The views expressed in Shorenstein Center Discussion Papers are those of the author(s) and do not necessarily reflect those of Harvard Kennedy School or of Harvard University. This paper was originally published in the July 2023 issue of Organizational Behavior and Human Decision Processes.
Abstract
Conflict plays a profound role in the lives of individuals, organizations, and entire societies – and has become an ever-expanding area of interdisciplinary research. This special issue brings together five new papers examining conflict antecedents and processes using the experimental method. In the following introduction, we consider the challenges inherent to studying conflict using experiments and the various approaches that researchers have developed to overcome some of those challenges. In doing so, we present a high-level taxonomy of successful experimental approaches to the study of conflict and highlight the manner in which the papers in the Special issue exemplify each of these approaches. We conclude with several pieces of specific advice to researchers seeking to make robust and impactful contributions to this area.
1. Introduction
Where does conflict come from? How does it develop? What consequences does it have for participants and their groups? These questions are central to the social and behavioral sciences, including social and organizational psychology, behavioral economics, and decision science. Conflict comes in a variety of forms, from shouting matches between individuals to organized warfare between cultural groups, and can be resolved through behaviors ranging from debate to violence. And while conflict sometimes benefits individuals and their organizations (De Dreu and Weingart, 2003, Jehn, 1995), these local benefits are typically outweighed by the profound costs (De Dreu, 2008).
Given the many research questions to be asked in this area and the importance of the answers to human flourishing, conflict can and has been examined with a variety of scientific methods and techniques (Bornstein, 2003, De Dreu and Carnevale, 2004, Druckman, 2005, Walton and Dutton, 1969). For example, in the literature on conflict across ethnic or political lines, research is often conducted by surveying impacted individuals (Bozzoli & Brück, 2009) or by analyzing specific instances of conflict emergence and resolution (De Vries & Maoz, 2013). In organizational behavior, conflict has been studied between firms, among executives, and both within and between teams using case analyses (Bartunek, 1984, Gould, 1999, Gould, 2003, Morrill, 1995, Morrill et al., 2003, Owens and Sutton, 2001, Strauss et al., 1963), qualitative interviews (Behfar et al., 2008, Behfar et al., 2011, Bendersky and Hays, 2012, Jehn, 1995, Jehn, 1997), and surveys (Amason and Sapienza, 1997, Bendersky and Hays, 2012, Jehn et al., 1999, Jehn et al., 2010, Oc et al., 2021, Todorova et al., 2014). Each of these methods can provide rich insight into conflict origins, dynamics and consequences.
Alone or in combination, however, these methods and techniques can fall short if one’s goal is to test hypotheses about causes and effects of conflict dynamics and their components. To this end, scientists have relied on experimental methods to identify what can trigger conflict, how people regulate conflict, and what proximal effects conflict can have, based on the recognition that experiments allow for attribution of causality with greater precision and certainty than most other approaches. Experiments further allow for the measurement and/or manipulation of the specific psychological mechanisms underpinning outcomes of interest. Especially in studies testing the effectiveness of conflict interventions, understanding the underlying psychology is crucial for effectively replicating an intervention across contexts (Ernstoff et al., 2022). Finally, the controlled nature of an experiment enables scholars to be specific about the conditions required for an effect, ruling out alternatives or so-called “third variable” problems.
And yet, studying conflict through experimental manipulations can be difficult, and experiments cannot – and perhaps should not – reproduce the enmity of the real world. Accordingly, as a background to the articles in this Special Issue, we provide a focused discussion of the various techniques and common problems scientists face when designing experiments on conflict, along with guidance on how to navigate the most common challenges. We hope that these observations will be useful, in particular, to junior scholars seeking to make a contribution to this vast, exciting, and impactful area of research.
2. Common challenges of studying conflict with experiments
The experimental study of conflict poses some unique challenges. The most obvious is that conflict is difficult to generate in an experimental setting. Prior research has defined conflict as a situation in which (groups of) people pursue incompatible goals – what is in the best interest of one is least preferred by the other (e.g., Deutsch, 1973, Pruitt, 1998). It is such opposing interests, values, and viewpoints that trigger strategic behaviors, accompanied by specific cognitions and emotions. Experiments cannot typically reproduce the intensity of conflicts people experience in their daily lives. What experiments can do, however, is to dissect the mechanisms underlying particular behaviors that, for instance, escalate conflict or help the parties find common ground. For example, an extensive literature on negotiations has leveraged simulation games where participants assume a fictional role complete with specific values, preferences, and private and shared information, and interact with their ‘opponent’ for a limited amount of time. Interactions are coded, providing rich insight into strategic communication and decision-making, and how these predict impasse, victories, or mutually-beneficial solutions (De Dreu et al., 2000, Galinsky and Schweitzer, 2015, Hart and Schweitzer, 2020).
