Investigating Blame for Human-Wildlife Conflict: Reason Conditions for Human-Elephant Conflict in Borneo

Abstract

Blame attribution, the process of assigning responsibility for a negative event, has critical implications for managing human-wildlife conflict (HWC). This study advances understandings of blame attribution in human-elephant conflict (HEC) on the island of Borneo. Specifically, we advance theory on how internal (villager-related) and external (societal) attributions influence HEC and villagers’ willingness to participate in its mitigation efforts. We conducted surveys with villagers living in and near elephant habitats who have experienced HEC firsthand. We collected data on participants’ attributions of blame for HEC, dividing them into internal and external factors, as well as their willingness to engage in HEC mitigation actions. Findings reveal that villagers attribute blame to both external factors, such as global demand for products cultivated in elephant habitat, and internal factors, including local misunderstandings of elephant behavior. Additionally, villagers who blamed external factors expressed a greater willingness to engage in HEC mitigation efforts. These findings underscore the importance of blame attribution in shaping attitudes toward HEC mitigation. Villagers’ propensity to engage in mitigation actions varies based on whether they attributed blame for HEC to external or internal factors. The study highlights the need to address socio-political and environmental drivers of HEC in Sabah, Borneo, Malaysia. Acknowledging external attributions may foster local participation in conflict mitigation efforts by leveraging underlying motives that gave rise to the source of blame in our study.

Keywords

Asiatic elephants attribution theory conflict Malaysia socio-ecological systems

Introduction

Scientists and officials are increasingly concerned that the ability of communities and institutions to manage human-wildlife conflict (HWC), defined as interactions between people and wildlife that result in harm to either side, is not strong enough to ensure long-term wildlife conservation (Hoare, 2015; Hodgson et al., 2020; Peterson et al., 2010). At the local level, people living in areas affected by HWC often lack the resources, training, or support to manage these conflicts effectively (Madden, 2004). At state and national levels, policies and funding are limited, while development goals often take priority over conservation needs (Toh & Grace, 2006; United National Development Program [UNDP], 2008). These gaps in capacity, across all levels, make it harder to reduce conflict and design sustainable, long-term solutions for HWC (Acrenaz et al., 2007; Desai & Riddle, 2015).

Blame attribution is central to understanding how people interpret and respond to HWC. Blame is more than a reaction; it reflects judgments about cause, responsibility, and who should be held accountable for negative events (Shaver, 2012). These judgments are shaped by personal experience, cultural context, and broader expectations about fairness and justice (Leland et al., 2021). The way blame is assigned can influence outcomes such as forgiveness, cooperation, trust, or disengagement (Kim et al., 2006). Blame attribution is typically categorized into two types. Internal attribution involves holding oneself or one’s own group responsible for the problem. External attribution assigns responsibility to outside forces such as institutions, other groups, or environmental and economic systems (Heider, 1958). Broader social factors, including political beliefs and values, can influence how blame is assigned. For example, political ideology can shape whether someone holds individuals or social systems responsible for complex societal problems such as homelessness or violence (Joslyn & Haider‐Markel, 2013; Pellegrini et al., 1997).

HWC is an ideal but understudied domain to further understand blame attribution because outcomes are typically negative (Peterson et al., 2010). However, in comparison to other arenas, researchers have scantly studied the role of blame attribution in wildlife contexts. The literature often mentions blame ascription in the context of HWC, but mainly in passing. However, a small number of studies have focused increasingly on blame, exploring to whom or what the media assigns blame when reporting instances of HWC (Dayer et al., 2019; Stafford et al., 2018 [species itself, policies, or agencies]). Because blame has been undertheorized and empirically examined, particularly in HWC contexts, we asked two research questions: How do villagers attribute blame to HWC? and How do different blame attributions relate to villagers’ willingness to participate in various forms of HWC mitigation?

To answer these questions, we applied attribution theory, with a focus on on internal versus external blame attributions, to the context of human-elephant conflict (HEC) in Borneo, Malaysia. In this region, growing human populations, expanding infrastructure, and the rapid proliferation of oil palm plantations have brought people and Bornean elephants (Elephas maximus borneensis) into closer contact (Estes et al., 2012; Evans et al., 2020). These interactions often result in crop damage, property loss, and, at times, retaliatory actions against elephants (Cheah & Yoganand, 2022). HEC has been framed as a territorial struggle between humans and elephants. However, emerging perspectives suggest that affected communities often perceive HEC not as a direct conflict with elephants, but as a symptom of deeper political-economic forces such as land dispossession, industrial agriculture expansion, or limited community-level agency in HEC governance (Doolittle, 2004; Margulies & Karanth, 2018). Recognizing this framing is important, as it influences how blame is assigned and how affected communities respond to conflict. Although the Sabah Elephant Action Plan 2020–2029 outlines mitigation protocols and conservation priorities, the persistence of conflict suggests that deeper insights into local perceptions of responsibility and accountability are needed (Ahmad Zafir & Magintan, 2016; Othman et al., 2019, 2022). To our knowledge, ours is the first study to quantitatively investigate how different types of blame attribution (e.g., internal/villager-based vs. external/societal or institutional) influence local behavioral intentions to engage in HEC mitigation.

