Experimental Evidence of Factors Influencing Voluntary Contributions to Marine Conservation By

Experimental evidence of factors influencing voluntary contributions to marine conservation By

KATHERINE M. NELSON

A thesis submitted in partial fulfilment of the requirements for the degree of

Doctor of Philosophy In Economics

Approved Dissertation Committee

Prof. Dr. Achim Schlüter

Head of Institutional and Behavioral Economics at Leibniz ZMT, Professor of Social Systems & Ecological Economics, Jacobs University Primary advisor and Chair of Dissertation Committee

Prof. Dr. Colin Vance

Deputy Head of Environment and Resources Department at Leibniz RWI, Professor of Quantitative Methods, Jacobs University Secondary advisor

Prof. Dr. Andreas Löschel

Chair of Energy and Resource Economics, University of Münster External Examiner Date of defense: March 15, 2018

Department of Business and Economics

Katherine M. Nelson, 2018

Statutory Declaration

Family name, Given name Nelson, Katherine

Matriculation number 20331347

Type of thesis PhD thesis

English: Declaration of Authorship

I hereby declare that the thesis submitted was created and written solely by myself without any external support. Any sources, direct or indirect, are marked as such. I am aware of the fact that the contents of the thesis in digital form may be revised with regard to usage of unauthorized aid as well as whether the whole or parts of it may be identified as plagiarism. I do agree my work to be entered into a database for it to be compared with existing sources, where it will remain in order to enable further comparisons with future theses. This does not grant any rights of reproduction and usage, however.

This document was neither presented to any other examination board nor has it been published.

German: Erklärung der Autorenschaft (Urheberschaft)

Ich erkläre hiermit, dass die vorliegende Arbeit ohne fremde Hilfe ausschließlich von mir erstellt und geschrieben worden ist. Jedwede verwendeten Quellen, direkter oder indirekter Art, sind als solche kenntlich gemacht worden. Mir ist die Tatsache bewusst, dass der Inhalt der Thesis in digitaler Form geprüft werden kann im Hinblick darauf, ob es sich ganz oder in Teilen um ein Plagiat handelt. Ich bin damit einverstanden, dass meine Arbeit in einer Datenbank eingegeben werden kann, um mit bereits bestehenden Quellen verglichen zu werden und dort auch verbleibt, um mit zukünftigen Arbeiten verglichen werden zu können. Dies berechtigt jedoch nicht zur Verwendung oder Vervielfältigung.

Diese Arbeit wurde noch keiner anderen Prüfungsbehörde vorgelegt noch wurde sie bisher veröffentlicht.

……………………………………………………………………………………………………… Date, Signature

List of publications and conference contributions

Manuscript 1:

Publication in peer reviewed journal: Nelson, K. M., Schlüter, A. and Vance, C. 2017, “Funding Conservation Locally: Insights from Behavioral Experiments in Indonesia.” Conservation Letters. doi:10.1111/conl.12378 http://onlinelibrary.wiley.com/doi/10.1111/conl.12378/full

Working paper publication: Nelson, K. M., Schlüter, A. and Vance, C. 2016, “Funding Conservation Locally: Insights from Behavioral Experiments in Indonesia.” Ruhr Economic Papers 652. Bochum, Germany. ISSN 1864-4872 (online), http://dx.doi.org/10.4419/86788758 http://www.rwi-essen.de/media/content/pages/publikationen/ruhr-economic- papers/rep_16_652_neu.pdf

Conference contributions: Experimental economics evidence for contributions to marine and costal collective goods. Estuarine and Coastal Sciences Association (ECSA) Conference, September 5, 2016, Bremen, Germany.

Donations of time and money for the environment. Experimental Economics for the Environment Conference, February 3, 2017, Bremen, Germany.

Manuscript 2:

Publication in peer reviewed journal:

Nelson, K. M., Schlüter, A., and Vance C. 2017, “Distributional preferences and donation behavior among marine resource users in Wakatobi, Indonesia.” Ocean & Coastal Management. ISSN 0964-5691, https://doi.org/10.1016/j.ocecoaman.2017.09.003. http://www.sciencedirect.com/science/article/pii/S0964569117300984

Working paper publication: Nelson, K. M., Schlüter, A., and Vance C. 2017, “Distributional preferences and donation behavior among marine resource users in Wakatobi, Indonesia.” Ruhr Economic Papers 690. Bochum, Germany. ISSN 1864-4872 (online), http://dx.doi.org/10.4419/8678880. http://www.rwi-essen.de/media/content/pages/publikationen/ruhr-economic- papers/rep_17_690.pdf

List of publications and conference contributions

Conference contributions: Distributional preferences and donation behavior. Leibniz Environment and Development Symposium (LEADS), December 7, 2016, Berlin, Germany.

Distributional preferences and donation behavior. Annual Conference for the International Association for the Study of the Commons (IASC), July 10-14, 2017, Utrecht, Netherlands.

Manuscript 3:

Submitted to peer reviewed journal: Nelson, K. M., Partelow, S., Schlüter, A., IN REVIEW, “Extending the scope of voluntary marine park user fees to terrestrial conservation across coupled land-sea ecosystem boundaries.” Journal of Environmental Management. Submitted January, 2018.

Conference contributions: Extending the scope of voluntary marine park user fees. Leibniz Environment and Development Symposium (LEADS), January 29-30, 2018, Berlin, Germany.

Acknowledgements

Acknowledgements First and foremost, I would like to express my sincere gratitude to my thesis advisor, Prof. Dr. Achim Schlüter, for his continuous support and guidance throughout my PhD. His door was always open and he welcomed dialogue, debate, and interaction. His patience and trust in his students allows for personal discovery and the ability to work independently. I would also like to thank Prof. Dr. Colin Vance for his support, expertise, and feedback from the beginning of this PhD journey. He was always available to help and provided insightful contributions and encouragement. Many thanks to my external advisor, Prof. Dr. Andreas Löschel, for his time and expertise in evaluating my thesis.

My sincere thanks also goes to Dr. Luky Adrianto, Dr. Eva Anggraini, Febrina Desrianti, and Delphine Robbe who provided assistance and support throughout the research process. Without their support it would not have been possible to conduct this research and I am deeply grateful both professionally and personally. I am also grateful to the team of students that helped execute the research in Wakatobi and Gili Trawangan. Their persistence, understanding, and sense of humor made the research not only possible, but also immensely enjoyable.

I would also like to acknowledge the great team from Triple C: Contributions to Coral Commons. Special thanks to Dr. Sebastian Ferse, Dr. Sonia Bejarano, Carlo Gallier, Dr. Jörg Langbein, and Abdul Halik for the exchange of ideas, mutual encouragement, friendship and always entertaining company. It has been a pleasure to work together and I hope we continue to collaborate in the future.

The Institutional and Behavioral Economics research working group at ZMT has been my research ‘home’ for the last three years and I am appreciative for the friendships and endlessly interesting discussions and professional and emotional support we provide for each other. I am thankful for the financial support from the Leibniz Association SAW-2014-ZMT-1 317 and the Waitt Foundation Rapid Ocean Conservation (ROC) Grants that made this research possible. I also respectfully acknowledge my privilege in these life accomplishments.

Last, but certainly not least, I owe the success in my life to my family Bob, Joan, and Jenny. Your unwavering support and encouragement has helped me persevere throughout this challenge and I honestly could not have done it without you. My parents provide the foundation to lift me up and provide me with the courage to pursue my dreams. My sister, Jenny, is a constant inspiration to seek more from life and be the change I wish to see in this world. And finally, I cannot express enough gratitude for my friends around the world that make this life more fun and a better world because they exist!

Abstract

Abstract Conserving the Earth’s natural resources is of great importance to the future of all living things. The science behind conservation is dominated by the natural sciences although it is clear that human behavior is at the root of most environmental degradation problems as well as the solutions. The behavioral social sciences offer relevant theory and valuable methodological tools to understand human behavior. Yet, research on human behavior remains underrepresented in the conservation sciences. Voluntary contributions are widely accepted mechanisms for promoting conservation and for measuring individual economic behavior. This thesis aims to address several aspects of human behavior and how they relate to contributions to marine conservation. This thesis consists of an introduction followed by three self-contained chapters and a conclusion.

Proximate stressors such as destructive fishing are key drivers damaging coral reef public goods. Conservation strategies that marshal local action and are tailored to the preferences of the target group are thus needed to sustain coral resources. Research 1 uses data from field experiments with a fishing community in Indonesia to test economic theory regarding preferences for giving time and money to environmental and other charitable causes. Each person is subject to one of four treatments: monetary donation, monetary donation match, volunteer time donation, and volunteer time donation match. Contrasting with the existing literature, we find that participants give significantly more when donating money compared to time. We also find that matching donations increases the percent of people giving but does not increase the amount donated. This research furthers our understanding of what motivates resource users in a developing country to contribute to the provision of public goods.

Using data collected from the same study population, research 2 examines the effect of social and psychographic characteristics on giving to public goods. Using an incentivized task to elicit preferences for the distribution of wealth between oneself and an anonymous other, participants are classified into categories based on preferences for benevolence, egalitarianism, own-money- maximization, and malevolence. The data show that these intrinsic characteristics, such as preferences for equality, are a significant predictor of donation behavior. Practical application of these results would call for conservation marketing practices to develop targeted messages that emphasize social norms, promote cooperative values, and consider the needs of resource-users in the design of local conservation campaigns and goals.

Research 3 solicits voluntary user fees from tourists visiting a marine reserve in Indonesia. Contributions support the local conservation organization to provide public good services such as keeping the island clean, providing recycling services, and protecting the fragile coral ecosystem. Real donations were solicited under four treatment conditions: control (write-in amount), default opt-in, default opt-out, and reference levels. The results from study 3 show that the default opt- out condition represents the highest rate of donations, but the total donations received under the reference level treatment were comparable due to a higher average amount given.

Table of Contents Statutory Declaration ...... i List of publications and conference contributions ...... ii Acknowledgements ...... v Abstract ...... vi Figures ...... ix Tables ...... x I. Introduction ...... 1 1.1 Background motivation ...... 2 1.2 Studying conservation behavior through a lens of marine conservation ...... 4 1.3 Methodology: Field Experiments ...... 7 1.4 Research focus ...... 9 1.5 Study locations ...... 15 II. Manuscripts ...... 23 Chapter 1: Giving time or money to fund public goods ...... 24 2.1 Introduction ...... 24 2.2 Theory: Time is money? ...... 25 2.3 Matching ...... 26 2.4 Background...... 26 2.5 Methods ...... 27 2.6 Results ...... 30 2.7 Discussion ...... 34 Appendix ...... 37 Chapter 2: Individual characteristics and donation behavior ...... 42 3.1 Introduction ...... 42 3.2 Wakatobi National Marine Park ...... 44 3.3 Distributional Preferences and Contributive Behavior ...... 45 3.4 Sample participants ...... 49 3.5 Study design ...... 50 3.6 Part One: Real effort task and Donation Decision ...... 51 3.7 Part Two: Distributional Preferences Elicitation Task ...... 53 3.8 Results ...... 55 3.9 Discussion ...... 61 vii

3.10 Conclusion ...... 64 Chapter 3: Soliciting voluntary user fees ...... 65 4.1 Introduction ...... 65 4.2 Fundraising Literature Review ...... 70 4.3 Materials and methods ...... 72 4.4 Results ...... 76 4.5 Discussion and recommendations ...... 84 III. Concluding remarks ...... 88 5.1 Summary of research ...... 89 5.2 Limitations and future research opportunities ...... 93 Appendices ...... 95 References ...... 118

viii

Figures Figure 1: Research objectives ...... 9 Figure 2: Map of coral triangle region ...... 15 Figure 3: Map of Indonesia ...... 16 Figure 4: Photos of Bajo Mola village ...... 18 Figure 5: Zonation map of Gili Matra marine reserve ...... 21 Figure 6: Photos of Gili Trawangan ...... 22 Figure 7: House in the Bajo Mola village...... 27 Figure 8: Visual depiction of the difference between monetary and time donation treatments...... 28 Figure 9: Charity selection and donations by charity type...... 30 Figure 10: Bar graphs of treatment comparisons...... 31 Figure 11: Total funds received by charities ...... 34 Figure 12: Demographic distribution of district and regional population data ...... 39 Figure 13: Map of study site ...... 45 Figure 14: Bajo Mola house...... 50 Figure 15: Choices in the distributional preferences elicitation task ...... 53 Figure 16: Characterization of distributional preference types ...... 55 Figure 17: Percentage of distributional preferences by type and binary donation decision ...... 55 Figure 18: Analysis of distributional preferences by gender ...... 57 Figure 19: Choice of charity by preference type ...... 61 Figure 20: Maps ...... 73 Figure 21: Tourist perceptions ...... 78 Figure 22: Perceptions of environmental management and personal experience ...... 79 Figure 23: Percentage of sample that donated by treatment ...... 80 Figure 24: Mean amounts donated by treatment ...... 81 Figure 25: Total donations received by Gili Eco Trust...... 82 Figure 26: Estimated cumulative revenue based on the ratio and magnitude of giving ...... 86

Tables Table 1: Description of between-subject treatments ...... 27 Table 2: Summary Statistics by treatment ...... 32 Table 3: Effect of clustering standard errors: ...... 37 Table 4: Regression table ...... 40 Table 5: Comparison of demographics across treatments ...... 41 Table 6: Comparison of mean giving across distributional preference types ...... 56 Table 7: Probit and Ordinary Least Squares Regression Table ...... 59 Table 8: Field experiment treatment conditions and descriptions ...... 70 Table 9: Hypotheses ...... 72 Table 10: Descriptive statistics of sample population ...... 77 Table 11: Probit and Ordinary least squares regression model ...... 83

Introduction

I. Introduction

Introduction

1 Introduction

1.1 Background motivation

Protecting the Earth’s resources is of vital interest for humankind, and, although most problems involving environmental degradation can be attributed to human behavior, we know remarkably little about the behavioral factors that influence nature conservation (Cowling 2014, Wright, Verissimo, et al. 2015, Schultz 2011). Conservation science has long been dominated by ecologists recording losses and identifying causes for environmental degradation, largely ignoring human behavior as the root of the cause. There has been considerable success in identifying the ecological processes that are affected by human behavior but the focus remains mostly on scientific documentation of degradation instead of understanding the drivers linked to human behavior and how change occurs. It is widely recognized within the conservation science community that a paradigm shift toward understanding human behavior is needed to address the underlying mechanisms driving ecological losses; however, research on human behavior remains an underrepresented area of research in the conservation literature (Reddy et al. 2016, Veríssimo 2013, Cowling 2014, Andriamalala et al. 2013, Partelow, Schlüter, Wehrden, et al. 2017, Bennett et al. 2017, Mascia et al. 2003, Nelson, Schlüter, and Vance 2017b).

The intersect between behavioral and environmental economics is a research area with great potential to deliver insights into the environmental behavior of humans (Kesternich, Reif, and Rübbelke 2017). This area of research combines psychological insights and economic principles to adapt theory and guide environmental policy (Shogren, Parkhurst, and Banerjee 2010). It deviates from the neoclassical economic model of humans characterized as fully rational and purely self-interested and is replaced by models involving humans with limited rational capabilities due to constraints in cognitive ability, time, willpower, and concern for others (Simon 1972, Mullainathan and Thaler 2000, Smith 1998, Shogren and Taylor 2008). Many, if not all, of these constraints are commonly faced in environmental decision-making (Poff et al. 2003). Furthermore, decision processes do not happen in a vacuum and are highly dependent on context. Environmental conditions and the economic, socio-cultural, and political institutions influencing them (and being influenced by them) differ considerably across contexts. Research also shows that socio-psychological factors (i.e. values, beliefs, attitudes, preferences) play an important role in the provision of public goods but it is not well understood how these factors translate to

Introduction contributions to environmental public goods (Shang and Croson 2009). Given that context is an important factor in environmental decision-making, field research is especially relevant to provide a detailed view on human behavior in the natural environment (Henrich et al. 2001, Kessler and Vesterlund 2015).

Biodiversity conservation has the potential to generate substantial global environmental, economic, and social benefits but many efforts fall short due to lack of sufficient funding (Pimentel et al. 1997). Non-government organizations (NGOs) are a driving force in the conservation movement and often rely heavily on individual donations of money and time to fund and implement conservation programs. Scientific exploration into altruistic behavior draws heavily from research on charitable giving, but the links to environmental conservation are ambiguous. Relatively few conservation NGOs focus efforts on understanding donor behavior and preferences (Wright, Verissimo, et al. 2015, Veríssimo et al. 2018). This is an interesting area of inquiry for behavioral environmental economics given that it is not well understood if altruistic behavior extends to concern for nature and the environment (Perkins 2010). In the environmental sector, there are very few published accounts of research on charitable market behavior as fundraising has traditionally been considered more of an art than a science (Veríssimo et al. 2018, Nelson, Schlüter, and Vance 2017b). Few environmental organizations are tapping into the wealth of market research opportunities in this area and few are applying proven methods from the charitable giving literature to influence donations or other pro-environmental behavior. (Bénabou and Tirole 2006, Ariely, Bracha, and Meier 2009, Fischbacher, Gächter, and Fehr 2001, Fehr and Fischbacher 2003, Andreoni and Miller 2002, Henrich et al. 2001, Nolan and Schultz 2015).

A main purpose of the research conducted within this thesis is to contribute to conservation science and behavioral environmental economics by linking and testing theory from the domain of charitable giving to gain a better understanding of intrinsic and extrinsic factors that influence contributions to environmental public goods. The ‘factors’ studied through this research include those that come from within the individual (i.e. preferences and values) and those controlled by external information (i.e. the value of donation manipulated through third-party matching; and the design of the ask based on choices presented to the donor). This thesis is divided into several chapters structured as follows: Chapter 2 focuses on testing economic theory which assumes that people have no intrinsic preference between giving money or time to charity, and testing the 3

Introduction effect of matching on donations; Chapter 3 examines the relationship between individual donor characteristics and contribution behavior; Chapter 4 addresses strategic choice factors provided with the donation request and their influence on donation decisions; and Chapter 5 presents the summary, limitations, and implications for conservation practitioners.

1.2 Studying conservation behavior through a lens of marine conservation

I chose to focus the research on fishers and tourists due to their direct interaction and impact on marine resources. The marine realm provides a fitting example to demonstrate the complexity of environmental goods. Fishing is an extractable activity that often represents a social dilemma of over appropriating the common resource due to the fact that the resource is rivalrous but non- excludable. On the other hand, many marine tourism activities, such as snorkeling, diving, swimming, and wildlife observation, are considered non-extractable and problems arise from underinvestment in the public good which is non-rivalrous and non-excludable. Both scenarios allow for free-riders who benefit from the resources without contributing to them.

These two user groups are interesting to study from a perspective of environmental conservation given that their decisions directly affect the resource. Information about the behavior of marine resource users can help guide local NGO conservation efforts. Although the purchasing power of small-scale fishers to fund conservation may appear insignificant, understanding preferences to give time or money to conservation has important implications for the design of conservation intervention programs. Alternatively, tourist user fees represent huge potential to fund the protection of natural resources. The research conducted herein addresses another important, yet often overlooked, function in marine protected area (MPA) planning and funding which connects environmental problems generated on land (i.e. pollution, erosion, land modification) to the impacts on coastal and marine resources.

The marine realm represents resources of critical concern for conservation. Oceans cover 70 percent of the earth’s surface, and more than one-half of the world’s population lives within 60 kilometers of the coast (IUCN 2017). The oceans have been regarded as global commons whose resources are highly rivalrous in consumption (often treated as if inexhaustible) and face difficulties in exclusion. This results in a social dilemma for governance given that no central international authority exists to be able to enforce regulations. In turn, this means that voluntary action is crucial. 4

Introduction

Many species of marine life have become depleted or even threatened with extinction due to proximate and distal anthropogenic stressors. Less than two percent of the world’s marine space is located within protected areas (IUCN 2017). Nearshore marine zones are claimed by countries as exclusive economic zones (EEZs) and therefore have legal jurisdiction for managing large areas of continental shelf. This area is where the world’s most productive fisheries, most biodiverse coral reefs, and most accessible underwater resources are located, as well as being the areas of greatest interest for conservation even though protected areas currently cover less than 3% of EEZs (Spergel and Moye 2004, IUCN 2017). In many cases the management of these zones consists of little more than large-scale foreign fishing rights that are often poorly regulated (Spergel and Moye 2004). Substantial amounts of money are required to manage and protect marine areas, and to implement and enforce regulations. Voluntary contributions to NGOs constitute a sizeable portion of nature conservation funding. Although funding is a major factor, money alone is not the solution. It is necessary to consider that many of these marine areas are connected land-sea ecosystems and integrate cross-boundary management into planning and funding.

Most marine conservation planning ignores the terrestrial coastal system although many of the threats facing marine areas originate on land (i.e. solid waste pollution, erosion and habitat loss from land conversion, or eutrophication from agricultural run-off), proceeding largely as if the ecological systems were unconnected (Stoms et al. 2005). From the perspective of marine protection, this lack of integration is especially problematic because the marine areas are often more influenced by land than vice versa (Stoms et al. 2005, Alvarez-Romero et al. 2011). Nearshore marine natural resources, such as coral reefs, cannot be de-coupled from terrestrial coastal ecosystems. Considering that the land and sea are connected systems and interchange materials, energy, and organisms, it is essential to incorporate and address terrestrial-originated threats into marine conservation planning and funding to ensure successful protection of resources.

Coral reefs are a perfect example of a global public good that suffer from under provisioning and the fisheries harbored within these ecosystems represent common resources that often suffer from over appropriation. Healthy coral reefs provide universal benefits. Coral ecosystems are hotspots of marine biodiversity; they protect coastlines against storm surges; they provide habitat, spawning, and nursery grounds for important and diverse fish species (which in turn provide a 5

Introduction source of food for millions of people); they provide jobs and income to local economies from fishing, recreation, and tourism; and they are a source for new medicines. The destruction of coral reefs can be attributed to direct and indirect proximate causes (i.e. pollution, over fishing, destructive fishing, and coastal development) and distal causes (i.e. climate change resulting in rising sea temperatures and ocean acidification, increases in the global demand for fish). The free-rider phenomenon is exacerbated in the case of coral reef ecosystems because free-riders are not just limited to people within a local community, but extend to people that live far away and may not even be familiar with coral reefs but who still benefit from their existence and contribute to their destruction. Currently, coral reef ecosystems around the world are under grave threat (Hughes et al. 2003, Hughes et al. 2014). The forecast for the next 20 years looks grim unless we succeed at making major changes. In order for change to occur, both local populations and the wider global population will need to invest in marine conservation.

According to marine science experts, marine protected areas (MPAs) are currently the best management tool for conserving coral reefs and natural fish hatcheries (Hamilton, Potuku, and Montambault 2011, Lubchenco et al. 2003, Hooker et al. 2011). Effectively managed protected areas can generate significant gains in environmental conservation. However, protected areas face many barriers to effectiveness including insufficient financial, logistical, and technical support; heterogeneity of users’ needs; lack of scientific information; and insufficient institutional, decision-making, and political support (Pomeroy et al. 2005).

Many researchers focus on issues of marine governance while financing conservation remains less frequently studied (Mascia 2003, Alexander, Andrachuk, and Armitage 2016, Pittman and Armitage 2016, Christie and White 2007, Glaser et al. 2012, de Morais, Schlüter, and Verweij 2015). MPAs are typically financed through individual fees, international grants, or government support (or some combination of the above) (Lundquist and Granek 2005, Rife et al. 2013). NGOs are often involved at some level to provide support. NGOs play a variety of roles in different MPA contexts, from small local NGOs focused on community issues to big international NGOs that lobby globally for more protected areas, but one thing that unites most all NGOs is the reliance on voluntary action.