In addition, one should ask whether it is even ethical to create conflict among strangers. Should psychologists be in the business of sowing enmity among hundreds of unsuspecting research participants? Especially when conducting experimental investigations of conflicts that have clear parallels in the real world, there is a risk that participants may carry distrust toward and negative impressions of their counterparts beyond the experiment. This concern applies in particular when researchers bring conflict partisans together to study their interactions. For example, experiments have featured interactions between members of hostile ethnic groups, opposing political parties, or supporters of mutually exclusive campus policies. In the course of the experiment, participants have been instructed to interact in a certain manner (Maoz, 2000), to do so after receiving specific information about the other side (Broockman & Kalla, 2016), or after experiencing a particular emotional induction (Halperin, 2011, Halperin, 2016). In such settings, in particular, the participants need to be provided with in-depth debriefings to ensure the experimental manipulations do not exacerbate the problems they are intended to address.
Another challenge of the experimental approach is logistical. Participants from opposing sides of a conflict must be paired with each other at a specific time and in a specific setting, a laborious process that often turns wasteful when one member of a dyad fails to show up, or two members of the same group are accidentally paired. Studies of partisan conflict in the US are further thwarted by the extreme geographical sorting that has separated liberals and conservatives into ever more politically homogeneous enclaves (Brown & Enos, 2021). In settings with a recent history of violent conflict (e.g., Israel/Palestine, Syria, Ukraine) individuals from opposing groups are often unwilling to participate in any interaction with their opponents, even if such interaction is logistically feasible. Finally, in all of these settings, individuals who do agree to participate are likely to be less extreme than the average conflict participant in their level of negativity toward the other side.
A final challenge for experiments on conflict arises from the combined need for maximizing statistical power and working with constrained resources – whether those resources are research funding or access to participants. Most experiments across the social sciences produce one data point from each individual surveyed. Indeed in many research designs, statistical power can be maximized further by collecting multiple measures from each participant, for instance by having a single individual solve multiple problems or evaluate multiple stimuli. However, studying interaction between conflict participants usually requires two individuals for each data point. Research on team conflict is even more challenging – often requiring much larger samples with entire teams of 3–5 individuals producing a single observation. Designs containing several treatment arms, the crossing of multiple factors, or capturing statistical interactions can quickly become resource prohibitive.
Despite these challenges, the literature boasts many elegant solutions that have enabled scholars to conduct experimental research on conflict successfully, ethically, and with limited resources. Examples of such approaches can be found in this special issue and elsewhere throughout the vast and interdisciplinary literature. Below, we first organize the most common experimental approaches into three broad categories that represent large swaths of the literature, presented roughly in order of increasing resource and logistical demand. Namely, we discuss survey experiments, laboratory experiments, and experiments conducted in field contexts. Although we recognize that these categories are not entirely comprehensive, and in some cases overlap (for example, experimental games can be embedded in a survey which is administered in a field setting), we find this to be a useful organization that we hope will stimulate future work. We then offer some practical advice to scholars seeking to make a contribution to this field based on our own experience as both researchers and editors.
3. Survey experiment
Some of the most influential studies on conflict and misunderstanding feature the humble survey experiment (Robinson et al., 1995, Ross and Ward, 1996). These study designs rely on recruiting participants in naturally occurring conflict (e.g., often political conflict or ethnic conflict) and producing experimental variation by randomly assigning the affected individuals to respond to different versions of the same survey. This basic structure can be achieved in many ways.
