{"id":1076,"date":"2025-08-06T18:00:56","date_gmt":"2025-08-06T18:00:56","guid":{"rendered":"https:\/\/mll.iiit.ac.in\/?p=1076"},"modified":"2025-08-06T18:00:56","modified_gmt":"2025-08-06T18:00:56","slug":"designing-refund-bonus-schemes-for-provision-point-mechanism-in-civic-crowdfunding","status":"publish","type":"post","link":"https:\/\/mll.iiit.ac.in\/index.php\/2025\/08\/06\/designing-refund-bonus-schemes-for-provision-point-mechanism-in-civic-crowdfunding\/","title":{"rendered":"Designing Refund Bonus Schemes for Provision Point Mechanism in Civic Crowdfunding"},"content":{"rendered":"\n<p><strong>TL;DR.&nbsp;<\/strong><em>Civic crowdfunding<\/em>, the process of raising voluntary contributions from interested agents for&nbsp;<em>public&nbsp;<\/em>projects, such as public parks, libraries, etc., has grown in popularity in recent decades. As these projects are non-excludable, strategic agents often&nbsp;<em>free-ride<\/em>, i.e., choose not to contribute. To address this, researchers have used&nbsp;<em>incentive engineering&nbsp;<\/em>to construct mechanisms that&nbsp;<em>incentivize<\/em>&nbsp;strategic agents to contribute. This incentive is in the form of a \u201crefund,\u201d which is paid out to contributing agents in case the project was not funded. In this work, we characterize this refund \u2014 theoretically as well as practically. First, we present&nbsp;<em>sufficient&nbsp;<\/em>conditions that a refund bonus scheme should satisfy to crowdfund a project at equilibrium successfully. Then, we provide certain&nbsp;<em>desirable&nbsp;<\/em>conditions that are useful for crowdfunding in practice. We then present three novel refund schemes (and their respective&nbsp;<em>mechanisms<\/em>) that satisfy these conditions. We show that the mechanisms presented are better than the current state-of-the-art: (i) In terms of cost-efficiency when deployed as a&nbsp;<em>smart contract&nbsp;<\/em>over&nbsp;<em>Ethereum<\/em>; and (ii) In terms of performance in a Bagnoli and Lipmanreal-world setting through simulations using Reinforcement Learning (RL).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><em>Crowdfunding&nbsp;<\/em>has been gaining momentum, thanks mainly to the success of online platforms such as&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/www.kickstarter.com\/\" target=\"_blank\">Kickstarter<\/a>&nbsp;and&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/www.gofundme.com\/\" target=\"_blank\">GoFundMe<\/a>. When used to fund non-excludable&nbsp;<em>public&nbsp;<\/em>goods, the process is referred to as&nbsp;<em>civic crowdfunding.&nbsp;<\/em>This success, however, necessitates the need for&nbsp;<em>transparency&nbsp;<\/em>and<em>&nbsp;anonymity&nbsp;<\/em>of payments. As a result, crowdfunding is now being deployed as&nbsp;<em>smart contracts<\/em>&nbsp;over&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/ethereum.org\/\" target=\"_blank\"><em>Ethereum<\/em><\/a>.&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/http:\/\/weifund.io\/\" target=\"_blank\">WeiFund<\/a>&nbsp;and&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/starbase.co\/\" target=\"_blank\">Starbase<\/a>&nbsp;are some examples of Ethereum based crowdfunding platforms.&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/doi.org\/10.2307\/2297502\" target=\"_blank\">Bagnoli and Lipman<\/a>&nbsp;present the baseline approach for civic crowdfunding with their mechanism,&nbsp;<em>Provision Point Mechanism&nbsp;<\/em>(PPM). In PPM, the social planner announces a target, known as&nbsp;<em>provision point,&nbsp;<\/em>and a deadline. If the agents\u2019 contribution meets the target (by the deadline), the project is said to be&nbsp;<em>provisioned.&nbsp;<\/em>Otherwise, each agent is returned its contribution. While PPM has been used successfully, it leads to&nbsp;<em>free-riding.&nbsp;<\/em>This is because, as public projects are non-excludable, strategic agents may prefer not to contribute. Thus, the major challenge in civic crowdfunding is to&nbsp;<em>incentivize strategic agents to contribute.<\/em><\/p>\n\n\n\n<p><a href=\"https:\/\/web.archive.org\/web\/20231001062945\/https:\/\/doi.org\/10.1016\/j.jpubeco.2014.10.006\" target=\"_blank\" rel=\"noreferrer noopener\">Zubrickas<\/a>&nbsp;addresses the free-riding problem through his mechanism, the&nbsp;<em>Provision Point mechanism with Refunds&nbsp;<\/em>(PPR). PPR introduces a \u201crefund bonus\u201d to be paid to contributing agents, along with their contributions. The refund bonus scheme in PPR offers a bonus to agents, which is proportional to their contribution, in the case&nbsp;<em>underprovisioning<\/em>, i.e., the project not being provisioned. This incentivizes greater contributions from the agents. With this incentive structure, the author shows that PPR results in a&nbsp;<em>simultaneous-move&nbsp;<\/em>game in which the project is provisioned at equilibrium.<\/p>\n\n\n\n<p>As observed by&nbsp;<a href=\"https:\/\/web.archive.org\/web\/20231001062945\/http:\/\/ebooks.iospress.nl\/publication\/44825\" target=\"_blank\" rel=\"noreferrer noopener\">Chandra et al.