Introduction

The research presented in this thesis aims to advance theory and present practical applications by addressing gaps in both the research on charitable giving and behavioral environmental economics through the use of field experiments on voluntary contributions to NGOs.

1.3 Methodology: Field Experiments

Experimental investigation is an appropriate methodological tool when the research is driven by questioning theoretical assumptions. Typically, a hypothesis is developed through deductive reasoning based on existing theory and then a research strategy is designed to test the hypothesis. Using experiments to test hypotheses is an important component in the scientific discovery process. This process allows researchers to control for specific variables, measure concepts quantitatively, generalize findings to some extent, and to confirm or reject theory. While lab experiments have dominated in economics for the past several decades, field experiments have gained momentum more recently. Economic lab experiments are conducted with university students in highly controlled environments, and, while these have their place in testing theory, transferability outside of the lab is not always a given (Roe and Just 2009, Benz and Meier 2008, Levitt and List 2007). Field experiments in economics occupy a powerful middle ground between lab experiments and naturally occurring data by allowing control for randomization in an environment that captures real world characteristics (List 2008). If context matters in environmental decision-making (as we think it does), then conducting research in the field is an important determinant of the validity of the results.

In this thesis, field experiments are defined as experiments with non-standard subjects (i.e. not students), performing familiar or realistic tasks set in a context that is applicable to participants (Harrison and List 2004). The benefits of using field experiments in this research are to test theory and also to shed light on the transferability of results from the lab to different field contexts. Field experiments are often used to capture as much of the local context as possible and to examine the effects of implementing new or different institutions (Carpenter, Harrison, and List 2005, Vollan 2008, Harrison and List 2004). To maximize external validity while still controlling for specific variables, the experiments herein were designed such that participants use earned money when faced with economic consequences for actual goods and services (as opposed to making decisions based on abstract situations using windfall endowments)

Introduction

(Carpenter, Harrison, and List 2005). The individual experimental designs used in each of the research papers are explained in more detail in Section 1.4.

The benefits of studying donation behavior in an experimental field setting are that participants make choices in real-life contexts and these decisions provide insight to practitioners. For example, the giving behavior of university students in a highly controlled laboratory setting may not reflect the same choices made by people in a real-world setting with different cultural backgrounds constraints, needs, or motivations. In fact, previous studies have shown that the sterility of the lab setting itself may affect behavior. List (2006) found that prosocial behavior in laboratory settings disappeared when subjects were in a naturally occurring marketplace. Given that my research focuses on the behavior of marine resource users, field experiments are ideal even if some level of control found in the lab is traded-off for an increase in external validity.

Many field experiments on charitable giving focus on donors from Western, educated, industrialized, rich, and democratic countries, and, although highly relevant for the non-profit sector, these are not necessarily the ideal population for understanding the contribution behavior of resource users in other types of countries, who also need to finance their public goods (Eckel and Grossman 2008, Shang and Croson 2009, Meier 2007, Karlan and List 2007, List 2006).

The two stakeholder groups chosen as the focus of research for this thesis were selected because the fishing and tourism industries are responsible for many of the local threats facing marine resources. Small-scale fishers and young backpackers in Indonesia may not sound like the typical donor target group for conservation organizations but they represent key target groups whose behavior has direct consequences on the resource and can greatly influence the funding and implementation of local conservation programs. We know very little about the incentives that drive resource users’ behavior to voluntarily allocate their income and time to conservation. Behavior in experimental interventions depends on the ecological field context, such as scarcity and quality of the resource, as well as the societal context including cultural norms that depend on knowledge, beliefs, and past experiences, hence the importance to conduct this type of study in the field rather than in a lab setting. In addition, surveys and qualitative data collection methods are useful tools for understanding and documenting the field context that may have an effect on behavior, and also for explaining behavior when field observations differ from the lab and/or theoretical assumptions.

Introduction

1.4 Research focus

The research in this thesis is divided across three research papers (see Figure 1). The first two papers are based on a field experiment and survey with participants from a fishing community in Wakatobi, Indonesia. The third paper is based on field experimental research soliciting environmental contributions from tourists on the island of Gili Trawangan, Indonesia.

Figure 1 Research objectives, research questions, and methodologies guiding the three research papers

1.4.1 Research 1: Comparison of monetary and time donations with local resource users

The first objective of my research is to understand local resource users’ preferences for giving time or money to public goods. Like most NGOs, those working towards the development of

Introduction sustainable MPAs rely on donations of both money and time. Though both types are substantial, most of the literature on donations addresses aspects of monetary donations. Although volunteering is less frequently studied, it is a key segment contributing to the NGO industry, and volunteers are often fundamental to the success of local programs. Volunteering is the act of performing a service willingly and without pay. Volunteers are actively contributing time towards the provisioning of a public good. Even if this service is being performed outside of an individual’s regular working schedule so it does not lead to lost income per se, there are still opportunity costs associated with trading-off one’s free time to do volunteer work. This type of behavior may be crucial to the success of MPAs and other environmental goods, especially in the cases of MPAs that rely on community monitoring efforts which often come at a high personal cost. However, to my knowledge, there are no experimental studies examining donations of volunteer time from resource users.

In research paper 1, I engage resource users from a local fishing community to work on a piece rate task and I vary the conditions between the possibility to give earned income to charity or work time to charity. Similar experiments have been conducted in a laboratory setting with university students in the U.S.A and Australia. The design of my experiments sets this research apart from existing studies in several distinct ways. First, I use a non-standard subject pool by recruiting residents that are highly dependent on reef fishing for their livelihoods from a village in Wakatobi, Indonesia. Second, the task I use is a realistic task that is taught by NGOs in developing country contexts as a means of earnings for alternative livelihoods. Last, I introduce new treatment conditions that match the value of volunteer time.

Theoretically speaking, when money and time are of equal value, there should be no difference in the marginal willingness to give (Andreoni et al. 1996). However, using laboratory experiments, researchers found that participants prefer to give time over money when all else is equal (Lilley and Slonim 2014, Brown, Meer, and Williams 2013). They attribute the theory of ‘warm glow’ giving as the main driver of this effect. The theory of warm glow is based on the assumption that people derive satisfaction from the act of giving (Andreoni 1990). Therefore, individual donations are not completely crowded out when the needs of the public good are met by other sources (i.e. taxes, grants). The previous studies found that when participants are provided the opportunity to work so their wages accrue to charity, the value they give to charity is more than

Introduction when they are paid their wages and can donate money to charity (Brown, Meer, and Williams 2013, Lilley and Slonim 2014).

Interestingly, when charitable contributions are subsidized, such as through matching grants, more people give, but the average amount given tends to be lower (although giving is not decreased at a 1:1 ratio) (Huck and Rasul 2011, Meier 2007, Eckel and Grossman 2003, 2008). This generally means that the charity receives a greater amount overall by announcing the matched funds (Davis and Millner 2005). It is not known if people volunteering time will respond in the same way when the value of their labor is matched through a monetary donation to charity. It is common practice among grant-awarding entities to require that funding is matched by the institution receiving the grant. Announcing matches when soliciting monetary donations is a widely utilized fundraising tactic in the non-profit sector. Donated labor (volunteer time) often accounts for a significant portion of the in-kind match used to secure these grants. Much less common, however, is the practice of disclosing these matches to the volunteer labor base to validate the value of their volunteer time (worth double when matched) to encourage more total volunteer hours. If indeed people respond the same to matches of time as they do to matches of money, this could be a novel and successful method to increase total volunteer hours, but until now, there is no research to approve or refute this assumption.

The literature on the relationship between volunteerism and monetary donations consists of theoretical, empirical, and experimental approaches, but even with the various techniques there is no consensus on whether volunteering is motivated by the same mechanisms as giving monetary donations. And, to my knowledge, no one has examined the effects of matching on volunteer labor. Research 1 is shaped on questions that will provide empirical insight to gaps in the literature on: 1) comparing donations of money and time, and 2) the effects of matching on time donations.

Following the experiments, participants completed an incentivized task used to elicit distributional preferences1 and a survey on fishing behavior, market participation, environmental perceptions, group membership, and demographic information. The analysis of these factors and their relationship to donation behavior are presented in research paper 2.

1 The term ‘distributional preferences’ coined by experimental economists is used to describe different intrinsic characteristics based on the decision-makers concern for the (material) welfare of others (Balafoutas, Kerschbamer, and Sutter 2012). 11

Introduction

1.4.2 Research 2: Individual characteristics and giving behavior

The objective of research 2 is to determine which social and psychological characteristics influence marine resource users to give to public goods. Traditional conservation outreach efforts have attempted to convince people to share the values of those conducting the outreach through information and education about a given cause (Bjorkland and Pringle 2001), which, on their own, have largely been ineffective at fostering sustainable behavior (McKenzie-Mohr and Schultz 2014, Schmuck and Schultz 2012). In contrast, marketers put the target audience at the center of the focus by trying to ensure what is being offered meets the needs and preferences of that target audience (Wright, Verissimo, et al. 2015, Akchin 2001). Some conservation NGOs use marketing tools to increase the amount of financial support they receive from the public (Verissimo, MacMillan, and Smith 2011, Di Minin et al. 2013), but few organizations implement these tools to understand behavior change among resource users (Wright, Verissimo, et al. 2015). Tapping in to the values and norms of resource users may provide insight into what motivates them to behave prosocially and this can be used to create successful conservation campaigns (Butler, Green, and Galvin 2013).

One such determinant that could account for giving to public goods is based on understanding if personal values and personality characteristics are good predictors of prosocial behavior. Social scientists tend to see internalized values and norms as an important influence on human behavior and these are often reflective of the social values and norms of society, thereby, determining the choices individuals make. Social norms are standards of behavior that are based on widely shared beliefs how individual group members should behave in a given situation (Fehr and Fischbacher 2004). The group members might obey the norm voluntarily if their individual morals are in line with the normatively required behavior. Staub (1974) found that a prosocial orientation index (combining measures of feelings of personal responsibility, social responsibility, moral reasoning, and prosocial values), was a good predictor of helping behavior. More recently, measures aimed at understanding how individuals prefer to distribute wealth between themselves and another individual have been used to predict prosocial behavior (Kamas and Preston 2008). I use the ‘distributional preferences’ measurement method developed by Kerschbamer (2015) to categorize participants based on their responses into four distinct types: benevolents, egalitarians, own-money maximizers, and malevolents. Then I analyze donation behavior dependent upon the

Introduction distributional preference type to determine if these psychological characteristics are good predictors of pro-environmental behavior (measured through contributions to charity).

Several studies have found that personal preferences for how wealth is distributed between individuals shapes behavior on a range of issues related to: competition in the labor market (Balafoutas, Kerschbamer, and Sutter 2012), political party affiliation (Dawes, Loewen, and Fowler 2011), collective behavior (Fehr and Fischbacher 2004) and productivity (Carpenter and Seki 2011). Yet few studies focus on how the distributional preferences of resource users relates to contributions to public goods (Nelson, Schlüter, and Vance 2017a, Kamas and Preston 2008). It is also not well understood whether concern for the welfare of others extends to the environment or to benefits that are dispersed among many individuals such as the case with open- access resources. With this research, I will examine the relationship between distributional preference types and charitable giving behavior among marine resource users from a fishing village in Wakatobi, Indonesia.

1.4.3 Research 3: Financing land-sea conservation through voluntary tourist eco-fees

In research paper 3, tourists on the island of Gili Trawangan, Indonesia are asked for voluntary contributions to support the local conservation NGO. I use an experimental design incorporating varied choice factors into the donation request to solicit real donations for conservation. Many studies soliciting willingness to pay use hypothetical scenarios which often result in overestimations (Ajzen, Brown, and Carvajal 2004). This study is ideally suited for soliciting real payments because the services are already being provided by the NGO and there is an existing voluntary payment collected from scuba divers. The objective is two-fold: 1) to understand the effectiveness of different choice factors in soliciting donations to expand the voluntary user fees beyond scuba divers; and 2) to understand donor interests of incorporating terrestrial issues into conservation planning across land-sea ecosystem boundaries.

Many factors constrain the success of marine conservation initiatives. A plethora of scientific literature exists that describes constraints related to inadequate governance (Marian 2012, Young et al. 2007, Garcia, Rice, and Charles 2014), conflicts between stakeholders (Pomeroy et al. 2005, Chollett et al. 2017, Flannery and Ellis), and limited enforcement capacity (Beddington, Agnew, and Clark 2007, Walmsley and White 2003). Yet the subject of finance is an overarching

Introduction challenge to marine conservation worldwide that has not been adequately addressed in the literature or in practice (Bos, Pressey, and Stoeckl 2015).

User fees2 paid by tourists who benefit from marine and coastal public good resources (i.e. clean public beaches and public spaces, clean sea water, healthy marine ecosystem) constitute a significant potential revenue source to finance conservation. Some popular dive destinations have government imposed marine park user fees for divers (Thur 2010). Yet there are many circumstances in which a government imposed fee may not be ideal or possible to implement, or in which a non-government entity maintains public goods in the absence of government. In these cases, a system of methodically requesting voluntary user fees can be an effective approach to generate considerable revenue for conservation. In fact, one study by Arin and Kramer (2002) found that most tourists preferred NGOs as the most trustworthy organization type to collect and manage marine park entrance fees. In many cases, user fees collected by an NGO could not be a mandatory fee (unless government approved) as they do not have the authority to impose a ‘tax’3 on public goods and services, and instead these would necessarily be voluntary payment collections. Although several studies focus on the willingness to pay user fees, there is a gap in the literature on the most effective methods to request voluntary donations. The method of requesting a voluntary donation can have a significant effect on both the amount of people that choose to donate and the amount given. Getting this right is crucial to the sustainability of a program dependent on voluntary user fees.

Research 3 focuses on the potential for multiple-use marine areas to be financed by tourists’ voluntary user fees. I focus on both the willingness to pay for user fees and the most effective methods for collecting this voluntary payment. Additionally, unlike the majority of studies that focus only on divers’ willingness to pay, I expand the scope of user fees to all tourists regardless of the use type to explore the potential for financing conservation across users and land-sea boundaries.

I chose Gili Trawangan (see section 1.5.2 for more information) as the location for research 3 because of the current coastal problems faced here by the unsustainable growth in tourism and the

2 A ‘fee’ is defined as a sum paid or charged for a service (Merriam-Webster 2017a). ‘Voluntary’ is defined as proceeding from the will or from one’s own choice or consent; acting or done of one’s own free will without legal obligation (Merriam-Webster 2017b). Therefore, what is meant by the term ‘voluntary fee’ is a sum paid for a service from one’s own choice. 3 ‘Tax’ is defined as a compulsory contribution to state revenue, levied by the government on workers' income and business profits, or added to the cost of some goods, services, and transactions (Oxford 2017). 14

Introduction existing, but limited, structure of voluntary contributions for conservation. This makes an ideal location for research 3 to focus on methods of privately funding marine protected areas through soliciting contributions for conservation across different types of resource users.

1.5 Study locations

The Coral Triangle is an archipelagic region of approximately 5.7 million km2 with 153,000 km of coastline, which includes the seas of Indonesia (central and eastern), Malaysia (Sabah), the Philippines, Timor Leste, Papua New Guinea and the Solomon Islands (see Figure 2) (Veron et al. 2009). The Coral Triangle is recognized as the epicenter of marine biodiversity and a global priority for conservation (Veron et al. 2009, Hoeksema 2007). This area contains the highest coral diversity on the planet, where 76% of the world’s 798 coral species can be found (Hoeksema 2007). Given the chronic nature of local anthropogenic disturbances compounded by the effects of climate change, the Coral Triangle also has the highest proportion of ‘vulnerable’ and ‘near threatened’ coral species (Carpenter et al. 2008). The Coral Triangle region has a combined population of over 370 million people with around 120 million who benefit from marine ecosystem goods and services for fishery production, shoreline protection, and tourism (Foale et al. 2013). High levels of threat combined with high economic dependence on coral reefs and associated ecosystems mean that significant numbers of people in the Coral Triangle region are ecologically, socially, and economically vulnerable to degradation of the marine environment.

Figure 2 Map of coral triangle region with number of coral species highlighted. Source: Veron et al. (2009) and Coral Triangle Atlas.

Introduction

This study will focus on two locations in Indonesia, a nation of 17,000 islands that covers a significant portion of the Coral Triangle region and represents the greatest diversity of coral species within the region (see Figure 2) (Veron et al. 2009). Additionally, more people live close to reefs and depend on marine resources in Indonesia than anywhere else on the planet (Gurney et al. 2014). The two locations: (1) Wakatobi National Park, and (2) Gili Trawangan (see Figure 3 below) were chosen based on their high marine biodiversity, and fragile, but mostly healthy, coral reef ecosystems that are at immediate threat from numerous human activities including rapid development, overfishing, destructive fishing, and pollution. There are also distinct social economic differences between Wakatobi and Gili Trawangan that make for ideal research locations.

(a)

Wakatobi

Gili Trawangan

(b) Wakatobi (c) Gili Trawangan

Figure 3: (a) Map of Indonesia with Wakatobi island chain circled in red and Gili Islands circled in blue; (b) Wakatobi island chain - Wangi, Kaledupa, Tomia, and Binongko islands. Bajo Mola Village highlighted in red; (c) Gili Islands – from left Gili Trawangan, Gili Meno, and Gili Air. Source: Google (2017).

Introduction

1.5.1 Wakatobi, South East Sulawesi, Indonesia

The Wakatobi National Park (WNP) encompassing 13,900 km2 is located in the province of Southeast Sulawesi and was classified as a national park in 1996 (Clifton 2013). It is Indonesia’s third largest marine national park and is an IUCN Category II multiple-use protected area (Green et al. 2011). Hard coral cover is estimated to be around 35–40% (Clifton 2013) and in 2012, the park was designated a World Biosphere Reserve recognizing the unparalleled biodiversity found here and the importance of conservation. The name ‘Wakatobi’ is an acronym based on the four main islands that make up the region: Wangi Wangi, Kaledupa, Tomia, and Binongko. All together the four islands are home to around 100,000 people which makes it the most populated marine national park in Indonesia (Clifton and Majors 2012). Two distinct ethnic groups comprise the population of the park. The majority of park residents (92%) are of Butonese origin. The minority Bajo (sometimes spelled Bajau or Badjo) ethnic group number approximately 7000 in six settlements across the islands (Clifton 2013). Nearly all people on these islands depend on marine resources at some level, but the Bajo are almost exclusively dependent upon the marine environment for food, income, fuel and building materials. They generally live in the intertidal zone in houses constructed upon stilts or a foundation of mined coral (see Figure 4a) (Von Heland and Clifton 2015, Clifton 2013). Southeast Sulawesi is ranked towards the bottom of most national socio-economic indicators, with a GDP per capita less than half that of the national average and a workforce predominantly dependent upon agriculture and fishing (Clifton 2013).

Introduction

(a) (b)

(e) (f)

Figure 4: (a) Bajo Mola village showing houses built over the water on stilts; (b) Photo showing fish traps; (c) Spear fisherman in Wakatobi; (d) Local Bajo villager drying fish from home; (e) Canal through Bajo Mola Village with homes built on reclaimed land from mined coral; (f) Assortment of small reef fish and juvenile fish sold in the local market. Photo credits: Katie Nelson (2015).

The original zonation plan for WNP neglected the importance of local knowledge and community participation in designing and defining the national park. The entire 13,900km2 was originally declared as a no-take zone which resulted in conflict with the local Bajo population that exclusively depends on fishing. The region is difficult to patrol due to the sheer size of the national park and fishermen largely ignored the zonation and continued to fish even after the park was declared a no-take zone (Clifton 2013). Although blast fishing and cyanide poisoning are forbidden everywhere in the park, there were frequent occurrences in the past that have since decreased in frequency but still remain a major concern within the park (von Heland, Clifton, and Olsson 2014).

Introduction

To address overfishing and destructive fishing practices in Wakatobi, international NGOs worked with the Wakatobi National Park Authority and a broad range of stakeholders to implement a revised management plan. International NGOs, namely the World Wildlife Fund (WWF) and The Nature Conservancy (TNC), contributed substantial funding and logistical support to this process. In 2008 the zonation was revised with input from the local community in defining no-take zones, areas open to fishing only by local residents and licensed fishermen, and dive sites and fish spawning aggregation sites where fishing is not allowed (Clifton 2013). NGOs have continuously carried out activities with local communities to increase environmental awareness with the intention to encourage behavior change through education and participation (Butler, Green, and Galvin 2013). In 2014, based on the recognition that the management system is ‘mature’, TNC ended its partnership with Wakatobi National Park and the WWF scaled back. This led to a significant drop in financing and a changing management structure. At the time, Wakatobi was considered to be a model MPA for Indonesia. Since the decrease in funding, there has been a considerable decline in monitoring and enforcing regulations. This raises questions about the long-term financial sustainability and viability of the national park and its resources (Middelveld, van der Duim, and Lie 2016).

Interestingly, a private model of conservation also exists within the WNP between the Wakatobi Dive Resort and the surrounding fishing villages. A 20 km section of reef near the resort is designated as a no-take zone and direct payments are provided to 17 fishing villages to honor this agreement. These combinations of approaches to marine conservation management make Wakatobi an interesting location to study voluntary behavior to finance public goods.

This location site was chosen as an area for research due to its high biodiversity, international recognition for conservation, large common fishing grounds, minority ethnic group dependent on fishing, rapidly growing tourism industry, and multiple approaches to conservation management. Overcoming the commons challenge requires individuals to bear personal costs in order to benefit the collective group. As the local economy transitions from an economy that is heavily dependent on fishing to an economy dependent on dive tourism, much of the conservation effectiveness will depend on the behavior of the local community. Therefore, we chose to focus research 1 and research 2 on the local Bajo fishing community in WNP.

Introduction

1.5.2 Gili Trawangan, Lombok, Indonesia

The Gili Islands consist of three islands off the northwest coast of Lombok: Gili Air, Gili Meno and Gili Trawangan (see Figure 3c). Gili Trawangan, the most westerly and the largest of the three islands at 6km2, was uninhabited until the mid-1970’s (Bottema and Bush 2012). Situated between Bali and Lombok in the ‘Indonesian Through flow’ where the Pacific flows into the Indian Ocean, the islands are fringed by shallow coral reefs supporting high fish and coral species biodiversity. Early sources of income on the island were from coconut plantations and fishing until dive tourism began to develop in the late 1980’s-early 1990’s with three established dive operators. The tourism industry has proliferated through the 2000’s with currently over 30 dive shops and 750 hotels and other businesses. Today, Gili Trawangan is one of the most popular destinations in South East Asia for travelers to become scuba certified. Approximately 1 million tourists visit Gili Trawangan per year with between 1200-3000 per day visiting these islands (Halim 2017). The surrounding corals are threatened by destructive fishing practices and other human activities from the rapid growth in tourism including waste pollution, anchoring from boats, overcrowding of dive and snorkel sites, erosion from land clearing, and bleaching from global warming.

The percentage of live coral surrounding the islands is between 5-20% which prompted the central government to declare the marine area around the islands a conservation area in 1998 (Satria, Matsuda, and Sano 2006). This was re-appointed as the Gili Matra marine reserve in 2009 dedicating 29.54km2 of protected area (see Figure 5) (Kurniawan et al. 2016). There were conflicts regarding the management of the area between the local government and the Agency for Natural Resources Conservation which largely resulted in a lack of coordination and thus no enforced regulation and continued destructive fishing (Kurniawan et al. 2016). There was strong motivation from the head of the island and business owners to prevent destructive fishing practices given the economic dependence on coral reef tourism. Therefore, much of the marine protection has been driven by community efforts and private funding through voluntary diver contributions (Halim 2017).

Introduction

Figure 5 Zonation map of Gili Matra marine reserve. Source: Conservation (2017).