One of the most common approaches involves asking respondents to consider their own versus their counterpart’s arguments and behaviors (e.g. Lord et al., 1979, Minson et al., 2020, Noor et al., 2019). For example, in a typical “self-other design” individuals are required to report their attitudes, predictions, or attributions regarding a particular set of events when considering them from their own perspective or from the perspective of a disagreeing other. Thus, individuals in one experimental treatment might report their own motivations for a conflict behavior and those in another would do their best to infer the motivations of the members of the opposing group (Collins et al., 2022, Pronin et al., 2001). Or the members of one experimental group might report their own affective reactions to certain stimuli and the members of another experimental group would infer their opponents’ reactions to the same (Campbell et al., 2014, Dorison and Minson, 2022, Klein, 2019, Kteily and Bruneau, 2017, Kteily et al., 2016, Lees and Cikara, 2020, Van Boven and Loewenstein, 2005, Van Boven et al., 2013).
Yet another popular version uses time as the independent variable asking conflict participants to consider the same events at different time points. For example, following the “affective forecasting” literature (Wilson and Gilbert, 2003, Wilson and Gilbert, 2005), participants in one treatment might forecast specific events or their own reactions to those events. At a later point in time, individuals assigned to the other condition would report their actual reactions to those same events (Dorison et al., 2019). Relatedly, work on “reactive devaluation” uses a similar design to elicit evaluations of concessions before or after they have been proffered (Maoz et al., 2002, Ross, 1993).
An elegant example of a survey experiment in this special issue is the policy-capturing experimental design developed by Brykman and O’Neill (2023) in “How Conflict Expressions Affect Recipients’ Conflict Management Behaviors.” In this paper, the authors examine how specific dimensions of conflict expression (i.e., the level of entrenchment, subversiveness, ambiguity, and target-directness) identified by Weingart et al. (2015) influence receivers’ conflict management behaviors (i.e., competitive, integrative, and non-confrontational behaviors (Van de Vliert, 1997)). The policy-capturing design involves presenting participants with many different scenarios that vary slightly, based on unique combinations of predictors at varying levels (e.g., high and low ambiguity), and asks participants to make decisions in response to each scenario. In this within-person design, the authors presented each facet of conflict expression with the full combination of high and low levels of all other facets to precisely control the causal attributions for participants’ conflict management responses. In two experiments with 454 total participants who each evaluated between 32 and 64 scenarios, the authors found that receivers were more likely to respond with competitive (forcing) versus integrative (problem-solving, compromising) or non-confrontational (yielding, avoiding) behaviors when conflict was expressed unambiguously with high entrenchment and subversiveness. This experimental manipulation of the specific facets of conflict expressions advances scholarship by precisely identifying what triggers more and less constructive conflict management behaviors.
An advantage of survey experiments is that they allow researchers to study the attitudes, beliefs and (behavioral) intentions of participants engaged in real-world conflicts without the necessity to endow participants with specific beliefs, preferences, or attitudes toward the other side. Furthermore, survey experiments often remove the need to match participants with dyad partners, or ask them to interact with someone they dislike or even loathe. These studies also enable researchers to investigate the effects of conflicts on unrelated tasks without specifically asking participants’ opinions regarding other parties (Marks et al., 2019). Importantly, this approach also enables researchers to engage with populations that might be difficult to reach and are thus under-represented in social science research (Henrich et al., 2010). As difficult as it is to translate a survey into multiple languages and distribute it to respondents in different locations, it is still far more feasible than conducting high-powered studies involving live interaction in those same locations.
However, surveys also have important downsides, some of which are directly related to the benefits listed above. The results of survey experiments lack the richness of live interaction. Can we really boil down murderous rage to a 7-pt Likert scale? Furthermore, most survey experiments elicit self-reported attitudes and beliefs on valenced topics, which may be particularly likely to suffer from demand characteristics (Zizzo, 2010) or people’s simple lack of self-insight. Even if individuals are accurately reporting their cognitive and affective experiences, one might wonder whether those experiences are powerful enough to predict behavior when faced with the complexity and emotional intensity of real-world situations. Importantly, when survey experiments offer incentives for participation in an intervention, we must question the extent to which the intervention would be taken up without the incentives, limiting external validity.
Ultimately, some questions simply cannot be answered with a survey, including observation of behavioral choices, alongside live interactions and responses to counterparts. Research questions that require physiological measurement or close control of participant attention also pose a challenge to the survey method. To address these shortcomings, researchers have turned to more logistically intensive approaches.
