order to examine the impact of ideology on human trafficking, we draw on the ideological categories presented in BAAD2: ethnic, separatist, religious, and leftist.

Territorial control measures whether an organization controls territory of its own (“0” if does not control; “1” if controls territory).

Territorial loss is a dummy variable that we created on the basis of the Territorial Control measures. If the group lost territory compared to the size of the territory it controlled a year prior, we coded these organization-years as “1”; if there was no change, “0,” and “−1,” if the organization gained territory.

Funding includes a number of dichotomous variables denoting whether a group engages in various criminal forms of funding: Drug Trafficking; Extortion; Kidnapping for Ransom; Smuggling; and Robbery.

To capture alliance ties, we incorporated a measure of network connectivity from BAAD, which updates and extends the network connectivity measure in BAAD1 by creating an annualized measure. Labeled a_degree, this indicator gives the number of ties each insurgent organization has to any other organization in the data. To probe H8, we include the count of alliance ties with organizations engaged in organized crime.

To capture an active rivalry, we incorporate the rivalry measure from BAAD2. Dubbed r_degree, this indicator counts the number of rival organizations per each insurgent group.

For the baseline model, we included only group-level characteristics. For the extended model, we incorporated a number of country-level variables that have been linked empirically and conceptually to the human trade.

Findings

In general, most insurgent organizations committed more than one form of human trafficking activity during their lifespan or during the time period under consideration (1998 to 2015). Of 209 insurgent groups, we found that 137 have been engaged in some form of human trafficking. This corresponds to 1,001 organization years, or 57 percent of the data.

The most common form of human trafficking is kidnapping: 46% of our organization-years report kidnapping, followed by forced recruitment, corresponding to 32% of organization-years. Sexual exploitation comprises 21% of the cases. Slavery is the rarest form of human trafficking, amounting to 10.2% of organization-years. Table 1 below lists these organizations along with the number of years in which they committed human trafficking.

Table 1.

List of Militant Groups Committing Human Trafficking.

Group Name	Number of Years Committing Trafficking
Abu Sayyaf Group (Asg)	18
Al-Aqsa Martyrs Brigade	14
Al-Fatah	4
Al-Gama’at Al-Islamiyya (IG)	5
Al-Ittihaad Al-Islami (AIAI)	5
Al-Qa’ida	18
All Tripura Tiger Force (ATTF)	15
Democratic Front for the Liberation of Rwanda (FDLR)	16
Baloch Liberation Army (BLA)	8
Black Widows	6
Eastern Turkistan Islamic Movement (ETIM)	17
Free Aceh Movement (GAM)	8
The Front for the Liberation of the Cabinda Enclave—Renewed (FLEC)	2
Hamas (Islamic Resistance Movement)	14
Hizballah	12
Liberation Tigers Of Tamil Eelam (Ltte)	12
Lord’s Resistance Army (LRA)	18
Moro National Liberation Front (MNLF)	9
Movement for Democracy and Justice in Chad (MDJT)	3
National Democratic Front Of Bodoland (Ndfb)	10
National Liberation Army of Colombia (ELN)	18
National Liberation Front of Tripura (NLFT)	18
Islamic State Of Iraq And Al Sham (Isis)	11
Oromo Liberation Front	7
Purbo Banglar Communist Party	7
Palestinian Islamic Jihad (PIJ)	18
People’s War Group (PWG)	4
Popular Front For The Liberation Of Palestine (Pflp)	8
Popular Liberation Army (Epl)	10
Popular Resistance Committees	4
Real Irish Republican Army (RIRA)	12
Revolutionary Armed Forces Of Colombia (FARC)	18
Revolutionary United Front (RUF)	5
Shining Path (SL)	18
Sudan People’s Liberation Army (SPLA)	15
Taliban	16
National Union For The Total Independence Of Angola (Unita)	1
United Liberation Front Of Assam (Ulfa)	12
United Tajik Opposition (UTO)	2
Ogaden National Liberation Front (ONLF)	15
Communist Party Of India—Maoist (Cpi-M)	12
National Socialist Council of Nagaland-Isak-Muivah (NSCN-IM)	10
Allied Democratic Forces (ADF)	12
Restoration Council of Shan States	14
Shan State Progressive Party	1
National Socialist Council of Nagaland-Khaplang (NSCN-K)	6
People’S Liberation Army (Pla)	8
United National Liberation Front (Unlf)	4
Baloch Liberation Front (Blf)	6
National Council for Defense of Democracy-Forces For The Defense Of Democracy (NCDD-FDD)	6
Niger Delta People’s Volunteer Force (NDPVF)	2
People’S Revolutionary Party Of Kangleipak (Prepak)	7
People’s United Liberation Front (PULF)	6
Free Syrian Army	5
Revolutionary Front for an Independent East Timor (FRETILIN)	2
South Sudan Liberation Army (Ssla)	1
United Baloch Army (Uba)	3
Sudan People’S Liberation Movement In Opposition (Splm-Io)	3
Patriotic Movement of Ivory Coast (MPCI)	2
Tehrik-i-Taliban Pakistan (TTP)	7
Boko Haram	7
Tehreek-e-Nafaz-e-Shariat-e-Mohammadi (TNSM)	3
Forces Nouvelles (FN)	2
Movement for the Liberation of Congo (MLC)	7
National Liberation Army (NLA) (Macedonia)	4
Movement of Niger People for Justice (MNJ)	3
Baloch Republican Army (BRA)	5
National Congress for the Defense of the People (CNDP)	1
Movement for Democracy in Liberia (MODEL)	2
Somali Reconciliation and Restoration Council (SRRC)	2
Movement of Democratic Forces of Casamance	13
The Northern Alliance (or United Islamic Front for Salvation of Afghanistan - UIFSA)	2
Union of Democratic Forces	6
Union of Forces for Democracy and Development (UFDD)	1
West Side Boys	4
Sudan Liberation Movement	10
National Alliance (Chad)	1
Bangsamoro Islamic Freedom Fighters (BIFF)	4
Sudan Liberation Movement/Army-Minni Minawi Faction	2
Myanmar National Democratic Alliance	1
Democratic Karen Buddhist Army Brigade 5	2
South Sudan Defence Movement/Army	3
Popular Front For National Renaissance (Pfnr)	1
Sudan People’s Liberation Movement-North	4
Movement for Oneness and Jihad in West Africa (MUJAO)	5
Sudan Revolutionary Front	5
National Democratic Front Of Bodoland-Songbijit	3

