Psychological predictors of fishing and waste management intentions in Indonesian coastal communities

Accepted Manuscript Psychological predictors of fishing and waste management intentions in Indonesian coastal communities Erik Simmons, Kelly S. Fielding PII:

S0272-4944(18)30774-6

DOI:

https://doi.org/10.1016/j.jenvp.2019.101324

Article Number: 101324 Reference:

YJEVP 101324

To appear in:

Journal of Environmental Psychology

Received Date: 30 October 2018 Revised Date:

12 July 2019

Accepted Date: 15 July 2019

Please cite this article as: Simmons, E., Fielding, K.S., Psychological predictors of fishing and waste management intentions in Indonesian coastal communities, Journal of Environmental Psychology (2019), doi: https://doi.org/10.1016/j.jenvp.2019.101324. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

Abstract The populations most susceptible to environmental degradation are often the populations that

RI PT

rely most on the natural world for sustenance. Within the many isolated islands that are part of rural Indonesia, many communities are dependent on natural resources for their livelihoods, but paradoxically members of these communities often engage in practices that destroy their natural resources (Fox &

SC

Caldwell, 2006; Glaeser & Glaser, 2011; Pet-soede, Cesar, & Pet, 1999). The current research uses survey methodology to investigate determinants of sustainable behavioral intentions of participants (N =

M AN U

104) living in coastal communities in Sulawesi, Indonesia—specifically through the lens of an adapted theory of planned behavior model. Results showed that participants with stronger intentions to use nets and lines to fish had more negative attitudes to destructive fishing, a greater sense that their behavior and that of their community affects marine life, and greater belief that other villages are responsible for

TE D

degrading reefs. Participants with stronger intentions to prevent their waste from going into the ocean had more negative attitudes to throwing waste in the ocean, greater perceptions of control over the behavior, and more positive perceptions of change in the health of the reefs. Although some of the

EP

findings align with theory and past research, some were unexpected, highlighting the importance of conducting research to identify motivators of sustainable practices in developing world, low resource

AC C

communities.

Key words: pro-environmental behavior; low-resource communities; Theory of Planned Behavior; sustainability; fishing; waste

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 1. Introduction According to the Food and Agricultural Organization (FAO), there is an increase in the number of biologically unsustainable fisheries because of overfishing and destructive fishing practices (FAO,

RI PT

2018). This poses significant risk to ecosystems and humans alike. The World Wildlife Foundation (WWF) suggest this could prove devastating for natural habitats, coastal civilizations, and the economy (WWF, 2015). Similarly, the oceans are being devastated by unmanageable plastic waste (Jambeck et

SC

al., 2015). This plastic waste does irrevocable damage to natural habitats and, consequently, our sources of sustenance (Lamb et al., 2018). Moreover, destructive fishing and plastic waste can often have

M AN U

disproportionate effects on low and middle income countries and communities (WWF, 2015). These worrying facts highlight the need for greater understanding of the drivers of practices, such as destructive fishing and plastic pollution, especially in low-resource communities. One of the challenges of addressing the issue of destructive fishing and plastic pollution is that

TE D

local communities in low-income countries are often reliant on these methods and commodities due to perceived ease and financial benefits of destructive methods, financial entrapment schemes used by bomb and poison suppliers to keep fishermen in debt, and the ubiquity of plastic packaging. But

EP

destructive fishing practices and plastic pollution can have far-reaching negative social and economic impacts including contaminated environment, blasted and polluted sites being less desirable and livable

AC C

for visitors and locals, health risk from plastics and poison fishing, and reduced fish catch (Chan & Hodgson, 2017; Dirhamsyah, 2004; Landrigan et al., 2017; WWF, 2015). Research that develops an understanding of the social-psychological factors influencing the environmental decision-making of low-resource coastal community members is a critical first step to helping to change destructive fishing and polluting waste management practices.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR To date, research investigating environmentally-related behavior has usually been conducted with populations who are not reflective of the diversity of the world’s population, that is, primarily individuals from western developed countries (Henrich, Heine, & Norenzayan, 2017). This is

RI PT

problematic when considering that the findings of the research may not generalize to low-resource, developing world coastal communities where the consequences of environmental degradation can directly impact on livelihoods. Clearly more research is needed to illuminate the psychological

SC

mechanisms underlying the environmental behavior of underrepresented cultures and populations. The current research seeks to address this gap through investigating whether a commonly used model in the

M AN U

environmental literature, the Theory of Planned Behavior (TPB), translates to novel behaviors, such as sustainable fishing and waste management practices, in novel populations, such as low-resource coastal communities in Southeast Asia.

The current study provides a unique opportunity to conduct research on a population that is

TE D

under-represented in the literature: low-resource, Southeast Asian cultures, in Indonesia. Our research took place on a small archipelago, Selayar, located in South Sulawesi. Figure 1 below presents a map of Selayar. This study took place as a part of a larger project, Capturing Coral Reef and Related Ecosystem

EP

Services (CCRES). The objective of the project was to investigate the dimensions relating to the use and utility of ecosystems, as well as to develop solutions to help protect the biosphere and enhance the

AC C

livelihoods of coastal communities in Southeast Asia. Selayar Island as a whole was selected as a project site because of overall awareness of environmental issues and desire to adopt more sustainable practices expressed by villagers. Much of the research generated from this project has focused on marine protected areas (Krueck et al., 2017, 2018), pollution inputs into the ocean (Wolff et al., 2015), and coral reef ecosystem degradation (Lamb et al., 2017; Rogers, Blanchard, & Mumby, 2014). Building on prior project research and engagement with Selayar communities, the current research is part of the project

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR that focuses on the human dimension of ecosystem services and what factors may contribute to more environmentally sustainable intentions. The predictors included in the model, the behaviors used as dependent variables, and the procedures have all been informed by two years of site visits, local

RI PT

contextual knowledge, and approximately ten hours of focus group discussions (FGDs) with target communities. The thematic analysis from our FGDs aided in informing which behaviors to focus on (i.e. fishing and waste disposal), and additional predictors to augment standard predictors of the TPB (i.e.

SC

descriptive norms, awareness of consequences, responsibility diffusion, and perceptions of change). Statements that mapped onto these predictors and behaviors were discussed at a much higher frequency

AC C

EP

TE D

predictors (i.e. self-efficacy or moral norms).

M AN U

than other environmental behaviors (i.e. transport or energy saving) or other commonly cited additional

Figure 1. A Map of Selayar Island located in South Sulawesi. The top left panel depicts a zoomed in view of Selayar Island with dots indicating study village locations (Google, 2019).

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR Selayar comprises communities who remain relatively untouched by western influences. This population is also uniquely reliant on the natural, marine resources that surround the island. Communities rely heavily on the coastal epipelagic fish (e.g., grouper fish, parrotfish, prawn, and squid)

RI PT

for food and trade, as well as natural resources such as coconuts, sea grass and mangroves for food and resources. They rely significantly more on coastal flats because most boats are not suitable for deep ocean fishing. The soil and topography makes agriculture, farming, and raising livestock difficult

SC

(Dirhamsyah, 2004). The marine ecosystems in proximity to the island are the primary source of sustenance and the economy, with 47% of the island workforce exclusively devoted to aquaculture due

M AN U

to the unavailability of land-based agriculture (BPS Selayar Statistics, 2017). Selayar also faces barriers of infrastructure and capacity. A majority of households do not have access to clean water with 59% of households relying on protected wells or protected springs for drinking water. It is estimated that 41% of Selayar’s adult population have only completed primary school, and 25% have no schooling at all.

TE D

Additionally, reports suggest that one in every eleven adults is entirely illiterate (BPS Selayar Statistics, 2017). These are a few among the many challenges small islands like Selayar face. Against this backdrop, we investigated the social psychological predictors of villager’s intentions to use nets and

EP

lines to fish (sustainable fishing methods) and intentions to dispose of waste in a responsible manner (as opposed to throwing it in the ocean).