4. Interactive experiments using games
A classic approach to engaging participants in interaction invokes the principles of Game Theory to design experimental conflict games (e.g., Deutsch, 1973, Pruitt, 1998). A basic game involves two players, each of whom can choose from one of two actions. The choice that is in one player’s best interest is least preferred by the other player, and vice versa. Experimental games thus model situations in which players are interdependent, in that their individual actions not only impact their own outcomes, but also those of the other player(s) (Van Dijk & De Dreu, 2021). Commonly, actions are identified as serving the individual’s personal interests or the joint interests of all players involved and individual and collective benefits are negatively correlated.
Well-known examples of such experimental games include the Prisoner’s Dilemma and related games such as the Hawk-Dove and Stag-Hunt Game, which often (but not necessarily) involve a binary choice between cooperation and defection (Gibbons, 1992). There is a small literature on contest games, in which individuals or groups invest personal resources to acquire some desirable prize (viz. territory, food, market share), to prevent others from acquiring the prize (viz. companies using the poison pill to prevent a hostile take-over), or some combination of both (see Dechenaux et al., 2015, for a review). Contests model conflicts that are more competitive than mixed-motive games, and can offer additional insights into the conditions under which individuals and groups find a path to de-escalation (e.g., Abbink and de Haan, 2014, De Dreu et al., 2016).
Whether within a binary or continuous action space, experimental games can be one-shot or repeated. In one-shot games, participants are introduced to the game and make one decision only (in so-called “random partner matching” designs, they are then paired to another player for another decision). One-shot play illuminates antecedents to conflict – how variations in players’ cultural background, the physical environment, or personality drives toward competitive or cooperative behavior. By contrast, repeated play provides insight into conflict dynamics, and allows researchers to identify when and how dyads get locked into particular patterns that persist over time (e.g., Axelrod, 1984).
Experimental games offer flexibility in that they may be modified to examine the micro-foundations of specific conflict structures and scenarios. For example, Böhm, Halevy and Kugler (this issue) asked whether individual participation in intergroup conflict is partly explained by participation being presented as the default, and non-participation requiring an active choice. The authors report three experiments (total N = 893) that used incentivized economic games to test this hypothesis. Designating intergroup conflict as the default option significantly increased individual conflict participation relative to a no-default condition and to designating other behavioral options as defaults. The effects of defaults on intergroup conflict generalized across different social identities and levels of group identification. Findings thus reveal a heretofore unidentified reason for the stickiness of conflict and highlight choice architecture as a potential solution: changing existing defaults can redirect intergroup behavior.
Games can also be modified to examine within-group dynamics. In such multi-level or team games, individuals are nested in small groups that compete with another group for some prize (Bornstein, 2003, De Dreu et al., 2020). The incentive structure is such that groups with more cooperators – who contribute personal resources to their in-group’s fighting capacity – win the intergroup conflict, although individuals are better off when they do not contribute.
An example of this approach is the study by Weisel and Zultan (2021) in this issue. Building on past research, Weisel and Zultan (2021) suggest that individual participation in conflict is driven mostly by parochial cooperation, rather than outgroup spite, but also that the relative unimportance of spite may depend on framing the conflict at the group or individual level. In a controlled laboratory experiment, they manipulate perception of the conflict level by varying the framing, while keeping the objective strategic aspects fixed. While parochial cooperation was the main motivation under an individual frame (replicating prior results), outgroup spite emerged as an important motivation when conflict was perceived at the group level. Furthermore, whereas under an individual frame intragroup communication and chronic prosociality related only to parochial cooperation, under a group frame intragroup communication related to both parochial cooperation and outgroup spite. Weasel and Zultan conclude that although experimental team games naturally focus on the strategic aspects of conflict, it is possible to extend the paradigm to incorporate conflict perceptions, and doing so can enrich understanding.
Because of the experimental control inherent to games of conflict, researchers have begun to investigate the shadow of conflict – how tension and conflict within and between groups impacts their future cooperation. Gross, De Dreu and Reddmann (this issue) induced conflict by dividing groups of four into two “attackers” that could take away resources from two participants in the role of “defenders.” After a series of attack-defense interactions, groups engaged in a repeated public goods game in which individuals could invest resources to benefit the group and punish other group members for their decisions. Previous conflict did not significantly reduce group cooperation compared to a control treatment in which groups did not experience conflict. However, when having experienced an intergroup conflict, individuals punished free-riding during the repeated public goods game less harshly and did not react to punishment by previous attackers, ultimately reducing group welfare. Among other insights, the study reveals that intergroup conflict undermines past perpetrators’ legitimacy to enforce cooperation norms. More generally, results reveal that past conflict can reduce the effectiveness of institutions for managing the commons.