Table 2 summarizes our hypotheses, giving the corresponding indicator(s) the models deploy, followed by the direction of effect, positive (+) or negative (−), postulated by the hypothesis.

Table 2.

Descriptive Statistics.

Variable Names	Observations	Mean	Std. Dev.	25th Percentile	Median	75th Percentile	Min	Max
Human Trafficking (HT) Indicators
Human Trafficking (All)	1,757	0.495	0.495	0	1	1	0	1
Human Trafficking (Narrow)	1,757	0.486	0.486	0	0	1	0	1
Forced Recruitment	1,757	0.468	0.468	0	0	1	0	1
Sexual Exploitation	1,757	0.409	0.409	0	0	0	0	1
Slavery	1,757	0.304	0.304	0	0	0	0	1
Kidnapping	1,757	0.465	0.499	0	0	1	0	1
Independent Variables
Group Characteristics	Observations	Mean	Std. Dev.	25th percentile	Median	75th percentile	Min	Max
Organization Age	1,353	2.686	0.709	0	2	3	0	4
Size Loss	1,757	0.019	0.136	0	0	0	0	1
Territorial Control	1,353	0.247	0.431	0	0	0	0	1
Territorial Change	1,214	0.006	0.288	1	0	0	1	1
Hierarchical Organization	1,353	0.789	0.408	0	0	1	0	1
Religious Ideology	1,353	0.345	0.476	0	0	1	0	1
Ethnic Ideology	1,353	0.551	0.498	0	1	1	0	1
Leftist Ideology	1,353	0.208	0.406	0	0	1	0	1
Rivalries	1,353	0.327	0.645	0	0	0	0	4
Alliances with criminal groups	1,215	0.436	0.969	0	0	1	0	10
Alliances	1,353	0.834	1.611	0	0	1	0	15
Group’s Age	1,757	17.853	14.841	5	14	28	0	68
Country Covariates
Human Trafficking Flows (UNODC)	1,671	2.445	1.525	1	3	4	0	5
HT Policy Index	1,700	8.923	2.386	7	9	11	4	14

Table 3 details the summary statistics, including range, mean, and standard deviation for outcome and independent variables. Given that our outcome variables are binary, and our independent variables are binary or ordinal, we also present the median and 25th and 75th percentile values for all variables, to give a meaningful assessment of variables’ central tendencies and spread. Our independent variables pertain to organizational traits that we use in the main analysis. In addition, we computed cross-correlations and variance inflation factors (VIFs). Supplemental Appendix Tables A2 and A3 in our supplementary file contain the correlation matrices for our outcome indicators and organization indicators, respectively. All VIF values remained below 2.5, easing potential concerns about multicollinearity.

Table 3.

Hypotheses and Expectations.

Hypothesis	Indicator(s)	Expectation
H1	Organization’s Size; Size Loss	+;+
H2	Hierarchical Organization	−
H3	Religious Ideology; Ethnic Ideology	+
H4	Territorial Control; Territorial Loss	+; +
H5	Rivalry	+
H6	Drug Trafficking	+
H7	Alliances; Alliances with Criminal Orgs	+

Table 4 presents the full logistic regression results for the main and narrow human trafficking variables followed by the results for the four sub-indicators. We run the same analyses on sex_exploit, forced_recruit, slavery, and kidnap, in models 3, 4, 5, and 6, respectively.

Table 4.

Effects of Organization Characteristics on Human Trafficking Involvement.