This provides a unique perspective of locally organized and funded marine conservation efforts. There has never been a government imposed marine park fee but the dive shops have organized and agreed upon collecting a one-time contribution from each diver of 50.000 Indonesian Rupiah (IDR) (approximately $3.75USD). Tourism has grown considerably over the last ten years. There has been a shift from a majority of dive tourists to a majority of beach and party seekers with everything from luxury beach villa holiday-makers to partying backpackers on the South East Asia circuit. This growth has brought many economic advantages to the island but it has also led to devastating effects on the terrestrial and marine ecosystem from the increased pressure exploiting the minimal natural resources. Considerable efforts are being made by local businesses and the local environmental NGO but funding remains an issue. The installation of biorock reefs represent conservation efforts to protect corals that are becoming more degraded from overcrowded dive sites and illegal anchoring (see Figure 6d). Plastic waste and pollution are a huge problem on the island with an estimated 8-10 tons of garbage produced daily (Halim 2017). This causes a build-up of waste on the island resulting in unsightly beaches, roads, and surrounding waters (Figure 6f). The overall number of visitors to the island has increased considerably but the conservation funding has remained in the realm of diver contributions. In

Introduction order to tackle the mounting environmental problems, funding for conservation will need to considerably increase.

This location was selected for research due to the existing NGO that provides many public goods services, a voluntary payment structure already in place for divers, the mounting environmental issues spread between the land-sea ecosystems, and the escalating tourism industry. Research 3 focuses on tourist perceptions of environmental threats to the island and their willingness to pay for conservation.

(a) (b)

(e) (f)

Figure 6: (a) Aerial view of Gili Trawangan. Photo credit: The Jetlagged (2017); (b) Photo of one of the islands many turtles which attract marine tourism. Photo credit: The Jetlagged (2017); (c) Hard and soft coral reef teeming with biodiverse fish life. Photo credit: The Jetlagged (2017); (d) Biorock structure with pieces of live coral connected to form new reef substrate. Photo credit: Gili Eco Trust (2017); (e) Waste separation and recycling bins. Photo credit: Gili Eco Trust (2017); (f) The rubbish dump far overcapacity and the ponies and workers that collect the rubbish. Photo credit: Gili Eco Trust (2017).

II. Manuscripts

Chapter 1 2 Giving time or money to fund public goods

Funding conservation locally: Insights from behavioral experiments in Indonesia Nelson, K. M., Schlüter, A., and Vance, C. * Published June 29, 2017. Conservation Letters. doi:10.1111/conl.12378

2.1 Introduction

Fishing and pollution are the key proximate stressors that threaten coral reefs ecosystems. In Indonesia, 95 percent of reefs are threatened, of which 50 percent are in the high or very high threat category (Burke et al. 2011). Conservation science often applies ecological methods to document losses and identify causes for such decline (Verissimo, MacMillan, and Smith 2011). A paradigm shift is needed that addresses the problem from the perspective of local human drivers so that context appropriate strategies can be implemented (Smith et al. 2009). It is widely accepted that behavioral economic experiments are useful in understanding human behavior, yet conservation science has all but ignored this potential (Cowling 2014, Reddy et al. 2016).

The provision of local environmental public goods is essential for socio-economic development, yet there is limited experimental evidence testing various measures that influence contributions to these goods in developing countries – where coral reefs are prevalent (Carlsson, Johansson- Stenman, and Nam 2014, Rode, Gómez-Baggethun, and Krause 2015). And, to our knowledge, there are no field experiments that compare voluntary contributions of money and time.

Indonesian’s depend heavily on the health of coral ecosystems for the multitude of local resources provided: they sustain a complex food system, protect people from storm surges, and support economic growth. Yet the country’s decentralized government and limited public funding for conservation makes local community initiatives all the more important. Participation in local conservation activities, such as when an individual donates money, volunteers, or otherwise expends effort for the purpose of conservation, is of particular research interest.

This paper contributes to the gap in research between the charitable giving literature and contributions to public goods in developing countries by employing a behavioral economics field 24

Chapter 1 Giving time or money to fund public goods experiment in a coastal village in Indonesia. We focus on two types of contributions: 1) donating money, and 2) donating time. In addition, we examine the effects of matching donations of money and time at a rate of 1:1 (i.e. the value of contributions is doubled). Participants, who are heavily dependent on marine resources and whose behavior directly influences the health of the ecosystem, begin by selecting a charity and then performing a task to earn income subject to one of the four treatments: monetary donation (D), monetary donation match (Dm), volunteer time donation (V), and volunteer time donation match (Vm).

Contrary to existing lab studies, which have identified higher donations of time than money (Brown, Meer, and Williams 2013, Lilley and Slonim 2014), we find that members of an Indonesian fishing community give significantly more when donating money compared to time. We also find that matching increases the percent of people who give but has a crowding-out effect on the percent of earnings donated under the monetary treatment. Taken together, these results highlight the importance of factoring human behavior – and specifically the role of incentive schemes in influencing preferences for giving – into the design of conservation strategies (Reddy et al. 2016, Veríssimo 2013) .

2.2 Theory: Time is money?

This research addresses the conventional economic theory that whenever the value of cash donations equals the value of time donations, people are indifferent between giving monetary contributions or the value of volunteer labor to the charity (Andreoni et al. 1996). The validity of this assumption has largely escaped empirical scrutiny, with the majority of studies focusing on monetary contributions. To our knowledge, only two behavioral studies4 compare monetary and time donations. Conducted with university students in developed countries, both studies identify stronger preferences for time donations. Using a lab experiment, Brown, Meer, and Williams (2013) find that students give substantially more time – voluntarily performing tasks while the earnings accrue to the charity – rather than donating income they earned. Similarly, in the lab experiment by Lilley and Slonim (2014), subjects simultaneously choose how much time and money they want to donate to charity under different wage rates, tax rates, and endowments. Their results show that students give more time than money, suggesting greater “warm glow”

4 Rai et al. (2015) use choice experiments and Eom and Larson (2006) use contingent valuation methods to identify differences in local demand for environmental services. Their results show a stronger preference for offering time for local environmental services rather than making a monetary payment. 25

Chapter 1 Giving time or money to fund public goods benefits from donating time. We model our experimental design loosely on that of Brown, Meer, and Williams (2013) and test the hypothesis that the marine resource users in this fishing village are indifferent between donating time and money.

2.3 Matching

In principle, matching effectively lowers the “price” of a charitable donation. Following standard economic demand theory, if the price of something falls, consumers should consume more. Nevertheless, the literature on donation matching is inconclusive. Some studies show increased propensity to donate and increased donation amounts with matching (Karlan and List 2007, Karlan, List, and Shafir 2011, Meier 2007, Okunade and Berl 1997), while other studies report decreased individual giving (Eckel and Grossman 2008, Huck and Rasul 2011).

Even with inconclusive evidence, the ubiquitous prevalence of matching incentives among philanthropic industry practitioners begs the question of whether this technique works in a developing country context to increase either money or time donations. We consequently test the null hypothesis that matching has no impact on the individual gift amounts or on the percentage who donate.

2.4 Background

302 individuals were recruited5 from Bajo Mola village, a settlement of stilted houses constructed upon mined coral in the reef flat zone (Sather 1997) and located on Wangi-Wangi Island in South East Sulawesi, Indonesia (see Figure 7). Being a fishing community that is almost exclusively dependent upon the marine environment for income, food, fuel and building materials, the Bajo are significant stakeholders in marine resource management6. They are simultaneously often held responsible for destruction to the reef ecosystem due to bomb fishing and coral harvesting (Caras and Pasternak 2009). There are various NGOs and community organizations within and outside the village that provide public goods, such as community clean-ups, or environmental education.

5 One-third of all houses participated. 6 For in-depth ethnographies of the Bajo sea nomads, see Chou (2005), Sather (1997), and Clifton and Majors (2012). 26

Chapter 1 Giving time or money to fund public goods

Figure 7 House in the Bajo Mola village in Wangi Wangi, Wakatobi, South East Sulawesi. The homes are built on coral mined from the local reefs by the villagers. Photo credit: Katie Nelson (2015).

Ninety-nine percent of participants in our sample identify as Muslim. The concept Sadaka (Sadaqah), meaning voluntary charity, is important in Islam and is widely practiced. Self-reported figures indicate that 93% of the study participants voluntarily gave money to charity and 76% volunteered time in the last year.

2.5 Methods

Invitation letters with randomly assigned dates and times of sessions were distributed to all houses in the village. Participants were grouped together for the briefing instructions and then continued with the task individually7. In all treatments (see Table 1) respondents chose one charity from a list of six. Then each person performed the same piece rate task for one hour and made a donation decision. Finally, they completed a survey questionnaire.

Table 1 Description of between-subject treatments

(D) Donate Participants can donate money at the end of the experiment after payment for work.

Participants can donate money at the end of the experiment after payment for work and (DM) Donate Match donation will be matched 1:1.

(V) Volunteer Participants choose to switch between working for themselves and volunteering.

Participants choose to switch between working for themselves and volunteering. The (VM) Volunteer Match value of beads produced for charity is matched 1:1 by monetary donations.

7 See Appendix for a detailed description of the experimental set-up and location, the invitation letters, and experimental instructions. 27

Chapter 1 Giving time or money to fund public goods

2.5.1 Charities

Participants received a list of six charities with descriptions of their missions in randomized order (see Appendix D). They were instructed to confidentially select one charity to which they can contribute8. Two of the six charities target marine conservation while the remaining four do not have an explicit environmental focus. We followed the standard protocol of other charitable giving studies, which provide several options of different charitable causes to create a clear treatment effect and increase the likelihood that participants will find a cause they feel worthy of supporting (Brown, Meer, and Williams 2013, Gallier, Reif, and Römer 2014). This design feature is a methodological necessity, with the added virtue of revealing preferences for marine protection. We hypothesize there will be no differences in the patterns of giving behavior across the charity options.

Figure 8 Visual depiction of the difference between monetary and time donation treatments. Top: The monetary donation treatment involved 1 hour of participants making beads and then collecting their earnings and deciding how much to keep for themselves and how much to give to the charity they selected at the beginning. Bottom: The time donation treatment involved one hour of participants making beads and after each bead deciding whether to allocate their effort to earn money for themselves by placing the bead in the unmarked container or to let those earnings accrue to the charity they selected at the beginning by placing the bead in the container marked ‘charity’. Note: For both treatments, there was an identical ‘match’ treatment where any donation to charity was doubled. Photo credit: Katie Nelson (2015).

8 Each participant was informed that all donations would be sent to the charities within 90 days and that signs would be posted publicly in the village showing the total amounts donated to all of the charities. 28

Chapter 1 Giving time or money to fund public goods

2.5.2 Treatments

Each participant was involved in only one treatment. In the monetary donation (D) treatment subjects earned money performing a task and then decided whether to donate money to charity. The volunteer time donation (V) treatment allowed subjects to choose as they work whether each bead accrued money for themselves or for their chosen charity (see Figure 8).

To examine the effects of matching, the experiment included two additional treatments – monetary donation match (Dm) and volunteer time donation match (Vm). These are identical to the previous treatments except that the value of the individual’s contribution to charity in either case is matched at a rate of 1:1, so that double the amount went to their chosen charity.

2.5.2.1 Real effort task

Participants earned the money they donated to charity rather than receiving it as an endowment – the more common practice in experiments (Davis and Millner 2005, Eckel and Grossman 2003, Gallier, Reif, and Römer 2014). This is an important distinction because it is more similar to behavior in the real world9. Participants were given one hour to roll paper beads (see Appendix E) and were paid 1000 Indonesian Rupiah (IDR)10 for each bead completed. This type of task was chosen because it does not require prior knowledge; it is easy to teach to a person of any education level or age; it does not require any particular skill; and the activity is commonly taught by NGO’s as an income-generating activity in developing countries (Holt and Littlewood 2015).

Participants were instructed to deposit each bead into the transparent collection receptacle (see

Figure 8). The D and Dm treatments have only one receptacle while the V and Vm treatments have two, such that any beads placed in the unmarked receptacle will earn private income and any beads placed in the receptacle marked “charity” will earn money directly for their chosen charity. After sixty minutes, the beads were counted and the respondent was paid privately in cash in bills of various denominations. In D and Dm, participants were handed an envelope with their name, which contained their personal earnings, and an empty charity envelope. There was a separate

9 Reinstein and Riener (2012) find that those subjects who earned their compensation choose to donate less than those who received an endowment. 10 European Central Bank exchange rate 7 October, 2015 is EUR 1 = IDR 15,492. Therefore, 1000IDR is equivalent to 0.07€. 29

Chapter 1 Giving time or money to fund public goods

private area where they made their donation decision. They were asked to seal both envelopes

before leaving the area so that their decision was confidential. In V and Vm, the value of the beads from the unmarked receptacle was paid in cash and placed into the envelope labeled with the participant’s name. The value of the beads from the charity receptacle was paid in cash into the envelope labeled with the name of the charity the participant selected. In the case of the match treatments, the donated amount is doubled and placed into an envelope in front of the participant.

2.6 Results Summary statistics of the donations by treatment are presented in Table 211. The table is split into the averages across all participants plus the averages conditional on donating a nonzero amount. We report on both absolute amounts donated and percentage of earnings donated. Due to the wide range in earnings, we focus our discussion on the percentage of earnings donated.

Result 1. There are no significant differences in the pattern of donations between marine conservation charities versus those dedicated to other objectives.

9a) Choice of Charity 9b) Percent of people that gave something by charity type

100 85 90 Marine 80 conservation 36% 60 Other 64% 40 20

0 Marine conservation Other

9c) Average percent of earnings 9d) Average amount* donated by donated by charity type charity type 15 15 11.5 10.3 11.7 10 9.8 10

5.2 6.2 5.4 6.1 5 5 0 0 Marine conservation Other Marine conservation Other 2c) Total average Conditional on giving Total average Conditional on giving

Figure 9 Charity selection and donations by charity type. Note: None of the differences are significant at p<0.05.

11 Analysis of mean age, income, education, and gender distribution across treatment groups does not show any significant differences. See appendix for results of analysis of demographics across treatments. 30

Chapter 1 Giving time or money to fund public goods

As seen in Figure 9a, 36% of the sample chooses a marine conservation charity. Figure 9b shows no significant difference between charity types in the percent of participants that make a donation based on a Chi-square test (p=0.21). A one-way analysis of variance (ANOVA) test with Bonferroni correction shows that there are also no significant differences in the percent of earnings donated (p=0.61), nor in the amount donated (p=0.28) when comparing the marine conservation charities to the other charity options (see Figures 9c and 9d).

10a) Average percent of earnings donated 10b) Percent of N donating any amount 20 100

15 80 60 10 40 5 20 0 Donation Donation Volunteer Volunteer 0 Donation Donation Volunteer Volunteer match match match match Total N Conditional on giving

10c) Average Earnings* 10d) Average amount donated* 80 10 70 8 60 50 6 40 30 4 20 2 10 0 0 Donation Donation Volunteer Volunteer Donation Donation Volunteer Volunteer Match Match Match Match

Total N Conditional on giving Total N Conditional on giving

Figure 10 Bar graphs of treatment comparisons. Note: Refer to Table 2 for values and significant differences between treatments *Amounts shown in Indonesian Rupiah divided by 1000 (1000IDR = 0.07€)

Chapter 1 Giving time or money to fund public goods

Table 2 Summary Statistics by treatment

Total Sample Donation Donation Volunteer Volunteer Match Match N 75 76 75 76

Average percent of earnings 15a 10.6ab 7.5b 7.6b donated (16.7) (9.7) (9.8) (7.3)

Percent of N giving something 85.3a 92.1b 82.7a 93.4b

Average earnings* 51.7a 57.2a 58.2a 57a (15.6) (16.8) (16.4) (14.7)

Average amount donated* 7.0a 5.6ab 4.4b 4.4b (6.0) (4.2) (6.5) (4.6)

Conditional on giving Donation Donation Volunteer Volunteer Match Match N 64 70 62 71

Average percent of earnings 17.6a 11.6b 9.1b 8.2b donated (16.8) (9.6) (10.1) (7.2)

Average earnings* 52.7a 57.7ab 60.9b 58.0ab (16.2) (16.5) (16.3) (14.1)

Average amount donated* 8.2a 6.1ab 5.3b 4.7b (5.7) (4.0) (6.8) (4.6)

(a,b) Different letters between the means indicate significant difference at p<0.05 in One-way ANOVA test with Bonferroni correction, or Binomial probability test, as appropriate (means that share the same letter, even if it is in combination with another letter, are not significant) *Amounts shown in Indonesian Rupiah divided by 1000 (1000IDR = 0.07€) Standard deviations in parentheses

Result 2. The average percent of earnings donated is significantly higher in the monetary donation (D) compared to the volunteer time donation (V).

The ANOVA test with Bonferroni correction shows a highly significant difference (p=0.00) between D and V in the average percentage of earnings donated. Participants in D give an average of 15.03% of their income to charity while those in V give an average of 7.54%. This holds true whether we include those that donated nothing in the average donation or whether we analyze the results conditional on giving (p=0.00) (see Figure 10a). This result remains robust when analyzing the absolute amount donated (see Table 2). We also explored the results when we

Chapter 1 Giving time or money to fund public goods correct the standard errors for clustering at the session level, which has only a negligible bearing on the precision of the estimates (see Appendix 1). We can therefore reject the hypothesis suggested by Andreoni et al. (1996) that there should be no differences in the average amounts of money or time donated when they are of equal value. On the other hand, our results are the opposite of the findings of Brown, Meer, and Williams (2013) and Lilley and Slonim (2014), who showed that participants prefer to donate time rather than money.

Result 3. The percent of participants who donate increases significantly with the presence of the match.

As seen in Figure 10b, the percentage of participants that give to charity increases significantly in both of the matching treatments. There is a seven percentage point increase in the percent of people giving, from 85% in D to 92% in Dm (p=0.05) (see Table 2). The difference is even greater in Vm, with nearly an eleven percentage point increase in frequency of giving (from 82.7% to 93.4%; p=0.001) with the offer of the match.

Result 4. Matching does not increase the percent donated in either the money or time treatments.

Table 2 shows the average percent of earnings donated is 15% for D and 10.6% for Dm (p=0.461). Conditional on giving some amount, this decrease in percent of earnings donated becomes significant with D at 17.6% and Dm at 11.6% (p=0.008). There is no significant difference in the average percent of earnings donated between V and Vm. All results hold true when absolute donation amounts are analyzed (see Table 2).

Thus, offering a match can be a counterproductive fundraising mechanism. However, in a dynamic strategy of identifying and developing a new donor sub-population, the significant increase in the percentage of participants giving something in both match treatments (from Result 3) may be of strategic importance to charity organizations (see Figure 11).

Chapter 1 Giving time or money to fund public goods

Total amount received by charities Not including match

523 427 327 335

Donation Donation match Volunteer Volunteer match

Figure 11 Total funds received by charities (not including match amounts). *Amounts shown in Indonesian Rupiah divided by 1000 (1000IDR = 0.07€)

2.7 Discussion

Voluntary contributions to conservation are highly important yet receive little research attention in the conservation sciences (Scarlett et al. 2013). Here we present the first experimental methodology designed to evaluate resource users’ preferences for contributing time or money and their response to matching incentives. This method allows for evidence-based design of conservation campaigns based on the preferences of the target audience.

Participants from this fishing community display similar preferences for selecting and donating to marine conservation charities as compared to other charitable causes. Marine conservation charities represent one-third of the charity choices and slightly more than one-third of participants select this type of charity. Additionally, participants that choose marine conservation charities donate an equivalent percent of their earnings as those participants that chose other charities. We find clear treatment effects regardless of the type of charity selected. These are important findings for conservation organizations trying to involve communities in engagement and investment in sustaining their natural resources.

Contrary to previous experimental studies, all of which were done in the lab, we find that participants donate a higher percentage of earnings as monetary contributions than time to charities. This result shows the risk in extending insights from university lab experiments in developed countries to behavior in a field setting in a developing country when designing

Chapter 1 Giving time or money to fund public goods conservation campaigns. Several plausible explanations exist to explain why monetary donations would be larger.

One possibility is that participants may gain more gratification from giving away the relatively scarcer resource (Macdonnell and White 2015) – cash in the case of a low-income fishing community in Indonesia. Tentative evidence is seen by a regression interacting the treatments with income, which indicates that the positive effect of the donation treatment decreases in magnitude with increases in the income of the participant (Appendix 3).

Second, religious background may also play a role. With 99.7% of the sample self-identifying as Muslim, it is possible that the effects are based on the deeply ingrained obligation of monetary charitable giving in Islam, known as ‘Zakat’ (Lambarraa and Riener 2015). Indeed, the sample’s self-reported frequency of voluntarily donating money to charity (93%) compared to volunteering (76%) confirms the pattern seen in the data.

A third possible explanation for higher monetary donations may owe to risk aversion, given that those in the monetary donation treatment (D) are aware of the total amount they earned before they have to make the donation decision, thus making it easier to calculate how much private income they will take home after giving. While warranting consideration, we do not believe that this factor drives our results. Participants were able to monitor the accumulation of beads in the transparent containers, a highly repetitive process that varies little from bead to bead, making it straightforward to anticipate the total amount that would be produced. Moreover, anecdotal evidence from post-experimental surveys indicates that participants in the volunteer treatments applied different strategies to account for earnings and donations, such as counting beads and giving one in every 2 or 10 beads, or deciding on a value to donate at the outset.

Some practical insights have emerged that can inform efforts to raise funds and encourage community engagement in conservation. If the goal is to increase monetary donations, matching does not appear to be effective, but if the goal is to increase the donor base, matching significantly increases the percentage of people donating, which can have great value over the long-term. If the goal is to get people actively involved through participation and volunteering, announcing that their time will be matched can allow organizations to better recruit new volunteers, and will lead overall to more individual volunteer hours received by the charity. An overwhelming majority of conservation organizations are non-profit and depend on grants, 35

Chapter 1 Giving time or money to fund public goods donations, and volunteer time. Re-framing secured funds as matches does not incur additional cost to the charity and it significantly increases the number of money- and time donors. This evidence paves the way for additional studies that focus on whether people are more likely to participate in meetings and activities if the value of their individual volunteered time is known and matched with monetary funds.

The experiment further demonstrates that giving behaviors are not universal and are highly context-dependent (Lambarraa and Riener 2015, Henrich et al. 2004). We recommend that similar methods be applied across different cultural settings to provide more understanding as to whether our results are idiosyncratic or whether there is widespread cultural variation in giving behavior.

Chapter 1 Giving time or money to fund public goods

Appendix 1 Experimental Design

Participants were invited through a hand-delivered letter to each house in the village. The invitation letter (see Appendix A) specified the date and time of the session. The treatments were randomly assigned on the group level by a random drawing of a piece of paper marked with the treatment group. The same person always conducted the treatment instructions briefing. Participants were briefed in small groups and then continued to work individually. There were 63 groups overall. To explore whether this grouping had a bearing on statistical inference, we analyzed the percent donated and the absolute amount donated as the dependent variables in a regression with the treatments as the independent variables. The results indicate that the t- statistics change only marginally when correcting the standard errors for clustering by group (see table 3).