AC C

Prior work in the CCRES project with Selayarese communities and other populations in Indonesia (Chan & Hodgson, 2017; Lamb et al., 2018), has revealed fishing and waste disposal are the most focal environmental behaviors for Selayar communities. Fishing has become complicated with the emergence of cyanide poison and fertilizer bomb fishing methods over the past few decades. These methods do irreparable harm to coral reefs and fish stocks (Ferse, Glaser, Neil, & Schwerdtner Máñez, 2014; Fox & Caldwell, 2006); but these methods are also seen as being more profitable despite evidence

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR to the contrary (Chan & Hodgson, 2017; Pet-soede et al., 1999), and younger generations are at risk of not learning how to fish using traditional, sustainable methods. While villagers are aware that destructive fishing practices are harmful and sustainable alternatives are affordable and available, trends

RI PT

of destructive fishing persist.

The increase in plastic consumption is also problematic for low-resource island communities. Due to the lack of infrastructure, solutions to managing waste are sparse—especially plastic waste that

SC

can take centuries to degrade. Selayar communities often burn and bury waste. Though recently, more desirable alternatives have emerged, such as: local garbage banks that collect and sort plastics; informal

M AN U

composting pits where degradable waste is collected; co-ops that turn discarded plastic into commodities like furniture, artificial plants, or jewelry. These alternatives, despite being favorable, are often overlooked, and villagers opt to throw their waste into the ocean because it is the easiest disposal behavior. The plastic contaminants in the oceans are problematic for ecosystem health and human health

TE D

(Lamb et al., 2018; Landrigan et al., 2017; Thompson, Moore, vom Saal, & Swan, 2009). Drawing on the well-established theory of planned behavior as a starting point we seek to identify potential determinants of fishing and waste-related behaviors in low-resource coastal

EP

communities, specifically an Indonesian island community. If we are to develop effective ways to intervene to promote more sustainable marine protection practices in developing world communities, an

AC C

important first step is to understand the factors that underpin these practices (McKenzie-Mohr, 2000). The current research addresses this issue through conducting a survey of members of the coastal community on the island of Selayar, located in South Sulawesi, Indonesia. Our aim is to identify social psychological variables that may underpin community members’ decisions to engage in marine protective behaviors. Behaviors such as fishing and waste management have a substantial impact on livelihood and health. Fishing is a daily source of sustenance and income, and thus, the use of

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR destructive fishing practices can severely hinder access to food and revenue (Dirhamsyah, 2004; Fox & Caldwell, 2006; Pet-soede et al., 1999). Similarly, there is a growing body of evidence supporting the damaging effects of waste, specifically plastic, on oceans and communities. With no formalized system

RI PT

of waste processing or disposal, communities like Selayar are at increased risk of experiencing the harmful effects of ocean plastics (Geyer, Jambeck, & Law, 2017; Lamb et al., 2018; Thompson et al., 2009).

SC

1.1 Adapted theory of planned behavior

M AN U

In the current research we sought to identify social psychological factors associated with behavioral intentions of local villagers to engage in sustainable fishing behaviors (e.g., using nets and lines) and sustainable waste disposal behaviors (e.g., keeping their waste out of the ocean). The theory of planned behavior (TPB) is a widely utilized model for identifying the psychological determinants of behavioral intentions and subsequent behavior (Ajzen, 1991). According to the TPB, attitudes (i.e.,

TE D

positive or negative evaluation) toward the behavior, subjective norms (i.e., perceptions of support for the behavior of important others), and perceived behavioral control over a behavior predict behavioral intentions, which reflect the motivations of an individual to engage in the behavior (Ajzen, 1991).

EP

Intentions in turn predict behavior (Ajzen, 1985, 1991; Fishbein & Ajzen, 1977). TPB has been used to understand the underpinnings of environmental and conservation behavior (Gifford, 2007; Klöckner,

AC C

2013; Lee & Tanusia, 2016; López-Mosquera, García, & Barrena, 2014; Steg & Vlek, 2009; Stern, 2000) although to our knowledge no studies have applied it to environmental behaviors in developing world contexts. We sought to investigate determinants already validated in TPB and to add psychological constructs that we hypothesized may also play a role in influencing the focal behaviors. A strength of TPB is that it allows for the incorporation of other variables that may be important for the specific behavioral context.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 1.1.2. Attitudes. Research has suggested that attitudes—one’s degree of favorable or unfavorable assessment toward a behavior—are an important determinant of behavior (Ajzen & Fishbein, 1977; Fishbein & Ajzen, 1977). In the context of this study, attitudes toward fishing practices

RI PT

may play an integral role in whether villagers decide to use sustainable or destructive methods of fishing. Similarly, attitudes toward waste disposal could equally play a role in intention to engage in

(Mannetti, Pierro, & Livi, 2004; Taylor & Todd, 1995).

SC

sustainable waste disposal practices as has been shown in prior research in developed country settings

1.1.3. Descriptive Norms. Social norms, the perception of what most people do within a group,

M AN U

play a vital role in influencing behavior (Ajzen, 1991; Cialdini, Kallgren, & Reno, 1991; Nolan, Schultz, Cialdini, Goldstein, & Griskevicius, 2008). Norms are a key construct of focus in understanding environmental behaviors (Carrus, Passafaro, & Bonnes, 2008; Goldstein, Cialdini, & Griskevicius, 2008; Hurlstone et al., 2014; Klöckner, 2013; Nolan et al., 2008; Sawitri, Hadiyanto, & Hadi, 2015;

TE D

Schultz, Nolan, Cialdini, Goldstein, & Griskevicius, 2007; Steg, Bolderdijk, Keizer, & Perlaviciute, 2014). Within the theory of planned behavior norms are conceptualized as subjective norms, which are perceptions of what important others think we should do. A meta-analysis and further research suggest

EP

subjective norms may be the weakest TPB predictor and alternative norms could possess stronger predictive utility (Armitage & Conner, 2001; Rivis, Sheeran, & Armitage, 2006). In small homogeneous

AC C

village contexts, it may not be perceptions of social approval of important others, but rather perceptions of what other village members are actually doing in relation to fishing and waste management practices that may play an important role in determining behavior. This maps onto the concept of descriptive norms which refer to perceptions of what actions are believed to be most common in a given setting (Cialdini et al., 1991; Keizer, Lindenberg, & Steg, 2008). A meta-analysis investigating the importance of descriptive norms as an additional predictor in the TPB suggests that observing others’ behavior may

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR be more useful than perceptions of what others think we should do for predicting intentions (Rivis & Sheeran, 2003). Descriptive norms have been experimentally shown to play an important role in one’s decision to engage in littering behavior (Cialdini, 2003; Keizer et al., 2008) as well as other

RI PT

environmentally-related behaviors such as energy and water saving behavior (Abrahamse, Steg, Vlek, & Rothengatter, 2005; Goldstein et al., 2008; Lam, 2006; Lee & Tanusia, 2016; Nolan et al., 2008). In small communities with little external influence or policing, if individuals perceive that everyone in their

SC

village is engaging in a behavior, norms may provide a social license to engage (or not) in a given action.

M AN U

1.1.4. Perceived behavioral control (PBC). PBC reflects individuals’ perceptions of the difficulty of engaging in a behavior as well as the actual difficulty of engaging in a behavior. This ease or difficulty assessment is a vital determinant in the actor’s decision to engage in a given behavior (Ajzen, 1991). In the environmental context of Selayar, even if villagers have a strong desire to adopt

TE D

more sustainable practices, such as using nets or lines or proper disposal of waste, without the confidence that they can undertake these behaviors or the availability of favorable alternatives, it is unlikely that they will engage in them. It has been consistently demonstrated in relation to

EP

environmental behaviors that perceptions of efficacy, confidence, and competence can have a strong influence on the activities selected and maintained given various choices (Armitage & Conner, 2001;

AC C

Bamberg & Möser, 2007; Klöckner, 2013). 1.1.5. Awareness of consequences (AWC). In the current study, we also assess whether beliefs about whether one’s own behaviors and the behavior of the community can affect the status of marine ecosystem health, predicts fishing and waste behavior intentions. We reason that unless people perceive the connection between their behavior and the health of marine ecosystems, they are unlikely to be prepared to change their behavior. This concept is a construct encompassed in the value-belief-norm

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR (VBN) model (Stern, 2000). According to the VBN, the belief that one’s behavior will have consequences for the environment is part of a chain of beliefs that leads to a sense of obligation to act to protect the environment. Support for awareness of consequences as an antecedent to personal norms and

RI PT

behavioral intentions has been demonstrated in a meta-analysis of predictors of environmental behavior (Klöckner, 2013). In the current study we broaden this concept to include not just perceptions of whether one’s own behavior has consequences for the environment, but also whether the behavior of the

SC

community has consequences. This broader conception may be warranted in developing world contexts in which there is a high degree of interconnectedness between the self and others in the village and in

M AN U

other villages. An understanding of behavioral impact, and how behaviors produce consequences, would then be an important precursor to intentions—especially when managing an uncertain resource where minor consequences may seem negligible. Perceiving that individual and community behavior can have an impact on marine environments may therefore be an important motivator of actions that protect the

TE D

surrounding oceans.