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
	HTAll	HTNarrow	ForcedRecruitment	SexualExploitation	Slavery	Kidnapping
Organization’s Age	0.018	0.025+	-0.004	0.018	0.028*	-0.005
	(0.012)	(0.014)	(0.014)	(0.015)	(0.014)	(0.009)
Hierarchical Organization	0.276	0.454	0.618	0.276	0.144	0.009
	(0.322)	(0.400)	(0.449)	(0.424)	(0.540)	(0.311)
Organization Size	0.042	0.193	0.324	0.294	0.375+	-0.022
	(0.177)	(0.216)	(0.232)	(0.239)	(0.228)	(0.175)
Size Loss	0.402	0.925*	0.850+	0.717+	0.838+	0.337
	(0.476)	(0.432)	(0.451)	(0.392)	(0.492)	(0.464)
Alliances	0.390***	0.171*	-0.156	0.226**	-0.306	0.259**
	(0.106)	(0.077)	(0.239)	(0.079)	(0.211)	(0.087)
Rivalries	-0.042	0.001	-0.074	0.032	-0.211	0.141
	(0.214)	(0.243)	(0.294)	(0.240)	(0.295)	(0.167)
Drug Trafficking	0.990*	0.452	0.474	0.249	0.601	1.397***
	(0.497)	(0.457)	(0.508)	(0.438)	(0.715)	(0.398)
Religious Ideology	0.332	0.025	0.413	−0.155	0.867	0.475
	(0.350)	(0.439)	(0.591)	(0.463)	(0.680)	(0.324)
Ethnic Ideology	0.272	-0.009	-0.233	0.290	0.118	0.294
	(0.336)	(0.357)	(0.419)	(0.391)	(0.554)	(0.324)
Leftist Ideology	0.330	0.287	0.615	0.287	0.216	0.567
	(0.463)	(0.472)	(0.470)	(0.503)	(0.486)	(0.414)
Territorial Control	1.033**	1.474***	1.027*	1.583***	1.118*	0.549
	(0.384)	(0.363)	(0.406)	(0.367)	(0.536)	(0.364)
Territorial Loss	0.419*	0.638*	0.373	0.574*	0.407	0.049
	(0.265)	(0.256)	(0.266)	(0.263)	(0.326)	(0.255)
Constant	−1.173*	−2.459**	−3.055***	−2.942***	-4.436***	-0.905
	(0.597)	(0.776)	(0.890)	(0.883)	(0.903)	(0.580)
Likelihood Ratio	−720.225	−708.256	−576.670	−664.207	-385.769	-752.130
Model Fit	0.000	0.000	0.007	0.000	0.003	0.000
N	1,214	1,214	1,214	1,214	1,214	1,214

+p < .10, *p < .05, **p < .01, ***p < .001.

Several patterns are worth mentioning. Human trafficking in general is driven by network embeddedness (alliance ties) and territorial control. For both operationalizations of human trafficking, territorial gain exerts a significant effect. When insurgents are squeezed out of lands they once controlled and feel the adversarial groups, typically, the state military, encroaching on their territories, they resort to more brutal tactics (CTED 2018). Our findings parallel broader empirical patterns which show that territorial control incentivizes rebel groups to engage in civilian targeting (Stanton 2019), especially when the territory over which groups hold dominion contains few political constituents (Stewart and Liou 2016). Our findings show that similar motives propel not just civilian targeting but also victimization through human trafficking. Groups losing ground are similarly motivated to partake in the human trade, which somewhat mirrors the finding that contestation over territory among groups augurs violence against civilians (de la Calle 2017).

Alliances augment group capacity to undertake trafficking and alleviate logistical difficulties. Through alliance networks, organizations can transfer skills and know-how. Beyond that, organizations may be able to trade in humans among themselves, selling victims they abducted into forced domestic servitude or sexual labor to other organizations. Networks can also assist organizations in transporting victims across bases that different organizations in the same network control. Just as ties between criminal syndicates and terrorist organizations permit transferal of knowledge and skills, alliances among insurgent organizations should be conducive to mimicking and emulation (Makarenko 2004; Asal, Rethemeyer, and Schoon 2019). Convergent milieus with criminal organizations aid transmission of knowledge. Individuals with a criminal history can procure weapons more easily, are skilled at remaining under the radar, and further, have greater tolerance for violent acts (Basra, Neumann, and Brunner 2016).

There are several interesting differences between types of human trafficking in terms of how organizational covariates relate to patterns of trafficking. Alliance ties increase the probability that groups engage in all forms of human trafficking other than slavery and sexual exploitation. The latter are perhaps the two that laymen associate with human trafficking, sometimes referred to as the modern slave trade (Shelley 2014, 2020). At the risk of speculation, legitimacy may be at stake when organizations trade in flesh. Bowersox (2019) stresses that rebels that require the support and loyalty of the local population shy away from human trafficking. Sexual exploitation and slavery flout normative taboos and estrange populations, and therefore groups that commit these types of crimes endanger alliance ties. Therefore, just as concerns over potential loss of popular legitimacy constrains organizational behavior to some extent (Tokdemir and Akcinaroglu 2016), concerns over potential loss of allies may render some atrocities beyond bounds for organizations.

None of our ideological variables attain conventional levels of statistical significance. Religious ideology and ethnic ideology flip signs across models and do not lend the proposed positive effects. Of other organizational traits, only age and size obtain a modest positive effect in Model 5. Lastly, while hierarchical leadership imposes discipline on rebel organizations and delimits the use of sexual violence (Cohen 2016; Wood 2009), leadership structure has no influence on whether insurgents partake in human trafficking. The departure from previous findings may owe to differences in the way BAAD2I conceptualizes hierarchical leadership and Wood’s notion of strong leadership (Wood 2009).

