Matching Returning Donors to Projects on Philanthropic Crowdfunding Platforms

References

• Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge Data Engrg. 17(6):734–749.Crossref, Google Scholar
• Aguirregabiria V, Mira P (2010) Dynamic discrete choice structural models: A survey. J. Econometrics 156(1):38–67.Crossref, Google Scholar
• Akkiraju R (2015) IBM Watson tone analyzer—New service now available. Accessed July 31, 2019, https://developer.ibm.com/watson/blog/2015/07/16/ibm-watson-tone-analyzer-service-experimental-release-announcement/.Google Scholar
• Althoff T, Leskovec J (2015) Donor retention in online crowdfunding communities: A case study of DonorsChoose.org. Proc. 24th Internat. Conf. on World Wide Web (International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva) 34–44.Google Scholar
• Andreoni J (1988) Privately provided public goods in a large economy: The limits of altruism. J. Public Econom. 35(1):57–73.Crossref, Google Scholar
• Andreoni J (1989) Giving with impure altruism: Applications to charity and Ricardian equivalence. J. Political Econom. 97(6):1447–1458.Crossref, Google Scholar
• Andreoni J (1990) Impure altruism and donations to public goods: A theory of warm-glow giving. Econom. J. (London) 100(401):464–477.Crossref, Google Scholar
• Andreoni J (2001) Philanthropy, economics of A2. Smelser NJ, ed. International Encyclopedia of the Social & Behavioral Sciences (Pergamon, Oxford, UK), 11369–11376.Crossref, Google Scholar
• Andreoni J, Nikiforakis N, Stoop J (2017). Are the rich more selfish than the poor, or do they just have more money? A natural field experiment. NBER Working Paper No. 23229, National Bureau of Economic Research, Cambridge, MA.Google Scholar
• Anscombe FJ (1961) Estimating a mixed-exponential response law. J. Amer. Statist. Assoc. 56(295):493–502.Crossref, Google Scholar
• Aral S, Walker D (2011) Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management Sci. 57(9):1623–1639.Link, Google Scholar
• Ariely D, Bracha A, Meier S (2009) Doing good or doing well? Image motivation and monetary incentives in behaving prosocially. Amer. Econom. Rev. 99(1):544–555.Crossref, Google Scholar
• Armstrong JS (1985) Long-Range Forecasting: From Crystal Ball to Computer (Wiley, New York).Google Scholar
• Arrow KJ (1972) Gifts and exchanges. Philos. Public Affairs 1(4):343–362.Google Scholar
• Barseghyan L, Molinari F, Thirkettle M (2019) Discrete choice under risk with limited consideration. Preprint, submitted February 18, 2019, https://arxiv.org/abs/1902.06629.Google Scholar
• Batson CD, Shaw LL (1991) Evidence for altruism: Toward a pluralism of prosocial motives. Psych. Inquiry 2(2):107–122.Crossref, Google Scholar
• Becker GS (1974) A theory of social interactions. J. Political Econom. 82(6):1063–1093.Crossref, Google Scholar
• Bornstein J (2017) What’s best? All-or-nothing vs. keep-what-you-raise crowdfunding campaigns. Retrieved April 11, 2018, https://medium.com/cause-match/all-or-nothing-vs-keep-what-you-raise-crowdfunding-campaigns-170f0a9e3446.Google Scholar
• Boyd SP, Vandenberghe L (2004) Convex Optimization (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
• Breese JS, Heckerman D, Kadie C (1998) Empirical analysis of predictive algorithms for collaborative filtering. Proc. 14th Conf. Uncertainty in Artificial Intelligence (UAI'98). (Morgan Kaufmann Publishers, San Francisco), 43–52.Google Scholar
• Breeze B (2013) how donors choose charities: The role of personal taste and experiences in giving decisions. Voluntary Sector Rev. 4(2):165–183.Crossref, Google Scholar
• Burtch G, Ghose A, Wattal S (2013) An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Inform. Systems Res. 24(3):499–519.Link, Google Scholar