Theoretical Background

The literature suggests that the blame for HWC outcomes is often distributed across multiple actors and scales. At the micro level, villagers and local stakeholders may blame government wildlife agencies for poor planning, policy enforcement, inability to manage a population, or imposing wildlife risks without adequate mitigation (Dickman, 2010; Moreto, 2019). Conversely, institutions frequently assign blame back to local communities for inadequate cohabitation strategies or for contributing to conflict through land-use practices (Malley & Gorenflo, 2023). In some cases, blame is assigned horizontally, within the same social group. For instance, Pooley (2016) demonstrated that Nile crocodile (Crocodylus niloticus) attacks were sometimes perceived as divine punishment for immoral behavior. Non-human entities may also be blamed for HWC. Jadhav and Barua (2012) described how elephants (Elephas maximus) were perceived as demonic entities in parts of Northeast India. Similarly, Hahn (2019) documented retaliatory lion killings (Panthera leo) by Maasai herdsmen in Kenya after repeated livestock losses.

Environmental and systemic drivers also feature prominently. Factors such as overlapping land use with large carnivores (Viollaz et al., 2021), resource scarcity, and chemical pollution (Guerreiro, 2019) are increasingly recognized as contributors to conflict. These examples demonstrate that blame attribution in HWC settings can span multiple social and ecological levels and moves across a scalar continuum (individual, community, institutional, and societal contexts). Blame attribution is a near-universal human response to conflict, but an overly narrow focus on either internal psychology or broad structural conditions risks missing the complexity of real-world dynamics (Velempini, 2021). We consider that though viewing blame as solely a binary (internal vs. external) is useful, it is perhaps more helpful to treat blame as a product of, and contributor, to complex socio-ecological systems. Understanding these layered blame dynamics is essential not only for interpreting local perceptions of conflict but also for designing more inclusive, effective, and sustainable mitigation strategies.

To conceptualize this complexity, we developed a conceptual model of blame attribution specific to HEC (Figure 1). The model distinguishes between two broad attribution categories: internal and external. Internal attribution is depicted as a nested hierarchy of responsibility, ranging from general references to “humans,” to groups like “villagers,” and down to the “individual.” This structure captures how blame may be progressively focused based on proximity or perceived agency. External attribution, by contrast, is organized into four domains: environmental, societal, institutional, and economic, with situational factors positioned at the center to illustrate the intersectional and context-dependent nature of blame. Together, these dimensions reflect the diverse ways that individuals and communities assign blame for HEC.

Research indicates that who or what people blame for problems has significant implications for their responses. Blame attribution influences how individuals frame both the causes of conflict and the possible solutions, with the potential to either escalate or de-escalate HWC (Dayer et al., 2019). Attribution-driven tactics such as invoking shame or guilt can be used to stimulate action, yet these tactics are typically most effective when individuals perceive themselves as responsible (Tangney & Dearing, 2002). In many HWC contexts, blame is often directed at institutions, global economic forces, or environmental degradation rather than at local communities or individuals (Batanova et al., 2014; Rubino et al., 2020). This external orientation may actually enhance a willingness to act, particularly when the conflict is framed as the result of larger systemic pressures rather than local failings (Simon & Klandermans, 2001).

Conversely, when blame is internalized, such as when individuals believe they or their community are at fault, it may lead to emotional disengagement or reduced motivation to participate in mitigation efforts (Peeters et al., 2019). This pattern is consistent with literature suggesting that blame deflection serves as a coping mechanism to avoid perceived attribution, which, over time, can result in withdrawal from intervention or resistance to externally driven solutions (Bandura et al., 1996; Stoll-Kleemann & O’Riordan, 2020). Understanding how blame is assigned in HWC contexts is therefore critical not only for interpreting community attitudes but also for shaping conservation messaging and designing interventions that align with local perceptions of responsibility (Nicolai et al., 2022).

Relatedly, attribution errors may be made. Specifically, when negative outcomes happen to an individual, they often blame the situation, yet, they tend to blame others’ behavior or dispositional qualities for negative outcomes to that person while diminishing the contribution of situational characteristics (Flick & Schweitzer, 2021). Doubleday and Adams (2020) illustrated blame attribution and partiality with a compelling case from rural India: after a woman failed to collect enough fodder due to risk of tiger (Panthera tigris tigris) attack, her husband blamed and then beat her for establishing a deficient amount of bargaining power with the milkman after family income was substantially reduced that day. Instead of blaming the tiger population or the sanctuary system, the husband blamed the woman. In this study, forest officials blamed the community for choosing to live in a high-risk area though the sanctuary itself had introduced those risks, and the authors advocated for the feminization of natural resource collection and use as a way for actors to shift blame for negative outcomes from women to tigers. This case study underscores how uneven or conflicting blame assignments can hinder consensus and disrupt coordinated action.