Table 3 Effect of clustering standard errors:

% % donated Absolute Absolute donation donated Clustered SE donation amount amount Clustered SE Donation 0.000 0.000 0.000 0.000 Donation Match -0.044 -0.044 -1,354.912 -1,354.912 (2.37)* (2.12)* (1.55) (1.70)

Volunteer -0.075 -0.075 -2,613.333 -2,613.333

(4.02)** (3.64)** (2.97)** (2.63)*

Volunteer Match -0.074 -0.074 -2,565.439 -2,565.439 (3.98)** (3.66)** (2.93)** (2.87)**

_cons 0.150 0.150 6,973.333 6,973.333

(11.41)** (8.84)** (11.22)** (11.70)** 2 R 0.07 0.07 0.04 0.04 N 302 302 302 302

*p<0.05; ** p<0.01 ‘Percent of earnings donated’ and ‘Absolute amounts donated’ represent dependent variables in a regression with treatments as independent variables. Only marginal change in t-statistics when analyzing clustered standard errors. Note: T-statistics in parenthesis

Sessions were held throughout the day from 10:00am and into the evening until 20:00. Women preferred to attend sessions with other women and the same was true for men so we separated sessions by gender. The experimental location was in a neutral place, easily accessible by foot in a rented building outside of the village so as not to appear as affiliated with any local NGOs or

Chapter 1 Giving time or money to fund public goods government offices. There was a large open room where the participants performed the task while sitting on the floor and shielding their work from others by a cardboard box that was provided with their supplies. After the briefing, a demonstration was given on how to roll a bead and participants were given their supplies and had three minutes to practice. The collection containers where they deposit the beads were transparent so they could see and count their beads throughout the hour during the task. Participants were allowed to converse during the task but they were specifically instructed not to discuss their work. They could stop at any time to go to the bathroom or take a phone call but the timer would not stop. They were informed at regular intervals of the time remaining (15, 30, 45, 55, 58 minutes). Once the time was finished for the task, the participants came individually to a separate area in the back of the building where their beads were counted and they were paid for their work. The payment was placed in an envelope with their name on it. In the Donation and Donation Match treatment, we handed both the full envelope with their name and an empty envelope with the charity’s name to the participants. There was a private room where participants then made their donation decision discreetly. They were instructed to close and seal both envelopes before exiting the room to ensure privacy. The participants then took a survey questionnaire and at the end of the survey, they collected the envelope with their earnings. In the match treatments, we matched by 100% any amount the participants gave to charity. We put the matched amount into an envelope that was stapled together with the participants’ charity envelope. In the Volunteer and Volunteer Match treatments, participants brought the two containers to the separate area in the back where the beads in the unmarked container were counted and the earnings were deposited into the envelope with the participant’s name, and then the beads in the container marked “charity” were counted and the value of the beads was deposited in cash into the envelope with the charity’s name on it. For consistency, the same person always checked and counted the beads. The team consisted of 5 enumerators from a nearby university that spoke Bahasa and some also spoke the local dialect; a field manager from Indonesia; and the lead author. All paper strips used in the task were cut by the enumerators from recycled airline magazines with a width of 1.5cm at the base and tapering to a point.

Chapter 1 Giving time or money to fund public goods

Appendix 2 Demographic distribution and regional population data

Gender Distribution - Wangi-Wangi Gender Distribution - Sample 60 60 50 50 40 40 30 30 20 20 10 10 0 0 male female male female

Age Distribution - Wangi-Wangi Age Distribution - Sample 0.3 0.3 0.2 0.2 0.1 0.1 0 0

Education Distribution - Wakatobi Education Distribution - Sample 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0

Monthly Expenditure Distribution - Monthly Expenditure Distribution - Wakatobi Sample 0.3 0.3 0.2 0.2 0.1 0.1 0 0

Figure 12 Demographic distribution of district and regional population data compared to sample data. Source: BPS (2014)

The population demographic information is based on 2014 census data from the Wakatobi Regency (BPS 2014). Data is provided at the district level for gender and age and at the regional level for education and monthly expenditure; therefore, it is not possible to draw direct comparisons to the village level statistics from Mola Village where our sample was selected. 39

Chapter 1 Giving time or money to fund public goods

Although our demographic distribution differs somewhat from the district and regional level, having sampled one-third of the houses in the village provides a balanced perspective of the village demographics and this is confirmed in the relative similarity to the district and regional demographics.

Appendix 3 Regression table showing treatment and income interactions

To explore whether the income of the respondent has a mediating effect on contributions to charity, the below regressions include interactions of income with each treatment, designating the volunteer treatment (V) as the base case. The estimates confirm the key results presented in the text: The donation (D) treatment has the strongest effect, but its magnitude is reduced with matching. Moreover, in the model of absolute donations, income is seen to have a statistically significant effect.

Table 4 Regression table

Absolute amount % donated donated

Donation 3,753.875 0.090

(3.55)** (3.99)**

Donation Match 2,445.106 0.054 (2.09)* (2.18)*

Volunteer Match 1,344.087 0.017 (1.25) (0.76) Income x Volunteer 0.505 0.000 (2.04)* (1.06)

Income x Donation -0.576 -0.000 (2.00)* (1.19)

Income x Donation Match -0.622 -0.000

(1.47) (1.39)

Income x Volunteer Match -0.665 -0.000 (2.09)* (1.23)

_cons 3,381.924 0.065 (4.32)** (3.87)** R2 0.05 0.08

N 302 302

* p<0.05; ** p<0.01 Note: T-statistics in parentheses 40

Chapter 1 Giving time or money to fund public goods

With increases in income, people donate more under V, as evidenced by the positive coefficient of income (representing the base case). This effect, however, becomes negative with matching. The negative mediating effect of income is also seen under the donation (D) and donation match treatments (DM), although it is not statistically significant in the latter case.

Appendix 4 Comparison of demographics across treatment groups

There are no significant differences at p<0.10 in the demographics between treatments using a one-way ANOVA test with Bonferroni correction for multiple comparisons.

Table 5 Comparison of demographics across treatments

Donation Donation Match Volunteer Volunteer Match Female 51% 51% 45% 43% Age 31 33 31 32 Education level 4 4.5 4.3 3.7 Fisher 72% 61% 61% 71% Annual Income 2.32e+07 1.80e+07 1.94e+07 2.00e+07

Chapter 2 Individual characteristics and donation behavior

Chapter 2 3 Individual characteristics and donation behavior

Distributional preferences and donation behavior among marine resource users in Wakatobi, Indonesia

Nelson, K. M., Schlüter, A., and Vance, C. * Published October 5, 2017. Ocean and Coastal Management. doi:10.1016/j.ocecoaman.2017.09.003

3.1 Introduction

Human behavior is widely accepted as the key driver that threatens biodiversity (Wright, Veríssimo, et al. 2015). Humans have been dependent on marine resources for thousands of years and this dependency has altered the oceans through direct and indirect means (Halpern et al. 2008). Coral reefs sustain the livelihoods of millions of people around the world but they are facing serious decline and elevated levels of extinction (Mascia 2003, Carpenter et al. 2008). Coral reefs represent both local and global public goods in that they provide a source of food for millions of people; they are hotspots of marine biodiversity; they protect coastlines against storm surges; they provide habitat, spawning, and nursery grounds for diverse fish species; they provide jobs and income to local economies from fishing, recreation, and tourism; and they are a source for new medicines (Mumby et al. 2008). The destruction of coral reefs can be attributed to human behaviors such as pollution, overfishing, destructive fishing, coastal development, climate change resulting in rising sea temperatures, ocean acidification, and increases in the global demand for fish (Hilmi et al. 2017).

The marine conservation sciences often focus on documenting losses and identifying causes for declines in biodiversity. In order to move toward identifying the underlying drivers and implementing solutions, conservation practitioners must shift the focus from fish, reefs, and the underwater environment to equally focus on communities, people, and human behavior. Research suggests that management success depends upon social factors more so than biological or physical variables (Mascia 2003). The compelling logic is that damage is likely to be worse where natural resources are open-access because some people will be able to enjoy the benefits without contributing to the costs of provision. Maintaining large-scale cooperation for the

Chapter 2 Individual characteristics and donation behavior provision and management of open-access goods is fraught with this infamous cooperation dilemma in which people tend to free-ride, both by overusing resources and underinvesting in their maintenance. Coral reef ecosystems are the archetypal example of a natural resource that suffers from this cooperation dilemma. In countries that have few resources to support conservation, the situation is often exacerbated.

Much of the major funding for coral reef conservation comes from individuals and corporate philanthropy in Europe, North America, and Australia. However, a great deal of coral reef conservation work is focused in less wealthy countries. Countries in the Coral Triangle (i.e. Indonesia, Philippines, Malaysia) have been recognized as the global center of marine biodiversity and a priority for conservation (Allen 2008). In many cases where resources for regulation and enforcement are lacking, conservation activities require community involvement in the form of voluntary contributions and behavioral change on behalf of resource users. These contributions can be in the form of time or money (i.e. attendance at meetings, participation in training and events, donations, proper disposal of waste, following rules, etc.). The experiments in this paper are inspired by the need to better understand the contributive behavior of marine resource users to collectively sustain the conservation of coral reef public goods. McClanahan et al. (2006) provide evidence that marine management regimes designed to meet community goals can be more successful than those designed primarily for biodiversity conservation.

Indonesia has the highest diversity of corals and reef fishes and is home to one of the most biologically diverse and economically valuable marine ecosystems on earth (Allen 2008). Coral reefs in Indonesia sustain millions of people, providing the majority of protein and income for many coastal communities (Cinner 2014). Mass mortality events related to coral bleaching are increasing in frequency which threaten coral reef habitats and the high levels of biodiversity (Descombes et al. 2015, Pandolfi et al. 2011). The lack of sustainable funding for marine protected areas, coupled with low community involvement and ownership, contribute to the somber outlook for reef conservation in Indonesia (Bos, Pressey, and Stoeckl 2015). Therefore, we selected Wakatobi National Marine Park as our research site within Indonesia, which has large and vulnerable areas of reef, a relatively dense population (compared to other marine parks), a history of non-compliance, a strong fishing economy, and a rapidly growing tourism industry.

Chapter 2 Individual characteristics and donation behavior

3.2 Wakatobi National Marine Park

The Wakatobi National Marine Park is the third largest national marine park in Indonesia. Wakatobi covers 1.3 million hectares. The area was declared a marine national park in 1996 in an attempt to reduce destructive fishing practices and the threat of overfishing (Caras and Pasternak 2009) (see Figure 13). Wakatobi district is located in the province of Southeast Sulawesi and is made up of four larger islands: Wangi-Wangi, Kaledupa, Tomia, and Binongko. The marine environment includes extensive fringing shallow reefs and reef walls and boasts some of the highest recorded levels of marine biodiversity in any ecosystem in the world. It is ranked as one of the highest priorities for coral reef conservation in the Coral Triangle due to numerous human threats to the ecosystem including destructive fishing practices from bomb and cyanide fishing, overfishing, pollution, tourism development, and coral mining. The decentralization of government in Indonesia placed financial pressure on district governments which led to increased external involvement (e.g., non-governmental organizations or NGOs) into marine protected area plan production (von Heland, Clifton, and Olsson 2014). With input from the World Wildlife Fund (WWF) and The Nature Conservancy (TNC), the park regulation and zonation was significantly revised in 2009 due to a lack of community inclusion and participation in the initial zonation plan resulting in poor compliance and management (Clifton 2003).

With approximately 100,000 people living within the park, Wakatobi is one of the most densely populated marine national parks in Indonesia. The majority of residents rely on marine resources for food and income. Ninety-two percent are of local Butonese origin and the remaining eight percent (about 7,000 people) belong to the Bajo (sometimes spelled Bajau) ethnic group residing in six settlements across the islands (von Heland, Clifton, and Olsson 2014). The term ‘Bajo’ refers to several Austronesian ethnic groups across South East Asia. Historically, they are a sea- faring people that live much of their nomadic lives at sea or in huts erected on stilts over reef flats. They identify strongly with the ocean, calling other ethnicities ‘land people’, and their culture is strongly intertwined with the sea. They are linguistically and ethnically distinct from their Butonese neighbors. Even though they are strongly dependent on marine resources, in the past the Bajo have been systematically left out of participating in marine governance in Wakatobi because of their minority status. They represent key fisheries knowledge that is fundamental to the establishment and compliance of marine protected zones.

Chapter 2 Individual characteristics and donation behavior

Mola village

Wakatobi

Figure 13 Map of study site - Wakatobi National Marine Park and Bajo Mola Village (Clifton 2013).

3.3 Distributional Preferences and Contributive Behavior

Conventional economic reasoning is typically based on the self-interest hypothesis, i.e. the assumption that rational people are exclusively motivated by their material self-interest (Fehr and Fischbacher 2002). However, most economists recognize this assumption of pure selfishness is made mostly for simplicity. And there is overwhelming experimental evidence refuting the self- interest hypothesis by showing that people often behave with un-selfish preferences, which can help explain how and why communities are able to manage collective resources. Yet, the experiments used to elicit these preferences are typically played in small groups of only a few players. It is unclear if these preferences are stable when the exchange is between one to two individuals versus an organization (Schumacher et al. 2016). A core question pertaining to

Chapter 2 Individual characteristics and donation behavior conservation economics is: what are the conditions necessary for encouraging successful collective action for conservation? Behavioral studies that focus on individual decisions are crucial because they offer the possibility to understand environmental issues in connection with economic theory (Cecere, Mancinelli, and Mazzanti 2014).

Social preferences for the distribution of wealth (hereafter referred to as distributional preferences) shape individual behavior on a range of issues related to: competition in the labor market (Charness and Rabin 2002, Balafoutas, Kerschbamer, and Sutter 2012), political party affiliation (Fisman, Jakiela, and Kariv 2014), collective behavior (Fehr and Fischbacher 2002, Hedegaard, Kerschbamer, and Tyran 2011) and charitable giving (Kamas and Preston 2008, 2015). Relatively little is known about how the distributional preferences of resource users relates to contributions to public goods. It is unclear how distributional preferences factor in situations where the costs of an action are large, but the benefits are dispersed among many individuals, such as in the situation of environmental goods (Schumacher et al. 2014). Additionally, it is not clear whether concern for the welfare of others extends to the environment and open-access resources or whether they are linked at all. While there is literature showing that personal values affect contributions, the majority of research does not distinguish between the heterogeneity in prosocial motivations, such as differences between benevolence, inequity aversion, and efficiency or how this information could be useful to practitioners (Kamas and Preston, 2012). We also contribute to the literature that focuses on the stability of distributional preferences across social domains (i.e. distribution of funds to individuals vs. charitable organizations) (Schumacher et al. 2014, Schumacher et al. 2016, De Oliveira, Croson, and Eckel 2009).

Fundamental to achieving conservation goals is the ability to understand and manage biodiversity as a collective good that requires people to change their behavior by modifying, halting, or replacing detrimental activities (Secretariat 1992). According to Wright, Veríssimo, et al. (2015) and Harrison et al. (2014), in general, conservationists have failed to influence people’s behavior, and, as a result, biodiversity and natural environments continue to decline in extent and quality. Efforts to influence people's behaviors for the benefit of conservation should therefore seek new approaches from other disciplines such as marketing and charitable giving (Kraft-Todd et al. 2015, Wright, Veríssimo, et al. 2015, Veríssimo 2013). Voluntary approaches, as opposed to command-and-control regulatory approaches, are considered an important “new tool” for conservation and environmental management, but little is known about how to motivate 46

Chapter 2 Individual characteristics and donation behavior voluntary contributions for the environment (Dietz and Stern 2002, Brouhle, Griffiths, and Wolverton 2005).

Given the proximity and direct impact on the environmental good, understanding resource users’ ability and willingness to contribute to conservation is essential (Thaman et al. 2016). Environmental protection in many countries is funded from general tax revenues, but poor countries often have weak governmental financial support for conservation initiatives, meaning that a large proportion of conservation resources must be provided privately at the local, national and international level. Much of these funds come from voluntary contributions to NGOs and informal community groups, in the form of both volunteer services and monetary donations. Although much of the initial conservation funding may come from international sources, long- term planning must look beyond the project life to community-managed and sustainably financed conservation goals. Therefore, engaging in an experimental field setting with members of an Indonesian fishing community, we explore the relationship between the individual-to-individual and the individual-to-charitable organization distribution of resources and determine the practical implications of the results for conservation.

Previous studies indicate that different demographic, socioeconomic and psychographic characteristics make up market segments that affect the type of charity preferred and level of donations made to charities (Dolnicar and Randle 2007, Diamantopoulos, Schlegelmilch, and Love 1993, Nichols 1995, Straughan and Roberts 1999). The development of psychographically defined segments offers benefits in terms of greater precision when targeting marketing strategies, particularly promotional or behavior change strategies (Schlegelmilch and Tynan 1989). Dolnicar and Randle (2007) argue that motivation-based data-driven market segmentation represents a useful way of gaining insight into heterogeneity amongst donors. Such insight is useful to charity organizations to more effectively target segments with customized messages.

We investigate the demographic and psychographic factors that influence people from a fishing village in Indonesia to contribute to a charitable organization. We conducted a field experiment whereby participants earned money through the completion of a task and then had the opportunity to donate some or all of their earnings to local or national charitable organizations. Using the terminology from experimental economics, this is a simple ‘dictator game’ where the individual makes a decision about how to allocate an endowment between herself and a passive

Chapter 2 Individual characteristics and donation behavior recipient (which in this case is a charitable organization). Each participant was presented with one of the four treatment scenarios: 1) monetary donation, 2) monetary donation match, 3) volunteer time donation, and 4) volunteer time donation match. Each participant faced two decisions in sequence: whether to donate, and how much to donate. We incorporate this two-level decision structure into the analysis12.

This was followed by a binary-choice task to elicit distributional preferences in the psychographic dimension. Our analysis focuses on the relationship between distributional preferences between individuals and donation behavior to a charity organization, as experimental evidence on this topic is scarce (Kidd, Nicholas, and Rai 2013). The distributional preferences measurement is also a dictator game in which the decision maker’s choices have consequences for herself and an anonymous other individual participating in the experiment. We measure distributional preferences using the Equality Equivalence Test developed by Kerschbamer (2010). According to individuals’ payoff choices, the measurement test distinguishes between different categories of distributional preferences. The most prominent ones are benevolence (where increases in the payoffs to others enter positively into the decision maker’s utility function) (Andreoni and Miller 2002), egalitarianism (where there is a preference for equal payoffs, even when decision-maker’s payoffs could be higher) (Dawes et al. 2007, Fehr, Bernhard, and Rockenbach 2008), own-money-maximization (where the decision maker’s preference is for higher payoffs for self only and the welfare of the other does not enter into the utility function) (Kerschbamer 2015), and malevolence (where reductions in the payoffs to others are preferred) (Levine 1998). If the distributional preference type helps explain charitable giving behavior among resource users, we can use this information to customize communications regarding the benefits of conservation to appeal to specific psychographic types in the community of resource users. Therefore, understanding distributional preferences and the relationship to charitable giving behavior could be an important indicator in successfully managing collective resources (Fehr and Fischbacher 2002).

This research contributes to the growing literature on donation behavior by highlighting and analyzing the impact of an important factor – distributional preferences – on donations. Specifically, we build on an earlier study (Nelson, Schlüter, and Vance 2016) that exposed

12 Nelson, Schlüter, and Vance (2016) focus on an in-depth analysis of the differences between the treatments in this experiment. 48

Chapter 2 Individual characteristics and donation behavior participants to a real effort task under four different treatments. The results from this study address the conventional economic assumption that whenever the value of cash donations equals the value of time donations, people are indifferent between giving monetary contributions or the value of volunteer labor to the charity (Andreoni et al. 1996).13 By exposing individuals to different options to donate money or time, we found that participants gave a higher percentage of their earnings when donating money compared to time (Nelson, Schlüter, and Vance 2016). Additionally, matching contributions does not increase the amount given in either case (Nelson, Schlüter, and Vance 2016).

In the present paper, we report on the findings from the second part of the experiment, where we first elicit distributional preferences using the measurement test proposed by Kerschbamer (2010), and subsequently include the preferences revealed in the test as an independent variable in an econometric analysis of donation behavior. In previous lab experiments, Kamas and Preston (2008) found that preferences are heterogeneous and linked to particular patterns of giving. Using a comparable elicitation technique, they found that participants that behave equitably and altruistically give more to charity than do efficiency maximizers or the self-interested. They show a significant price response by altruists and self-interested individuals to matched giving. Similarly, we investigate whether distributional preference categories are reliable indicators for donation behavior.

3.4 Sample participants

Experiments took place in the township of Wanci, on the island of Wangi Wangi in Wakatobi. All 302 participants were from the Bajo community of the Mola village, which is home to the majority of fishermen in the area. Although the Bajo constitute only about 8% of the total population of Wakatobi, they represent key stakeholders as they rely almost exclusively on marine resources for food, building materials, trade, livelihood, and cultural identity. Over fifty percent of the total Bajo Mola population is engaged in fishing as their primary occupation and almost all households depend directly on fishing as a source of livelihood and subsistence. The Bajo settled in the area in 1958 and began to construct huts built on top of coral mined from the

13 Although there is very little cross-over between the literature on managing common-pool resources and charitable giving behavior as both occupy separate niches within economics, they both operate on the same economic theory that people will behave in their own best interest. However, empirical evidence from both disciplines shows that people often behave unselfishly by cooperating to manage common resources and donating to charity. It is my intention to draw these together to show how theories and methods from charitable giving research can be applied to common pool resource problems and potentially increase collective behavior. 49

Chapter 2 Individual characteristics and donation behavior nearby reef. With a population of 6,336, this is the largest settlement of Bajo people in Indonesia. At present, with the concrete roads and cement homes in the main area of the village, it is often times difficult to tell that the village is built upon reclaimed land (see Figure 14).

Figure 14 Bajo Mola house built upon reclaimed land from coral mined from reef flats. Photo credit: Katie Nelson (2015).

3.5 Study design Participants were recruited by a hand delivered invitation letter indicating the date and time of a session. Every house received an invitation, and approximately one-third of households from the village participated. Men preferred to participate in sessions with other men and the same was true for women. Therefore, we divided the sessions by gender and would invite only women or men to participate at certain times. The socio-demographics of the sample are in line with the average population socio-demographics for gender, occupation, and education level, suggesting that the sample is broadly representative of the economically active population.

The study was designed in two parts, where the first part featured four experimental treatments: Donation, Donation Match, Volunteer, and Volunteer Match and the second part involved a demographic survey and elicitation of distributional preferences.

Chapter 2 Individual characteristics and donation behavior

In all treatments, respondents performed the same effort task over a one-hour period and were offered the same choices for charities. Participants earned any money they donated to charity rather than receiving it as an endowment. This design allows for comparison between the Donation and Volunteer conditions, where participants can choose to work directly for charity, which would not be possible with an endowment. In addition, working for earnings and deciding what amount of time or money to allocate to charity more accurately resembles real-life behavior than a windfall endowment.

Participants were provided with a list of six charities and their missions (see Appendix D). The order of the charities was randomly determined to avoid any bias from anchoring effects. Participants were instructed to select one charity from the list and at this time they were informed that they would have an opportunity to donate some of their earnings to the selected charity. They were assured that a donation was not a requirement but was their choice and any donations would be sent to the charity within 90 days. Following the standard protocol of other charitable-giving studies, we provided participants with several options for charitable causes so as to increase the likelihood that each participant would find at least one cause they would consider supporting (Brown, Meer, and Williams 2013, Gallier, Reif, and Römer 2014).

The charities were selected based on interviews with key informants and locals to determine a selection of local and national charities that most participants would find worthy of supporting. We specifically chose charities that represented a wide range of causes to encourage charitable giving. This allowed for the possibility to measure charity choices based on distributional preference type. There were three local-level charities and three national-level charities representing marine/environmental conservation, rural potential, and religious activities respectively.

3.6 Part One: Real effort task and Donation Decision

Participants were given one hour to roll paper beads. This type of task was chosen because it does not require any prior knowledge; it is simple and easy to teach to a person of any education level or age; and it does not require any particular skill that would give any person an advantage over another. For a full description of instructions, please see Appendix C.

Chapter 2 Individual characteristics and donation behavior

Participants were informed that they would be paid 1000 Indonesian Rupiah (IDR)14 for each bead completed. Once the hour was finished, participants stopped the task and set aside their collection containers of their beads. One-by-one, participants brought their bead containers to a discreet area where the beads were counted and the respondent was paid privately in cash.