Logistic regression coefficients do not lend themselves easily to substantive interpretation. Accordingly, we evaluate predicted probabilities of our outcome variables when we move the regressors of interest across their full range. We consider only the regressors that yield significant effects: alliances, territorial control, and territorial change. In separate models, we reexamine the same models in Table 5 by incorporating an indicator that counts the number of alliances with organizations that participate in crime. We vary these variables across their full range, from 0 to 15 for the total count of alliances, and from 0 to 10 for the count of alliance ties with organizations that partake in crime. We also consider changes in predicted probabilities from changing territorial control from 0 to 1 and territorial loss from −1 (territorial gain) to 1 (loss). Table 5 displays these predicted probabilities across all four sub-indicators and the main and alternative human trafficking indicators.

Table 5.

Predicted Probabilities of Human Trafficking for Maximal Change in Select Variables.

Outcome Variables	Alliances	Alliances w/ criminal orgs	Territorial Control	Territorial Loss
Human trafficking (all)	0.449	0.4318	0.2168	0.1920
Human trafficking (narrow)	0.5246	0.4642	0.3520	0.2939
Sexual exploitation	−0.1876	−0.1648	0.1836	0.1150
Forced Recruitment	0.6454	0.5976	0.3648	0.2432
Slavery	−0.1102	−0.1024	0.1144	0.0661
Kidnapping	0.5282	0.5329	0.1356	0.0243

Note: Changes in predicted probabilities are reported when alliances and territorial control are moved from minimum to maximum and territorial control is moved from 0 to 1.

The insignificant predictions are displayed in italics. The general and specific alliance indicators exert mirroring effects on the probability of human trafficking. Moving these across the full range of alliance ties produces a 45% increase in the predicted probability of human trafficking. If we consider the narrower human trafficking variable, this number is 52.5%. Likewise, if we increase alliances with organizations participating in organized crime, we note a jump of 43% and 46% in predicted probabilities of human trafficking, with and without kidnapping, respectively. Alliances matter the most for forced recruitment. The predicted changes in probabilities are 64.5% and 59.7% respectively. Organizations that control territory have a 22% higher probability of partaking in trafficking. Territorial control boosts predicted probabilities for all forms but has the weakest effect on slavery. Territorial loss lends an increase in the probability of human trafficking for all forms other than slavery and sexual exploitation. This result is the most pronounced for forcible recruitment.

We graphically illustrate the combined effects of alliances and territorial control by plotting predicted probabilities of human trafficking across the full range of the number of alliances. We focus on these two indicators for several reasons. Conceptually, both determinants affect opportunity and motivations. Moreover, our findings mirror those of Asal, Rethemeyer, and Schoon (2019) who likewise find that territorial control and alliance networks influence insurgents’ participation in crime. Given that human trafficking is an important component of the crime-terrorism nexus (Shelley 2014, 2020), it is important to illustrate how determinants of crime-by-insurgents affect trafficking patterns. Finally, given the differing effects of alliances and territorial control in Asal, Rethemeyer, and Schoon (2019), we seek to illustrate the interactive effects of these determinants. Figure 1 displays these probabilities.

Figure 1.

Predicted probabilities of human trafficking by alliance ties and territorial control.

The blue and red lines chart predicted probabilities for organizations that command control of territory and those that do not. At first glance, we can see that territorial control proffers an advantage given limited network embeddedness. Absent alliance ties, organizations that lack territorial control have a predicted probability of 46.5% for engaging in human trafficking. This contrasts with 74.4% for organizations that do have territorial control. The gap between these two types of organizations starts to narrow once we hit five alliance ties. The gap in probability narrows to 7% difference at this stage. As we approach 10 alliances, both types of organizations converge to a 98% probability of engaging in the human trade. This pattern also demonstrates that alliance ties do the bulk of the heavy lifting in terms of the predicted probabilities that groups participate in human trafficking. That said, these results should be interpreted with caution. Only five organizations enjoy at least five alliance ties; and these are the same organizations that are able to cultivate and amass their alliance ties. Al Qaeda for example surfaces as the best-networked, and has grown its ties over time.

Figure 2 repeats the same exercise while focusing on the alternative alliance measure.

Figure 2.

Predicted probabilities of human trafficking by alliance ties with criminal organizations and territorial control.

Figure 2 sketches mirroring patterns to Figure 1. Absent territorial control, the likelihood of human trafficking stands at about 46% but climbs to 76% for organizations that enjoy territorial control. We should note that 75% of organizations are operating on their own and lack any tie. The same is true of ties with criminal organizations. Only four groups have more than four ties with criminal organizations. Not surprisingly then, the probability of human trafficking nears unity once alliance ties exceed six. Therefore, while the graphs portray that alliance ties would be the primary driving force, these effects are theoretical. In practice, only a select subset is embedded in networks to an extent that this would be the case. In other words, territorial control is integral for participation in the human trade.

Robustness Checks

We replicated our results using panel logistic regression (Supplemental Appendix Table A4), and with the alternate alliances variable (Supplemental Appendix Table A5). Whether we consider groups with ties to crime or all allies, it appears that friends, rather than foes, increase the likelihood of human trafficking involvement. In the rest of the supplementary analysis, we include country covariates pertaining to human trafficking: 1) The US Department of State tier scores for compliance with the US 2000 Victims of Trafficking and Violence Protection Act (TVPA). The scale ranges from one to three, with higher scores indicating non-compliance (United States Department of State 2010). 2) Cho et al. 3P Index: This measure gauges state efforts to combat trafficking along three dimensions (the three Ps): protection of victims, prevention of trafficking, and prosecution of perpetrators (Cho 2015).