Despite its relevance, the role of blame attribution in shaping responses to HWC has received limited empirical attention, particularly in species-specific contexts such as HEC. Without careful examination of the antecedents, dynamics, and consequences of blame, mitigation strategies may rest on flawed assumptions. To address this gap, we analyzed HEC survey data from Sabah, Borneo, Malaysia, to explore how local communities assign blame and how these attributions influence their willingness to participate in conflict mitigation. By linking blame attribution to behavioral intent, this study contributes new insights into the social and ecological dimensions of HEC and offers guidance for designing more inclusive, community-informed conservation strategies. Based on our review, we test three hypotheses:

• H1: villagers tend to assign blame to external factors rather than to themselves or their communities;

• H2: villagers’ external blame attributions, particularly those tied to global commodity demand and habitat degradation, will be positively associated with a willingness to act; and

• H3: villagers’ internal blame attributions will be associated with lower willingness to engage in mitigation efforts.

Methods

Study Area

This study was conducted across multiple rural communities situated within Sabah’s Managed Elephant Ranges (MER), encompassing the Lower Kinabatangan floodplain in eastern Sabah, Malaysian Borneo. This floodplain forms part of one of Southeast Asia’s most critical biodiversity hotspots, supporting a range of endemic and endangered species, including the Bornean elephant, a genetically distinct subspecies of the Asian elephant (Estes et al., 2012; Fernando et al., 2005). The Lower Kinabatangan region is a geologically young, alluvial floodplain shaped by prolonged fluvial sedimentation, with much of the area lying below 30 meters in elevation and highly prone to seasonal inundation (Horton et al., 2017).The region experiences a humid tropical climate with high annual rainfall averaging around 3,000 mm, most of which occurs during the northeast monsoon between November and January (Hai et al., 2001).

The landscape is a mosaic of riparian forests, freshwater swamps, oxbow lakes, and lowland dipterocarp forests that has become increasingly fragmented due to the rapid expansion of oil palm plantations and related infrastructure. (Alfred et al., 2011). These land-use changes have led to a significant decline in habitat availability and connectivity, thereby intensifying HEC in surrounding agricultural communities (Othman et al., 2019; Rubino et al., 2020). The Bornean elephant population in the region, estimated at 1,500 to 2,000 individuals, now routinely traverses cultivated areas, resulting in crop loss, property damage, and occasional retaliatory actions by affected communities (Cheah & Yoganand, 2022). According to the Sabah Wildlife Department (SWD), over 50 elephants were killed between 2018 and 2022 due to poisoning, snaring, and gunshot wounds, underscoring the persistent challenges to coexistence (Othman et al., 2022). While the Sabah Elephant Action Plan 2020–2029 aims to support long-term coexistence through landscape-level strategies, its implementation has been constrained by limited resources, governance gaps, and mismatches between institutional policy frameworks and local realities.

Study Design

We categorized the causes of HEC using two common attributional styles: internal and external (Lei & Rau, 2021). In this study, internal attribution refers to self-blame, where villagers see their own actions, either individually or as a group, as contributing to HEC. This approach follows cultural perspectives in many East Asian contexts, where groups, rather than individuals, are often seen as the main actors (Menon et al., 1999). In contrast, external attribution refers to assigning blame to factors beyond oneself.

However, we argue that the simple internal-versus-external distinction does not fully explain the social and ecological complexity of HEC. In our study, we defined external attributions to include institutions, society, and elephants. Internal attributions included actions taken by villagers themselves, both past and present (Kim et al., 2006). We used both internal and external attributions as predictor variables to examine the community’s willingness to take part in actions aimed at reducing HEC. We grouped our attribution variables as follows:

Internal (villagers)

1. Villagers’ dependence on crops for income

2. Villagers’ dependence on crops for subsistence

3. Villagers’ dependence on palm oil trees for income

4. Poor understanding of elephant behavior among villagers

External attribution (institutional)

5. Expanding human infrastructure (e.g., roads)

6. Strict laws that protect elephants

External attribution (natural/elephant)

7. Elephants are unpredictable

8. Damage to crops by elephants

9. Growing elephant populations

10. Competition for resources between humans and elephants

External attribution (societal)

11. Global demand for products cultivated in elephant territory

12. Human degradation of elephant habitat.

To ensure respondents felt comfortable sharing their views and did not fear negative consequences, we avoided using direct terms such as blame or fault in our survey questions. Instead, we relied on the concept of reason conditions for blame (Heuer, 2010). We originally planned to measure blame using a 1 to 5 scale, where 1 meant least important and 5 meant the most important reason for HEC. However, we simplified this to a binary scale, where 0 represented no blame and 1 represented blame. While measuring the strength and underlying reasons for blame would provide a more complete understanding (Lowry, 2011), that level of detail was beyond the scope of this exploratory study and should be considered in future research. We selected ten predictor variables (X1 to X10) for further analysis based on whether they showed a correlation greater than 0.2 with the dependent variables (see Table 1).

Table 1.