As these examples show, experimental games as a tool to study conflict have several advantages. However, downsides exist as well. The experimental game approach has historically been constrained to in-lab studies. However, recent work has shown how on-line platforms can also be used effectively (see, e.g., Gross et al., this issue). Sometimes the costs are high, especially when games are implemented using a no-deception/pay-for-performance protocol. Such studies can also be extremely logistically challenging, especially in the case of team games with small groups. Finally, some argue that the stylized action space and abstract incentives undermine the study’s ecological validity, and can make applications in specific settings problematic (Ledyard et al., 1995). Indeed, experimental games serve best to test general theory and examine possible psychological mechanisms underlying strategic decision-making rather than behavior in specific contexts.
5. Interactive experiments engaging participants in ongoing conflict
As mentioned above, another common approach to studying conflict experimentally is to recruit opposing partisans from ongoing real-world conflict for live interaction. Researchers then commonly manipulate the participants’ instructions for how they ought to behave during the engagement (Jeong et al., 2019, Minson et al., 2023, Schroeder et al., 2019, Yeomans et al., 2020), the information they have about each other or their discussion topic (Santos et al., 2022), their goals for the task (Collins et al., 2022), or the manner in which people communicate (Schroeder et al., 2017). While logistically challenging, this approach can lead to rich data augmenting the traditional survey responses ranging from recordings of natural language discussions, to video, to eye-tracking and biological data. The richness of the data can have multiplicative effects with the same datasets being analyzed to test different hypotheses by either the same or other authorship teams.
A related approach is to recruit one party from an ongoing real-world conflict into a study, furnish them with instructions on how to interact with their counterparts, and then collect data about their interactions after they have transpired. For example, a design might involve recruiting people involved in long-term romantic relationships, training them in emotion regulation, and then collecting their reports regarding their experiences interacting with their partner post intervention. Although such studies capture the experiences and reactions of only one party in a conflict, they allow for the testing of interventions against the complexity of real-world dynamics.
Interactive experiments have benefited tremendously from the advent of technological solutions which allow conflict counterparts to be brought together more easily. For example, studies conducted on ChatPlat allow groups of participants to be paired in a chat room embedded in a Qualtrics survey for unstructured (or minimally structured) conversation. SMARTRIQS, a related platform allows a mix of interaction, economic games and survey questions. Video chat software such as Zoom or WhatsApp enables video interactions between geographically distributed participants (Broockman et al., 2022, Yeomans et al., 2023). The innovative “Coat of Arms“ game enables participants to create strong group identities while using online tools to navigate through complex intergroup tasks (Kachanoff et al., 2020, Gray et al., 2021).
Although this approach often focuses on synchronous interaction, creative use of technology also enables asynchronous engagement. For example, rather than trying to pair participants to interact in real time, some studies have required participants to respond to previously crafted messages from opponents, often extending the process for several rounds of message exchange over days or weeks (Yeomans et al., 2020, Minson et al., 2023).
The benefits of technology for reaching large numbers of participants, notwithstanding, the limitations must also be discussed. Large online participant pools often feature predominantly American participants, and by definition feature only those with access to a computer, an internet connection, and possessing some amount of technological sophistication. This reliance on technology leaves large chunks of the world population out of the research.
Additionally, although interactive experiments produce rich data on naturally occurring and often deeply-rooted conflict, the participants are nevertheless removed from their habitual conflict environment by virtue of being recruited into the study. Extensive research shows the reluctance that conflict counterparts feel when faced with the prospect of interacting with the other side (Brown and Enos, 2021, Dorison et al., 2019, Frimer et al., 2017). Forcing conflict partisans to interact in a lab setting may present some challenges such as participants avoiding contentious topics (Santoro & Broockman, 2022). Thus, the broad generalizability of results may be limited by the absence of factors that exist in the contexts in which the focal conflict unfolds. To address these challenges researchers have developed a variety of approaches for carrying out experiments in ever more naturalistic contexts.