Supplemental Appendix Table A6 documents the full list of our country covariates. Supplemental Appendix Table A7 shows that our findings on alliance ties and territorial control are resilient to the inclusion of country controls. The one noteworthy difference in these results is that the coefficient in rivalries obtains significance in the general human trafficking model as well as the models for slavery and kidnapping. Interestingly, neither the 3-P index nor the US tier score produce consistent or significant effects on human trafficking by violent non-state actors. Of the other country factors, high income returns a positive and significant coefficient. Supplemental Appendix Table A8 includes country fixed effects and controls for root factors of human trafficking such as: conflict, poverty, corruption, regime type, as well as indicators for women’s economic, social, and political rights from the CIRI project (Cingranelli, Richards, and Clay 2014). Our key findings are robust to the fuller specification.

Conclusion

In this paper, we introduce a new dataset of insurgents’ human trafficking patterns. In doing so, we complement existing case studies of human trafficking by ISIS, Boko Haram, Al-Shabaab, and Aby Sayyaf, among others. Our results are in similar spirit to the patterns of organized crime participation by insurgents (Asal, Rethemeyer, and Schoon 2019). In brief, territorial control and network embeddedness motivate decisions to participate in the human trade. One intriguing proposition advanced by Asal, Rethemeyer, and Schoon (2019) is that forms of crime differ in terms of their dependence on territorial control. Systematic crimes – such as drug trafficking — require a modicum of skill and resources but hinge on command over territory. In contrast, episodic crimes—such as robberies—are less dependent on territorial control. Our results indicate that there may be similar differences among types of human trafficking. Possibly, forced recruitment requires that groups have established numerous sites of operation that they can police and monitor. Once coerced into joining armed groups, victims must be insulated from detection and rescue by state agents. Sexual exploitation likewise requires that victims are sequestered away in hideouts. Beyond that, some forms of sexual exploitation require groups to engage in entrepreneurial illicit activities such as enacting forced marriages, setting up marketplaces for sexual labor, and maintaining sites for purchase of coerced sexual labor. These sites of activity need to be isolated from and immune to state penetration. In contrast, kidnapping is akin to robberies in having a sporadic element, and is thus less dependent on territorial control.

Territorial control has the twin effects of generating opportunity and greater need for resources (Kenney 2007). Plausibly then, groups that exert control over greater land area also require more resources to finance their operations. On the one hand, territorial control means a resource-hungry organization that turns to human trafficking for profit. This is in congruence with the greed motive. On the other hand, territory enlarges opportunity. Groups can move individuals with a lessened risk of detection and interception by state authorities.

Our findings also resonate with Asal, Rethemeyer, and Schoon’s (2019) emphasis on network embeddedness. Alliances expand group capabilities and magnify the probability that insurgents will engage in human trafficking. Theoretically, alliances can override the effects of territorial control by widening opportunity. Alliances also abet learning, tactical emulation, and diffusion of knowledge. For example, Boko Haram fighters are alleged to have learned human trafficking from their mentors, Al-Shabaab. However, alliances matter less for certain types of human trafficking: namely sexual exploitation and slavery. These patterns suggest that legitimacy may be at stake whereby alliances fear losing alliance ties if they engage in brutalities deemed abhorrent by other groups in their network.

Our results also show that territorial loss incentivizes organizations to resort to human trafficking. This is more acute for specific types of trafficking such as forced recruitment. Possibly, insurgents try to recoup the losses suffered on the battlefield by turning to brutal atrocities. Forcible recruitment grows the membership base, which partially makes up for lost territory. There is, therefore, an interesting interaction between territorial control and territorial change. Whereas the former pertains mostly to opportunity, the latter provides a motivational story.

While our analysis suggests that the patterns of violent non-state actors’ involvement in human trafficking are fueled by organizational factors, rather than by country level attributes, the role of organizational characteristics is theorized through the concepts of opportunity and motivation. Some sub-national sites, such as the refugee camps and makeshift prisons, which are not readily captured by the national level indices, present unique opportunity and motivation for terrorist and insurgent groups’ recruitment and victimization of the vulnerable populations (Cockayne and Walker 2016). Future research into human trafficking by violent non-state actors should consider the various characteristics of sub-national sites where insurgent groups operate and how they interact with the organizational features of violent actors.

Supplemental Material

Supplemental Material, sj-docx-1-jcr-10.1177_00220027211010904 - Human Trafficking-Terrorism Nexus: When Violent Non-State Actors Engage in the Modern-Day Slavery

Supplemental Material, sj-docx-1-jcr-10.1177_00220027211010904 for Human Trafficking-Terrorism Nexus: When Violent Non-State Actors Engage in the Modern-Day Slavery by Nazli Avdan and Mariya Omelicheva in Journal of Conflict Resolution

Supplemental Material

Supplemental Material, sj-zip-1-jcr-10.1177_00220027211010904 - Human Trafficking-Terrorism Nexus: When Violent Non-State Actors Engage in the Modern-Day Slavery

Supplemental Material, sj-zip-1-jcr-10.1177_00220027211010904 for Human Trafficking-Terrorism Nexus: When Violent Non-State Actors Engage in the Modern-Day Slavery by Nazli Avdan and Mariya Omelicheva in Journal of Conflict Resolution

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Nazli Avdan

Supplemental Material

Supplemental material for this article is available online.