1.1.6. Responsibility diffusion. During preliminary interviews with villagers the notion of responsibility diffusion emerged. Each village claimed that their village was not responsible for

EP

destructive practices taking place, that instead it was neighboring villages. The act of blaming or scapegoating others has underlying psychological motives. It allows groups to maintain their perceived

AC C

moral value—villages can claim they are not the source of undesirable actions causing negative outcomes. And it allows groups to maintain their perceived control over outcomes (Rothschild, Landau, Sullivan, & Keefer, 2012). This dual motive model of scapegoating behavior has been demonstrated to motivate blaming behavior in other negative environmental outcomes such as climate change (Rothschild et al., 2012). This could consequently undermine intentions to behave sustainably by shifting the responsibility for the problem.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 1.1.7. Perceptions of Change. Another potentially important predictor of motivation for sustainable actions in this context is whether or not villagers actually perceive that their coastal environments are being degraded. Biophysical research shows significant declines in Southeast Asian

RI PT

reefs and fisheries (Burke, Reytar, Spalding, & Perry, 2011; Ferse et al., 2014; Pandolfi et al., 2003). If villagers perceive negative change, then they may be motivated to act to protect the environment. Research on protection motivation theory has highlighted the important role that negative perceptions

SC

play in motivating behavior (Floyd, Prentice-Dunn, & Rogers, 2000; Milen, Sheeran, & Orbell, 2000; R. W. Rogers, 1975) and more specifically sustainable behavior (Bockarjova & Steg, 2014; Keshavarz &

M AN U

Karami, 2016). Further, the protection motivation variables severity and probability of consequences has demonstrated in prior studies of environmental behavior to be an effective addition to theory of planned behavior variables (Kim, Jeong, & Hwang, 2013). If villagers perceive negative changes, they may be more likely to intend to engage in the sustainable focal behaviors.

TE D

However, the detection of degradation of these resources can often be hidden from direct view or difficult to observe. Shifting baseline syndrome suggests that perceptions of change can stand in the way of action (Papworth, Rist, Coad, & Milner-Gulland, 2009; Soga & Gaston, 2018). This perspective

EP

argues that whether due to personal or generational factors, the normalization of degradation can hinder intentions and action, despite resounding physical evidence. Prior research has suggested shifting

AC C

baseline syndrome may explain why Indonesian fishermen accept depleting fish stocks with few signs of intentions to act (Ainsworth, Pitcher, & Rotinsulu, 2008). From this perspective participants may not perceive that the marine environment has deteriorated and may not feel a need to act to protect it. 1.2. The current study The current research makes important contributions to the literature on determinants of environmental actions. The majority of the literature examining psychological predictors of

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR environmental behavior focuses on actions that can be taken by western, industrialized, and affluent populations. For example, conserving energy in the household (Abrahamse, Steg, Vlek, & Rothengatter, 2007), conserving water (Dolnicar, Hurlimann, & Grün, 2012), and driving one’s vehicle less (Steg,

RI PT

Vlek, & Slotegraaf, 2001). Although this research provides important insights, it is skewed toward behaviors that are only available and applicable to a small fraction of the world’s population. This paper

of prevalence in commonly studied populations.

SC

investigates behaviors that have direct effects on the environment, but are under-investigated due to lack

Our research tests the extent to which models of behavioral decision-making that have been

M AN U

widely utilized in the context of the developed world, map onto novel behaviors with significant implications for low-resource populations. We examine whether the same psychological constructs govern the behavior of low-resource coastal communities who engage in different behaviors than western, educated, industrialized, rich, and democratic (WEIRD) populations. With burgeoning scrutiny

TE D

on behavioral sciences focusing nearly exclusively on these types of samples, it is imperative that research be done in alternative contexts reflecting a broader demographic range (Henrich et al., 2017). 1.3. Hypotheses

EP

We hypothesized that determinants of the Theory of Planned Behavior (e.g. Attitudes, Norms, Perceived Behavioral Control) would be significant predictors of behavioral intentions of sustainable

AC C

fishing practices (e.g. using nets and lines to fish) and behavioral intentions of sustainable waste disposal practices (e.g. keeping one’s waste out of the ocean). Specifically, we predict that stronger negative attitudes toward destructive fishing practices and improper waste disposal; a stronger belief that people in their village engage in sustainable fishing practices and waste disposal practices, and greater perceived behavioral control over using nets and lines to fish and proper waste disposal practices, would predict villagers’ likelihood to engage in using nets or lines to fish and finding more responsible

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR methods to dispose of waste (i.e., informal land fills, burying, etc.). Further, we hypothesized that responsibility diffusion (placing the blame of negative consequences on others) and awareness of consequences (belief that one’s behavior and one’s community’s behavior will have an impact on

RI PT

marine resources), would be significant in predicting behavioral intentions. We hypothesized that those who were less likely to blame others for the destruction of the coral reefs and those who believe that their behavior and that of their village has an impact on the oceans would be more likely to intend to

SC

engage in the focal sustainable behaviors. Finally, we predicted that perceptions of change would have an inverse relationship with behavioral intentions, that is, participants who hold a negative outlook on

M AN U

ecosystem trends will be more likely to intend to engage in the sustainable actions of using nets and lines to fish and disposing of waste responsibly as these behaviors will be perceived as needed if the marine environment is being degraded.

2. Method

TE D

All research was conducted on Selayar Island, located in Southwest Sulawesi Indonesia using surveys. This site was selected as a prime case study because of its reliance on marine ecosystems and isolation from external influences. Participants (n = 104) were recruited via village heads and local

EP

project personnel. We asked for adult men, adult women, and young adults—it was required that these three groups be surveyed separately due to sociocultural practices. Additionally, we asked that

AC C

participants be able to read and write. Village heads then proceeded to initiate phone calls, letters, and word-of-mouth messages through local channels to recruit participants within their own villages. Participants were recruited from three villages. Researchers moved to each village to meet participants in an attempt to reduce the burden of travel for them. We recruited participants from three villages for two primary reasons. First, to reach an adequate sample size recruiting from one village would not be sufficient. Second, we sought to engage with communities who had not been previously studied for

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR other research in the project. The aim was to be considerate of the potential for research fatigue and avoid any influence of prior project exposure. 2.1. Participants

RI PT

The sample of N = 104 villagers had a mean age of 40.48 years (SD = 13.17), ranging from 1845. The sample consisted of 53 males (51%) and 51 females (49%). A majority of participants (61%) reported a monthly household earning of less than 1,050,000 Rupiah per month (approximately 100

SC

USD), with an additional 17.1% reporting monthly earnings of 1,050,000 to 1,505,000 per month (100 USD - 150 USD). Further, 61% of the sample reported fishing as their primary source of income, with

M AN U

14.3% reporting owning a business, 20% reporting miscellaneous sources of income, and the remaining 4.7% not reporting. 2.2. Procedure

Surveys were administered in groups of around 12 people in meeting venues in each of the

TE D

villages. Meeting venues included village community centers and the homes of village heads. Paper surveys were the only viable option, thus, meeting in a designated location to administer surveys was ideal for reaching the most participants. Due to cultural practices, participant groups were based on