• Burtch G, Ghose A, Wattal S (2014) Cultural differences and geography as determinants of online prosocial lending. Management Inform. Systems Quart. 38(3):773–794.Crossref, Google Scholar
• Burtch G, Ghose A, Wattal S (2015) The hidden cost of accommodating crowdfunder privacy preferences: A randomized field experiment. Management Sci. 61(5):949–962.Link, Google Scholar
• Burtch G, Ghose A, Wattal S (2016) Secret admirers: An empirical examination of information hiding and contribution dynamics in online crowdfunding. Inform. Systems Res. 27(3):478–496.Link, Google Scholar
• Carpenter B, Gelman A, Hoffman MD, Lee D, Goodrich B, Betancourt M, Brubaker M, et al.. (2017). Stan: A probabilistic programming language. J. Statist. Software 76(1):32.Google Scholar
• Center for Civil Society Studies (2004) 36-Country Data Tables (Johns Hopkins University, Baltimore).Google Scholar
• Charlton G (2015) What’s the best email frequency and how do you find it?” Retrieved September 21, 2019, https://www.clickz.com/whats-the-best-email-frequency-and-how-do-you-find-it/24027/.Google Scholar
• Chen T, Guestrin C (2016) Xgboost: A scalable tree boosting system. Proc. 22nd ACM SigKDD Internat. Conf. on Knowledge Discovery and Data Mining (ACM, New York), 785–794.Google Scholar
• Collins A, Beel J (2019) A first analysis of meta-learned per-instance algorithm selection in scholarly recommender systems. Koolen M, Bogers T, Mobasher B, Tuzhilin A, eds. 13th ACM Conf. on Recommender Systems (RecSys), 29–34. Workshop paper published online at http://ceur-ws.org/Vol-2449/.Google Scholar
• Cox DR, Oakes D (1984) Analysis of Survival Data (CRC Press, Boca Raton, FL).Google Scholar
• Cumming D, Leboeuf G, Schwienbacher A (2015) Crowdfunding models: Keep-it-all vs. all-or-nothing. Retrieved September 15, 2017, https://ssrn.com/abstract=2447567.Google Scholar
• DellaVigna S, List JA, Malmendier U (2012) Testing for altruism and social pressure in charitable giving. Quart. J. Econom. 127(1):1–56.Crossref, Google Scholar
• DonorsChoose.org (2019a) How is a school’s economic need level defined at Donorschoose.Org? Retrieved August 7, 2019, http://help.donorschoose.org/hc/en-us/articles/202375748-How-is-a-school-s-economic-need-level-defined-at-DonorsChoose-org-.Google Scholar
• DonorsChoose.org (2019b) Impact | Donorschoose.Org. Retrieved September 23, 2019, https://www.donorschoose.org/about/impact.html.Google Scholar
• Du RY, Kamakura WA (2008) Where did all that money go? Understanding how consumers allocate their consumption budget. J. Marketing 72(6):109–131.Crossref, Google Scholar
• Fabricant S (1970) Philanthropy in the American economy: An introduction. Dickinson FG, ed. The Changing Position of Philanthropy in the American Economy (National Bureau of Economic Research, Cambridge, MA), 3–30.Google Scholar
• Fleder D, Hosanagar K (2009) Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity. Management Sci. 55(5):697–712.Link, Google Scholar
• Gautier A, Pache A-C (2015) Research on corporate philanthropy: A review and assessment. J. Bus. Ethics 126(3):343–369.Crossref, Google Scholar
• Giving USA (2017) Giving USA 2017: Total charitable donations rise to new high of $390.05 billion. Retrieved July 26, 2017, https://givingusa.org/giving-usa-2017-total-charitable-donations-rise-to-new-high-of-390-05-billion/.Google Scholar
• Giving USA (2018) Giving USA 2018: Americans gave $410.02 billion to charity in 2017, crossing the $400 billion mark for the first time. Retrieved June 12, 2018, https://givingusa.org/giving-usa-2018-americans-gave-410-02-billion-to-charity-in-2017-crossing-the-400-billion-mark-for-the-first-time/.Google Scholar
• Hauser JR, Wernerfelt B (1990) An evaluation cost model of consideration sets. J. Consumer Res. 16(4):393–408.Crossref, Google Scholar