Notes

References

Asal

Victor

Brinton

Milward H.

Schoon

Eric W.

. 2015. “When Terrorists Go Bad: Analyzing Terrorist Organizations’ Involvement in Drug Smuggling.” International Studies Quarterly 59 (1): 112–23.

Asal

Victor

Karl Rethemeyer

. 2008. “The Nature of the Beast: Organizational Structures and the Lethality of Terrorist Attacks.” The Journal of Politics 70 (2): 437–49.

Asal

Victor

Karl Rethemeyer

Schoon

Eric W.

. 2018. “Replication Data for: “Crime, Conflict and the Legitimacy Tradoff: Explaining Variation in Insurgents’ Particiation in Crime.” Harvard Dataverse, V1. Accessed February 20, 2020. https://doi.org/10.7910/DVN/JT6GFR

Asal

Victor

Karl Rethemeyer

Schoon

Eric W.

. 2019. “Crime, Conflict, and the Legitimacy Trade-off: Explaining Variation in Insurgents’ Participation in Crime.” The Journal of Politics 81 (2): 399–410.

Attah

C. E.

2016. “Boko Haram and Sexual Terrorism: The Conspiracy of Silence of the Nigerian Antiterrorism Laws.” African Human Rights Law Journal 16 (2016): 385–406.

Bales

Kevin

. 2004. Disposable People: New Slavery in the Global Economy. Berkeley, CA: University of California Press.

Basra

Rajan

Neumann

Peter

Brunner

Claudia

. 2016. Criminal Pasts, Terrorist Futures: European Jihadists and the New Crime-terror Nexus. London, UK: International Centre for the Study of Radicalisation and Political Violence, pp. 29–34. Accessed October 11, 2020. https://icsr.info/wp-content/uploads/2016/10/ICSR-Report-Criminal-Pasts-Terrorist-Futures-European-Jihadists-and-the-New-Crime-Terror-Nexus.pdf.

Bigio

Jamille

Vogelstein

Rachel

. 2019. The Security Implications of Human Trafficking. New York: Council on Foreign Relations.

Binetti

Ashley

. 2015. “A New Frontier: Human Trafficking and ISIS’s Recruitment of Women from the West.” INFORMATION2ACTION, Georgetown Institute for Women, Peace & Security. Georgetown University. Accessed February 29, 2020. https://giwps.georgetown.edu/wp-content/uploads/2017/10/Human-Trafficking-and-ISISs-Recruitment-of-Women-from-the-West.pdf.

10.

Bloom

Mia M.

2003. “Ethnic Conflict, State Terror and Suicide Bombing in Sri Lanka.” Civil Wars 6 (1): 54–84.

11.

Bloom

Mia M.

2004. “Palestinian Suicide Bombing: Public Support, Market Share and Outbidding.” Political Science Quarterly 119 (1): 61–88.

12.

Bloom

Mia M.

2005. Dying to Kill: The Allure of Suicide Terror. Columbia University Press.

13.

Bloom

Mia M.

2007. “Female Suicide Bombers: A Global Trend.” Daedalus 136 (1): 94–102.

14.

Bowersox

2019. “Does Human Trafficking Extend Conflict Duration?” Journal of Human Trafficking 5 (4): 267–80.

15.

Campana

Paula

Varese

Federico

. 2016. “Exploitation in Human Trafficking and Smuggling.” European Journal of Crime Policy Research 22:89–105.

16.

Chenoweth

2010. “Democratic Competition and Terrorist Activity.” Journal of Politics 72 (1): 16–30.

17.

Cho

Seo-Young

. 2015. “Evaluating Policies Against Human Trafficking Worldwide: An Overview and Review of the 3P Index.” Journal of Human Trafficking 1 (inaugural edition): 86–99.

18.

Choi-Fitzpatrick

2016. The Good, the Bad, the Ugly: Human Rights Violators in Comparative Perspective. Journal of Human Trafficking 2 (1): 1–14.

19.

Cingranelli

David L.

Richards

David L.

Clay

K. Chad

. 2014. “The CIRI Human Rights Dataset.” Version 2014.04.14 . Accessed February 20, 2020. http://www.humanrightsdata.com.

20.

Clarke

Colin P.

2015. Terrorism, Inc.: The Financing of Terrorism, Insurgency, and Irregular Warfare. Santa Barbara, CA: Praeger Security International.

21.

Cockayne

James

Walker

Summer

. 2016. Fighting Human Trafficking in Conflict: 10 Ideas for Action by the United Nations Security Council. New York: UN University. Accessed October 12, 2020. http://collections.unu.edu/eserv/UNU:5780/UNUReport_Pages.pdf.

22.

Cohen

Dara Kay

. 2013. “Explaining Rape During Civil War: Cross-national Evidence (1980-2009).” American Political Science Review 107 (3): 461–77.

23.

Cohen

Dara Kay

. 2016. Rape During Civil War. Cornell University Press.

24.

Conrad

Greene

. 2015. “Competition, Differentiation, and the Severity of Terrorist Attacks.” Journal of Politics 77 (2): 546–61.