EP

gender and age (e.g., groups of all women, groups of all men, and groups of young adults with mixed genders). Surveys were conducted in groups because many participants struggle with vision impairment,

AC C

literacy, and using writing utensils. By conducting surveys in small groups it was possible for researchers to assist any participants who needed help. For example, participants with lower literacy levels or poor vision could ask for assistance reading questions; participants who did not understand likert-scales could ask for further clarification; and participants with no access to writing equipment could borrow pens.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR Upon arrival, participants were provided with a paper survey that they were asked to complete. Researchers read aloud to each participant the information and consent form attached to the front of each survey. Verbal consent was attained after all participants had the opportunity to ask any questions or

RI PT

voice any concerns. This included the reading of ethical rights for the participants to not complete the survey if they felt uncomfortable. Participants were reminded that their answers would remain

anonymous and that there were no right or wrong answers. Then a base set of rules was explained to

SC

participants to ensure smooth facilitation of survey completion: there are no right answers, participants should not share their answers with other participants, individuals should not tell other participants what

M AN U

the right answers are, talking should be kept at a minimum such that all participants are given the opportunity to focus, and if help is required, participants should raise their hands. We also provided a brief exhibition tutorial for participants to model how to answer survey questions using an unrelated examples (i.e., ‘I like fried bananas’ 1 = strongly disagree to 5 = strongly agree) to ensure participants

TE D

understood answers should reflect personal beliefs. Researchers and in-country personnel were present to aid any participants who struggled to understand any of the questions. Otherwise, no active intervention or guidance was permitted, and villagers were asked to answer questions candidly.

EP

Following the completion of the survey, researchers collected all materials. 2.3. Measures and questionnaire development

AC C

All materials were translated to Bahasa, and then back translated to ensure clarity. The survey was piloted internally with Bahasa speakers within our research group. Items were edited for clarity and removed based on feedback from this process. Also, with consideration to literacy levels, the entire inventory was constructed to be as short as possible and with very basic vocabulary. Consequently, a majority of the constructs investigated were assessed using one or two items. Questions assessing additional variables, such as locus of control, subjective norms, resource uncertainty, environmental

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR awareness, and intertemporal choice were also collected. Because of the lack of variance on responses to these questions they are not included in the analyses. Questions for the adapted TPB model were designed following Theory of Planned Behavior

RI PT

question design protocols recommended by Azjen (1991), but then adapted to the context. Questions assessing awareness of consequences were adapted from previous research (Umphrey, 2004). The remaining questions for responsibility diffusion and perceptions of change were created uniquely for this

SC

study. With the exception of the questions assessing perceptions of change and PBC, all other questions were measured on a 5-point likert scale—from strongly disagree to strongly agree (unless stated

M AN U

otherwise). Due to expectations of literacy levels, unfamiliarity with likert scales within the target population, and necessity of translation, questions were designed to be highly face valid. Each question, or in some cases pair of questions, was intended to capture a single psychological construct. 2.3.1. Attitudes. Single items were used to assess attitudes toward fishing sustainably and

TE D

attitudes toward sustainable waste disposal. The attitude items diverge from the usual theory of planned behavior format. We believed that asking participants their attitudes about the use of nets or lines to fish and proper disposal of waste (both legal behaviors) might have led them to feel obliged to ‘strongly

EP

agree’ in accordance with the law. With this consideration in mind, we instead asked their attitudes

AC C

towards the reciprocal, negative behaviors (both illegal, though commonly practiced) to see if we could elicit a more genuine response. We also used less confronting language (i.e., sometimes) such that people may be more likely to give us honest responses. The specific questions were: (a) sometimes it is okay to bomb fish; (b) sometimes it is okay to throw waste in the ocean. We then reverse-scored these

items (i.e., higher scores reflect stronger attitudes against destructive practices). 2.3.2. Descriptive norms were measured with single items: most people I know use nets or lines to catch fish; most people I know dispose of their waste responsibly.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 2.3.3. PBC was measured with single items: (a) how confident are you in your ability to fish using nets and lines over the next month; (b) how confident are you in your ability to keep your waste

confident).

RI PT

out of the ocean over the next month. The response options were: 1 (not confident at all) to 5 (very

2.3.4. Responsibility Diffusion was measured using a single-item: It is not our village destroying the coral reefs, it is other villages.

SC

2.3.5. Awareness of consequences: Two questions were used to measure this variable: I believe my actions have an impact on the oceans; I believe my community’s actions have an impact on the

M AN U

oceans. As the items were highly correlated (r = 0.63, p < 0.001), they were averaged to form a

composite awareness of consequences score with higher scores representing greater awareness of consequences.

2.3.6. Perceptions of change Participants’ perceptions of changes to marine ecosystem factors

TE D

were measured using two questions with binary response options. Participants were first asked two questions to indicate whether they perceived a change to coral reefs and fish stocks: Do you believe the health of the reefs has changed over the past three years?; Do you believe the fish stock has changed

EP

over the past three years?. If participants selected that they had perceived a change, they were then

asked to indicate whether they had changed in a “positive or a negative direction”. Answers for the

AC C

second questions were coded as 0 (negative perception) or 1 (positive direction). Individuals who indicated they believed no change had occurred to the health of the reefs or to fish stocks were excluded from further analysis (n = 7). Responses to the two questions were highly correlated (r = 0.67, p < 0.001) and were therefore aggregated forming a scale that ranged from 0=negative perceptions of ecosystem change, 1=some perceived positive change, 2=positive perceptions of ecosystem change.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 2.3.7. Behavioral Intentions Single items assessed intentions: Over the next month, will you use nets or lines to fish; Over the next month when disposing of your waste, will you keep your waste out of the ocean?

RI PT

2.4. Data Analysis

To address our hypotheses, two sets of multiple-regression analyses were conducted regressing behavioral intentions regarding sustainable fishing and waste disposal onto the predictor variables:

SC

attitudes, descriptive norms, perceived behavioral control (PBC), awareness of consequences,

responsibility diffusion, and perceptions of change. Effect sizes were then assessed using Cohen’s f2 for

M AN U

each respective model (Cohen, 1988).

3. Results

Table 1 below summarizes the means, standard deviations and correlations among the variables. Behavioral intentions to fish sustainably are significantly correlated with descriptive norms,

TE D

responsibility diffusion, and awareness of consequences whereas behavioral intentions to sustainably dispose of waste are significantly correlated with attitudes, descriptive norms, PBC, and perceptions of change. Participant intention scores for both behaviors are relatively high and attitudes x toward

EP

destructive, non-sustainable behaviors are relatively negative. Similarly norms tend to have high scores for both behaviors. Participant’s confidence in their ability to engage in either behavior is moderate,

AC C

sitting around the midpoint of the scale. Table 1

Correlation Matrix of Focal Variables for Sustainable Fishing and Waste Practices. Intentions to use nets and lines to fish Focal Variables 1

Behavioral Intentions

M (SD)

1

4.40(0.52)

-

2

3

4

5

6

7

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR Attitudes

4.44(0.56)

0.15

-

3

Descriptive Norms

4.33(0.48)

0.24*

0.20

-

4

PBC

2.95(0.51)

-0.11

0.26*

-0.12

-

5

Resp. Diffusion †

3.45(1.19) 0.41**

-0.12

-0.02

0.01

6

AWC

3.81(0.79) 0.37** -0.27** 0.01

-0.01

7

Perception of Change

1.19(0.90)

-.09

-.05

-.05

-.09

-

RI PT

2

.34**

-

-.13

-.12

-

Focal Variables

M (SD)

1 -

2

Behavioral Intentions

4.04(1.36)

2

Attitudes

4.13(0.73) 0.31**

3

Descriptive Norms

3.95(0.90) -0.34** -0.52**

4

PBC

2.59(0.71) 0.45**

5

Resp. Diffusion†

3.45(1.19)

-0.01

6

AWC

3.81(0.79)

0.13

7

Perception of Change

1.19(0.90) .37**

4

M AN U

1

3

SC

Intentions to keep waste out of the ocean 5

6

7

-

-

-0.17

-

-0.09

0.02

.12

-

0.05

0.02

0.23*

.34**

-.17

.33** -.13

TE D

0.05

-.11

-.19

-

Note: *p < .05. **p < .01. Significant correlations bolded. N =104. † Abbreviation for responsibility diffusion.