<\/a>, PPR applied in online platforms results in agents&nbsp;<em>delaying&nbsp;<\/em>their contributions until the deadline. This is because the&nbsp;<em>refund bonus scheme&nbsp;<\/em>in PPR is&nbsp;<em>independent&nbsp;<\/em>of the time of an agent\u2019s contribution. Thus, in an online setting, wherein agents can observe the history of the contributions, it becomes beneficial for agents to delay their contribution until the deadline. We define this delaying of contributions as a&nbsp;<em>race condition<\/em>. The race condition is undesirable as it can lead to the project not being provisioned due to server failures, transactions not being processed in time, etc. Towards this, the authors present&nbsp;<em>Provision Point mechanism with Securities&nbsp;<\/em>(PPS). PPS uses complex prediction markets (<a href=\"https:\/\/web.archive.org\/web\/20231001062945\/http:\/\/web.eecs.umich.edu\/~jabernet\/papers\/ACV12.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">Abernethy et al.<\/a>) to refund agents \u2014 such that an agent contributing early gets a&nbsp;<em>higher&nbsp;<\/em>refund than an agent contributing later, for the same contribution. This induces a&nbsp;<em>sequential&nbsp;<\/em>game in PPS, unlike PPR.<\/p>\n\n\n\n<p>Observe that a refund bonus scheme plays a crucial role in designing provision point mechanisms for civic crowdfunding. Motivated by this, in this paper, we look at all the conditions a refund scheme should satisfy to be used for civic crowdfunding in online settings, to avoid free riding as well as the race condition. Towards this, we define (i)&nbsp;<em>Contribution Monotonicity<\/em>: the refund increases with contributions; and (ii)&nbsp;<em>Time Monotonicity<\/em>: the refund is non-increasing with time. We then prove that a refund bonus scheme satisfying these two conditions induces a game in which the project is provisioned, and all agents contribute as soon as they arrive. This is the&nbsp;<em>first&nbsp;<\/em>general result of a refund bonus scheme in civic crowdfunding literature. Also, we require that a refund bonus scheme must be&nbsp;<em>clear<\/em>&nbsp;to a layperson as well as&nbsp;<em>cost-efficient<\/em>&nbsp;when deployed as a smart contract.<\/p>\n\n\n\n<p>To show that these mechanisms do not trade-off performance for cost-efficiency, we employ Reinforcement Learning based simulations to compare them with PPS. In our simulator, agents go through repetitive iterations and learn their best strategy through rewards as given by the respective mechanisms. We measure the performance through\u00a0<em>provision accuracy<\/em>, i.e., the fraction of the public projects provisioned by the mechanism.<\/p>\n\n\n\n<p>In summary, in this paper, we identify Contribution Monotonicity and Time Monotonicity as sufficient conditions for a refund bonus scheme to satisfy for the project to be funded at equilibrium. Further, we present PPRG, PPRE, and PPRP based on three simple refund bonus schemes that satisfy these conditions. We then show that PPRG is the most cost-efficient when deployed as a smart contract. Lastly, using reinforcement learning-based simulations, we show that PPRG performs at par with PPS, thereby not trading off cost-efficiency for performance.<\/p>\n\n\n<div class=\"taxonomy-post_tag wp-block-post-terms\"><span class=\"wp-block-post-terms__prefix\">Keywords: <\/span><a href=\"https:\/\/mll.iiit.ac.in\/index.php\/tag\/civic-crowdfunding\/\" rel=\"tag\">Civic Crowdfunding<\/a><span class=\"wp-block-post-terms__separator\">, <\/span><a href=\"https:\/\/mll.iiit.ac.in\/index.php\/tag\/ethereum\/\" rel=\"tag\">Ethereum<\/a><span class=\"wp-block-post-terms__separator\">, <\/span><a href=\"https:\/\/mll.iiit.ac.in\/index.php\/tag\/mechanism-design\/\" rel=\"tag\">Mechanism Design<\/a><\/div>","protected":false},"excerpt":{"rendered":"<p>TL;DR.&nbsp;Civic crowdfunding, the process of raising voluntary contributions from interested agents for&nbsp;public&nbsp;projects, such as public parks, libraries, etc., has grown [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[31,33,24],"class_list":["post-1076","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-civic-crowdfunding","tag-ethereum","tag-mechanism-design"],"_links":{"self":[{"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/posts\/1076","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/comments?post=1076"}],"version-history":[{"count":1,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/posts\/1076\/revisions"}],"predecessor-version":[{"id":1077,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/posts\/1076\/revisions\/1077"}],"wp:attachment":[{"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/media?parent=1076"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/categories?post=1076"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mll.iiit.ac.in\/index.php\/wp-json\/wp\/v2\/tags?post=1076"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}