6. Field experiments
Perhaps the most ambitious approach to testing conflict-related hypotheses is the full-blown “field experiment.” Researchers have created multiple categories to distinguish approaches that shift a paradigm from a pure lab experiment where randomly-selected participants knowingly step into a research setting and engage in structured activities designed to generate research data, to one where participants in an ongoing conflict unknowingly furnish data that is collected and recorded, while experiencing a treatment to which they were randomly assigned but of which they are largely unaware (Harrison & List, 2004).
Studies in this tradition usually use experimental methods to change people’s attitudes, emotions, social norms, policy support, and actual behavior in real conflict settings (e.g., Blattman et al., 2014, Goldenberg et al., 2018, Hasson et al., 2022, Kubin et al., 2021, Mousa, 2020, Scacco and Warren, 2018, Weiss, 2021, Weiss et al., 2023). These studies are conducted in the naturalistic environment where participants live, work or interact. In most cases the goal of such experimental designs goes beyond revealing causal mechanisms driving conflict dynamics, toward testing the effectiveness and scalability of intergroup interventions. Importantly, in most of these studies, participants are not aware of being part of an experiment, and are motivated to engage in the treatment either intrinsically or extrinsically. For example, Hasson et al. (2022) motivated Jewish and Arab participants to engage in their field experiment by incorporating the study into a large-scale art festival. Another example is a field intervention conducted by Goldenberg et al. (2018) in which the manipulated content (in that case – the belief that groups can change) was embedded within leadership training workshops.
In an optimal field experiment the random assignment process utilizes naturally occurring processes or structures, or is executed in a way that does not create confounds to interfere with the experimental process. For example, Weiss (2021) randomly assigned Jewish Israeli patients to be treated either by Arab or by Jewish physicians, using the standard procedure of the relevant clinics in Israel. Given that doctors pick up files in the order they are stacked, Weiss considered the assignment of participants to doctors to be random. In a similar vein, White et al (2021) exploited the randomization of Arab and Jewish Israeli teenagers to different activity groups in a summer camp experience to measure how proximity affected relationship formation. Other interesting examples can be found in the studies of Paluck (2009) and Hameiri et al. (2016) in which different communities or cities were matched and then randomly assigned to receive different media-based treatments. In both cases, participants were not aware of either the randomization process or the fact that they were part of a study.
A key advantage of the field experiment is that it exposes participants to an experimental treatment within the naturally occurring conflict context. This ensures that those exposed to the treatment are not only the people who are willing or able to participate because they are less involved in the conflict, or happen to live near a university, or have access to technology. Furthermore, interventions that show effects in such contexts can be considered to be more robust since they withstood the noise and complexity of the real conflict environment. Finally, all outcome variables in such field experiments – attitudinal, emotional, or behavioral are connected to relevant conflict related issues, meaning that their alteration can potentially cause meaningful change in the conflict dynamic.
However, like every approach discussed above, field experiments also possess important downsides. First, field experiments often require a waiver of informed consent either because the data would be uninterpretable if participants knew they are being studied or because obtaining consent from every participant is logistically prohibitive. Thus, researchers should carefully consider the potential harm that intervening in a real conflict might cause. Although ethical considerations are traditionally the purview of institutional review boards, researchers themselves have a responsibility to use their knowledge of behavior to weigh these issues.
A second, practical, downside of field experiments is the logistical and resource demands that they usually create, which might make relying on this method exclusively a risky choice for early career researchers. Most field experiments require collaboration with outside organizations who provide access to participants, logistical support, or actively engage in the delivery of the intervention (e.g., Paluck, 2009, Weiss et al., 2023). Working with such partners often takes months if not years of relationship building and knowledge sharing. And of course, like any research project, after years of effort a field experiment might deliver disappointing results. For this reason, this approach may be best suited as a capstone to a line of research where the phenomena have been carefully studied and the mechanisms are well-understood.
7. Practical advice to emerging conflict scholars
The above discussion illustrates the rich variety of approaches to experimental conflict research, and highlights both the benefits and downsides of some of the most common methodologies. That variety notwithstanding, a few pieces of practical advice apply across contexts and we hope may help scholars entering the field.