Correlations Between Blame Attributions and HEC Mitigation Willingness. Correlation Coefficients Between 10 Blame Attribution Variables (X1–X10) and 17 Mitigation Actions (Y1–Y17) Indicate How Perceived Causes of HEC Relate to Villagers’ Willingness to act. Only Variables With Correlations ≥ |0.2| are Included

Attribution		Predictor variables (X1 to X10)	Response variables	Correlation coefficient
Internal attribution	Villagers	Villager dependence on crops for income (X1)	Joining elephant ranger team for my village (Y17)	−0.21
		Villager dependence on crops for subsistence (X2)	Totally change the way I earn income to avoid HEC (Y2)	0.29
		Villager dependence on palm oil trees for income (X3)	Receive a small salary to live near elephants (Y4)	0.26
		Poor understanding of elephant behavior among villagers (X4)	Appreciate elephants because they exist (Y1)	−0.20
External attribution	Institutional	Expanding human infrastructure (e.g., roads) (X5)	Volunteer as a member of a village committee to minimize HEC (Y13)	0.25
	Institutional	Strict laws that protect elephants (X6)	Receive expert instruction on how to deal with elephant behavior (Y6)	0.21
	Natural (elephant)	Elephants are unpredictable (X7)	Appreciate elephants because they exist (Y1)	0.23
	Natural (elephant)	Growing elephant population (X8)	Appreciate elephants because they exist (Y1)	−0.24
	Societal	Global demand for products cultivated in elephant territory (X9)	Totally change the way I earn income to avoid HEC (Y2)	0.37
	Societal	Human degradation of elephant habitat (X10)	Appreciate elephants because they exist (Y1)	0.27

We also examined how blame is connected to the willingness to take action. Prior research suggests that how people assign blame can affect their thoughts, attitudes, and behavior. For example, people may consider forgiveness or revenge based on how blame is attributed (Bradfield & Aquino, 1999). Kogut (2011) showed that people are less likely to help a victim if they believe the victim is responsible for their situation. Takaku (2001) found that blaming others can have a different emotional effect than blaming oneself. When individuals or groups accept blame, they may be more willing to participate in actions that correct the issue (Bilstein, 2018). This relationship between blame and accountability may strongly influence whether individuals or communities are willing to engage in efforts to reduce HEC.

Using the action categories proposed by Naito et al. (2022), we grouped participants’ willingness to act into three types of transformative actions:

a. Private action: actions or behavior conducted on a personal level to live alongside elephants

b. Social signaling action: actions or behavior involving public act, like sharing or supporting values, attitudes, identities and opinions to further inspire others in participating in elephant conservation and minimizing the conflict.

c. System changing action: actions or behaviors aimed at supporting, reforming or developing a formal acceptable system to manage the conflict and promote elephant conservation.

These three types of action form our 17 dependent variables, labeled Y1 to Y17 (Figure 2). We measured willingness on a 1-to-5 Likert scale, where 1 meant “unwilling” and 5 meant “very willing.”

Data Collection

After approval by the Texas State University Institutional Review Board (#6716), we surveyed villagers living within a 5-km zone of the Kinabatangan, Tabin, and Central Sabah Elephant Managed Ranges (MERs) (Figure 3). The initial list of prospective subjects officially reported HEC to the Sabah Wildlife Department or experienced it (N=37). We concentrated our sampling efforts on farmers and parcel caretakers (in the case of absentee landowners) in 27 villages that fell within the buffer and where HEC had been identified (Diwara, Tampasak, Bobotong, Batu Puteh, Bauto, Brantian, Bulot, Desa Permai, Diwara, Gambaron, Kalabakan, Kenang-Kenangan, Karamuak Dalam, Kg. Abai, Kg. Litang, Kukuamas, Liningkung, Mukandut, Murut Ulu Kalabakan, Sg. Udin, Simatuoh, Tampasak, Tangkugan/Kuamut, Telupid, Tenaga Baru, Ulu Muanad, and Ulu Murut).

We collected data in three waves: February 2020 (n=29), July 2022 (n=31), and March through May 2023 (n=58). These waves were determined based on access, local conditions, and COVID-19 disruptions. The number of respondents per region roughly corresponded with the intensity and frequency of HEC as reported by the SWD and local leadership. For example, higher sampling concentrations were achieved in villages such as Kalabakan and Kinabatangan, where elephant-related conflict has historically been more acute. Final locations accessed for this study were based on HEC information obtained from official documents and state and local officials and then identified by villager leadership. The research team administered surveys by arranging a specific day and time with each village in advance and conducting interviews at preferred locations to ensure comfort and participation. The research team had one chance to collect data and gathered as many prospective participants as were available during the visit. We asked participants to reflect on their experiences with HEC over the past five years.