3.6.1 Experimental Treatments

The first part included four treatments to determine the effects of contributions of time versus money and how matching offers effect these contributions.

3.6.1.1 Donation

The Donation treatment reflects a condition in which agents work to earn money for themselves, receive their pay, and then decide how much of a donation to make to charity. At the end of the sixty minutes, participants were paid in cash15 for the completed beads into an envelope with their name on it. Each participant had another envelope with the name of the charity they selected and were allowed to make their donation decision discreetly in a private room and seal both envelopes before returning to complete the second part of the experiment.

3.6.1.2 Donation Match

The only difference in the Donation Match treatment is that participants are informed that any amount that is donated to their charity will be equally matched so that double the amount will go to the charity of their choice.

3.6.1.3 Volunteer

The Volunteer treatment represents an agent’s choice between having their effort accrue to their own earnings or to the charity of their choice. Each person had the choice between depositing each completed bead into the work-for-self container or the volunteer-for-charity container. Participants were instructed to place each bead as it was completed into one of the containers. The containers were visible to participants but were hidden from view of others during the course of the experiment by a cardboard box. Participants were told that they would be paid in cash for the value of their work that was allocated to the collection container for themselves and the

14 European Central Bank exchange rate 7 October, 2015 is EUR 1 = IDR 15,492.07. Therefore, 1000IDR is equivalent to 0.07€. 15 The cash payment always included several bills of differing amounts (bills ranged from 1000, 5000, 10,000 and 20,000 depending on the total payment) so the participant could make any combination of donation they liked. 52

Chapter 2 Individual characteristics and donation behavior charity they chose would receive the value of their labor for the beads they put into the container labeled “charity”.

3.6.1.4 Volunteer Match

The only difference in the Volunteer Match treatment is that participants are informed before the task began that the value of their time (measured in the number of beads made for their charity) will be equally matched so that double the amount will go to the charity of their choice.

3.7 Part Two: Distributional Preferences Elicitation Task

Following the protocol developed by Kerschbamer (2010), each participant was subjected to a randomized series of ten binary choices between allocations that both involved a payoff for the decision maker and a payoff for a randomly matched anonymous second participant (see Figure 15). We used the double-role-assignment protocol, where each subject makes ten decisions. After the experiment was completed, each subject received two randomly chosen payoffs – one based on their decision as the active person and one as a passive person based on the results of another anonymous participant (Kerschbamer 2015). In each of the ten binary choices, one of the two allocations was symmetric (i.e., both people get equal amounts), while the other decision was asymmetric – involving unequal payoffs. Left Your choice Right You get They get You get They get Disadvantageous inequality block*

1) 8.000 13.000 Left Right 10.000 10.000

2) 9.000 13.000 Left Right 10.000 10.000

3) 10.000 13.000 Left Right 10.000 10.000

4) 11.000 13.000 Left Right 10.000 10.000

5) 12.000 13.000 Left Right 10.000 10.000

Advantageous inequality block

1) 8.000 7.000 Left Right 10.000 10.000

2) 9.000 7.000 Left Right 10.000 10.000

3) 10.000 7.000 Left Right 10.000 10.000

4) 11.000 7.000 Left Right 10.000 10.000

5) 12.000 7.000 Left Right 10.000 10.000 Figure 15 Choices in the distributional preferences elicitation task *The asymmetric options were not labeled as ‘disadvantageous’ and ‘advantageous’ inequality blocks for participants, nor were they ordered from smallest to largest as seen in the figure above.

Chapter 2 Individual characteristics and donation behavior

As described in Balafoutas, Kerschbamer, and Sutter (2012), on the left-side asymmetric allocation options, half of the options involve a higher payoff of 13.000IDR for the other person while the payoff of the decision maker increased from one option to the next in 1.000IDR increments from 8.000IDR in the first choice to 12.000IDR. The other half of the asymmetric options involve a lower payoff of 7.000IDR for the other person while the payoff of the decision maker increases from one option to the next in 1.000IDR increments from 8.000IDR to 12.000IDR. In each of the two blocks, a decision maker is considered rational if their behavior is consistent with switching at most once from the symmetric (right-side) to the asymmetric (left- side) allocation (and never from Left to Right) (Balafoutas, Kerschbamer, and Sutter 2012).

Following the characterization rules from Balafoutas, Kerschbamer, and Sutter (2012), a subject who displays benevolent preferences, will switch to the left-side asymmetric option by no later than the third choice in the disadvantageous inequality block (see Figure 16). A person who switches to the asymmetric choice later than the third choice in the disadvantageous block is inconsistent with benevolence (and therefore counted as malevolence here). In the advantageous inequality block, a person with benevolent preferences will switch to the asymmetric option for the first time in the fourth choice or later. And those that switch earlier than the fourth option in the advantageous block are also inconsistent with benevolence. We use the following names for the four categories: decision makers who are benevolent in both domains are called benevolents; decision makers who always choose the symmetric option are called egalitarians; decision makers who are malevolent in both domains are called malevolents; and decision makers who are malevolent in the disadvantageous block, but benevolent in the domain of advantageous inequality, are called own-money-maximizers (see Figure 16 for a visual depiction). Approximately 10% of our sample makes choices that are not consistent with rational behavior in the distributional preferences elicitation task. Rather than drop them from the analysis altogether, we include them under the name of unclassified.

Chapter 2 Individual characteristics and donation behavior

Figure 16 Characterization of distributional preference types Note: Strongly benevolent types select left before the third line in the disadvantageous inequality block and strongly malevolent types select the left option before the third line in the advantageous inequality block and may select all right options in the disadvantageous inequality block.

3.8 Results

As shown in Figure 17, 4.7% of the sample is categorized as benevolents, 35.7% are categorized as egalitarians, 27.5% are malevolents, and 22.2% are own-money-maximizers. Figure 17 also shows that a high percentage of participants in our sample donate some amount to charity. Almost half of the non-donors are in the malevolents category.

Percentage of sample by preference type 40% 35% 30% 25% 20% 15% 10% 5% 0% Benevolents Egalitarians Malevolents Maximizers Unclassified

No Donation Donation

Figure 17 Percentage of distributional preferences by type and binary donation decision

Chapter 2 Individual characteristics and donation behavior

From Table 6 we can see prominent differences in the mean giving amount between the distributional preference types. Individuals with malevolent and own-money-maximizing preferences give the lowest amount of income to charity, both averaging around 4000IDR, while those with egalitarian preferences average 6000IDR, and those with benevolent preferences average 10000IDR. In Table 6, a multiple comparison of the means across the preference categories using the Bonferroni correction for multiple comparisons, we find significant differences between the amount donated by benevolents and egalitarians (p=0.008) and also between benevolents and malevolents (p=0.003). Additionally, there are significant differences between benevolents and maximizers (p=0.001).

Table 6 Comparison of mean giving across distributional preference types

Average giving across distributional types

Average donation Average donation Percent donating (conditional on giving)

Total mean 5338 88% 6038 N 302 302 267

Benevolents 10000a 86% 11667a (13144) (13527)

b b Egalitarians 5935 96% 6163 (5374) (5347) b b Malevolents 4434 80% 5576 (4612) (4513) b b Maximizers 4179 87% 4828 (3133) (2860) ab ab Unclassified 6100 90% 6778 (5033) (4846) Superscripts with different letters are significantly different from each other at p<0.01 using a One-way analysis of variance test with Bonferroni correction for multiple comparisons. Donation amounts are in Indonesian Rupiah (1000IDR=0.07€). Standard deviation in parentheses.

Similar studies examining distributional preferences observe strong gender differences across preference categories in relation to behavior in labor market tasks (Balafoutas, Kerschbamer, and Sutter 2012) and trust games (Kamas and Preston 2015). We do not observe significant differences in the percentage of males and females composing the preference types using a Chi

Chapter 2 Individual characteristics and donation behavior

square test (p = 0.60) (Figure 18a) or in the percent of males and females that make a donation (Figure 18b). However, there are differences in the mean donations between males and females, but statistical significance is only seen in the egalitarian (p=0.0021) type category (Figure 18c). Although the mean giving between male and female benevolents appears to be vastly different, the variance is large and therefore we do not observe significance.

18a) Gender representation by type 18b) Percent of females and males donating 60% 100%

50% 80% 40% 60% 30% 40% 20% 10% 20% 0% 0%

Male Female Male Female

18c) Average amounts donated by gender 16000 14000 13500 12000 10000 8000 7312 * 7308 5333 5177 6000 4691 4811 4149 4171 4000 3400 2000 0 Benevolents Egalitarians Malevolents Maximizers Unclassified Male Female

Figure 18 Analysis of distributional preferences by gender

Note: *denotes statistical significance at p<0.01 using a two-tailed t test. Donation amounts are in Indonesian Rupiah (1000IDR=0.07€).

6c) To assess whether these findings are robust to the inclusion of control variables, we now analyze these descriptive results econometrically using a two-stage procedure originally developed by Cragg (1971), sometimes referred to as the two-part model. The first stage employs a probit 57

Chapter 2 Individual characteristics and donation behavior model to identify what factors determine why people donate in the first place, while the second stage employs an ordinary least squares (OLS) regression to identify what factors determine how much they donate - among those who donated a positive amount. Of particular interest are the estimates on the dummy variables indicating the treatments as well as the distributional preference types.

The model additionally includes a suite of socioeconomic variables to control for age, education, gender, and income. Age and education are measured in years while gender is measured with dummy variable indicating females. Income is measured with two dummy variables indicating low and medium income households (high income is the base category). Given the nature of a subsistence fishing economy that ebbs and flows with the seasons and availability of fish, average income can be difficult to determine. Therefore, we employed a three-part question that asked for the lowest household monthly income earned and how many months per year this amount is expected, the highest monthly income earned and how many months, and the normal monthly income earned. This allowed us to calculate an estimated annual income. We then divided the sample into three income categories – low income, middle income, and high income. Those in the low income category earn less than the equivalent of 695€ per annum or less than 2€ per day. The middle income earns between 695€ - 3,095€ per year or between 2€ - 8.50€ per day. And the high income category earns over 3,095€ per year.

Referring to the first column of estimates in Table 7, we start by analyzing a parsimonious probit model that excludes the distributional preferences to see if any of the other variables explained by previous literature are relevant. Neither the demographic variables nor the treatments are seen to be statistically significant determinants of the discrete donation decision. The model in the second column includes the dummies indicating distributional preference type. With egalitarian serving as the base category, two of these dummies have negative and statistically significant coefficients, those indicating malevolents and own-money-maximizers. We thereby find that individuals that respond with malevolent and own-money-maximizing payoff decisions in the distributional preferences elicitation task are less likely to donate anything at all to charity than those with egalitarian preferences. Moreover, a Wald test indicates the four dummies to be jointly statistically significant, while a likelihood ratio test indicates that they significantly improve the fit of the model at p=0.01.

Chapter 2 Individual characteristics and donation behavior

Table 7 Probit and Ordinary Least Squares Regression Table

Probit: Probit: OLS Regression: OLS Regression: Independent Variables Binary donation Binary donation Amount Donated Amount donated decision decision N 302 302 267 267 Age -0.015 -0.014 0.001 0.001 (-1.71) (-1.61) (0.13) (0.21)

Female -0.016 0.024 -0.054 -0.039 (-0.08) (0.11) (-0.59) (-0.43)

Education -0.040 -0.038 0.090 0.078 (-0.60) (-0.54) (3.05)** (2.64)** Low income 0.311 0.265 -0.014 -0.025 (0.94) (0.80) (-0.08) (-0.15)

Mid income 0.292 0.235 0.025 0.015 (0.89) (0.71) (0.14) (0.09) o.Hi income 0.000 0.000 0.000 0.000 o. Donation 0.000 0.000 0.000 0.000 Donation match 0.402 0.357 -0.301 -0.292 (1.41) (1.22) (-2.45)* (-2.39)*

Volunteer -0.110 -0.120 -0.630 -0.659 (-0.44) (-0.46) (-4.96)** (-5.23)** Volunteer match 0.461 0.507 -0.675 -0.710 (1.59) (1.63) (-5.50)** (-5.83)** Unclassified -0.506 0.072 (-1.25) (0.48)

Benevolents -0.643 0.494 (-1.29) (2.27)*

Malevolents -0.957 -0.071 (-3.38)** (-0.64) Maximizers -0.718 -0.197 (-2.33)* (-1.68) o. Egalitarians 0.000 0.000 _cons 1.402 2.007 9.220 9.298 (2.55)* (3.32)** (34.34)** (34.20)** R2 0.16 0.20 z statistics in parenthesis; * p<0.05; ** p<0.01

The latter two columns of Table 7 present the estimates from the OLS model of the amount donated, conditional on having donated some positive amount. We accommodate non-normal errors with a transformation on the dependent variable. Following Yen, Boxall, and Adamowicz (1997), we use the inverse hyperbolic sine transformation of the dependent variable. The transformation ensures robustness to non-normality (Brown et al. 2015), is scale invariant, and is

Chapter 2 Individual characteristics and donation behavior known to be well suited for handling extreme outliers of the dependent variable (Burbidge, Magee, and Robb 1988).

The parsimonious model in the third column reveals that the level of education of an individual has a significant and positive effect on the donation amount, while the donation match, volunteer, and volunteer match treatments all have negative effects relative to the base category of donation. Income, age, and gender do not have any significant effect on the amount that is donated. These findings are contradictory to other donation studies that show that women are more likely to donate than men (Lee and Chang 2007, Wiepking and Bekkers 2012, Kamas and Preston 2015, Simmons and Emanuele 2007), and that higher income has a positive effect on the donation amount (Bryant et al. 2003, Clotfelter 1997, James and Sharpe 2007, Wiepking and Bekkers 2012, McClelland and Brooks 2004). Including the distributional preference types into the regression model in column four significantly improves the fit of the model at p=0.03 using the Likelihood Ratio Test. The inclusion of the dummies indicating preference type in the final column has little bearing on the estimates on the control variables; their magnitude changes only marginally. Participants with benevolent distributional preferences donate more than any other preference category (p<0.05), while those with malevolent and maximizing preferences do not have a significant effect compared to individuals that respond with egalitarian preferences.

Analyzing the correlates of distributional preference types using a multinomial logistic regression reveals few differences between the psychographic types. The only demographic variable determining membership into a distributional preference category is that benevolents have higher levels of education. We have graphically displayed the choice of charities by distributional preference type using pie charts (Figure 19). Benevolents most often choose Islamic Relief Worldwide, a religious aid organization, and TERANGI, the coral reef conservation charity. Own-money-maximizers show a preference for TERANGI and all local charity organizations (seemingly regardless of their mission) – Sintesa, Karang Taruna, and Nahdlatul Ulama. The egalitarians and malevolents appear to have less discretion overall for the type of charity chosen.

Chapter 2 Individual characteristics and donation behavior

Benevolent Maximizer

Oxfam Oxfam Terangi Terangi Islamic Relief Islamic Relief Karang Taruna Karang Taruna Sintesa Sintesa Nahdlatul Ulama Nahdlatul Ulama

Malevolent Egalitarian

Oxfam Oxfam Terangi Terangi Islamic Relief Islamic Relief Karang Taruna Karang Taruna Sintesa Sintesa Nahdlatul Ulama Nahdlatul Ulama

Figure 19 Choice of charity by preference type

3.9 Discussion

We use a preferences elicitation tool in combination with a donation experiment to disentangle the impact of distributional preferences from that of other variables on the amount that local marine users donate to real public goods. The distribution of preference types found in our sample is rather different from the previous literature. Kerschbamer (2015) observe the most frequent distributional preference types to be benevolents and own-money-maximizers (displaying positive or neutral attitude towards others in both domains) and the least frequent to be egalitarians and malevolents (displaying malevolent preferences in at least one of the domains). Balafoutas, Kerschbamer, and Sutter (2012) found similar results, with 71% of respondents

Chapter 2 Individual characteristics and donation behavior displaying benevolent preferences, 16% and 13% displaying egalitarian and malevolent preferences, respectively. In contrast, we find that a high percentage, 28%, of participants display at least weakly malevolent preferences in both domains (malevolents) and 36% prefer equal payoffs even at a loss to themselves (egalitarians). In stark contrast to other studies, we find a very low percentage (<5%) of participants that display (even weak) benevolent preferences. Just as a reminder, to be considered “benevolent” the individual decides to move from the equal payout option (10.000 for both) to the payout option where she makes the same amount (10.000) but the other participant would earn more (13.000). Although less than 5% of our sample population chose this option, which has no effect on their own pay out, 88% of the total sample gave something to charity. It is noteworthy that the assessment of distributional preferences focuses on allocation of resources between self and another person (rather than a group). This raises questions as to whether the motivations for behaving altruistically towards similar individuals are activated by different mechanisms than the motivations that drive giving to charity. Are these results driven by the difference in giving to individuals versus giving to groups (organizations) or the difference between giving to people similar to you versus the neediness represented by charity? Although we cannot answer what drives this difference from our results, we contribute to the literature on stability of preferences across domains (De Oliveira, Croson, and Eckel 2009, Luccasen and Grossman 2017) and we believe this is an area worthy of further research in understanding motivations across domains.

Of particular interest to environmental resource management, the implications of these results shed light on interpretations regarding giving to public goods based on how individuals behave in experimental games (Schumacher et al. 2016). The context of most experimental social dilemma games generally involves decisions about resource allocation between small groups comprised of anonymous, yet similar or familiar individuals (i.e. university students, or members of the same community/village). Based on the results of the distributional preference task alone, we would have a very different impression of the cooperative nature of our sample. Instead, we observe plenty of people in our sample who behave selfishly, even spitefully, when making choices of how to distribute resources between themselves and anonymous others in the experiment, but then generously contribute to real public goods.

There is strong evidence in the charitable giving literature that ‘warm glow’ giving (i.e. giving to feel good) is a powerful strategy to motivate donors (Andreoni 1990, Brown, Meer, and Williams 62

Chapter 2 Individual characteristics and donation behavior

2013, Crumpler and Grossman 2008) but this discussion does not seem to have garnered much attention in the environmental conservation literature (Hartmann et al. 2017). This is relevant to marine management in that strategies directed to appeal to the sense of ‘warm glow’ and similar motivations can be used to increase conservation participation by local resource-users. This can be achieved through framing marine conservation communications to appeal to ‘warm glow’ or to build upon social norms surrounding the personal benefits of participation and involvement. For encouraging volunteers, identifying the value of an individual’s time contributions to the community can help validate the activities. The organization ‘Rare’ provides interesting examples by focusing their conservation efforts using the principles of social marketing. In a case in Madagascar, they focus on ‘pride in being responsible fisherman’ in much the same way we are advocating to focus on the moral satisfaction gained from prosocial behavior (Andriamalala et al. 2013). Following the scientific trend towards integration, just as marine protected areas require inclusion of local resource-users in management (Oracion, Miller, and Christie 2005, Christie and White 2007), we suggest putting the resource-users and their needs at the center of the local conservation campaign messaging and goals.

Controlling for other factors, the behavior of individuals in the distributional preferences elicitation task is highly indicative of whether an individual will decide to donate any amount. As intuition would suggest, and as is confirmed by the results, those individuals that display own- money maximizing and malevolent behavior are less likely to donate any amount at all. However, once they decide to donate (and many do), there is no significant difference between them and the egalitarians in the amount they donate. This is an important contribution to the literature on giving to environmental goods. If self-interested people can be motivated to give, perhaps by appealing to their interests, they will give generously.

The importance of this study is to shed light on the relationship between distributional preference types and donation behavior. We find that even though malevolents and own-money maximizers are less likely to donate than egalitarians, many of them are still giving to charity. There is a plethora of literature showing that selfish motivations drive free-riding behavior but there is also considerable evidence to support that selfish motivations, such as moral satisfaction or feeling good (‘warm glow’), motivate giving to public goods (i.e. charity). We recommend practitioners apply the ‘warm glow’ theory from charitable giving literature to encourage people to locally provision public goods by voluntarily contributing to conservation. Moving toward more rigorous 63

Chapter 2 Individual characteristics and donation behavior experimental field methods to document, measure, and evaluate changes in attitudes and behavior provides us with a better understanding of individual decision-makers, and ultimately helps policy makers to design more effective interventions aimed at increasing both the likelihood that an individual will contribute and the amount they will give.

3.10 Conclusion

Our results suggest that distributional preferences are an important explanatory control variable for donation behavior. Conservation appeals should take into consideration the psychographic characteristics of the community addressed when focusing on motivating local resource users. Specifically, the issue should be explored of whether different kinds of approaches might be more or less effective at engaging different segments of the population in conservation. Thus further investigation is needed, not into segmentation for different types of charities but into the scope for segmentation for different types of engagement techniques (Schlegelmilch and Tynan 1989). In the community studied in this research, a message reinforcing the personal benefits to resource-users (i.e. increased moral satisfaction, ‘warm glow’ feeling, pride for sense of responsibility, etc.) would capture a large percentage of the intended audience. This could be a useful insight in crafting communications on environmental impacts and benefits for marine resource users. Additionally, this research helps to bridge the gap between the research on open- access resource management and charitable giving by using experimental methods that reveal the factors motivating collective behavior among resource users.

Chapter 3 4 Soliciting voluntary user fees

Extending the scope of voluntary marine park user fees to terrestrial conservation across coupled land-sea ecosystem boundaries

Nelson, K. M., Partelow, S. Schlüter, A. *Submitted January 20, 2018. Journal of Environmental Management. In review.

4.1 Introduction

Coastal and near shore marine areas are invaluable to humankind. The coastal zone is generally accepted as the land-sea interface extending from the inland margin of the coastal plain to the continental slope waters offshore. This region, although it represents less than 10% of the earth’s surface, is home to over 40% of the world’s human population (CIESIN 2013), is as biologically diverse and productive as any system on Earth, and supports viable economic activities from fisheries to mining to tourism (Adger et al. 2005, Kummu et al. 2016, Moberg and Folke 1999). Despite global recognition of the importance of coastal ecosystems, they are often overexploited and misused (Cloern et al. 2016, Jackson et al. 2001). The unsustainable use and degradation of marine and coastal ecosystems threatens human development and well-being. These threats are driven by proximate local to regional human activity such as overfishing, pollution, and development. Simultaneously, distal anthropogenic stressors from climate change are threatening coastal systems with rising ocean levels, increased ocean temperatures, ocean acidification, and increased severe weather events (Cloern et al. 2016). Holistic and appropriately funded management of coastal systems that can account for the variety of human activities occurring on land and at sea is a key determinant in the resilience of an area to withstand stress and recover from threats (Dutra et al. 2015).

4.1.1 Management across land-sea ecosystem boundaries

Threats across coupled boundaries are pervasive in most coastal ecosystems, making their consideration essential for successful management. There has been a push for more integrated conservation management across land-sea ecosystem boundaries in the last decade; however,

Chapter 3 Soliciting voluntary user fees there are few examples of land-sea conservation projects in practice (Alvarez-Romero et al. 2011, Pittman and Armitage 2016, Reuter, Juhn, and Grantham 2016). Tallis, Ferdana, and Gray (2008) concede that if conservation planning ignores cross-system interactions it may (unintentionally) leave populations and ecosystems at high risk from external threats. Effective management can generate significant gains in environmental conservation, however, lack of funding to enforce regulations is a common issue shared across many protected areas throughout the world (Lundquist and Granek 2005, Rife et al. 2013). Additionally, the link between terrestrial-to-marine conservation and regulation is often non-existent (weak at best), even though many stressors faced by marine ecosystems are generated on land, such as sedimentation from land erosion, and pollution from waste run-off (Álvarez‐ Romero et al. 2013, Partelow, von Wehrden, and Horn 2015, Reuter, Juhn, and Grantham 2016, Roberts et al. 2002).