EP

3.1. Predicting intentions to engage in sustainable fishing practices As Table 2 shows, the variables in the model accounted for a significant proportion of the

AC C

variance in intentions to engage in fishing using nets and lines, F(6,98) = 6.260, p < .000, R2= 0.366, f2= 0.58. This is a large effect size (Cohen, 1988). Three of the six variables in the model emerged as significant predictors: attitudes, awareness of consequences, and responsibility diffusion. Villagers who had stronger intentions to use nets and lines had more negative attitudes to using bombs for fishing, had greater perceptions that their own and community actions impacted on oceans, and had greater perception that other villages rather than their own are damaging the reefs.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 3.2. Predicting intentions to engage in sustainable waste disposal practices Table 2 also shows that the variables in the model accounted for significant variance in intentions to dispose of waste appropriately (i.e., not in the ocean), F(6,98) = 7.503, p < .000, R2= 0.369,

RI PT

f2= 0.58 (see Table 2). This is again a large effect size (Cohen, 1988). Three of the six variables

significantly contributed to the explained variance in intentions to dispose of waste responsibly, although the significant predictors for waste intentions were somewhat different to sustainable fishing

SC

intentions. Attitudes, perceived behavioral control, and perceptions of change, all emerged as significant predictors. Villagers who had stronger intentions to dispose of their waste sustainably (i.e., responsible

M AN U

disposal through landfill) had more negative attitudes toward throwing their waste in the ocean, had greater confidence in their ability to dispose of their waste responsibly, and also had higher perceptions of change, that is, felt that the marine ecosystems were changing in a positive direction. A full summary of regression models can be found in Table 2.

TE D

Table 2

EP

Regression Results for Models Predicting Behavioral Intentions of Sustainable Fishing and Waste Disposal Practices Model For Behavioral Intentions of Sustainable Fishing Beta SE p CI (lower) CI (upper) Variables

0. 293 0. 174 -0.166 0.339 0. 342 0.054

0.103 .010 .068 .479 0.113 .096 -.035 .418 0.106 .117 -.378 .043 0.046 .002 .056 .239 0.071 .003 .081 .365 0.058 .597 -.085 .147 2 F(6,98) = 6.260, p < .001, R = 0.366, f2= 0.58 Model For Behavioral Intentions of Waste Disposal Beta SE p CI (lower) CI (upper)

AC C

Attitudes Descriptive Norms PBC Responsibility Diffusion AWC Perceptions of Change

Variables Model 2

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR 0.266 0.102 0.301 -0.016 0.089 0.290

0. 205 .021 .078 .907 .168 .370 -0.186 0.494 0.193 .004 .189 .957 0.112 .872 -.241 .205 0.171 .376 -.188 .493 0.155 .006 .130 .746 2 F(6,98) = 7.503, p < .001, R = 0.369, f2= 0.58

RI PT

Attitudes Descriptive Norms PBC Responsibility Diffusion AWC Perceptions of Change

M AN U

4. Discussion

SC

Note. Beta values, standard error, and 95% confidence intervals were obtained through bias-corrected bootstrap with 10,000 resamples. CI (lower) = lower bound of a 95% confidence interval; CI (upper) = upper bound. The dependent variable for the sustainable fishing model is behavior intentions to use nets and lines to fish. The dependent variable for the waste model is behavior intentions to keep waste out of the oceans. PBC = perceived behavioural control and AWC = awareness of consequences.

We sought to investigate whether an adapted TPB may be a useful model in understanding behavioral intentions to engage in sustainable fishing and waste disposal practices of villagers in lowresource coastal communities in Indonesia. It is interesting to note that there were more differences in

TE D

the significant predictors across the two behaviors than there were similarities. Indeed, attitudes were the only predictor that significantly predicted both behaviors. This pattern highlights that participants likely do not conceptualize these 'sustainable' behaviors in the same way and therefore it is important to

EP

identify the unique predictors of the different behaviors. As noted above, attitudes were the only variable that was a consistent predictor across both

AC C

behaviors: participants who had stronger negative attitudes toward destructive fishing practices had greater intentions to use nets and lines for fishing and those who had stronger negative attitudes to throwing waste into the ocean had greater intentions to properly dispose of their household waste. The link from attitudes to intentions has been well established in past literature, and specifically in the context of environmental behavior (Abrahamse et al., 2005; Klöckner, 2013; Lam, 2006; Lee & Tanusia, 2016).

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR Despite past research showing that descriptive norms influence environmental behavior (Cialdini et al., 1991; Goldstein et al., 2008; Steg & Vlek, 2009; van der Linden, 2015), this variable did not emerge as a significant predictor of either sustainable fishing or waste management intentions. One

RI PT

potential reason for this finding could be that the village is not the relevant reference group for the focal behaviors. We focused on the descriptive norms of the village whereas the theory of planned behavior focuses on subjective norms, that is, perceived support of important others. We chose to do this because

SC

of the relatively weak effects that subjective norms have exhibited in past TPB studies (Armitage & Conner, 2001), and the demonstrated effect of descriptive norms on intentions and behavior (Goldstein

M AN U

et al., 2008; Rivis & Sheeran, 2003). It may be that we did not identify the most relevant important others. It might be the family, village elder, or informal leaders who are the most important influence on these behaviors. Specifying the most influential members may have yielded stronger findings. In many TPB studies it is suggested that an elicitation survey be done to establish relevant reference groups.

TE D

Future research in developing country contexts would benefit from this approach, as well as incorporating subjective norms into predictive models. Perceived behavioral control emerged as a significant predictor of sustainable waste management

EP

intentions: those who feel confident in their capacity to properly dispose of their waste were more likely to intend to do so. This may be indicative of the context surrounding waste disposal practices and how

AC C

that differs from fishing behaviors. The infrastructure and services for proper processing of waste and plastics is sparse and this reality may explain the importance of PBC in intentions to dispose of waste. The lack of infrastructure may contribute to perceptions of control, as the availability of sustainable options is severely limited. Those who do have abundant access to desirable waste disposal options or live in communities that prioritize sustainable methods may experience increased PBC. In such a case, a person who has a high PBC score may have individuals around her who can show her how to dispose of

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR waste and facilities to dispose of waste sustainably would be accessible. The TPB highlights that PBC reflects both perceived and actual control (Ajzen, 1985, 1991). In the current study, participants’ perception of their ability to manage their waste could be a realistic reflection of the differences in

RI PT

availability of appropriate waste management options. Thus, these objective constraints present tangible barriers to intentions and actions of sustainable waste management. Conversely, PBC did not

significantly predict intentions to fish using nets and lines. One reason why this variable did not

SC

influence fishing intentions may be that fishing is such a ubiquitous daily necessity that perceived difficulty or confidence has no significant link to sustainable or destructive intentions in this context.