Data Analysis

We used descriptive statistics (mean and standard deviation) to summarize the demographic characteristics of study participants. To examine the relationship between respondents’ willingness to engage in HEC mitigation (ordinal dependent variables Y1–Y17) and perceived causes of conflict (predictor variables X1–X10), we employed ordinal logistic regression using the cumulative link model (CLM) framework. All analyses were conducted in R version 4.3.1 (R Core Team, 2023) via RStudio version 2023.06.1+524, utilizing the ordinal package, version 2023.12-4.1 (Christensen, 2023). The clm() function was used to estimate model coefficients, which reflect the direction and strength of the relationship between predictors and ordinal response categories. Significance was evaluated at p < 0.05. To ensure reproducibility and retain individual-level resolution, we linked all responses using anonymized survey IDs. This structure allowed us to assess how each participant’s blame attribution corresponded with their stated willingness to take specific actions.

To select predictors, we first examined the correlation between blame attribution variables and willingness-to-act items, retaining variables with correlation coefficients ≥ |0.2|. These ten selected predictors (X1–X10) were used in model construction and are presented in Table 1. For each of the 17 response variables (Y1–Y17), we constructed a separate ordinal logistic regression model with simultaneous consideration of the selected predictors. We interpreted model coefficients to assess the direction and magnitude of each effect and examined statistical significance to determine meaningful associations. To improve model robustness, we applied model averaging using the MuMIn package, version 1.48.4 (Bartoń, 2024). The model.avg() function combined parameter estimates from multiple models weighted by their corrected Akaike Information Criterion (AICc) values, allowing us to identify the most influential predictors across all outcomes (Lundberg et al., 2019).

Results

We surveyed 118 villagers, of whom 109 reported experiencing HEC. Only these 109 responses were included in the analysis. The sample was majority male (n = 77, 71%), and the mean age of respondents was 42.7 years (SD = 11.3). Most respondents were over the age of 35 (n = 91, 83%). In terms of ethnicity, respondents primarily identified as Sungai (n = 45, 50%) or Kadazan-Dusun (n = 34, 38%). Study participants’ monthly household income ranged from RM150 to RM5,000, with a mean income of RM938 (SD = RM691), approximately USD $204 (SD = $150). Regarding education, most respondents had achieved at least a primary education (n = 41, 38%), with n = 53 (50%) attaining secondary or higher education.

On HEC experiences, 81% (n = 88) reported experiencing crop or property damage to varying degrees, with incidents occurring rarely to frequently. Perceptions of crop damage trends over time indicated that n = 50 (47%) saw no change, while n = 35 (33%) believed incidents were increasing. Most (n = 59, 57%) had not participated in SWD-led training or meetings within the past five years, although n = 59 (61%) were attended by agency representatives. Preferred sources of learning about elephants were friends and family (n = 49), social media (n = 32), and popular press (n = 33).

Respondents were drawn from 27 villages across Sabah’s MERs, with variation in representation. Communities such as Kenang-Kenangan (n = 13), Kg. Abai (n = 9), and Kg. Litang (n = 9) had higher participation, whereas many villages such as Murut, Desa Permai, and Tangkugan/Kuamut were represented by one respondent. Due to this uneven geographic distribution, comparative statistical analysis by village was not feasible. However, all responses were included to retain the breadth of perspectives across the landscape.

Attributing Blame

Our preliminary analysis revealed that ten out of the twelve predictor variables exhibited correlation coefficients of ±0.2 or higher, suggesting their potential relevance for inclusion in our model (Table 1).

Further analysis using model averaging of ordinal logistic regression identified three of these ten predictors as statistically significant in explaining respondents’ attribution of blame for HEC (Table 2):

i. Poor understanding of elephant behavior among villagers (X4)

ii. Global demand for products cultivated in elephant territory (X9)

iii. Human degradation of elephant habitat (X10).

Table 2.

Model-Averaged Coefficients for Predictors of Blame Attribution. Results From Ordinal Logistic Regression Show Which Internal and External Factors Significantly Influence Villagers’ Likelihood to Assign Blame for HEC. Positive or Negative Beta Coefficients Indicate Direction and Strength of Influence

Predictors (blame vs. no blame)	Estimate (β)	S.E.	z-value	Pr(>\|z\|)
Poor understanding of elephant behavior among villagers (X4)	−2.13	0.76	2.80	0.005**
Global demand for products cultivated in elephant territory (X9)	1.68	0.52	3.20	0.001**
Human degradation of elephant habitat (X10)	1.08	0.53	2.01	0.04*
Strict laws that protect elephants (X6)	−0.77	0.58	1.32	0.18
Villager dependence on crops for subsistence (X2)	−0.85	0.67	1.27	0.20
Expanding human infrastructure (e.g., roads) (X5)	0.65	0.56	1.15	0.24
Villager dependence on palm oil trees for income (X3)	0.93	0.87	1.06	0.28
Villager dependence on crops for income (X1)	−0.69	0.76	0.90	0.36
Elephants are unpredictable (X7)	−0.36	0.49	0.74	0.45
Growing elephant population (X8)	−0.18	0.44	0.41	0.68

*indicates a p-value less than 0.05 (significant at the 5% level).