7.1. Use technology
Recent years have seen the emergence of many technologies to enable more efficient study of conflict processes. Even commonly used tools such as Qualtrics surveys possess an ever-growing variety of advanced features, making them increasingly flexible in the designs they can support. Particularly important for conflict research are platforms such as ChatPlat and SMARTRIQS (Molnar, 2019) that allow researchers to structure online interactions among participants dispersed around the globe. Both of these tools can be embedded into a Qualtrics survey, which can then be shared through a variety of distribution approaches. The platform iDecisionGames is frequently used in the negotiation classroom, but can also be used for research purposes to engage participants in many popular simulations.
Many researchers have taken creative approaches to using internet communities and their public communication as a source of data. For example, online interactions can be analyzed for conflict expression, conversational receptiveness, and evidence of attitude change. Researchers have also experimentally manipulated participants’ exposure to Facebook posts and Twitter threads (Bail et al., 2018, Levy, 2021, Mosleh et al., 2022). Thinking about the entire internet as a source of stimuli and data opens many novel and relatively low cost research opportunities. Also, using virtual reality environments (e.g., Hasler et al., 2021) or developing conflict related smartphone apps (Porat et al., 2020) can be useful in creating and testing experimentally the impact of conflict situations.
Taking advantage of these tools and approaches often requires advanced technical and analytical skills. To this end, junior researchers should advance their coding skills including R, Python, basics of web scraping, and natural language processing. This can be done by participating in “data bootcamps,” summer courses, or even Massively Open Online Courses available for free through many universities.
7.2. Engage with the real world
Some of the most interesting papers in conflict management present a mix of methods, including those that provide tight experimental control and those that connect the phenomena to real world contexts and outcomes. A good example of such a mixed methods approach can be found in the current volume in the paper by Molnar, Chaugdhry and Lowenstein (2023), in which the authors used one observational study, two hypothetical choice experiments, and then one real choice experiment to test their hypothesis that revenge seekers want the offender to understand why they are being punished. This work advances our understanding of the motives behind revenge beyond deterrence behavior as postulated by the prior literature, and requires us to consider other drivers of this common behavior. The fact that the authors first documented the existence of their focal phenomenon in the real world, and then manipulated different aspects of the phenomenon across contexts, strengthens the credibility of their findings.
More broadly, engaging with conflict in the world requires keeping an eye on relevant events, including both those reported on the front pages of major newspapers as well as more local conflicts. Ideas for the study of conflict can be gathered from our own relationships, family gatherings, and the stories our friends and colleagues share. Indeed, the supply of real-world conflict examples seems to be limitless.
Studying conflict beyond that which occurs in our daily life might require a willingness to spend hours, days and months cultivating relationships and understanding conflict contexts in order to be ready to collect data when the right opportunity arises. This might mean studying the dynamics of a particular workplace (Danbold and Bendersky, 2020, Levin et al., 2023) so that you can intervene wisely when the time arrives, or becoming deeply familiar with a specific part of the world by following the news, understanding the cultural trends, and building relationships with local researchers.
Research projects that involve real-world conflicts can be exciting but also risky in terms of the balance of time invested to likelihood of generating usable data. Field partners often fail to grasp the details of randomization; non-disclosure agreements take months to be vetted by legal counsel; participants return incomplete responses, resulting in years of work going down the proverbial drain. A wise approach is to manage a portfolio of projects, including ones that rely on easily accessible samples where data can be gathered quickly and reliably, and ones that might seem more exciting but involve greater risk.
7.3. Cultivate relationships
Impactful, replicable and rigorous research often involves more skills and resources than any one person or lab could possess. To this end, it is important to cultivate relationships with other researchers (within and beyond one’s home discipline), field partners, and conflict management practitioners in order to build an engaged and supportive network. Any one of these individuals might become a co-author, share data, enable access to difficult-to-reach participants, or help generate new ideas over coffee.
In addition to reading journals and identifying theoretical gaps, successful researchers often genuinely enjoy communicating their work to non-researchers and explaining both its scientific merit and its real world relevance. Such communication might involve teaching, writing for the popular press, giving talks to non-academic audiences, or even regaling/torturing dinner party guests with stories about conflict research. Although more senior academics have more opportunities to disseminate their work, some early career scholars stand out for their sheer excitement about and enthusiasm for research. Repeated practice talking about your work with non-academics helps both with academic writing and broader idea dissemination. Importantly, such conversations also have the potential to generate new ideas, offer access to new data, or cultivate sources of funding.