• Helsen K, Schmittlein DC (1993) Analyzing duration times in marketing: Evidence for the effectiveness of hazard rate models. Marketing Sci. 12(4):395–414.Link, Google Scholar
• Herlocker JL, Konstan JA, Terveen LG, Riedl JT (2004) Evaluating collaborative filtering recommender systems. ACM Trans. Inform. Systems 22(1):5–53.Crossref, Google Scholar
• Ho Y-C, Wu J, Tan Y (2017) Disconfirmation effect on online rating behavior: A structural model. Inform. Systems Res. 28(3):626–642.Link, Google Scholar
• Jing H, Smola AJ (2017) Neural survival recommender. Proc. 10th ACM Internat. Conf. on Web Search and Data Mining (WSDM '17) (ACM, New York), 515–524.Google Scholar
• Johnson SL, Faraj S, Kudaravalli S (2014) Emergence of power laws in online communities: The role of social mechanisms and preferential attachment. Management Inform. Systems Quart. 38(3):795–808.Crossref, Google Scholar
• Kaggle (2018a) Data science for good: Donorschoose.Org. Accessed July 4, 2020, https://kaggle.com/donorschoose/io.Google Scholar
• Kaggle (2018b) Data science for good: Kiva crowdfunding. Accessed July 4, 2020, https://kaggle.com/kiva/data-science-for-good-kiva-crowdfunding.Google Scholar
• Klasky B, Goggins A, Marshall C (2002) Method and System for Matching Donations. U.S. Patent Application 09/966,747, filed March 28, 2002, https://patents.google.com/patent/US20020038225.Google Scholar
• Kokkodis M, Lappas T (2016) Realizing the activation potential of online communities. Agerfalk PJA, Levina N, Kien SS, eds. Proc. Internat. Conf. on Information Systems - Digital Innovation at the Crossroads (Association for Information Systems).Google Scholar
• Köppe M (2012) On the Complexity of Nonlinear Mixed-Integer Optimization (Springer, New York).Crossref, Google Scholar
• Koren Y (2009a) The Bellkor solution to the Netflix Grand Prize. Retrieved February 20, 2018, https://netflixprize.com/assets/GrandPrize2009_BPC_BellKor.pdf.Google Scholar
• Koren Y (2009b) Collaborative filtering with temporal dynamics. Proc. 15th ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining. (ACM, New York), 447–456.Crossref, Google Scholar
• Labianca I (2019) 11 email marketing frequency best practices for 2019. Retrieved September 21, 2019, https://www.theseventhsense.com/blog/11-email-marketing-frequency-best-practices-for-2018.Google Scholar
• Lambert D (1992) Zero-inflated poisson regression, with an application to defects in manufacturing. Technometrics 34(1):1–14.Crossref, Google Scholar
• Li X, Hitt LM (2010) Price effects in online product reviews: An analytical model and empirical analysis. Management Inform. Systems Quart. 34(4):809–831.Crossref, Google Scholar
• Liang D, Charlin L, McInerney J, Blei DM (2016) Modeling user exposure in recommendation. Proc. 25th Internat. Conf. on World Wide Web. (International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE), 951–961.Crossref, Google Scholar
• Lin M, Viswanathan S (2016) Home bias in online investments: An empirical study of an online crowdfunding market. Management Sci. 62(5):1393–1414.Link, Google Scholar
• List JA (2011) The market for charitable giving. J. Econom. Perspective 25(2):157–180.Crossref, Google Scholar
• Mo J, Sarkar S, Menon S (2018) Know when to run: Recommendations in crowdsourcing contests. Management Inform. Systems Quart. 42(3):919–944.Crossref, Google Scholar
• Mullen J (1997) Performance-based corporate philanthropy: How “giving smart” can further corporate goals. Public Relations Quart. 42(2):42–48.Google Scholar
• Murphy KP (2012) Machine Learning: A Probabilistic Perspective (MIT Press, Cambridge, MA).Google Scholar
• Murthi B, Sarkar S (2003) The role of the management sciences in research on personalization. Management Sci. 49(10):1344–1362.Link, Google Scholar
• Nagel T (1978) The Possibility of Altruism (Princeton University Press, Princeton, NJ).Google Scholar