25.

Cornell

Svante E.

2009. “The Interaction of Drug Smuggling, Human Trafficking and Terrorism.” In Human Trafficking and Human Security, edited by Jonsson

Anna

, 60–78. New York: Routledge.

26.

Cornell

Svante E.

Jonsson

Michael

. 2014. “The Nexus of Crime and Conflict.” In Conflict, Crime, and the State in Postcommunist Eurasia, edited by Cornell

Svante

Jonsson

Michael

, 1–22. Philadelphia, PA: University of Pennsylvania Press.

27.

Crawford

2017. “International Sex Trafficking.” Women & Therapy 40 (1-2): 101–22.

28.

CTED (Counter-Terrorism Committee Executive Directorate). 2018. “Identifying and Exploring the Nexus between Human Trafficking, Terrorism, and Terrorism Financing.” Accessed November 1, 2020. https://www.un.org/sc/ctc/wp-content/uploads/2019/02/HT-terrorism-nexus-CTED-report.pdf.

29.

Dahlberg

Stefan

Holmberg

Sören

Rothstein

Pachon

Natalia Alvarado

Svensson

Richard

. 2018. “The Quality of Government Basic Dataset.” Version Jan18. University of Gothenburg: The Quality of Government Institute. Accessed August 20, 2020. http://www.qog.pol.gu.se. doi:10.18157/QoGBasJan18.

30.

de Brouwer

A. M.

de Volder

Paulussen

. 2020. “Prosecuting the Nexus between Terrorism, Conflict-related Sexual Violence and Trafficking in Human Beings Before National Legal Mechanisms: Case Studies of Boko Haram and Al-Shabaab.” Journal of International Criminal Justice 18 (2): 499–516.

31.

De la Calle

2017 “Compliance vs. Constraints: A Theory of Rebel Targeting in Civil War.” Journal of Peace Research 54 (3): 427–41.

32.

De La Calle

Luis

Sanchez-Cuenca

Ignacio

. 2015. “How Armed Groups Fight: Territorial Control and Violent Tactics.” Studies in Conflict and Terrorism 38 (10): 795–813.

33.

Dishman

Chris

. 2001. “Terrorism, Crime, and Transformation.” Studies in Conflict & Terrorism 24 (1): 43–58.

34.

Dishman

Chris

. 2005. “The Leaderless Nexus: When Crime and Terror Converge.” Studies in Conflict and Terrorism 28 (3): 237–52.

35.

Fanusie

Yaya J.

Entz

Alex

. 2017. “Hezbollah: Financial Assessment.” Foundation for Defense of Democracies: Center on Sanctions & Illicit Finances (September 2017). Accessed February 25, 2020. https://s3.us-east-2.amazonaws.com/defenddemocracy/uploads/documents/CSIF_TFBB_Hezbollah.pdf.

36.

Farley

Alexander

. 2018. “The New Slave Trade: Migration, Trafficking, and Terrorists in Libya: Wilson Center: New Security Beat, 29 August.” Accessed February 23, 2020. https://www.newsecuritybeat.org/2018/08/slave-trade-migration-trafficking-terrorists-libya/.

37.

FATF-APG. 2018. Financial Flows from Human Trafficking. Paris, France: FATF. www.fatf-gafi.org/publications/methodandtrends/documents/human-trafficking.html

38.

Freeman

Michael

. 2011. “The Sources of Terrorist Financing: Theory and Typology.” Studies in Conflict and Terrorism 34 (6): 461–75.

39.

Haer

Faulkner

C. M.

Whitaker

B. E.

. 2020. “Rebel Funding and Child Soldiers: Exploring the Relationship between Natural Resources and Forcible Recruitment.” European Journal of International Relations 26 (1): 236–62.

40.

Hernandez

Joel

. 2013. “Terrorism, Drug Trafficking, and the Globalization of Supply.” Perspectives on Terrorism 7 (4). Accessed February 23, 2020. http://www.terrorismanalysts.com/pt/index.php/pot/article/view/281/html.

41.

Hutchinson

Steven

O’Malley

Pat

. 2007. “A Crime-terror Nexus? Thinking on Some of the Links between Terrorism and Criminality.” Studies in Conflict and Terrorism 30 (12): 1095–107.

42.

Juergensmeyer

Mark

. 2003. Terror in the Mind of God: The Global Rise of Religious Violence, 3rd ed. Berkeley, CA: University of California Press.

43.

Kara

Siddharta

. 2009. Sex Trafficking: Inside the Business of Modern Slavery. New York: Columbia University Press.

44.

Kara

Siddharta

. 2011. “Supply and Demand: Human Trafficking in the Global Economy.” Harvard International Review 33 (2): 66–71.

45.

Kenney

Michael

. 2007. “The Architecture of Drug Trafficking: Network Forms of Organization in the Colombian Cocaine Trade.” Global Crime 8 (3): 233–59.

46.

Kenny

Coman

Malik

Nikita

. 2019. “Trafficking Terror and Sexual Violence: Accountability for Human Trafficking and Sexual and Gender-based Violence by Terrorist Groups under the Rome Statute.” Vanderbilt Journal of Transnational Law 52:43.

47.

Kloer

Amanda

. 2009. “Human Trafficking is Al-Qaeda’s New Business Model.” December 20. Accessed February 23, 2020. http://news.change.org/stories/human-trafficking-is-al-qaeda-s-new-business-model.