**indicates a p-value less than 0.01 (significant at the 1% level).

***indicates a p-value less than 0.001 (significant at the 0.1% level).

These three predictors emerged as the primary reasons to which respondents attributed blame for HEC. Notably, the variable representing global demand for products cultivated in elephant habitats (X9) produced a positive beta coefficient (β = 1.72, p = 0.001). Similarly, human degradation of elephant habitat (X10) also showed a positive association (β = 1.08, p = 0.04). In contrast, the internal attribution to villagers’ poor understanding of elephant behavior (X4) yielded a negative coefficient (β = -2.06, p = 0.006). This negative association indicates that respondents who internalize blame may be less likely to perceive HEC as a broader systemic issue, potentially reflecting a sense of resignation or reduced perceived efficacy.

Threshold Analysis for Willingness Categories

The ordinal logistic regression model identified a highly significant threshold between categories 2 (“not that willing”) and 3 (“somewhat willing”), with an estimated threshold value of -5.2322 (p < 0.001). This sharp distinction in willingness categories reveals meaningful differences in how blame attributions influence villagers’ motivation to act:

• (X4) poor understanding of elephant behavior: Associated with a decreased likelihood of being in category 3 (“somewhat willing”)

• (X9) global demand for products cultivated in elephant territory: Associated with an increased likelihood of being in category 3 (“somewhat willing”)

• (X10) human degradation of elephant habitat: Associated with an increased likelihood of being in category 3 (“somewhat willing”).

Willingness to Act as a Function of Blame Attribution

We then examined how these three significant predictors influenced villagers’ willingness to engage in specific mitigation actions (Table 3). These actions ranged from individual changes (private) and community signaling (social) to more institutional or systemic responses.

Table 3.

Blame Attribution Predictors and Willingness to act on HEC. Shows Significant Links Between Three Blame Predictors (X4, X9, X10) and Specific Actions Villagers are Willing to take. Each Action is Categorized as Private, Social Signaling, or System-Changing Behavior

Predictor variables	Estimate	Pr(>\|z\|)	Response variables (willingness to take action)	Action categories
X4	−2.06	0.006**	Willing to travel other villages to learn how to minimize HEC (Y11)	Social signaling action
X9	2.18	1.81e-05***	Willing to totally change the way to earn income to avoid HEC (Y2)	Private action
	1.29	0.005**	Willing to diversify income source to minimize HEC (Y5)	Private action
	1.45	0.003**	Willing to advocate for elephant conservation in community (Y9)	Social signaling action
	1.72	0.001**	Willing to travel to other villages to learn how to minimize HEC (Y11)	Social signaling action
	1.23	0.005**	Willing to purchase insurance that will pay for loss due to elephant damage (Y16)	System changing action
X10	1.18	0.008**	Willing to appreciate elephants because they exists (Y1)	Private action
	−1.03	0.02*	Receive expert instruction on how to deal with elephant behavior (Y6)	Private action
	1.08	0.04*	Willing to travel other villages to learn how to minimize HEC (Y11)	Social signaling action
	1.06	0.02*	Willing to purchase insurance that will pay for loss due to elephant damage (Y16)	System changing action

*indicates a p-value less than 0.05 (significant at the 5% level).

**indicates a p-value less than 0.01 (significant at the 1% level).

***indicates a p-value less than 0.001 (significant at the 0.1% level).

(X4) Understanding of elephant behavior: Internal (villagers) attribution

The individual coefficient for X4 (β4 = -2.06, p = 0.006) indicated a significant negative relationship with the response variable Y11, which measures the willingness to travel to other villages to learn how to minimize HEC.

(X9) Global demand for products from elephant territory: External (societal) attribution

External attribution to global market demand was strongly linked to willingness across multiple action types. Specifically, it was significantly associated with a willingness to:

• Completely change income-generating activities to avoid HEC (β2 = 2.18, p < 0.001)

• Diversify income sources (β5 = 1.29, p = 0.005)

• Advocate for elephant conservation (β9 = 1.45, p = 0.003)

• Travel to learn from other villages (β11 = 1.72, p = 0.001)

• Purchase insurance for HEC-related losses (β16 = 1.23, p = 0.005)

(X10) Human degradation of elephant habitat: External (societal) attribution.

Attributing blame to habitat degradation was associated with:

• Greater appreciation of elephants for their existence (β1 = 1.18, p = 0.008)

• Willingness to travel for learning (Y11, β11 = 1.08, p = 0.04)

• Willingness to purchase insurance (β16 = 1.06, p = 0.02).

However, it was negatively associated with the willingness to receive expert instruction on elephant behavior (β6 = -1.18, p = 0.008). These findings are visually summarized in Figure 4, which maps the significant blame attribution variables to corresponding types of willingness to act.

Discussion

Blame Attribution

Our findings revealed a clear distinction between internal versus external blame attributions. Findings suggest that respondents who assigned blame for the occurrence of HEC were signaling a desire to maintain a sense of control and predictability about the conflict, as well as expressing unmet expectations about how it should be managed (Ames & Fiske, 2015; Malle et al., 2014). Given HEC has persisted in Sabah for over half a century, perhaps villagers, at this point, see HEC as foreseeable, anticipated, or even intentional (Alicke, 2000; Ames & Fiske, 2015), or they have grown weary of carrying the burden of living with Bornean elephants (Bernama, 2021), thus providing the impetus to assign blame. The literature on the Sabah case offers several variables that could influence blame attribution in this study, such as emotions, economic loss, or power imbalances (Zafir & Magintan, 2016; Rubino et al., 2020; Pimid et al., 2022). Further research is needed, however, to develop models that explain the drivers of blame attribution in HEC and HWC contexts.