M AN U

Engaging in sustainable fishing practices may be less difficult or cost intensive than previously assumed, thus rendering PBC inconsequential to intentions. Overall, the findings from this study provide support for the TPB with attitudes and PBC emerging as significant of intentions of one or both behaviors. Of the additional variables included to augment the TPB, awareness of consequences was a

TE D

significant predictor of sustainable fishing intentions. The more participants perceived their behaviors and those of their community have an impact on the environment, the more likely they were to intend to use nets and lines to fish. Villagers who hold beliefs that their behaviors produce tangible impacts

EP

should rationally feel an obligation to engage in behaviors that produce positive outcomes and not negative ones. Conversely, if people do not see a connection between their individual and collective

AC C

behavior and environmental outcomes, then there will be little motivation to adopt sustainable behaviors (Lam, 2006). Rather, their fishing or waste management practices would depend on which methods are easiest, most available and which methods are perceived to maximize yield (in the case of fishing). As we outlined earlier, in preliminary discussions with villagers, beliefs that people from other villages are the perpetrators of environmental destruction emerged. To assess whether these beliefs were important predictors of behavioral intentions we assessed the effects of responsibility diffusion on

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR behavioral intentions. Interestingly, this variable emerged as a significant predictor of sustainable fishing intentions but in the opposite direction of our prediction. Our findings suggest that those who blame others for harming the environment are more likely to intend to fish using nets and lines. One potential

RI PT

explanation can be derived from the dual-motive scapegoating approach, which allows each village to retain their sense of virtue and value. They can witness negative behaviors taking place without conceding that it may be members of their own village. This is consistent with the dual-motive model of

SC

scapegoating, wherein individuals respond to a value and moral threat by blaming others, whilst maintaining a sense of perceived personal value and control. In our case, villagers are consistently

M AN U

witnessing boats engaging in destructive fishing practices off their shores. Instead of acknowledging that these boats belong to fellow villagers, it may be cognitively easier to insist these fishermen are coming from other villages and that these external fishermen are the ones responsible for reef damage. Another finding that ran counter to predictions was that those who perceived that the health of

TE D

the ecosystems and the fish stock surrounding their island is changing in a positive direction (e.g., more fish and better health of surrounding marine ecosystems) had greater intentions to dispose of waste sustainably. Perhaps optimistic villagers feel the resources are improving and they would like to

EP

contribute to future improvement. It may be motivating to perceive change has been incrementally positive and individuals should do their part to sustain positive change. This approach is consistent with

AC C

the broaden and build theory held within positive psychology that positive thoughts and actions can create psychological momentum aimed to sustain, strengthen, and reinforce further positive thoughts and actions (Fredrickson, 2001). The perception of positive trends may be the proof necessary to increase sustainable intentions. Another possibility is that the habitats experienced by villagers may vary in their quality, with some more or less degraded. When responding to this question, villagers may have those habitats that have experienced little or less change in mind.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR Conversely, perceptions of change were not significant for sustainable fishing practices. This could be explained by the differences in visibility between waste and fishing. Despite optimistic perceptions of change scores for both practices, perhaps the ability to see the effect of fishing versus

RI PT

waste mediates the impact on intentions. When an individual collects a piece of plastic off the ground the environment visibly looks cleaner, contributing to perceptions of positive changes and creating a positive feedback loop for intentions to dispose of waste sustainably. When an individual fishes

SC

sustainably they do not immediately see the effect of selecting a sustainable method over a destructive method. It is difficult to envisage the net positive impact on habitat health when a practice is selected

M AN U

that sustains the status quo. This lack of immediate visible effect would explain why perceptions of change are not strongly predictive of intentions to fish sustainably.

In contrast to the positive perceptions of change on the part of some participants, evidence suggests that marine ecosystems are in danger and fish stock is constantly under threat from destructive

TE D

fishing and toxic waste disposal—practices known to be prevalent on the island. It could be that villagers might not perceive a drastic decline of resource availability because resources have not suddenly vanished, but instead, declined slowly over time. This finding aligns with what might be

EP

expected with shifting cognitive baselines (Ainsworth et al., 2008; Papworth et al., 2009; Soga & Gaston, 2018). Without physical inspection or proper monitoring mechanisms of these resources, it may

AC C

be difficult for villagers to detect an objective change beyond their own fishing experiences. Future research is needed to explore the explanations we have advanced for the unexpected findings, and to confirm that the findings generalize to other communities. 4.1. Limitations

The context of the research presented a range of challenges including language, literacy levels, and the introduction of novel data collection methods like surveys and likert-scales to these

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR communities. In terms of language, in Selayarese (the local dialect) words, phrases, or ideas taken as commonplace within the English language had no direct translation for Selayarese. In addition, Selayarese lacks tenses; consequently anything spoken is presented as a present statement and future

RI PT

action becomes a difficult concept to convey. When literacy levels fall below a certain threshold, it becomes impractical to maintain questions in their original format, as the understanding of the questions diminishes. These constraints meant that we used simply worded single items to measure most of our

SC

constructs and this is a limitation to the measurement in the study. Literacy also limited how many variables we could test. For example, we opted to test descriptive norms in our model instead of

M AN U

subjective norms. Ideally we would have collected data on multiple types of norms, however, this was not possible in the current study. Future research should expand and validate the model, such that potentially influential variables like injunctive norms need not be left out and construct validity can be supported.

TE D

Another limitation of the research is that we measured intentions rather than actual behavior and past research has shown that intentions do not always translate into behavior due to factors of volitional control—both internal and external (Ajzen, 1985; Kollmuss & Agyeman, 2002; Sheeran, 2002; Sheeran

EP

& Webb, 2016). Frequently in field research the ability to actively and accurately monitor direct behaviors is difficult. In the context of this study, there are added legal and physical complications that

AC C

make direct behavioral monitoring unfeasible. We attempted to address this by measuring behavioral intentions as a proxy for actual behavior. Behavioral intentions, along with its determinants, has been used and validated as a sufficient link to determine how one may behave in the future (Ajzen, 1991). A final limitation of the research was the internal validity of constructs and the lack of specificity within the model. Constrained by literacy levels, lack of transferrable concepts, and the ability to conduct pilot surveys, we were not able to use previously validated survey items that would normally be

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR used when predicting behavioral intentions. Ideally, it would have been possible to travel to Selayar prior to this body of research to specifically test our survey items with the target population. This was not feasible based on the resources available.

RI PT

4.2. Conclusions

The results of the current study show some support for theory of planned behavior variables in relation to intentions to engage in sustainable fishing and waste disposal. Attitudes predicted both

SC

sustainable fishing and waste disposal intentions, and perceived behavioral control predicted sustainable waste disposal intentions. We did not find any support that descriptive norms were predictive of

M AN U

intentions to fish or dispose of waste sustainably, although as we noted above, this may be because we did not identify the most relevant reference group. Overall, these findings suggest that while context and behaviors may be starkly different, mechanisms underlying intentions identified in prior TPB work extend to the current context. Hence, the TPB may have utility even in non-WEIRD context such as low

TE D

resource, developing world, coastal communities. Of the additional variables included to augment the TPB, awareness of consequences, perceptions of change and responsibility diffusion emerged as significant predictors, although the findings relating to perceptions of change and responsibility

EP

diffusion ran counter to predictions. This suggests that other psychological factors play a role in determining intentions in complex resource management scenarios, and in ways that are not necessarily

AC C

predicted from previous research and theory. In the future, investigating psychological factors as they pertain to specific behaviors will lead to more robust and accurate portrayals of what factors drive intentions.

Understanding the behavioral mechanisms that regulate intentions and actions is vital to reversing the current degradation of our ecosystems. A more sophisticated understanding will aid in the development of psychological strategies to be employed in low-resource communities to mitigate

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR destructive practices and enhance desirable behaviors. The findings can provide useful insights to inform interventions to promote more sustainable practices that can protect ecosystems for future generations. For example, our findings suggest focusing on interventions that increase perceptions of control through

RI PT

behavioral training or modeling around healthy waste practices for villagers. Or reducing the

psychological distance between fishing methods and consequences of fishing practices by increasing ownership and making impacts of destructive fishing more visible. We hope that the current research

SC

contributes to a groundswell of research focusing on environmental behaviors that have critical

AC C

EP

TE D

M AN U

implications for populations that are not western, educated, industrialized, rich, and democratic.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

References

RI PT

Acknowledgments: The authors would like to thank the Capturing Coral Reefs and Related Ecosystem Services team for their contributions to both personnel and funding for this work. We would also like to acknowledge the efforts and contributions of IPB Bogor University for helping collect data. And a final, substantial thank you to Bronwyn Theroux for her assistance in data entry, data analysis, and masterful contributions to the interpretation process.