Generally speaking, the most vulnerable coastal systems tend to be in densely populated and poor countries in the tropics. According to the IUCN (2017), three quarters of the world’s population living in vulnerable coastal zones call Asia home. Many of these people live on coastlines of the Coral Triangle, depending on healthy coastal ecosystems for their survival. Coastal ecosystems within the Coral Triangle such as coral reefs, mangroves and seagrass beds provide food, building materials, coastal protection, industries such as fishing and tourism, and many other benefits for millions of people (Hoegh-Guldberg et al. 2009). However, tropical coastal research does not emphasize its research focus on all ecosystems and human impacts equally, with considerable gaps on social-ecological interactions and land-sea connectivity (Glaser et al. 2012, Partelow, Schlüter, von Wehrden, et al. 2017).

Indonesia, situated at the center of the Coral Triangle, represents some of the highest levels of marine biodiversity and is considered a strategic area for marine conservation efforts by international organizations such as The Nature Conservancy, Conservation International, and the World Wildlife Fund. Gross domestic product (GDP) from coastal- and marine-based tourism in Indonesia is increasing each year, suggesting that the economic incentives for conservation are becoming progressively more important for the national and local economy. Tourism helps to diversify local economies away from exploitation of natural resources. Ironically, the characteristics of pristine nature that attract tourists are also the most impacted by the unchecked growth in development (Arkema et al. 2015, Hampton and Jeyacheya 2015). The present state of

Chapter 3 Soliciting voluntary user fees coastal ecosystems in Indonesia and the rest of the Coral Triangle is bleak and immediate action is necessary to halt further degradation (Treml et al. 2015). Mobilizing adequate resources and capacity is essential for successful management plans that conserve the ecosystem (Sterling et al. 2017, Whitney et al. 2017).

Marine Protected Areas (MPAs) are the dominant management strategy employed for marine conservation; yet, MPAs rarely incorporate terrestrial-based regulations that have a direct impact on the marine environment (Adams et al. 2014, Gilby et al. 2016, Thur 2010). Additionally, many of these parks exist mostly as ‘paper parks’16 due to a lack of proper planning (Halpern 2014) and funding (Gelcich et al. 2013, Terk and Knowlton 2010). Some exceptions exist, including Komodo National Park where both terrestrial and marine resources are a major attraction for visitors, but generally terrestrial conservation issues are left out of MPA planning. Establishing MPAs for coral reef ecosystems brings additional challenges as the majority of the world’s reefs are situated off coasts that are often characterized by high growth rates, intense development for tourism, weak state governance institutions, and a lack of sufficient funding for conservation.

4.1.2 Financing management through user fees

The management of MPAs can be financed through a combination of instruments, including government support, donor funding, and user fees. Due to insufficient and uncertain long-term funding for marine conservation, self-financing mechanisms that augment other types of funding are popular in protected areas (Gelcich et al. 2013, Nelson, Schlüter, and Vance 2017b). For example, environmental user fees are widespread across terrestrial National Parks to fund conservation (Bernard, de Groot, and Campos 2009, Dharmaratne, Sang, and Walling 2000). Marine Protected Areas that are frequented by divers, wildlife enthusiasts, travelers, and recreational anglers have also generated considerable income through user fees (Edwards 2009). However, marine park user fees are often imposed on one type of user (i.e. divers, whale watchers, etc.) and rarely incorporate a universal fee across multiple use types, including passive use (i.e. people staying in nearby hotels, golfers, beach-goers, and others that may not directly

16 The term "paper park" is defined as, "a legally established protected area where experts believe current protection activities are insufficient to halt degradation." (Dudley and Stolton 1999)

Chapter 3 Soliciting voluntary user fees enter the marine space). The terrestrial coastal area of marine parks cannot be de-coupled from the sea area of the marine park. Expanding fees to all users is particularly important on many small island destinations as they transition from mostly marine-focused tourism to multiple-use tourism (Partelow and Nelson forthcoming).

Understanding how users value ecosystem services and benefit from ecosystem quality enables fees to reflect user preferences (Arkema et al. 2015). Few studies, however, have attempted to measure user preferences across ecosystem boundaries (Dharmaratne, Sang, and Walling 2000, Gelcich et al. 2013). One exception is a recent publication by Roberts, Hanley, and Cresswell (2017) which focuses on understanding divers’ willingness to pay a user fee for terrestrial biodiversity conservation in connection to an MPA and linked marine conservation. However, focusing solely on diver willingness to pay ignores the large and important population that frequent coastal travel destinations and impact the ecosystem considerably – all the other users that travel to the destination but may not dive. An area that hasn’t received much attention in the literature is the scope for soliciting marine park user fees from all visitors regardless of their use- type based on the premise that all visitors to the area use and impact the coupled land-sea ecosystem boundaries and should therefore contribute to its maintenance. The concept of a designated park area imposing fees on all visitors regardless of use-type is not unique and is used extensively for terrestrial areas, such is the national park model. However, this is much less common in marine park areas and is especially important to consider as an area develops and transitions from mostly marine-focused tourism that can be sustained by single-use fees (i.e. diver fees) to multiple-use tourism as non-divers far outnumber divers (Partelow and Nelson forthcoming).

Contingent valuation studies are widespread and well accepted in determining the willingness to pay for park fees (Asafu-Adjaye and Tapsuwan 2008, Mathieu, Langford, and Kenyon 2003, Peters and Hawkins 2009, Togridou, Hovardas, and Pantis 2006). However, these studies rarely focus on the method of asking for payment which can have a strong influence on effectiveness of payment systems. This is especially important when the user fees are voluntary payments (Dharmaratne, Sang, and Walling 2000, Rivera-Planter and Muñoz-Piña 2005, Stithou and Scarpa 2012). Many protected areas function without formal governance wherein community- based institutions lead conservation efforts and require funding to do so (Alexander, Andrachuk, and Armitage 2016, Maliao, Pomeroy, and Turingan 2009). This funding can come from

Chapter 3 Soliciting voluntary user fees voluntary donations for use of protected areas (Alpizar, Carlsson, and Johansson-Stenman 2008). Understanding human behavior in relation to voluntary fund raising or payments for environmental use is important to determine the most effective way to request a donation and how much to ask for (i.e. reference amounts) which affects total contribution amounts. There is a need for more studies that provide empirical evidence of voluntary contributions for environmental conservation, and from the broader social sciences to better understand human dimensions of marine and coastal management (Bennett et al. 2017, Chan et al. 2007). Behavioral field experiments provide a powerful methodological tool to vary the donation conditions using controlled methods with actual users and real payments to observe the variation in and degree of participation in fundraising schemes.

The purpose of this research is to gather evidence for the most effective method to solicit voluntary contributions from tourists to support land-sea conservation in MPAs which struggle to finance community-based efforts. This study provides practical results for how to increase conservation financing, with direct implications at a local-level and at a broad scale. Using a case study in Indonesia, we provide a novel examination of voluntary land-sea conservation financing through engaging all types of users visiting a small tropical island. A natural field experiment reveals price preferences under four treatments based on real contributions to a conservation organization. The treatments have been designed based on the literature that empirically investigates methods for encouraging pro-social behavior, such as charitable donations and organ donations (Bekkers and Wiepking 2011, Johnson and Goldstein 2003, Johnson, Bellman, and Lohse 2002, Johnson and Goldstein 2004, Briers, Pandelaere, and Warlop 2007). To the authors’ knowledge this is the first record of such combination of treatments being used in soliciting contributions for environmental conservation. Each participant was exposed to one of the four treatments displayed in Table 8. The results provide evidence for an acceptable donation amount to inform the implementation of a tourist eco-fee and the best method to introduce this fee to encourage the highest amount of total contributions. Although the amounts are case specific, the treatments are generalizable given the variation indicating differences in solicitation success.

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Table 8 Field experiment treatment conditions and descriptions Treatment Description Control Open-ended write-in amount Reference price levels Choice of four suggested contribution amounts or write-in Default opt-in Check box to contribute set amount Default opt-out Check box NOT to contribute set amount

4.2 Fundraising Literature Review

When faced with a request for donation, typically two decisions are made. A person must decide whether to donate at all, followed by the decision about the amount to be donated. The effectiveness of any campaign to solicit voluntary contributions depends upon the ratio of those giving as well as the magnitude of the donations (De Bruyn and Prokopec 2013). Many mechanisms can influence the ratio and magnitude of donations (Bekkers and Wiepking 2011). We use the assimilation–contrast theory (Sherif, Taub, and Hovland 1958) and heuristic decision making (Gigerenzer 2008) to establish predictions about the effects of the treatment conditions. The assimilation-contrast theory states that individuals evaluate a new stimulus using a reference point that is based on other experiences. An amount that is close to their reference point is then accepted, whereas an amount that is far from their reference point is rejected. Thus, a donor decides to donate depending on whether she finds the suggested amounts acceptable or not (De Bruyn and Prokopec 2013). Similarly, heuristic decision making employs the concept that less can lead to more and, in this case, less thinking about giving leads to more giving. Providing a set default donation amount removes the need to decide how much to give and situating the amount close to a widely accepted reference point will lead to more people accepting the request (Gigerenzer 2008).

4.2.1 Open-ended condition (Control)

The control condition is an open-ended approach which requires the participant to write-in an amount they will pay for the eco-fee. Cooperating participants then actually donate their own money as an eco-fee. Although the open-ended write-in method has been criticized in hypothetical willingness to pay studies (Donaldson, Thomas, and Torgerson 1997, Arrow et al. 1993), it is a widely used and accepted method in understanding valuation and it has been shown

Chapter 3 Soliciting voluntary user fees to be ‘valid’ in terms of the relationship of WTP to prior preferences and to factors indicative of ability to pay, such as income (Bateman, Willis, and Garrod 1994, Loomis 1990). Additionally, open-ended valuation method surveys combined with real contributions reduce strategic bias overcoming many of the cognitive limitation problems noted in the literature, including anchoring bias (Prince et al. 1992).

4.2.2 Reference price levels

A standard practice in donation requests is to present a set of suggested amounts, sometimes referred to as ‘anchors’, ‘reference levels’, or ‘close-ended’ (Briers, Pandelaere, and Warlop 2007, Smith and Berger 1995). Anchoring is a well-known cognitive bias that affects decision making based on a heavy reliance on the information offered (Van Exel et al. 2006). Affecting donation amounts through the use of different reference levels is an extremely robust phenomenon that appears in many contexts (De Bruyn and Prokopec 2013). Tversky and Kahneman (1975) suggest that people are influenced by the presentation of specific values, or reference levels, to help make decision judgments. They noted that people make heuristic judgments relative to specific reference points to reduce decision processing and mental effort. Brockner et al. (1984) found that when a specific dollar amount was mentioned in telephone and face-to-face fundraising, subjects were more likely to comply and make a pledge than when no amount was mentioned. Alpízar and Martinsson (2010) found that exposing potential National Park donors to donation amounts of other visitors significantly increased the number of donors, but did not increase the average individual gift compared to the control. Total average donations increased due to the increase in share of donors. This is consistent with the conceptualization that suggested reference points serve as decision heuristic anchors that allow donors to quickly infer a range of reasonable gift amounts. Hence we propose that the presence of reference levels will yield a greater ratio of donors compared to the control (H1) but there will be no difference in the average amounts donated between the reference and control treatments (H2) (see table 9).

4.2.3 Default amount and opting-in versus opting-out

Default amounts act as single reference points, compared to the previous option where participants receive a variety of recommended amounts. In direct marketing fundraising, it is generally accepted (Brockner et al. 1984) that asking for a specific amount results in increased cooperation compared to not mentioning an amount.

Chapter 3 Soliciting voluntary user fees

If transaction costs are small, standard economic theory would suggest that defaults should have little impact on economic outcomes. People with well-defined preferences will opt-out of any default that does not maximize their utility, regardless of the nature of the default. In practice, however, defaults can have quite sizeable effects on economic outcomes. For example, switching from a non-participation default (opt-in) to a participation default (opt-out) can increase retirement saving participation rates by more than 50 percentage points (Choi et al. 2003, Madrian and Shea 2001). This property of default options has been documented in a wide range of other settings: organ donation decisions (Abadie and Gay 2006, Johnson and Goldstein 2004), public goods (Altmann and Falk 2009), car insurance plan choices (Johnson et al. 1993), car option purchases (Park, Jun, and MacInnis 2000), and consent to receive e-mail marketing (Johnson, Bellman, and Lohse 2002).

Hence we propose that the ratio of donors will be higher in the opt-in default treatment compared to the control (H3). And the opt-out default treatment will generate a higher ratio of donors than the opt-in default (H4) (see table 9).

Table 9 Hypotheses

H1 The proportion of donors will be higher with the presence of reference levels compared to the control.

H2 There will be no difference between the average amount donated in the reference level and control treatments. H3 The proportion of donors will be higher in the opt-in default treatment compared to the control.

H4 The proportion of donors will be higher in the opt-out default treatment compared to the opt-in default treatment.

4.3 Materials and methods

4.3.1 Study location

In choosing a location to study the willingness to pay a user fee for coupled land-sea ecosystem conservation, we selected a site with high marine biodiversity and multiple-use criteria in a limited area with clear boundaries and threats (Groves et al. 2000, Margules and Pressey 2000, Tallis, Ferdana, and Gray 2008). The Gili Matra Marine Park is comprised of three islands lying just off the Northwest coast of Lombok, Indonesia with Bali to the west (see Figure 20). The islands are situated in the ‘Indonesian Through flow’ (see Figure 20b). This is an ocean current

Chapter 3 Soliciting voluntary user fees

pathway that connects the Pacific to the Indian Ocean and hosts an immense amount of biodiversity.

Figure 20: (a) Map of Indonesia with Coral Triangle highlighted in blue and Bali and Lombok area circled in black, (b) Bali Gili Islands circled and Indonesian Throughflow marked, (c) map of Gili Islands and Gili Matra Marine Park Bali highlighted. Source: Google (2017).

The study took place on Gili Trawangan, the largest and most populated of the three Gili Islands (Figure 20c). The island receives heavy tourist traffic, up to 2000 new visitors per day and approximately one million tourists visit annually. Although the island is only six square kilometers, it has more than 750 businesses and is the most the most developed of the three islands. The Gili Islands have long been a backpacker destination, and over the last decade the islands have grown into a major destination for tourists of all budgets and interests. Gili Trawangan is the second most frequented destination in South East Asia for scuba diving certification (second only to Koh Tao in Thailand). The increase in tourism is resulting in rapid development, challenging the infrastructure on the island to keep up with the growth (Partelow and Nelson forthcoming). All food, drinks, consumable goods, and amenities must be imported and the daily waste generated by the thousands of tourists, restaurants, hotels, dive shops, and other businesses remains on the island and ends up in the landfill. The landfill is currently far over capacity with no current plans by the local government to address waste reduction, develop collection or recycling infrastructure or to finance its management. Solid waste pollution and air pollution from burning waste are a major environmental issue for the island and surrounding marine habitat, creating an impending crisis.

Chapter 3 Soliciting voluntary user fees

The marine park does not currently have a government sanctioned fee for entry. At present, an eco-fee is imposed only on divers as a collective agreement between dive shops. Each diver pays a voluntary one-time fee of 50,000IDR (approximately $3.75USD). The fees support the community-based conservation organization, Gili Eco Trust. The Gili Eco Trust is a non- governmental organization (NGO) that was created in 2000 by a group of local dive shops to protect and restore the coral reefs from destructive fishing. At the time it was founded, dynamite and cyanide fishing proliferated and the funds were used to pay for local patrols and reef restoration. Over the years, destructive fishing practices decreased as tourism rapidly increased and environmental threats shifted to terrestrial generated issues such as erosion from coastal development and solid waste pollution.

Although only divers are currently paying for the eco-fee, which represent about 15% of all tourists on the island, all visitors contribute to the impact on the ecosystem and benefit from its quality. Recognizing the waste problem, the Gili Eco Trust expanded their services to land-based conservation through provision of the only sustainable waste management services available on the island. They established a ‘rubbish bank’ which provides payment for selected recyclable waste, thereby creating incentives for properly disposing waste while reducing the environmental impact of waste. Additional services they provide include: training to local businesses on sorting garbage for recycling; distributing recycle bins; collecting recyclables and organic compost; transporting recyclable material off the island; sourcing sustainable materials for local businesses; organizing weekly island clean-ups; and producing communication materials for eco- friendly tourism. Recently, in April 2017, they acted as the de facto waste collection service during a collapse of the local waste company due to allegations of corruption. This much needed transition into land conservation has not been matched by a transition to a universal eco-fee paid by all tourists, which reflects the magnitude of services the Eco Trust now provides beyond the marine realm. Many of the dive shops and hotels are supportive of a universal eco-fee paid by all tourists but there is disagreement on how to implement the eco-fee and how much to charge. This issue motivated the research in this paper.

Chapter 3 Soliciting voluntary user fees

4.3.2 Methods 4.3.2.1 Sampling

There is no central daily record of tourists visiting Gili Trawangan so a random sampling method was not possible. Therefore, a convenience sampling method was employed. This method does, however, capture a representative sample of the tourist population on the island. Tourists gather in the harbor area on Gili Trawangan as they wait for boats departing the island on an hourly basis throughout the day. The harbor area provides the best possibility for a natural semi-random sample. The overwhelming majority of tourists arrive and depart the island from the harbor area (except the few (<1%) that arrive directly to the resort by private boat) representing a wide variety of ages, nationalities, budgets, and interests.

592 tourists were surveyed from March 2017 to May 2017. We partnered with the local NGO, the Gili Eco Trust, to design the survey and recruit research assistants. The trained research assistants would visit the harbor daily to conduct the donation surveys. They identified themselves as students interning at Gili Eco Trust and working on a research project. They notified all people that participation was completely voluntary. If people agreed to participate, they were provided with a survey printed on the front and back of a half sheet of A4 paper (see Appendix F). There was a wooden box painted with the logo of Gili Eco Trust with a slit in the top that the research assistant used to collect the surveys and any donations the participants wished to give to the Gili Eco Trust. Although respondents were aware they were participating in a research study, they were unaware that there were randomly assigned treatment groups. Requests for further information regarding the activities and purpose of the Eco Trust were responded to by providing a pre-printed one-page guide on efforts of the organization to avoid bias in explaining more in-depth to some tourists and not others which might have influenced donations.

4.3.2.2 Survey Design

The survey instrument was refined following exploratory research and open-ended interviews with several hotel and dive managers as well as the staff of Gili Eco Trust providing feedback on the fee amounts and survey questions. In addition, fifty-two pilot surveys were conducted between March 25 and March 30, 2017 enabling further refinement of the questions, survey

Chapter 3 Soliciting voluntary user fees design, and payment amounts. Specifically, we lowered the default amounts from 50,000IDR to 10,000IDR based on feedback from the pilot surveys. To maintain anonymity, no identifying information was collected from participants. The survey instrument was comprised of a combination of multiple choice and questions based on a Likert ordinal response scale. Additionally, basic sociodemographic and travel information was collected.

We employed a between-subjects randomized design meaning that each participant was subjected to only one randomly-selected treatment. There were four treatments which we refer to as: control, reference levels, default opt-in, and default opt-out. The control treatment required the respondent to write-in an amount they wished to contribute to the Gili Eco Trust. Participants that failed to write anything in the control were automatically appointed as giving zero. The reference level condition consisted of three suggested contribution amounts: 10,000IDR, 20,000IDR, 50,000IDR and a blank write-in option. The default was set at 10,000IDR (approximately $0.75USD), informed by our pilot study. The default opt-in required that the participant check the box that they wished to contribute the set amount of 10,000IDR. The default opt-out condition required that the participant check the box if they did not want to contribute the set amount of 10,000IDR.

4.4 Results 4.4.1 Descriptive statistics of sample

The descriptive statistics of the sample population are shown below in Table 10. The sample was comprised of slightly more females (58%) than males (42%). The majority of participants (62%) were from the European continent (including UK and Scandinavia). Sixty-nine percent of respondents were between the ages of twenty-one and thirty-two. The average number of days spent on Gili Trawangan was 4.4 days with a standard deviation of 6.8 and a minimum of one day and maximum of one hundred days. Given the wide range of nationalities traveling to Gili Trawangan, collecting information on monthly or annual income was avoided due to confusion in recording the data based on different currencies that may have been reported. Rather, we use the hotel price and type as a proxy for traveling style and income. The majority of respondents (>65%) stayed in hotels that we have identified as either ‘High-end’ or ‘Luxury’. ‘High-end’ was defined as hotels that cost between 400,000-700,000IDR per night (approximately $30-

Chapter 3 Soliciting voluntary user fees

$50USD/night) and ‘Luxury’ was defined as hotels that cost more than 700,000IDR/night (more than $50USD/night). Only 15% of the total sample went diving on Gili Trawangan which means they would have already paid the 50,000IDR voluntary eco fee for conservation.

Table 10 Descriptive statistics of sample population

Category Descriptor % of sample N 592

Gender Female 58% Male 42%

Nationality Australia/New Zealand 7% Asia (excl. Indonesia) 5% Europe (excl. UK and Scandinavia) 32% Indonesia 8% North American 9% Scandinavia 10% South America 4% UK 20% Other (Africa, Middle East, Russia, India) 5%

Age range 15-20 13% 21-26 38% 27-32 31% 33-40 11% 41-60 7% >61 0.3%

Hotel type Budget ≤120,000IDR/night 1% Inexpensive 121,000-200,000IDR/night 12% Intermediate 201,000-400,000IDR/night 20% High-end 400,000-700,000IDR/night 42% Luxury ≥701,000IDR/night 25%

Marine tourism Divers 15% Snorkelers 67%

Figure 21 shows participants’ responses regarding their perception of who should be responsible for financing conservation on Gili Trawangan, as well as their perceptions of the main problems on the islands. It is clear from Figure 21a that tourists believe the government should take more responsibility in providing environmentally sustainable services on the island, but, interestingly, 23% and 17% respectively of the total responses perceive hotels and tourists should also be responsible for financing environmentally sustainable services. In Figure 21b, waste sorting and recycling garnered the most attention as problems on the island. Pollution was also perceived to

Chapter 3 Soliciting voluntary user fees be a problem on the island, and, if these are combined, waste issues make up 39% of the perceived issues on Gili Trawangan - far more than any other issue. Issues pertaining to terrestrial conservation (including beach erosion, pollution, and waste build-up due to lack of recycling services) make-up 46% of the perceived problems on the island while marine conservation makes up 15% of the perceived problems.

21(a) Who should pay for environmentally 21(b) Tourist Perceptions of Problems sustainable services? Waste sorting/recycling 22% Government 27% Animal Welfare* 18% Pollution 17% Hotels 23% Marine reef restoration 15% Tourists 17% Beach erosion 7% Infrastructure 6% Dive shops 15% No govt involvement 5%

Other businesses 13% Safety/security 4% Corruption 4% Privatize 6% Rules not enforced 2%

Figure 21 Tourist perceptions of 21(a) of who should pay for environmentally sustainable services, and 21(b) problems on Gili Trawangan. Note: *Motorized vehicles are prohibited on the island and therefore traditional horse carts provide transportation and hauling of materials around the island, hence the perception of animal welfare as an issue.

Figure 22 provides descriptive statistics based on tourists’ personal experiences and perceptions of environmental management on Gili Trawangan. Although the overwhelming majority (89%) of respondents had a positive overall experience and would recommend the island to a friend (Figure 22a) most disagreed that the island is environmentally sustainable. Figure 22b shows that more than half of respondents disagreed that the businesses on the island were environmentally conscious offering alternatives to single-use plastic. Sixty-nine percent of respondents disagreed that the current system of waste collection and recycling is functioning (Figure 22c) and 61% disagreed that the streets, beaches, and public areas are clean and free of pollution (Figure 22d). Fifty-seven percent of respondents disagreed that the marine ecosystem and marine pollution are effectively managed compared to the 37% of respondents that agreed the marine ecosystem is effectively managed (Figure 22e). We observe that 77% of participants agree there should be a tourist eco-fee to ensure that environmental sustainability is practiced on Gili Trawangan (22f).