7.4. Start simple and build up
A common mistake committed by researchers in almost every area, but one that is particularly costly given the complexities of conflict research, is to begin a new project with an unnecessarily complex design. Research is fundamentally a learning process. If we take seriously the idea that we run experiments to test hypotheses, we need to be open to the possibility that our hypotheses will be proven wrong. Thus it does not make sense to begin a new project with a 2x2x3 design involving dyads with opposing perspectives on an armed conflict in a remote nation. Rather, new projects should begin with more modest survey or scenario studies, featuring a minimal number of treatments. Early studies in a project inevitably lead to new insights and violations of previously held assumptions. Only once the pattern of data is clear and has been confirmed in multiple datasets does it make sense to invest time and resources into a large, expensive and complex paradigm that may have been the one that originally sparked a researcher’s interest.
7.5. Post your data
The open science movement which has spurred researchers to pre-register their hypotheses and post data and materials is sometimes critiqued for placing restrictions on freedom and creativity (Gonzales and Cunningham, 2015, Scott, 2013). But beyond helping to ensure the integrity of our findings, open science practices can also have tremendous benefits for collaboration and efficiency if we share our painstakingly designed surveys and carefully collected data. For example, several researchers have created open repositories of data on conflict processes that others have already benefited from (Dorison and Minson, 2022, Gross et al., 2022, Schroeder, 2022). If you post your materials and your data, you will be able to contribute to this growing community, grow your reputation as a researcher committed to transparency and grow your citation count (Logg and Dorison, 2021, Moore et al., 2022, Tenney et al., 2021)!
8. Conclusion
Conflict is an inevitable part of human interaction as individuals and groups seek to advance their own ideas and agendas onto those who do not share the same. Yet, to the extent that conflict can be prevented, de-escalated, and wisely managed, it does not have to exact a punishing cost on individuals and societies. Researchers play an important role in helping to accurately identify conflict dynamics so as to minimize the toll of conflict, as well as gain fundamental insight into human behavior.
This special issue contains five new papers exemplifying cutting edge work that examine conflict using the experimental method. In this introduction, we sought to offer a broad overview of methodological approaches used to study conflict experimentally, including some costs and benefits of each. It is worth noting that three of the five papers that succeeded in the review process used a game-theoretic approach. This pattern is somewhat coincidental, due to the papers that happened to be submitted. However, it also reflects the power of the game theoretic method to draw clean, causal conclusions with broad relevance to both individuals and organizations.
We hope that our review of the other common methods to studying conflict with experiments provides researchers with new insights about the trade-offs involved in pursuing one method over the other. Furthermore, we hope that readers recognize the complementarities of these different approaches, as well as the complementarities between the experimental method on which the special issue focused and other approaches such as correlational surveys, qualitative interviews, and case analysis. For junior scholars in particular, the choice of method is often pre-determined by the research tradition in which they are being trained. However, even in those cases it is worth considering how a specific project and the field in general can benefit from more “cross-talk” between domains and methods. Combining experimental research with qualitative work, or finding ways to include both field and lab data in a paper can add a level of richness and generalizability that is difficult to achieve with any single method. Such “hybrid” projects can be more risky, requiring a team with knowledge of multiple methodologies and the patience to address critiques from reviewers with different backgrounds and tastes. However, they can result in papers that are more widely cited and taught, making a lasting impact on the field.
A less ambitious version that still achieves “cross-pollination” of work from different fields involves simply citing a broader swath of the literature including different methods and different settings. This approach enables drawing theoretical and applied links between different parts of the research space and contributes to both the building of knowledge and the building of relationships. We strongly urge scholars to look beyond their corner of the world for relevant theories, methods, and insights.
The advent of information technology that has connected us in new and more intimate ways and the concomitant advances in statistical analysis techniques promises a productive future for conflict research. Twenty years ago, it would be unthinkable to run experiments involving hundreds of participants dispersed across the globe but still interacting in real time. Now, such ambitious studies are not only possible but growing ever more common. We hope that the consideration of a variety of available methods as well as vivid examples of prior papers that have made important contributions using each can serve the next generation of conflict scholars as they seek to make the world a more collaborative place.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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