• Peng J, Zeng DD, Zhao H, Wang F-Y (2010) Collaborative filtering in social tagging systems based on joint item-tag recommendations. Proc. 19Th ACM Internat. Conf. on Information and Knowledge Management (ACM, New York) 809–818.Google Scholar
• Rakesh V, Choo J, Reddy CK (2015) What motivates people to invest in crowdfunding projects? Recommendation using heterogeneous traits in Kickstarter. Proc. Ninth Internat. AAAI Conf. on Weblogs and Social Media (ICWSM-15) (ACM, New York), https://ojs.aaai.org/index.php/ICWSM/issue/view/273.Google Scholar
• Salvatier J, Wiecki TV, Fonnesbeck C (2016) Probabilistic programming in Python using Pymc3. Peer J. Comput. Sci. 2:e55.Crossref, Google Scholar
• Schmidt P, Witte AD (2012) Predicting Recidivism Using Survival Models (Springer Science & Business Media, New York).Google Scholar
• Sen AK (1977) Rational fools: A critique of the behavioral foundations of economic theory. Philosophical Public Affairs 6(4):317–344.Google Scholar
• Sinha RK, Chandrashekaran M (1992) A split hazard model for analyzing the diffusion of innovations. J. Marketing Res. 29(1):116–127.Crossref, Google Scholar
• Steck H (2013) Evaluation of recommendations: Rating-prediction and ranking. Proc. 7th ACM Conf. on Recommender Systems, (ACM, New York), 213–220.Crossref, Google Scholar
• Tausczik YR, Pennebaker JW (2010) The psychological meaning of words: Liwc and computerized text analysis methods. J. Language Soc. Psych. 29(1):24–54.Crossref, Google Scholar
• Tawarmalani M, Sahinidis NV (2005) A polyhedral branch-and-cut approach to global optimization. Math. Programming 103(2):225–249.Crossref, Google Scholar
• U.S. Census Bureau (2015) 2009-2013 American community survey 5-year estimates. Retrieved August 17, 2016, https://factfinder.census.gov/bkmk/table/1.0/en/ACS/13_5YR/DP05/0100000US.Google Scholar
• Vana P (2016) Modelling the role of uncertainty in cause-based crowdfunding: A multiple discrete continuous choice approach. Retrieved June 15, 2018, https://sites.google.com/site/prasadvanalbs/2_JMP_Draft_PrasadVana.pdf.Google Scholar
• Wang H, Wang N, Yeung D-Y (2015) Collaborative deep learning for recommender systems. Proc. 21th ACM SIGKDD Internat. Conf. on Knowledge Discovery and Data Mining. (ACM, New York), 1235–1244.Crossref, Google Scholar
• Wang JH, Gleit N, Martinazzi PH, Sidhu KS, Arquette L, Wieland JC, Burge J, et al. (2013) Promoting Participation of Low-Activity Users in Social Networking System (Google Patents). U.S. Patent 8,560,962, issued October 15, 2013.Google Scholar
• Warr PG (1982) Pareto optimal redistribution and private charity. J. Public Econom. 19(1):131–138.Crossref, Google Scholar
• Wikipedia (2017) Symmetric mean absolute percentage error. Retrieved August 23, 2017. https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error.Google Scholar
• Wolpin KI (2007) Ex ante policy evaluation, structural estimation and model selection. Amer. Econom. Rev. 97(2):48–52.Crossref, Google Scholar
• Xu L, Duan JA, Whinston A (2014) Path to purchase: A mutually exciting point process model for online advertising and conversion. Management Sci. 60(6):1392–1412.Link, Google Scholar
• Yan J, Wang K, Liu Y, Xu K, Kang L, Chen X, Zhu H (2017) Mining social lending motivations for loan project recommendations. Expert Systems Appl. 111:100–106.Google Scholar
• Zhu Q, Zhou X, Song Z, Tan J, Guo L (2019) Dan: Deep attention neural network for news recommendation. Proc. AAAI Conf. on Artificial Intelligence, (AAAI Press, Palo Alto, CA), 33(1):5973–5980.Crossref, Google Scholar
• Zvilichovsky D, Inbar Y, Barzilay O (2015) Playing both sides of the market: Success and reciprocity on crowdfunding platforms. Retrieved June 1, 2017, https://ssrn.com/abstract=2304101.Google Scholar