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22(a) Good overall experience/would 22(b) Environmentally conscious recommend to a friend businesses 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Strongly Disagree Neither Agree Strongly Strongly Disagree Neither Agree Strongly disagree agree disagree agree

22(c) Waste collection/recycling 22(d) Streets/beaches/public areas clean

functioning 3c) ) from pollution debris 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Strongly Disagree Neither Agree Strongly Strongly Disagree Neither Agree Strongly disagree agree disagree agree

22(e) Marine ecosystem and pollution 22(f) Tourist eco-fee should be required ) effectively managed 60% 60%) 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Strongly Disagree Neither Agree Strongly Strongly Disagree Neither Agree Strongly disagree agree disagree agree

Figure 22 Perceptions of environmental management and personal experience on Gili Trawangan

4.4.2 Treatment comparisons

We find that the willingness to contribute to the conservation organization increases significantly with the treatments (see Figure 23a). Using a two-sided binomial probability test, the data show that the probability of making a donation is significantly higher at p<0.01 in all treatments (default opt-in, default opt-out, and reference levels) compared to the control condition. When comparing the default options to each other, the opt-out treatment results in significantly higher compliance compared to opt-in (p<0.01). The default opt-in and the default opt-out both have significantly higher compliance rates than the reference level condition (p<0.01).

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Using a Fisher’s exact test, we analyze gender differences in the decision of whether or not to donate under the treatment conditions (see Figure 23b). The ‘reference level’ treatment is the only treatment in which we observe significant differences (p<0.01) between men and women in the decision to donate. Only 24% of females chose to donate under the ‘reference level’ treatment compared to 44% of males that donated. The probability of compliance between females in the control treatment (21%) and the reference level treatment (24%) are not significantly different using the binomial probability test.

23(a) Percent of people that donate 23(b) Percent of donations by gender

68% Female Male

68% 69% 48% 48% 48% 32% 44%

19% 21% 24% 15%

Control Reference Default Default Control Reference Default Default level Opt-in Opt-out level** Opt-in Opt-out

Figure 23(a) Percentage of sample that donated by treatment, and 23(b) percentage of men and women that donated by treatment. Note: **p<0.01 difference between percentage of men and women donating in the reference level condition

Using bootstrapped t-tests, we compare the average donation amount (including those that gave nothing) given under the different treatment conditions (see Figure 24a). The average amount donated was higher in the default treatments compared to the control but the difference is only significant in the opt-out treatment (p<0.05). The mean amount donated in the default opt-in and default opt-out conditions are significantly different from each other (p<0.01). The average donation amount in the control compared to the reference level treatment is weakly significant at p<0.10. There are no differences between the mean amounts donated in the default opt-in or opt- out treatments compared to the reference level condition.

Similarly, we compare the average donation amounts conditional on giving (see Figure 24b). When we analyze mean amounts based only on those that donated something, we observe higher average donation amounts in the control and reference level treatments compared to the set default amount (p<0.01). There are no significant differences in the mean amounts given

Chapter 3 Soliciting voluntary user fees between the control and reference level conditions when analyzed conditionally on giving a donation. Likewise, there are no differences in the mean default amounts conditional on donating but this is to be expected considering the default was set at 10,000IDR in both the default opt-in and default opt-out. Therefore, the differences observed in the total mean donations (24a) between the default treatments are driven solely by a difference in propensity to donate.

24(a) Mean donation by treament 24(b) Mean conditional on donating

6822b b 6343ab 19750b 20667

4863a 3906a 10000a 10000a

Control Default Reference Default Default Default Reference Control Opt-in level Opt-out Opt-in Opt-out level

Figure 24(a) Mean amounts donated by treatment, and 24(b) mean amounts donated based on donating a non-zero amount. Note: a,b superscript letters denote significance between treatments. Treatments that share the same superscript letter do not significantly differ from each other at p<0.05.

The total donations received by the Gili Eco Trust were highest in the default opt-out treatment (see Figure 25). When analyzing only those that donated, even though the average amount donated in the default treatments was about half of the average amount donated in the control and reference levels, the total amount received by the Gili Eco Trust was highest in the default opt-out condition due to the increased propensity to donate in the default opt-out treatment. Simply put, more people give but they give smaller amounts on average. The smaller average amounts are explained by the fact that the default amount was set at 10,000IDR so the respondent only had to make one decision of whether to donate or not. Although the default methods prove to be more successful in ensuring donation compliance, the set default amount may be too low based on the higher mean donation amounts observed in the control and reference level treatment. Although 20% fewer respondents donated, the total amount received in the reference level treatment is comparable to the default opt-out treatment.

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Total donations to Gili Eco Trust

869,000 880,000 710,000

496,000

Control Default Opt-in Reference level Default Opt-out

Figure 25 Total donations received by Gili Eco Trust. Note: Amounts reported in Indonesian Rupiah (1000IDR=$0.07USD)

4.4.3 Two-part model: Probit and Ordinary Least Squares Regression

To assess whether the above findings are robust to the inclusion of control variables, we analyze the data using a two-part model developed by Cragg (1971). The first part of the model employs a probit analysis to define what factors determine whether a person will donate, while the second stage of the model uses an ordinary least squares (OLS) regression to identify which factors are responsible for how much a person donates – once they have made the decision to donate.

The first column in Table 11 excludes the treatment variables so we may observe if any of the control variables are relevant. We analyzed several models including a variety of demographic variables as independent variables with the decision to donate as the dependent variable. We controlled for age, gender, continent of nationality, price of hotel (as a proxy for income), number of days on the island, and activities. The only control variables that are statistically significant determinants of the discrete donation decision are the continent of nationality and activities. Therefore, we dropped insignificant variables and compared the fit of the models with and without the aforementioned variables. The likelihood ratio test does not indicate a statistically significant improvement (p=0.08) over the model that includes the entire suite of control variables, therefore, for simplicity we have left all control variables except the continent of nationality and activities out of the model in Table 11.

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Table 11 Probit and Ordinary least squares regression model

Probit Probit OLS OLS Donation Donation Donation Donation Decision Decision Amount Amount N 546 530 230 224 Europe 0.000 0.000 0.000 0.000 North America 0.623 0.632 -1,244.689 -733.096 (3.20)** (3.03)** (0.62) (0.41) South America -0.119 0.046 -3,474.084 -5,081.511 (0.41) (0.15) (0.89) (1.49) Asia 0.349 0.456 -1,540.390 -3,931.840 (2.19)* (2.65)** (0.85) (2.28)* Oceana -0.272 -0.392 2,891.757 4,569.442 (1.21) (1.63) (0.94) (1.71) Biking 0.241 0.246 1,265.543 791.334 (2.15)* (2.04)* (0.90) (0.63) Snorkel 0.159 0.220 2,283.165 1,405.407 (1.34) (1.73) (1.53) (1.05) Dive 0.042 0.089 2,357.205 2,288.281 (0.28) (0.55) (1.27) (1.41) Control 0.000 0.000 Default opt-in 0.904 -9,971.401 (5.23)** (4.63)** Default opt-out 1.460 -10,675.376 (8.14)** (4.96)** Reference levels 0.519 160.709 (2.92)** (0.07) Constant -0.539 -1.359 10,627.389 18,914.914 (4.24)** (7.18)** (6.10)** (7.39)** R2 0.03 0.26 z statistics in parentheses, * p<0.05; ** p<0.01

With Europeans serving as the base category, two nationality dummies have positive and statistically significant coefficients - those respondents from North America and Asia. We thereby find that respondents from North America and Asia are more likely to donate than Europeans. Those respondents that went biking on the island were also more likely to donate than those who did not bike. We do not find any statistical significance effecting the donation decision if the respondents engaged in snorkeling or diving activities. The model in the second column includes the treatment dummies with the control serving as the base category.

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Confirming the results of the binomial probability test, all treatments have statistically significant and positive coefficients compared to the control thereby indicating that there is a strong treatment effect determining the discrete donation decision.

The third and fourth columns in Table 11 reveal the estimates from the OLS model of the amount donated, contingent on donating a non-zero amount. None of the demographic control variables (including the full suite of demographics: gender, age, hotel price, number of days on island) have a statistically significant effect on the amount donated unless we include the treatment dummies (fourth column) wherein respondents from Asia are revealed to donate a significantly lower amount than Europeans. We analyzed the OLS models including all the control variables and with the limited version using only the continent of nationality and activities. The likelihood ratio test comparing the OLS regression models does not indicate a statistically better fit (p=0.3) when the aforementioned suite of control variables are included, therefore, they have been eliminated from the final models. When we include the treatment dummies, we observe statistically significant and negative coefficients for both the default opt-in and default opt-out conditions in comparison to the left out control variable.

4.5 Discussion and recommendations 4.5.1 Fund raising options and potential on Gili Trawangan

The results from this study reveal important information at a crucial time in the development of Gili Trawangan. As recent as September 2017, the government discussed plans to impose a tourist fee of 100,000IDR per person per day ($7.40USD). Our results provide evidence that an appropriately priced and executed tourist eco-fee could have immense positive benefits but the suggested fee of 100,000IDR per day could deter tourists from visiting the island if faced with choices of many other islands with no fee. This may additionally undermine fund raising efforts by local institutions, such as the Gili Eco Trust, who rely on self-organized financing to directly invest in finding solutions to problems facing the island. Based on the results from our survey, we find strong evidence that the majority of tourists do not perceive the island to be environmentally sustainable under current management practices and that they are willing to pay an eco-fee that is used to manage sustainable practices on Gili Trawangan. Tourists who biked around the island were more likely to donate and this may be explained by the fact that biking

Chapter 3 Soliciting voluntary user fees around the island exposes them to more of the challenges facing the island beyond comparatively well-kept main tourist beach area. Thus more exposure to environmental problems may increase the willingness to donate.

When respondents were given the choice to either write-in a donation amount or select an amount from choices ranging from 10,000IDR to 50,000IDR, the average donation amount was approximately 20,000IDR (~$1.50USD). However, a higher percentage of respondents selected the 10,000IDR level in the reference treatment, such that the total revenue earned for conservation was the same under the 10,000IDR level and the 20,000IDR level (see Figure 26). The default donation price was set at 10,000IDR and both the opt-in and opt-out treatments sustained higher willingness to donate compared to the control and reference level conditions. However, the opt-out condition generated the highest percentage of donors resulting in the highest overall revenue across all treatments (Figure 25). With the estimated number of around 1 million tourists visiting Gili Trawangan annually, a properly imposed eco-fee of 10,000IDR- 20,000IDR per person would result in a reliable and significant financing mechanism for both terrestrial and marine conservation.

Figure 26 shows the potential cumulative annual conservation revenue based on the control and reference treatments. At 10,000IDR, more people are willing to donate and therefore the revenue is the same as giving at the 20,000IDR level. Although less people donate as the donation amount increases, the total potential for fund raising does not drop off drastically until after 50,000IDR. These results could inform government ambitions to impose a fee of 100,000IDR, which may actually raise less than a fee of 50,000IDR, if these results are interpreted as an upper threshold for willingness-to-pay, or as an anchor point for decision making on whether to visit the island if a fee was imposed.

Chapter 3 Soliciting voluntary user fees

Figure 26 The bars indicate the percent of tourists willing to donate at the amount indicated on the X axis in Indonesian Rupiah and the markers indicate the estimated cumulative annual conservation revenue in USD based on the ratio and magnitude of giving. *Estimate based on 1 million tourists visiting Gili Trawangan annually.

Given that the eco-fee is a voluntary payment and not a government imposed tax (at the present time), our results indicate the most effective way to implement a voluntary eco-fee would be to include the payment as a default opt-out condition. This option could be added to the cost of accommodation or to the transport cost to the island. Given the hundreds of accommodation options on the island and third-party payment sites (i.e. Booking.com), attaching the payment to accommodations would introduce complicated logistical and regulatory requirements and the potential for corruption. There are about ten to fifteen boat transport companies operating on Gili Trawangan which are already regulated by a centralized transportation organization that requires the daily manifest for all boats arriving and departing the Gili Islands. We would suggest that each purchase of a boat transfer to the Gili Islands includes a default opt-out condition of a 10,000IDR eco-fee. This amount would be automatically added to the cost of the trip unless the traveler specifically opts out of paying the eco-fee.

Interestingly, we observe significant gender differences in willingness to donate but only under the reference level treatment (Figure 23b). Croson, Handy, and Shang (2010) find similar results that men are more influenced by suggestion amounts than are women. Croson, Handy, and Shang (2010) find that men are influenced by temporarily created social norms more so than

Chapter 3 Soliciting voluntary user fees women. This gender difference, however, disappears in the default conditions when only one reference amount is suggested providing further support of our recommendation to use the default opt-out method for requesting donations.

4.5.2 Expanding the scope of financing for land-sea conservation

While the results from this study provide critical information for Gili Trawangan, this study can additionally inform future research and practical approaches for financing land-sea management by exemplifying the role that social science research can play in advancing conservation. We show that extending community-based fees to all users of a land-sea area has the potential to generate substantial revenue to finance conservation while keeping the price at a low enough level to stay within what users are willing to pay. We also show that tourists are observant of environmental impacts and are willing to contribute to mitigating them and that tourists are willing to finance both NGOs and governmental organizations to do the work.

Understanding how tourists, and resources users more broadly, engage with and perceive environmental problems is key for designing effective mechanisms for conservation, including financing. The social sciences, which have historically been less influential in informing conservation research and practice (Chan et al. 2007, Bennett et al. 2017, Partelow, Schlüter, von Wehrden, et al. 2017) need to play a more substantial role in the future if land-sea conservation efforts aim to be more effective. Behavioral economics, in combination with other social and natural sciences, can make a key contribution to advancing conservation by better understanding human behavior and decision making in relation to multi-use areas, such as the coast, where preferences for donating and engaging with conservation efforts may vary by activity (Nelson, Schlüter, and Vance 2017a). Creating more sustainable interactions between people and nature on the coast will be in part dependent on how well we understand the role of human behavior in relation to what activities people do, how they perceive potential problems and the solutions they believe are viable and would be willing to support.

III. Concluding remarks

5 Concluding Remarks

5.1 Summary of research

The main purpose of this thesis was to examine the influence of specific intrinsic and extrinsic factors on voluntary contributions to marine conservation. I chose to investigate the voluntary contribution behavior of two distinct stakeholder groups, members of a fishing community and tourists. I conducted three different studies to fulfill the objectives set out for this thesis research. The thesis as a whole offers novel disciplinary and methodological contributions to the literature on conservation science, charitable giving, and behavioral environmental economics.

The first part of the research focuses on donations of money and time. I used an experimental setting to simulate a work scenario where participants were able to earn money by performing a task. This allowed me to examine differences between giving money and time as participants were divided into treatments where some had the opportunity to donate their time working so their earnings would accrue to charity and others were able to donate their earned wages to charity. Additionally, there were two more treatments wherein any donations of money or time were matched by the same value and donated to the charity they chose. Contrary to the findings of previous lab studies, participants from the Bajo Mola fishing community in Wakatobi National Park, Indonesia gave more money on average than the same value in time. Additionally, more people donated when the donations were matched although the average amount given did not increase. In fact, in the monetary donation treatment, the average percent of earnings donated significantly decreased in the match treatment compared to no match. There was no change in the average percent of earnings donated between the matched time treatment and the unmatched time treatment.

Some practical behavioral insights emerge from these results that could be useful for conservation practitioners and the Wakatobi National Park. The results indicate that Bajo fishers are willing to contribute to conservation and they give on average more money than time. The overall donor base can be increased through offering matched donations for both money and time. I cannot assume the long-term effect of monetary matching given that my results only show a snapshot in time, but it is possible that with the increase in donor base there may be positive effects over time for monetary donations even if the average individual amount given decreases with the match. Announcing a match to volunteer time is recommended given there is no 89

Concluding Remarks decrease in the average individual value of time donated and more people give overall. Therefore, the total value of volunteer time to the charity is higher in the volunteer match treatment.

These results provide important behavioral evidence for funding local public goods in Wakatobi. Additionally, this research gives some perspective of local resource users’ preferences for how they might like to contribute to the provisioning of public goods. The prevalent approach to conservation work in the field is to organize many community meetings and events to raise awareness of environmental issues. This research shows that announcing and matching the value of people’s time encourages more people to give. The data also show that people may prefer to give money. Now, I am not recommending that NGOs count soliciting donations from fishers into their major funding strategy but this shows that local resource users are willing to give to public goods and this is a good start to understanding the relationship between giving behavior and use of the environment. In doing so, this field experimental research approach contributes to conservation science and behavioral environmental economics to provide a better understanding of the voluntary behavior of resource users to provision environmental public goods.

I would also like to note the potential application of these results to a broader charitable giving context but it is not without reserve given the uncommon population of my research sample. Therefore, any more general applications should take into consideration the restrictions of such a non-standard subject pool. Having said that, this research can offer empirical evidence in the value of matching volunteer time where, otherwise, no scientific evidence exists. Given the relative scarcity of research on matches to volunteer time, more lab and field experiments examining the effect of matches on volunteer time are needed. I would now like to draw attention to a common funding practice and potential missed opportunity in the non-profit sector. There are two such applications of volunteer matching that would benefit from further scientific analysis: 1) large funding grants are often contingent on matching from the NGO, and 2) corporate volunteer matching.

It is common practice with large grants from international institutions, national governments, and private foundations to require an NGO to leverage other resources to match the value of the awarded grant (i.e. office space, supplies, equipment, personnel, services, training, fundraising, volunteer time). These NGOs then rely on donations from an individual support base and depend heavily on volunteer time to match the value of these grants. In many cases, there are strict

Concluding Remarks reporting regulations for the NGO to the awarding institution. My research shows that announcing funds as matched donations incentivizes donors to give time which leads to more value generated for the NGO. Although, as previously mentioned, context is important and it is unknown if the results from my research will be stable under different conditions. Mainly I want to emphasize that this area represents a wealth of opportunities for NGOs to engage in behavioral marketing research which could affect not only voluntary contributions, but also reporting, evaluation, and future grant funding.

Corporate volunteer matching, also known as ‘Dollars for Doers’, is when a company donates a fixed amount for every hour an employee volunteers. The company is matching the employees volunteer time. The charity receives double the value by getting the work for free and a donation for each hour worked. Anecdotal evidence suggests that corporate volunteer matching programs can attract better candidates and retain employees as well as increase employee engagement, thereby leading to more productivity and more profit (Forbes 2012). According to Forbes (2012), Microsoft gave $5.6 million as a result of the 383,000 volunteer hours logged through the company's employee volunteer program in 2011. The magnitude of volunteer hours and corporate matching programs alone is worthy of research attention to better understand donations of time. Linking donors directly to resource users in the field to match monetary donations to sustainable resource use and voluntary environmental behavior also holds interesting potential for the intersect between charitable giving research and behavioral environmental economics. Hopefully the research in this thesis, and other similar studies, continue the momentum to shift the paradigm away from trusting mostly anecdotal evidence toward a goal of understanding the science behind donor behavior.

The second research objective involved exploring the relationship between social and psychological factors and donations to charity among marine resource users. This study found a high percentage of participants (35.7%) prefers egalitarian pay-off structures. There was also a high proportion of participants displaying malevolent pay-off preferences (27.5%). Although I do observe significant differences in the mean amounts donated between distributional preference types, it is important to note that there is a high rate of giving across all participants in the study. Individuals with own-money-maximizing and malevolent preferences give the lowest amount of income to charity, whereas those with benevolent and egalitarian preferences donate a higher percentage of their earnings. In analyzing the discrete donation decision, neither the demographic 91

Concluding Remarks variables nor the treatments are seen to be statistically significant determinants. However, the distributional preference types are statistically significant indicators of the donation decision. Malevolent and own-money-maximizers are less likely to donate anything at all than the egalitarian and benevolent types. Those with benevolent preferences give statistically more on average to charity compared to the other types. There are no observable differences in the average amounts given between the egalitarian, own-money-maximizers, and malevolent types. The results imply that if own-money-maximizers and malevolents can be convinced to donate, then they will donate generously. The results from research 2 suggest that distributional preferences are an important explanatory control variable for donation behavior. Given that I observe own-money maximizers and malevolents giving to charity, I can conclude that social norms and societal expectations of prosocial behavior can override inherent personality characteristics. In my sample, this can be attributed to the fact that there is a strong social norm in Muslim societies to give to charity. It is unclear whether the concept of charity in Islam extends to environmental protection and this could be an interesting area for future research. Successful conservation campaigns require understanding and targeting the heterogeneity of the audience by putting the resource-users and their needs at the center of the local conservation campaign messaging and goals. In the case of Indonesia, there may be great value in partnering with the local mosques and religious leaders to actively promote pro-environmental behavior or appealing to one’s sense of pride and moral satisfaction in doing good.

On a broader scale, this study sheds light on interpretations between behavior in experimental games and giving to real public goods. Most social dilemma games involve decisions about resource allocation between anonymous but similar individuals with limited group size. In research 2, had I only observed the behavior from the distributional preferences elicitation task, the sample would appear to be much less cooperative than I observe in the real donation task. This raises questions as to whether the motivations for behaving altruistically towards similar individuals are activated by different mechanisms than the motivations that drive giving to charity. This needs further investigation but contributes to the literature on stability of preferences across domains.

To focus on another important group of stakeholders, in research 3 I examine tourist contributions to conservation. In this study, I find that the most effective way to solicit voluntary contributions from tourists is through a set default donation amount requiring individuals to opt- 92

Concluding Remarks out of donating if they do not wish to give. Setting the default amount to a level that is within the acceptable reference range results in the highest ratio of donors. Many marine protected areas rely on voluntary contributions for conservation and the majority of studies examining the willingness to pay for conservation limit the study population to scuba divers. The results from my research demonstrate the need, and the potential, to extend funding mechanisms to all types of resource users in coastal and small island destinations. The additional revenue earned through expanding the donor base represents further possibilities to focus conservation efforts across land-sea boundaries.

5.2 Limitations and future research opportunities

Although there are many strengths to a field experimental approach, these methods are limited in several ways. I address the weaknesses of the individual research methods in the previous chapters. In this subsection, I will focus on the broader issues and directions for future research.

This thesis examines the giving behavior of small-scale fishers and tourists in Indonesia. Naturally, the applicability and generalizability of the results is somewhat limited to the context in which the experiments have been conducted. Many of the same concepts that give strength to field experiments as a method, are also a weakness in how far the results can be applied to other contexts. Indeed, one of the main purposes of this research is to draw attention to contextual factors that may be present in determining the relationship between social and psychological factors and giving behavior.

An additional limitation to the experimental approach is that while useful to observe behavior in the field, experimental research is limited to describing the actions people make, not explaining why people make these choices. In-depth qualitative inquiry is necessary to understand and explain the nuances about human behavior, emotions, cultural expectations, and religious beliefs in different contexts. Interdisciplinary collaboration and mixed methods approaches is a practical way forward to ensure the development of a broader base of knowledge to improve conservation outcomes.

Broadly speaking, the global perspective of a wider, more diverse audience is missing in this narrative. We cannot discuss the protection and conservation of marine natural resources without taking into consideration the global public goods provided by the existence of healthy coral

Concluding Remarks ecosystems and clean ocean waters. Local behavioral changes will be of little concern in the long run if we cannot manage the overarching global stressors. The literature investigating the willingness to donate for the existence value of non-use environmental goods is mostly limited to hypothetical studies. Conservation NGOs using field experiments to solicit real donations for non-use environmental goods could benefit greatly from understanding the intrinsic and extrinsic motivations, such as those explored within this research, driving their donor base.