Causal factors revealed by this study were primarily anthropocentric, oriented towards politicaleconomy and activities that degrade elephant habitat. Villagers rarely blamed themselves for HEC. Studies indicate that denying culpability is a tactic people use to protect oneself from outcomes or repercussions (Sedikides, et al. 1998). Because our study demonstrated that behaviors and policies causing elephant habitat degradation increased willingness to act, findings suggest that past environmental events may influence how people assign blame in HEC cases in Sabah. Rural people living near the forest have a long history of being blamed for forest degradation by technocrats and political elites (Doolittle, 2004) while the influence of legal, political and economic level forces is rarely implicated though they create conditions that result in violence against those who outwardly oppose them (Zuckerman, 2021). Our results may be interpreted as the villagers pushing back on that silence, echoing calls by researchers to take seriously the influence of political economy on conservation outcomes (Fletcher & Toncheva, 2021; Margulies & Karanth, 2018). Often, rural people lay blame for HWC at the feet of government and non-governmental conservation entities, which oversee managing elephant populations and their habitat, as well as oil palm companies (e.g., Dhakal & Thapa, 2019; Jadhav & Barua, 2012; Law, 2022). Guilty by association, elephants may also be entangled in the blame web because they can be a symbol of government control or decision making or devastation (Borah et al., 2022). Elephants can be viewed as wards of the government or their responsibility (Gross et al., 2021) and, thus targets for retaliation (Wilshusen et al., 2002). That does not seem to be the case in our study. Elephants have been, for the most part, disentangled from larger social forces (e.g., elephants as ancestors [Rubino et al., 2020]).

Governing bodies hold significant power and resources to influence HWC outcomes, whereas rural communities often lack the means to stop the harmful effects driven by unchecked economic development and poverty. Our results suggest that villagers still long for decision makers to integrate their perspectives and needs in natural resource decision making, including elephant conservation, and to be viewed as a valued partner rather than an obstacle. Rebuilding relationships between government and citizens to address HEC requires reciprocal commitment from all parties, with each acknowledging the consequences of both their actions and inactions (Othman et al., 2019). Sabah’s elephant action plan made HEC a central issue to resolve, which is a start to operationalizing the “everyone…join hands” approach (Free Malaysia Today, 2024), but urgent action at the highest levels of government is required if humans, corporations, and elephants are to prosper in the same region. A future-oriented HEC mitigation design requires commitment to innovative governance thinking, cross-jurisdictional collaboration, and policy experimentation at the highest levels of society (Serenari & Schlechte, 2023).

Willingness to Act

Our results revealed a connection between blame attribution and how villagers negotiate HEC in Sabah. Respondents were more willing to engage in social signaling and system changing actions, but their stated proclivities depended on how fault was framed, with larger scale reasons being more powerful in terms of driving willingness to take action. Our findings may be explained by studies of attribution bias, which help us understand how bias orients blame and influence how people negotiate situations (Hsung et al., 2023). Studies are inconsistent concerning how human agents involved in HEC will respond ranging from adaptation (Fernando et al., 2005) to retaliatory actions (Best, 2007; Kopnina, 2016; Othman et al., 2022). These relationships between blame attributions and action types are illustrated in Figure 4, which summarizes how internal versus external attribution patterns shaped villagers’ willingness to engage in private, social, and system-level responses.

In the context of rural Malaysia, many communities operate within landscapes heavily shaped by external political and economic forces. Historical land alienation, top-down forest management, and palm oil expansion have marginalized rural people’s access to land and decision-making (Doolittle, 2004). Conservation efforts, though well-intentioned, are often perceived as externally imposed and inattentive to local needs (Margulies & Karanth, 2018), while the palm oil industry continues to shape ecological and social conditions that exacerbate HEC (Suba et al., 2017). As a result, villagers may perceive themselves not as primary contributors to conflict, but as victims of structural systems that generate risk and restrict agency. This externalized blame may increase their willingness to act, as the source of the problem lies outside their immediate control (Batanova et al., 2014). Nonetheless, as is common of environmental behavior, the ability to respond is often limited by situational constraints such as lack of resources, support, or influence (Gaspar et al., 2010). The variety of reasons linked to villagers’ willingness to act, along with the range of actions they endorsed, highlights the need for future research to clarify how blame attribution influences mitigation behaviors. A clearer understanding of these connections can guide more targeted interventions. In the meantime, elephant conservation decision makers can apply insights from this study to improve governance by strengthening human-elephant relationships, designing responsive policies, and creating more inclusive engagement strategies.