AC C

EP

TE D

M AN U

SC

Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25(3), 273–291. https://doi.org/10.1016/j.jenvp.2005.08.002 Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2007). The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. Journal of Environmental Psychology, 27(4), 265–276. https://doi.org/10.1016/j.jenvp.2007.08.002 Ainsworth, C. H., Pitcher, T. J., & Rotinsulu, C. (2008). Evidence of fishery depletions and shifting cognitive baselines in Eastern Indonesia. Biological Conservation, 141(3), 848–859. https://doi.org/10.1016/J.BIOCON.2008.01.006 Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In: Kuhl J., Beckmann J. (eds) Action Control. Springer, Berlin, Heidelberg. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T Ajzen, I., & Fishbein, M. (1977). Attitude-Behavior Relations: A Theoretical Analysis and Review of Empirical Research. Psychological Bulletin, 84(5), 8–918. Armitage, C. J., & Conner, M. (2001). Efficacy of the Theory of Planned Behaviour: A meta-analytic review. British Journal of Social Psychology, 40(4), 471–499. https://doi.org/10.1348/014466601164939 Bamberg, S., & Möser, G. (2007). Twenty years after Hines, Hungerford, and Tomera: A new metaanalysis of psycho-social determinants of pro-environmental behaviour. Journal of Environmental Psychology, 27(1), 14–25. https://doi.org/10.1016/J.JENVP.2006.12.002 Bockarjova, M., & Steg, L. (2014). Can Protection Motivation Theory predict pro-environmental behavior? Explaining the adoption of electric vehicles in the Netherlands. Global Environmental Change, 28, 276–288. https://doi.org/10.1016/J.GLOENVCHA.2014.06.010 BPS Selayar Statistics. (2017). Statistik Daerah Kepulauan Selayar. Burke, L. M., Reytar, K., Spalding, M., & Perry, A. (2011). Reefs at risk revisited. World Resources Institute. Carrus, G., Passafaro, P., & Bonnes, M. (2008). Emotions, habits and rational choices in ecological behaviours: The case of recycling and use of public transportation. Journal of Environmental Psychology, 28(1), 51–62. https://doi.org/10.1016/j.jenvp.2007.09.003 Chan, A., & Hodgson, P. (2017). A systematic analysis of blast fishing in South-East Asia and possible solutions. https://doi.org/10.1109/UT.2017.7890330 Cialdini, R. B. (2003). Crafting Normative Messages to Protect the Environment. Current Directions in Psychological Science, 12(4), 105–109. https://doi.org/10.1111/1467-8721.01242 Cialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). A Focus Theory of Normative Conduct: A Theoretical Refinement and Reevaluation of the Role of Norms in Human Behavior. In M. P. B. T.A. in E. S. P. Zanna (Ed.) (Vol. 24, pp. 201–234). Academic Press.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

AC C

EP

TE D

M AN U

SC

RI PT

https://doi.org/https://doi.org/10.1016/S0065-2601(08)60330-5 Cohen, J. E. (1988). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Dirhamsyah. (2004). Regional Policies and Regulations for Coral Reef Management: Case Studies on Riau Archipelago. Maritime Studies, 136, 7–20. https://doi.org/10.1080/07266472.2004.10878743 Dolnicar, S., Hurlimann, A., & Grün, B. (2012). Water conservation behavior in Australia. Journal of Environmental Management, 105(14), 44–52. https://doi.org/10.1016/j.jenvman.2012.03.042 FAO. (2018). The State of World Fisheries and Aquaculture 2018 - Meeting the sustainable development goals. Rome. Ferse, S. C. A., Glaser, M., Neil, M., & Schwerdtner Máñez, K. (2014). To cope or to sustain? Eroding long-term sustainability in an Indonesian coral reef fishery. Regional Environmental Change, 14(6), 2053–2065. https://doi.org/10.1007/s10113-012-0342-1 Fishbein, M., & Ajzen, I. (1977). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Floyd, D. L., Prentice-Dunn, S., & Rogers, R. W. (2000). A Meta-Analysis of Research on Protection Motivation Theory. Journal of Applied Social Psychology, 30(2), 407–429. https://doi.org/10.1111/j.1559-1816.2000.tb02323.x Fox, H. E., & Caldwell, R. L. (2006). Recovery From Blast Fishing on Coral Reefs: A Tale of Two Scales. Ecological Applications, 16(5), 1631–1635. https://doi.org/10.1890/10510761(2006)016[1631:RFBFOC]2.0.CO;2 Fredrickson, B. L. (2001). The role of positive emotions in positive psychology. The broaden-and-build theory of positive emotions. The American Psychologist, 56(3), 218–226. Geyer, R., Jambeck, J. R., & Law, K. L. (2017). Production, use, and fate of all plastics ever made. Science Advances, 3(7). Gifford, R. (2007). Environmental Psychology and Sustainable Development: Expansion, Maturation, and Challenges. Journal of Social Issues, 63(1), 199–212. https://doi.org/10.1111/j.15404560.2007.00503.x Glaeser, B., & Glaser, M. (2011). People, Fish and Coral Reefs in Indonesia. GAIA, 20(2), 139–141. Goldstein, N. J., Cialdini, R. B., & Griskevicius, V. (2008). A Room with a Viewpoint: Using Social Norms to Motivate Environmental Conservation in Hotels. Journal of Consumer Research, 35(3), 472–482. https://doi.org/10.1086/586910 Google. (2019). [Google Map images of Selayar island in South Sulawesi and El Nido in Palawan province Philippines]. Henrich, J., Heine, S. J., & Norenzayan, A. (2017). Beyond WEIRD: Towards a broad-based behavioral science. https://doi.org/10.1017/S0140525X10000725 Hurlstone, M. J., Lewandowsky, S., Newell, B. R., Sewell, B., Anderegg, W., Prall, J., … Pelli, D. (2014). The Effect of Framing and Normative Messages in Building Support for Climate Policies. PLoS ONE, 9(12), e114335. https://doi.org/10.1371/journal.pone.0114335 Jambeck, J. R., Geyer, R., Wilcox, C., Siegler, T. R., Perryman, M., Andrady, A., … Law, K. L. (2015). Marine pollution. Plastic waste inputs from land into the ocean. Science (New York, N.Y.), 347(6223), 768–771. https://doi.org/10.1126/science.1260352 Keizer, K., Lindenberg, S., & Steg, L. (2008). The Spreading of Disorder. Science, 322(5908), 1681– 1685. https://doi.org/10.1126/science.1161405 Keshavarz, M., & Karami, E. (2016). Farmers’ pro-environmental behavior under drought: Application of protection motivation theory. Journal of Arid Environments, 127, 128–136. https://doi.org/10.1016/J.JARIDENV.2015.11.010