48.

Kupatadze

Alexander

Argonamiz

Javier

. 2019. “Introduction to Special Issue – Understanding and Conceptualizing European Jihadists: Criminals, Extremists, or Both.” The European Journal of Criminology 16 (3): 261–77.

49.

Kydd

Andrew H.

Walter

Barbara F.

. 2006. “The Strategies of Terrorism.” International Security 31 (1): 49–80.

50.

Llana

Sara Miller

. 2010. “Mexico Massacre: How the Drug War is Pushing Cartels into Human Trafficking.” Accessed February 23, 2020. http://www.csmonitor.com/World/Americas/2010/0830/Mexico-massacre-How-the-drug-war-is-pushingcartels-into-human-trafficking.

51.

Makarenko

Tamara

. 2004. “The Crime-terror Continuum: Tracing the Interplay between Transnational Organised Crime and Terrorism.” Global Crime 6:129–45.

52.

Malik

Nikita

. 2017. Trafficking Terror: How Modern Slavery and Sexual Violence Fund Terrorism. London, UK: The Henry Jackson Society. Accessed February 23, 2020. http://henryjacksonsociety.org/wp-content/uploads/2017/10/HJS-Trafficking-Terror-Report-web.pdf

53.

Metelits

C. M.

2009. “The Consequences of Rivalry: Explaining Insurgent Violence Using Fuzzy Sets.” Political Research Quarterly 62 (4): 673–84.

54.

Paul

Christopher

Clarke

Colin

Grill

Beth

. 2010. Victory Has a Thousand Fathers: Sources of Success in Counterinsurgency. Santa Monica, CA: RAND Corporation.

55.

Pearson

Elizabeth

. 2018. “Wilyat Shahidat: Boko Haram, the Islamic State, and the Question of the Female Suicide Bomber.” In Boko Haram Beyond the Headlines: Analyses of Africa’s Enduring Insurgency, 33–52. West Point, NY: Combating Terrorism Center at West Point (CTC). Accessed February 23, 2020. https://ctc.usma.edu/app/uploads/2018/05/Boko-Haram-Beyond-the-Headlines_Chapter-2.pdf.

56.

Roth

Mitchel P.

Sever

Murat

. 2007. “The Kurdish Workers Party (PKK) as Criminal Syndicate: Funding Terrorism through Organized Crime, A Case Study.” Studies in Conflict & Terrorism 30 (10): 901–20.

57.

Shelley

Louise I.

2010. Human Trafficking: A Global Perspective. New York: Cambridge University Press.

58.

Shelley

Louise I.

2014. Dirty Entanglements: Corruption, Crime, and Terrorism. New York: Cambridge University Press.

59.

Shelley

Louise I.

2020. “Illicit Trade and Terrorism.” Perspectives on Terrorism 14 (4): 7–20.

60.

Shelley

Louise I.

Picarelli

John T.

. 2005. “Methods and Motives: Exploring Links between Transnational Organized Crime and International Terrorism.” Trends in Organized Crime 9 (2): 52–67.

61.

Stanton

Jessica A.

2019. “Terrorism, Civil War, and Insurgency.” In The Oxford Handbook of Terrorism, 348–65. Oxford: Oxford University Press.

62.

Stewart

M. A.

Liou

Y.-M.

. 2016. “Do Good Borders Make Good Rebels? Territorial Control and Civilian Casualties.” Journal of Politics 79 (1): 284–301.

63.

Tokdemir

Efem

Akcinaroglu

Seden

. 2016. “Reputation of Terror Groups Dataset: Measuring Popularity of Terror Groups.” Journal of Peace Research 53 (2): 268–77.

64.

Traughber

Colleen M.

2007. “Terror-crime Nexus? Terrorism and Arms, Drug, and Human Trafficking in Georgia.” The Quarterly Journal 6 (1): 47–64.

65.

United Nations. 2000. United Nations Convention against Transnational Organized Crime and the Protocols Thereto, adopted by the UN General Assembly on 15 November 2000 by resolution 55/25. Entered into force on 29 September 2003. Accessed Feburary 23, 2020. https://www.unodc.org/unodc/en/organized-crime/intro/UNTOC.html.

66.

United Nation Security Council. 2016. Resolution 2331 (2016) of 20 December 2016. New York, NY: United Nation Security Council.

67.

United States Department of State. 2010. Annual Report on Trafficked Persons. Washington, DC: US Department of State.

68.

UNODC. 2018. Trafficking in Persons in the Context of Armed Conflict. New York: United Nations.

69.

Warner

Jason

Matfess

Hilary

. 2017. Exploding Stereotypes: The Unexpected Operational and Demographic Characteristics of Boko Haram’s Suicide Bombers. West Point, NY: Combating Terrorism Center at West Point. Accessed February 23, 2020. https://ctc.usma.edu/app/uploads/2017/08/Exploding-Stereotypes-1.pdf

70.

Weitzer

Ronald

. 2014. “New Directions in Research on Human Trafficking.” The ANNALS of the American Academy of Political and Social Science 653:6–24.

71.

Wood

E. J.

2009. “Armed Groups and Sexual Violence: When is Wartime Rape Rare?” Politics and Society 37:131–61.

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