The limitation here is that NGOs have to be open to working with academics and comfortable with sharing proprietary data that may reveal strategic insights about the impact of their fundraising strategies. Additionally, academics must be flexible as there may be compromises regarding adherence to strict academic requirements for treatment randomization given that NGOs may not understand or may fear the consequences of subjecting clients to different information.

Promoting the mutual benefits of collaborations between academics and NGOs is one way of fulfilling the need for more research on human behavior in the conservation NGO sector. From the perspective of voluntary contributions to conservation, collaborations between large international NGOs and academics will allow academics access to large volumes of real-world data and the ability to ensure their research remains applied. Likewise, NGOs would benefit from working with researchers with advanced analytical skills and an understanding of relevant theory. Although challenging, such partnerships could play a decisive role in conservation outcomes if environmental giving behavior is better understood (Veríssimo et. al 2018).

Appendices

Appendix A Invitation Letter

Dear head of household,

We would like to officially invite you to participate in an educational study. During the study, you will work for one hour and you will be compensated for your effort. This research project is done in cooperation between a German university, PKSPL-Institut Pertanian Bogor, and Haluoleo University. The purpose of the study is to understand more about the livelihood decisions and preferences of people living in the Wakatobi National Park.

The study will take approximately 2 hours from start to finish. The first part will include a simple work activity and this will be followed by a survey questionnaire.

If you are interested in participating, please come to the location below at the time listed AND BRING THIS INVITATION LETTER WITH YOU OR YOU WILL NOT BE ABLE TO PARTICIPATE. Your participation in this study is completely voluntary. We have a limited number of available spaces and will accept people on a first come, first served basis. In the case that the study is already full for the day, you may have an opportunity to return at a later time or on a different day.

To participate in the study, you must present this invitation letter when you arrive. In the case that the head of household is not available at the time and date requested, the next decision maker in the house may come. All participants must be at least 18 years of age.

Participant number: Date: Time: Location: MEN ONLY

We greatly appreciate your time and hope to see you soon! Best regards,

Katie Nelson Febrina Desrianti

Appendices

Appendix B Survey

Sociodemographic Survey - 2015

RESPONDENT IDENTIFIER: VILLAGE RESP

NAME CODE

DISTRICT

VILLAGE NAME

DATE

NAME CODE

SUBJECT NAME

CONTACT NUMBER

ADDRESS

MALE 0 AGE FEMALE 1

INTERVIEWER

Hello. My name is ______, I am an interviewer and student from Haluoleo University in We are running a study which aims to gather more information on how people here make a living and how people have adapted fishing and livelihood behavior since the establishment of the national park zone. This research project is done in cooperation between a German university and PKSPL-Institut Your responses will be treated confidentially, and will only be used for the purposes of this study. Nobody except me and a small group of other researchers in this project will know your name and the answers you give will be processed in such a way that they cannot be linked to your name. In the reports we will ensure that participants in this survey cannot be identified. I would greatly appreciate your cooperation. We will need approximately 2 hours of your time. You can ask any questions during the interview and you can refuse to answer questions, or terminate the interview at any time. If you have any questions or concerns about this study, you may contact Dr. Luky Adrianto, Director, PKSPL-IPB. Are there any questions you would like to ask at this moment? Do you declare to have understood the purpose of this study and agree to participate in this survey? YES [ ] NO [ ]

Do you agree that we can use your picture in the future when presenting the results of the study? YES [ ] NO [ ]

Appendices

INFORMATION ABOUT HH ONLY Section 1 Household

(1.01) Are you the head of the household? No 0 ► (1.01a) Yes 1 ► (1.02) (1.01a) What is your relationship to the household head?

WIFE 1 CHILD 2 ADOPTED CHILD 3 GRANDCHILD 4 NIECE / NEPHEW 5 FATHER / M OTHER 6 BROTHER / SISTER 7 SON/ DAUGHTER IN LAW 8 BROTHER / SISTER IN LAW 9 GRANDFATHER / MOTHER 10 FATHER/ MOTHER IN LAW 11 OTHER SPECIFY 12 (1.02) How many people live in your household (including you)?

(1.03) How many people does your income support (including you, those that live in your household, and those that live outside your household)?

No income ► 0

(1.04) How many people in your household have a steady income (including you)?

(1.05) What jobs earn the steady income (starting with your job)? a CODE b GOVERNMENT EMPLOYEE 1 SELF-EMPLOYED 2 c PRIVATE SECTOR 3 FISHERMAN DEPENDENT 4 d FISHERMAN INDEPENDENT 5 FARMER (INCL. SEAWEED) 6 e OTHER: write it in 7

(1,06) The main building of (1,07) The floor is made of… your house has walls made of…

BAMBOO 1 BAMBOO 1 WOOD 2 SOIL/SAND 2 BRICK/CEMENT 3 PLANK WOOD 3 CORRUGATED IRON 4 FINISHED (tiles, etc) 4 OTHER 5 OTHER 5

Appendices

Section 2 Expenses and INFORMATION ABOUT HH ONLY Activities

(2.01) Do you own the house you live in? NO 0 YES 1

(2.02) Approximately how much does your household spend on each of these items per week? LOCAL CURENCY a Food and beverages b Transport (petrol or other) and communications (mobile credit) c Gas or wood for cooking d Electrictiy

(2.03) And approximately how much does your household spend on each of these items per year? LOCAL CURENCY a Education (including tuition, books, kindergarten expenses) b Health (including medicines and health insurance) c Weddings, funerals, religious ceremonies, and festivals (gifts included) d Rent or mortgage for house or boat Other expenses without rent (DO NOT PROMPT - RECORD HERE ONLY ANY ADDITIONAL e EXPENSES THAT THE RESPONDENT WOULD LIKE TO REPORT)

(2.04) Does anyone in your household have…? NO 0 READ OUT - ONE ANSWER PER LINE YES 1 a A canoe or boat (no engine) b A motorbike c A boat with an engine d A bank account e A refrigerator f A generator g A television h A car

NO 0 (2.05) Does your household have…? YES 1 a Electricity b Running water

(2.06) Do you or anyone in the household do any…? NO 0 YES 1 a Fishing b Collecting coral rocks c Collecting invertebrates d Collecting mangrove wood

Appendices

(2.07) Do you alternate between fishing/collecting and doing other jobs? NO 0 YES 1

(2.08) In the last 12 months… 1 Once or 2 Few 3 Few 4 > few times/week never times/month times/week How often did you go a fishing? How often did you go b fishing in less productive season? How often did you go c fishing in more productive season? How often did you collect d invertabrates, coral, or mangrove wood?

(2.09) What are the top 3 fishing gears you use most often? Rank 1 being most often to 3 less often.

R a n k 1- 3 a Equipment using your hand (ie. Gleaning, hand held line) b Handheld gun (ie. speargun) c Stationary net (traps, gill net, trammel net) d Mobile net (trawl, purse seine, beach seine) e Stationary line (long line) f Mobile line (trolling) g Compressor diving h Trap fishing i Explosives or chemicals (bomb or cyanide) j Other

(2.10) What are your target fish species (most preferred) based on the most used fishing gear from previous question? Rank top 2 species per gear. Gear code #1 Target fish Average Average #2 Target fish (Write it Average Average from 2,10 (Write it in) catch/trip price in) catch/trip price a

(2.11) Do you often catch and keep juvenile fish? NO 0 YES 1

(2.12) If you could make as much money doing another job as NO 0 you make fishing, would you stop fishing for income? YES 1

100

Appendices

(2.13) What is the lowest monthly income your household has within a year?

(2.14) Approximately how many months do you experience this?

(2.15) What is the normal monthly income for your household?

(2.16) What is the highest monthly income your household has within a year?

(2.17) Approximately how many months do you experience this?

SECTION 3 INDIVIDUAL SOCIODEMOGRAPHICS INFORMATION ABOUT INDIVIDUAL ONLY

(3.01) What is your ethnicity? BUTON 1 BAJO 2 BUGIS 3 PULO 4 MEDA-MEDA 5 OTHER 6

(3.02) How long have you lived in this locality? IF THE WHOLE LIFE, WRITE 99 ► (3.04) YEARS

(3.03) What is the NO DEGREE / NO EDUCATION 1 highest degree DID NOT FINISH ELEMENTARY SCHOOL 2 you already COMPULSORY SCHOOL EDUCATION 3 obtained? BASIC VOCATIONAL EDUCATION 4 SECONDARY TECHNICAL EDUCATION 5 SECONDARY GENERAL EDUCATION 6 HIGHER EDUCATION (BA) 7 UNIVERSITY (MA) OR HIGHER (PH.D) 8

(3.05) What is your religion? MUSLIM 1 PROTESTANT / OTHER CHRISTIAN 2 CATHOLIC 3 TRADITIONAL BELIEVER 4 BUDDHIST 5 OTHER 6

101

Appendices

Section 4 Attitudes & Values INFORMATION ABOUT INDIVIDUAL ONLY

(4.01) How is the fishing in Wakatobi?

1 2 3 4 5 Overfished Plenty of fish

(4.02) Waste is a problem in my

1 2 3 4 5 No problem Huge problem with waste with waste

(4.03) Whose main responsibility is it to keep the community clean? 1 Individual household 2 Community effort 3 Government

(4.04) Generally speaking, would you say that most people can be trusted, or that you can't be too careful in dealing with people? Please answer on a scale of 1 to 5, where 1 means that you have complete distrust and 5 means that you have complete trust.

1 2 3 4 5 Complete Complete distrust trust

(4.05) To what extent do you trust the following institutions?

Complete distrust Complete trust Complete a The federal government 1 2 3 4 5 b District government 1 2 3 4 5 c Village head (Kepala desa) 1 2 3 4 5 d Wakatobi National Park 1 2 3 4 5 e The police 1 2 3 4 5 f Banks and the financial system 1 2 3 4 5 g Community leaders/organizations 1 2 3 4 5 h Religious leaders 1 2 3 4 5 i International NGOs (ie. British Council, WWF, Swiss Contact) 1 2 3 4 5 j Local NGOs 1 2 3 4 5 k microfinance institutions/Cooperatives 1 2 3 4 5

102

Appendices

(4.06) Some say that by helping others you help yourself in the long run. Do you agree?

1 2 3 4 5 Disagree Strongly agree stronlgy

(4.07) If you saw someone you know doing something illegal, would you NO 0 report them? YES 1

(4.08) Do you think most people would try to take advantage of you if they got a chance, or would they try to be fair? Please use this scale, where 1 means that “people would try to take advantage of you,” and 10 means that “people would try to be fair”

1 2 3 4 5 6 7 8 9 10 People would try to People take advantage of would try to you be fair

(4.09) In your opinion, what are the three most important problems a Poverty that your village faces? b Food security Rank the top three from most concern (1) to less concern (3) c Education d Health e Inequality f Safety g Environment h LossSocial of conflict fishing i ground due to zonation j Destructive k Alcohol, gambling, and fighting l Overpopulation m Damage to natural habitat n Waste o Others

(4.10) Out of the following environmental problems, please a Climate change number the three most important problems with 1 being of b Sea water quality most concern and 3 being of less concern: c Coral reefs dying Not enough d fresh water e Severe weather Loss of natural f habitat

(4.11) How important is it to you to preserve the environment? Please use this scale, where 1 means "not important at all" and 10 means "the most important"

1 2 3 4 5 6 7 8 9 10 Not at all The most important

103

Appendices

Section 5 Social Capital and Marine INFORMATION ABOUT INDIVIDUAL ONLY Management Questions

(5.01) Here is a list of voluntary a Religious Orgnization organizations. For each one, please b Non Governmental Organization indicate whether you are a member c Neighborhood group or not a member of that type of d Microcredit organization e Women's group NOT MEMBER 0 f Fisher cooperative MEMBER 1 g Other (specify)

(5.02) Have you attended any village meetings in the past NO 0 three months? YES 1

(5.03) Have you participated in any education programs NO 0 about the environment? YES 1

(5.04) Do you help out a local group as a volunteer?

1 2 3

Never Sometimes Frequently

(5.05) Did you donate this year to any charities NO 0 (including sedekah)? Zakat NOT included. YES 1

(5.06) Have you ever been part of a project to organize a new service in your area (i.e. cleaning the neighborhood together, social project, etc)?

1 2 3

Never Sometimes Frequently

(5.07) What happens to the garbage waste in your village? No service 1 Daily pick-up service (govt) 2 Weekly pick-up service (govt) 3 Weekly community clean-up 4 Monthly community clean-up 5 Burn trash 6 Throw trash in ocean 7

104

Appendices

(5.08) What would you be doing right now if you were not participating in this study? Nothing 1 Working 2 Housekeeping 3 Studying 4 Fishing 5 Other 6

(5.09) What charity did you select?

1 Muslimat Nahdatul Ulama 2 Karang Taruna 3 Terangi 4 SINTESA 5 Islamic Relief Worldwide 6 Oxfam Indonesia

(5.10) Did you give (donate/volunteer) to the charity you selected? NO 0 YES 1

(5.11) If no, is it because you did not find a charity that you would NO 0 like to give to? YES 1

(5.12) If yes, is it because…

1 You know the charity 2 You like the focus of the charity 3 You trust the charity 4 The charity is local 5 The charity is international The following questions are related to marine management in Wakatobi.

(5.13) Who, in your opinion, should be responsible for managing your local marine area? READ OUT CROSS ALL THAT APPLIES ▼ a The government (forestry/fisheries department) b Local government or village council c NGOs d Local community institutions and community members e Tourism organizations (hotels, dive shops, etc) f International organizations g Other: ______(do not prompt, record information voluntereed by respondent) MARK WITH A CROSS THE MOST IMPORTANT ▲

5.14 What conservation activities would you agree to do regularly? CROSS ALL THAT APPLIES ▼ a Keep the canals free of trash b Buy reusable bags and stop using plastic bags c Report illegal fishing activity d Monitor the reef fishing grounds to prevent illegal activity e Maintain boundary markers for no take zones 105

Appendices

(5.15) In your opinion, what are the potential benefits of a managed marine area? DO NOT PROMPT CROSS ALL THAT APPLIES ▼ a Increased resources in the long run (more fish, larger fish) b Improved coral reef c Increased tourism d Pride/prestige for this village e Protects future generations f Prevents exploitation g Punishes illegal fishers h More money and benefits from NGO or government in the future i Reduced conflict j Reduced pollution k Other (specify: )

(5.16) In your opinion, what are the potential disadvantages of a managed marine area? DO NOT PROMPT CROSS ALL THAT APPLIES ▼ a Unclear rules b Outsiders breaking the rules c Unfairness d Increased conflict e Difficulties to enforce rules f Bad for communities depending on marine resources g Less money for my family h No money to support or manage it i Other (specify: )

Section 6 Distributional INFORMATION ABOUT INDIVIDUAL ONLY Preferences

(6.01) You will make ten decisions. You will be paid out for one of the ten choices based on how much you decide 'you get' (the pay out will be in thousands). example ; Do you prefer that you get 10 and others mendapatkan13 or , that you and others alike gain 10

You will receive a payment based on your decision and you will receive a payment based on the choice of another participant.

Are the instructions clear? Do you have any questions?

106

Appendices

Left Right You get They get You get They get 8 13 1 10 10

You get They get You get They get 10 7 2 10 10

You get They get You get They get 10 13 3 10 10

You get They get You get They get 12 13 4 10 10

You get They get You get They get 12 7 5 10 10

Left Right

You get They get You get They get 8 7 6 10 10

You get They get You get They get 9 13 7 10 10

You get They get You get They get 11 7 8 10 10

You get They get You get They get 11 13 9 10 10

You get They get You get They get 9 7 10 10 10

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Appendix C1 Experimental Instructions – Donation

Today, you will be participating in a research study. Your performance in this study and the choices you make will determine the benefits to both you and a charity of your choice.

We will have a short explanation of how to do the task. Please pay attention to these instructions so you will understand how the study works.

During this study, it is important that you do not pay attention to other people's work or discuss your work with others. If you have any questions, or need assistance of any kind, please raise your hand and we will come to you.

You will be presented a list of charities and their descriptions. You will be asked to select a single charity. Based on your actions during the study, the charity you select can benefit from your decisions. Please note that you can choose only one charity from this list.

Once you have selected your charity, we can begin the study. You then will be able to earn money as you do the task. You will have one hour to work. At the end of the hour, you will be paid for each piece completed correctly. Then you will have the opportunity to donate any amount of your earnings to the charity you selected.

You have a box of supplies including one long rolling stick and two short rolling sticks, a tube of glue, an envelope full of pre-cut paper strips (1.5cm at the base), a plastic collection bottle for the beads, an envelope with your name and an envelope with the name of the charity you chose. The box will be used as a screen to shield your work from others.

You will have 1 hour to do the task. Each bead should be placed in the plastic bottle upon completion. Each piece of paper rolled correctly is worth 1,000IDR. At the end of the hour, you will submit your work and you will be paid for those beads that are done correctly, and, you will be able to decide if you would like to contribute to charity. After this, you will complete a survey.

Total funds raised for the charities will be posted publicly in the village after the study and all charities will be presented with the contributions within 90 days.

To summarize: 1. You will roll paper pieces. Each one completed correctly is worth 1,000IDR. 2. Once 60 minutes have passed, the task is finished. 3. You are paid based on the number of correct beads completed in the time of the experiment. 4. You will then decide how much you would like to donate to the charity of your choice (a donation is not required) by putting your donation in a separate envelope. 5. Then you will complete a survey questionnaire.

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Appendix C2 Experimental Instructions – Donation match

Today, you will be participating in a research study. Your performance in this study and the choices you make will determine the benefits to both you and a charity of your choice.

We will have a short explanation of how to do the task. Please pay attention to these instructions so you will understand how the study works.

This study consists of rolling pieces of paper that can be used to make different types of products, such as key chains, fishing lures, etc. You have the opportunity to work to earn money for yourself for every piece you roll correctly and then you can decide how much to donate at the end to charity and we will match your donation.

Total funds raised for the charities will be posted publicly in the village after the study and all charities will be presented with the contributions within 90 days.

To summarize: 1. You will roll paper pieces. Each one completed correctly is worth 1,000IDR. 2. Once 60 minutes have passed, the task is finished.

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3. You are paid based on the number of correct beads completed in the time of the experiment. 4. You will then decide how much you would like to donate to the charity of your choice (a donation is not required) by putting your donation in a separate envelope. 5. We will match your donation to charity. 6. Then you will complete a survey questionnaire.

Appendix C3 Experimental Instructions – Volunteer

Today, you will be participating in a research study. Your performance in this study and the choices you make will determine the benefits to both you and a charity of your choice.

We will have a short explanation of how to do the task. Please pay attention to these instructions so you will understand how the study works.

Once you have selected your charity, we can begin the study. You then will be able to decide as you do the task when you would like to earn money for yourself and when you would like to contribute that time to the charity you selected. At any point during the study you will be allowed to switch back and forth as often you like between working for yourself or volunteering your time for charity.

This study consists of rolling pieces of paper that can be used to make different types of products, such as key chains, fishing lures, etc. You have the opportunity to work to earn money for yourself for every piece you roll correctly or to volunteer your effort. There are containers marked “charity” and unmarked containers that allow you to switch between working for yourself and the charity selected earlier. As each bead is completed, deposit the bead into either the unmarked work-for-self or “charity” container.

You have a box of supplies including one long rolling stick and two short rolling sticks, a tube of glue, an envelope full of pre-cut paper strips (1.5cm at the base), two plastic collection bottles – one marked “charity” and one unmarked – for the beads, an envelope with your name and an envelope with the name of the charity you chose. The box will be used as a screen to shield your work from others.

110

Appendices in the unmarked container, and, your charity will be paid for those beads done correctly in the “charity” container. After this, you will complete a survey.

Total funds raised for the charities will be posted publicly in the village after the study and all charities will be presented with the contributions within 90 days.

To summarize: 1. You will roll paper pieces. Each one completed correctly is worth 1,000IDR. 2. You can decide between working for yourself or volunteering for your charity at any point in the experiment by putting the paper beads into either container. 3. Once 60 minutes have passed, all allocations are finalized. 4. You are paid based on the number of correct beads completed in the time of the experiment that you deposit into the unmarked container. 5. Any beads that were deposited in the ‘charity’ container will result in proceeds going to the charity. 6. Then you will complete a survey questionnaire.

Appendix C4 Experimental Instructions – Volunteer match

Today, you will be participating in a research study. Your performance in this study and the choices you make will determine the benefits to both you and a charity of your choice.

We will have a short explanation of how to do the task. Please pay attention to these instructions so you will understand how the study works.

Once you have selected your charity, we can begin the study. You then will be able to decide as you do the task when you would like to earn money for yourself and when you would like to contribute that time to the charity you selected. We will match your contribution with an equal monetary donation to the charity of your choice. At any point during the study you will be allowed to switch back and forth as often you like between working for yourself or volunteering your time for charity.

This study consists of rolling pieces of paper that can be used to make different types of products, such as key chains, fishing lures, etc. You have the opportunity to work to earn money for yourself for every piece you roll correctly or to volunteer your effort. There are containers marked “charity” and unmarked containers that allow you to switch between working for yourself and the charity selected earlier. As each bead is completed, deposit the bead into either the unmarked work-for-self or “charity” container.

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You will have 1 hour to do the task. Each bead should be placed in the plastic bottle upon completion. Each piece of paper rolled correctly is worth 1,000IDR. At the end of the hour, you will submit the two containers and you will be paid for those beads that are done correctly in the unmarked container, and, your charity will be paid for those beads done correctly in the “charity” container and we will match your effort with a donation on your behalf to the charity you selected. After this, you will complete a survey.

Total funds raised for the charities will be posted publicly in the village after the study and all charities will be presented with the contributions within 90 days.

To summarize: 1. You will roll paper pieces. Each one completed correctly is worth 1,000IDR. 2. You can decide between working for yourself or volunteering for your charity at any point in the experiment by putting the paper beads into either container. 3. Once 60 minutes have passed, all allocations are finalized. 4. You are paid based on the number of correct beads completed in the time of the experiment that you deposit into the unmarked container. 5. Any beads that were deposited in the ‘charity’ container will result in proceeds going to the charity and we will match the amount donated. 6. Then you will complete a survey questionnaire.

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Appendix D Charity choices

Charity Organizations

Charity Focus Description

TERANGI is dedicated to coral reef conservation in Indonesia. Terumbu Karang Indonesia Environment They focus on improving marine management and community- based conservation to reduce threats to local coral reef habitats. (TERANGI)

Karang Taruna is a village-level organization and support will go towards community clean-up activities to protect the marine Karang Taruna Environment environment from pollution.

SINTESA focuses on women’s empowerment and provides training programs on alternative livelihood projects, potable SINTESA Rural Potential water resources, and managing finances. They provide savings and loan services in addition to tourism training.

Oxfam has been operating in Indonesia since 1957 and focuses Rural Potential on improving rural livelihood and income opportunities, equal Oxfam access to resources, food security, and disaster relief.

Islamic Relief Worldwide has been working in Indonesia since 2000 and focuses on climate change relief, food security, Religious Islamic Relief Worldwide sustainable livelihoods, sanitation, women’s empowerment, and organization access to potable water.

Religious NU is an Islamic organization that focuses on children’s Nahdlatul Ulama Organization education, religious learning, and women’s empowerment.

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Appendix E Step-by-step visual guide to rolling paper beads

Photo credit from “Steps to making paper beads” by Teenuja Dahari, 2012, https://veganlovlie.com/how-to-make- paper-beads/. Copyright 2012 by Teenuja Dahari. Accessed 15 Oct. 2015. Reprinted with permission.

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Appendix F Survey

CONTROL (WRITE-IN) TREATMENT

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REFERENCE LEVELS TREATMENT

DEFAULT OPT-IN TREATMENT

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DEFAULT OPT-OUT TREATMENT

117

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