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

AC C

EP

TE D

M AN U

SC

RI PT

Kim, S., Jeong, S.-H., & Hwang, Y. (2013). Predictors of Pro-Environmental Behaviors of American and Korean Students. Science Communication, 35(2), 168–188. https://doi.org/10.1177/1075547012441692 Klöckner, C. A. (2013). A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Global Environmental Change, 23(5), 1028–1038. https://doi.org/10.1016/j.gloenvcha.2013.05.014 Kollmuss, A., & Agyeman, J. (2002). Mind the Gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research, 8(3), 239–260. https://doi.org/10.1080/13504620220145401 Krueck, N. C., Ahmadia, G. N., Possingham, H. P., Riginos, C., Treml, E. A., & Mumby, P. J. (2017). Marine Reserve Targets to Sustain and Rebuild Unregulated Fisheries. PLOS Biology, 15(1), e2000537. https://doi.org/10.1371/journal.pbio.2000537 Krueck, N. C., Legrand, C., Ahmadia, G. N., Estradivari, Green, A., Jones, G. P., … Mumby, P. J. (2018). Reserve Sizes Needed to Protect Coral Reef Fishes. Conservation Letters, 11(3), e12415. https://doi.org/10.1111/conl.12415 Lam, S.-P. (2006). Predicting Intention to Save Water: Theory of Planned Behavior, Response Efficacy, Vulnerability, and Perceived Efficiency of Alternative Solutions. Journal of Applied Social Psychology, 36(11), 2803–2824. https://doi.org/10.1111/j.0021-9029.2006.00129.x Lamb, J. B., van de Water, J. A. J. M., Bourne, D. G., Altier, C., Hein, M. Y., Fiorenza, E. A., … Harvell, C. D. (2017). Seagrass ecosystems reduce exposure to bacterial pathogens of humans, fishes, and invertebrates. Science (New York, N.Y.), 355(6326), 731–733. https://doi.org/10.1126/science.aal1956 Lamb, J. B., Willis, B. L., Fiorenza, E. A., Couch, C. S., Howard, R., Rader, D. N., … Harvell, C. D. (2018). Plastic waste associated with disease on coral reefs. Science (New York, N.Y.), 359(6374), 460–462. https://doi.org/10.1126/science.aar3320 Landrigan, P. J., Fuller, R., R Acosta, N. J., Adeyi, O., Arnold, R., Basu, N., … Zhong, M. (2017). The Lancet Commission on pollution and health. The Lancet. https://doi.org/10.1016/S01406736(17)32345-0 Lee, J. W. C., & Tanusia, A. (2016). Energy conservation behavioural intention: attitudes, subjective norm and self-efficacy. IOP Conference Series: Earth and Environmental Science, 40(1), 012087. https://doi.org/10.1088/1755-1315/40/1/012087 López-Mosquera, N., García, T., & Barrena, R. (2014). An extension of the Theory of Planned Behavior to predict willingness to pay for the conservation of an urban park. Journal of Environmental Management, 135, 91–99. https://doi.org/10.1016/J.JENVMAN.2014.01.019 Mannetti, L., Pierro, A., & Livi, S. (2004). Recycling: Planned and self-expressive behaviour. Journal of Environmental Psychology, 24(2), 227–236. McKenzie-Mohr, D. (2000). New Ways to Promote Proenvironmental Behavior: Promoting Sustainable Behavior: An Introduction to Community-Based Social Marketing. Journal of Social Issues, 56(3), 543–554. https://doi.org/10.1111/0022-4537.00183 Milen, S., Sheeran, P., & Orbell, S. (2000). Prediction and Intervention in Health-Related Behavior: A Meta-Analytic Review of Protection Motivation Theory. Journal of Applied Social Psychology, 30(1), 106–143. https://doi.org/10.1111/j.1559-1816.2000.tb02308.x Nolan, J. M., Schultz, P. W., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2008). Normative Social Influence is Underdetected. Personality and Social Psychology Bulletin, 34(7), 913–923. https://doi.org/10.1177/0146167208316691 Pandolfi, J. M., Bradbury, R. H., Sala, E., Hughes, T. P., Bjorndal, K. A., Cooke, R. G., … Jackson, J.

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

AC C

EP

TE D

M AN U

SC

RI PT

B. C. (2003). Global trajectories of the long-term decline of coral reef ecosystems. Science (New York, N.Y.), 301(5635), 955–958. https://doi.org/10.1126/science.1085706 Papworth, S. K., Rist, J., Coad, L., & Milner-Gulland, E. J. (2009). Evidence for shifting baseline syndrome in conservation. Conservation Letters, 2(2), 93–100. https://doi.org/10.1111/j.1755263X.2009.00049.x Pet-soede, C., Cesar, H., & Pet, J. (1999). An economic analysis of blast fishing on Indonesian coral reefs. Environmental Conservation, 26(2), 83–93. Rivis, A., & Sheeran, P. (2003). Descriptive norms as an additional predictor in the theory of planned behaviour: A meta-analysis. Current Psychology, 22(3), 218–233. https://doi.org/10.1007/s12144003-1018-2 Rivis, A., Sheeran, P., & Armitage, C. J. (2006). Augmenting the theory of planned behaviour with the prototype/willingness model: Predictive validity of actor versus abstainer prototypes for adolescents’ health-protective and health-risk intentions. British Journal of Health Psychology, 11(3), 483–500. https://doi.org/10.1348/135910705X70327 Rogers, A., Blanchard, J. L., & Mumby, P. J. (2014). Vulnerability of Coral Reef Fisheries to a Loss of Structural Complexity. Current Biology (Vol. 24). https://doi.org/10.1016/j.cub.2014.03.026 Rogers, R. W. (1975). A Protection Motivation Theory of Fear Appeals and Attitude Change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803 Rothschild, Z. K., Landau, M. J., Sullivan, D., & Keefer, L. A. (2012). A dual-motive model of scapegoating: Displacing blame to reduce guilt or increase control. Journal of Personality and Social Psychology, 102(6), 1148–1163. https://doi.org/10.1037/a0027413 Sawitri, D. R., Hadiyanto, H., & Hadi, S. P. (2015). Pro-Environmental Behavior from a Social Cognitive Theory Perspective. Procedia Environmental Sciences, 23, 27–33. https://doi.org/10.1016/j.proenv.2015.01.005 Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18(5), 429–434. https://doi.org/10.1111/j.1467-9280.2007.01917.x Sheeran, P. (2002). Intention-Behavior Relations: A Conceptual and Empirical Review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003 Sheeran, P., & Webb, T. L. (2016). The Intention-Behavior Gap. Social and Personality Psychology Compass, 10(9), 503–518. https://doi.org/10.1111/spc3.12265 Soga, M., & Gaston, K. J. (2018). Shifting baseline syndrome: causes, consequences, and implications. Frontiers in Ecology and the Environment, 16(4), 222–230. https://doi.org/10.1002/fee.1794 Steg, L., Bolderdijk, J. W., Keizer, K., & Perlaviciute, G. (2014). An Integrated Framework for Encouraging Pro-environmental Behaviour: The role of values, situational factors and goals. Journal of Environmental Psychology, 38, 104–115. https://doi.org/10.1016/j.jenvp.2014.01.002 Steg, L., & Vlek, C. (2009). Encouraging pro-environmental behaviour: An integrative review and research agenda. Journal of Environmental Psychology, 29(3), 309–317. https://doi.org/10.1016/j.jenvp.2008.10.004 Steg, L., Vlek, C., & Slotegraaf, G. (2001). Instrumental-reasoned and symbolic-a
ective motives for using a motor car. Transportation Research Part F: Traffic Psychology and Behaviour. Stern, P. C. (2000). New Environmental Theories: Toward a Coherent Theory of Environmentally Significant Behavior. Journal of Social Issues, 56(3), 407–424. https://doi.org/10.1111/00224537.00175 Taylor, S., & Todd, P. (1995). An Integrated Model of Waste Management Behavior. Environment and Behavior, 27(5), 603–630. https://doi.org/10.1177/0013916595275001

ACCEPTED MANUSCRIPT Running Head: PREDICTING INTENTIONS OF FISHING AND WASTE DISPOSAL BEHAVIOR

AC C

EP

TE D

M AN U

SC

RI PT

Thompson, R. C., Moore, C. J., vom Saal, F. S., & Swan, S. H. (2009). Plastics, the environment and human health: current consensus and future trends. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 364(1526), 2153–2166. https://doi.org/10.1098/rstb.2009.0053 Umphrey, L. R. (2004). Message Defensiveness, Efficacy, and Health-Related Behavioral Intentions. Communication Research Reports , 21(4), 329–337. https://doi.org/10.1080/08824090409359997 van der Linden, S. (2015). The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. Journal of Environmental Psychology, 41, 112–124. https://doi.org/10.1016/J.JENVP.2014.11.012 Wolff, N. H., Donner, S. D., Cao, L., Iglesias-Prieto, R., Sale, P. F., & Mumby, P. J. (2015). Global inequities between polluters and the polluted: climate change impacts on coral reefs. Global Change Biology, 21(11), 3982–3994. https://doi.org/10.1111/gcb.13015 WWF. (2015). Living Blue Planet Report Species, habitats and human well-being.

ACCEPTED MANUSCRIPT

Ref: JEVP_2018_714 Title: Psychological predictors of fishing and waste management intentions in Indonesian coastal communities

RI PT

Highlights 1. An adapted TPB was a statistically significant predictor of unconventional behavioral intentions for fishing and waste management, in an infrequently studied population.

SC

2. Additional variables, perceptions of change in marine resources, awareness of consequences for marine resources, and responsibility diffusion (e.g. blaming other groups for environmental degradation) were effective in predicting behavioral intentions for fishing and waste management.

AC C

EP

TE D

M AN U

3. Understanding the differences between psychological determinants that motivate environmental behavior is imperative for dealing with complex resource management scenarios in the future.