Changes in land use have reduced available elephant habitat, disrupted migration routes, and altered movement patterns. These shifts increase the likelihood of elephants entering farms and human settlements (Estes et al., 2012; Evans et al., 2020; Othman et al., 2019). It is therefore important to examine the extent to which elephants are blamed for HEC and to consider the broader drivers behind changes in their behavior. Few villagers in our study attributed blame to elephants’ unpredictability, population growth, or competition for resources. This aligns with earlier findings suggesting that elephants are sometimes unjustly blamed for their own decline (Lawton & Gough, 1970; Lötter, 2006) or for HEC itself (Malley & Gorenflo, 2023). Our study of blame attribution revealed that elephants are not exclusive targets of blame in Sabah, and causal factors are anthropocentric and environmental. Officials and conservationists with the power to make change in Sabah can build off the idea that the notion of HEC is really a fallacy. Elephants and humans are not viewed as locked in a battle for territory or supremacy. Rather, rural people fully understand that political-economic forces underpin HEC. Recognizing this reality can help build mutual understanding needed to engage afflicted communities in dialogue and actions that help them curb negative interactions with elephants that have gone on for what should arguably be considered far too long.

Implications for Conservation

Our findings offer several practical implications for the design and delivery of human-elephant conflict (HEC) mitigation strategies in Sabah. First, we observed that when villagers attributed blame to external forces such as global demand for palm oil and habitat degradation. They were more willing to engage in a wide range of mitigation actions. This highlights the importance of framing HEC not simply as a behavioral issue at the community level but as a result of broader political, economic, and environmental changes. On the ground, this takeaway aligns with how many villagers describe their situation: they did not start out in conflict with elephants, but over time, fragmentation and land-use change brought them into closer and more frequent contact.

In several areas of Malaysian Borneo, particularly Central Sabah, many communities settled in the 1970s to access land. Back then, forest cover was still substantial and elephant encounters were rare. Today, forest fragmentation has drastically increased human-elephant contact, resulting in property damage, injury, fear, and tension. Yet, rather than blaming elephants or themselves, many communities recognize that the HEC problem is systemic. This broader understanding has opened the door to collaborative efforts to mitigate it. In response, members of the research team and other critical stakeholders have co-developed community-based strategies that build upon the insights provided by this human dimensions study. For example, through the Community Honorary Wildlife Warden initiative, local villagers have been empowered to take an active role in elephant protection and monitoring. These wardens not only help respond to HEC but also serve as local ambassadors for coexistence with a variety of wildlife. Similarly, members of the research team have worked closely with communities to co-design and maintain HEC mitigation tactics tailored to villagers’ lived experiences and informed by elephant movement data, such as the installation of electric fencing These collaborations have strengthened relationships between HEC stakeholders and ensured the solutions are rooted in the realities of both people and elephants.

Second, our findings show that when communities internalize blame such as believing they lack knowledge about elephant behavior they are less willing to engage in learning opportunities. To address this finding in Sabah, officials avoid top-down training that can feel patronizing or irrelevant. Instead, the emphasis is on mutual learning, peer-to-peer exchanges, and storytelling that values local knowledge alongside scientific insights. When villagers feel heard and respected, they are more open to experimenting with new approaches and sharing their own successful strategies with others.

Third, our work confirms that support for income diversification, HEC-related insurance, and inter-village learning resonates strongly with communities who view conflict through a systemic lens. In practice, we are exploring pilot insurance models, promoting livelihood alternatives such as small-scale agroforestry, and organizing village-to-village learning exchanges where communities can learn directly from one another’s experiences. These approaches not only reduce risk but also build solidarity and confidence.

Finally, this study reinforces that blame attribution matters not just as a personal opinion but as a key driver of behavior. Conservation efforts must go beyond technical solutions and recognize how people emotionally and cognitively experience HEC. Combing this study with years of field experience in the study area, it has become apparent that when people feel respected, included, and supported rather than blamed they are more willing to become active partners in long-term coexistence with elephants.

Limitations and Future Research

While this study offers insights into how blame attribution influences willingness to act in the context of HEC, several limitations must be acknowledged. First, the survey data rely on self-reported perceptions and behaviors, which may be influenced by, for instance, social desirability or recall bias. Second, our sampling was concentrated in regions with documented conflict intensity, potentially limiting the generalizability of findings to lower-conflict or emerging HEC zones. Third, the cross-sectional design of the study restricts our ability to assess causal relationships or changes in attribution and willingness over time. Future research could benefit from longitudinal studies that track shifts in attitudes and actions in response to interventions or ecological changes. Additionally, integrating ethnographic or participatory approaches may deepen understanding of cultural norms and lived experiences that shape HEC perceptions and behaviors.

Footnotes

Acknowledgements

The research team would like to thank Marc Ancrenaz and HUTAN staff for their assistance with data collection, the people of Sabah who shared their perspectives with us and the reviewers and editorial staff for their thorough review. We are grateful to Texas State University International Research Accelerator grant for funding to conduct to this study.

ORCID iD

Kaushal Yadav

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Texas State University International Research Accelerator Grant.

Declaration of Conflicting Interests

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

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