This study examines public employees’ donations to a workplace giving campaign at a large public university in the south-east of the United States. First, we employed logistic regression to predict the likelihood of donating through workplace giving programmes using a sample of employees at a large public university (N = 11,726). Second, we estimated an ordinary least squares regression to identify the significant predictors of donation value with a subsample of employee donors (n=1,832). Third, we developed donor profiles (for example, clusters) of employee benefactors using K-medoids clustering. Factors such as sex, age, education and salary were significant predictors of both being a donor and the donation amount. Additionally, employment duration was significantly related to being a donor and the donation amount, while job classification only predicted being a donor. Employee donors fell into five distinct clusters. These findings contribute to our knowledge of workplace giving campaigns and can be used to develop strategic marketing campaigns.
Agypt, B., Christensen, R.K. and Nesbit, R. (2011) To Give or Not to Give: Longitudinal Predictors of Donation Decisions in Workplace Giving Campaigns, Toronto, Ontario, Canada, paper presented at the ARNOVA annual meeting, November.
Agypt, B., Christensen, R.K. and Nesbit, R. (2012) A tale of two charitable campaigns: longitudinal analysis of employee giving at a public university, Nonprofit and Voluntary Sector Quarterly, 41(5): 802–25. doi: 10.1177/0899764011418836
August, L. and Waltman, J. (2004). Culture, climate, and contribution: career satisfaction among female faculty, Research in Higher Education, 45(2): 177–92. doi: 10.1023/B:RIHE.0000015694.14358.ed
Bekkers, R. and Wiepking, P. (2011a) A literature review of empirical studies of philanthropy: eight mechanisms that drive charitable giving, Nonprofit and Voluntary Sector Quarterly, 40(5): 924–73. doi: 10.1177/0899764010380927
Bekkers, R. and Wiepking, P. (2011b) Who gives? A literature review of predictors of charitable giving. Part one: religion, education, age and socialization, Voluntary Sector Review, 2(3): 337–65. doi: 10.1332/204080511X6087712
Bennett, R. (2012) Why urban poor donate: a study of low income charitable giving in London, Nonprofit and Voluntary Sector Marketing, 41(5): 870–91. doi: 10.1177/0899764011419518
Bennett, R. (2018) Financial charity giving behaviour of the working poor: an empirical investigation, Journal of Marketing Management, 34(17–18): 1587–607. doi: 10.1080/0267257X.2018.1512516
Bernardi, K., Shah, P., Lyons, N.B., Olavarria, O.A., Alawadi, Z.M., Leal, I.M., Holihan, J.L., Bass, B.L., Jakey, C.E., Kao, L.S. et al. (2020) Perceptions on gender disparity in surgery and surgical leadership: a multicenter mixed methods study, Surgery, 167(4): 743–50. doi: 10.1016/j.surg.2019.12.004
Borden, V.M., Shaker, G.G. and Kienker, B.L. (2014) The impact of alumni status on institutional giving by faculty and staff, Research in Higher Education, 55(2): 196–217. doi: 10.1007/s11162-013-9318-3
Brooks, C. (2019) Classical linear regression model assumptions and diagnostic tests, in Introductory Econometrics for Finance, Cambridge: Cambridge University Press, pp 182–245.
Brown, E. (2005) College, social capital, and charitable giving, in A. Brooks (ed) Gifts of Time and Money in America’s Communities, Lanham, MD: Rowman & Littlefield, pp 185–204.
Charoensap-Kelly, P. (2017) Crafting faculty and staff fundraising campaign: predictors of giving, donor motivations and effective strategies, Journal of Education Advancement and Marketing, 2(1): 20–37.
Christensen, R.K., Nesbit, R. and Agypt, B. (2016) To give or not to give: employee responses to workplace giving campaigns over time, Nonprofit and Voluntary Sector Quarterly, 45(6): 1258–75. doi: 10.1177/0899764015619704
Creswell, J.W. and Clark, V.L.P. (2017) Designing and Conducting Mixed Methods Research, Thousand Oaks, CA: Sage Publications.
Donmoyer, R. (1990) Generalizability and the single‐case study, in E. Eisner and A. Peskhkin (eds) Qualitative Research on Education: The Continuing Debate, New York, NY: Teachers College Press, pp 175–200.
Driscoll, A. (2009) Carnegie’s new community engagement classification: affirming higher education’s role in community, New Directions for Higher Education, 2009(147): 5–12. doi: 10.1002/he.353
Florida Statutes (Chapter 119) [Online] http://www.leg.state.fl.us/Statutes/index.
Fox, J. (2015) Applied Regression Analysis and Generalized Linear Models, Thousand Oaks, CA: Sage Publications.
Gittell, R. and Tebaldi, E. (2006) Charitable giving: factors influencing giving in U.S. states, Nonprofit and Voluntary Sector Quarterly, 35(4): 721–36. doi: 10.1177/0899764006289768
Hager, M., Rooney, P. and Pollak, T. (2002) How fundraising is carried out in US nonprofit organizations, International Journal of Nonprofit and Voluntary Sector Marketing, 7(4): 311–24. doi: 10.1002/nvsm.188
Hall, B.L. (2009) Higher education, community engagement, and the public good: building the future of continuing education in Canada, Canadian Journal of University Continuing Education, 35(2): 11–23. doi: 10.21225/D5BC7N
Han, J., Kamber, M. and Pei, J. (2011) Cluster Analysis: Basic Concepts and Methods in Data Mining Concepts and Techniques, 3rd edn, Waltham, MA: Morgan Kaufmann-Elsevier.
Harder, A. (2019) Public value and partnership: critical components of extension’s future, Journal of Extension, 57(3).
Haski-Leventhal, D. (2013) Employee engagement in CSR: the case of payroll giving in Australia, Corporate Social Responsibility and Environmental Management, 20(2): 113–28. doi: 10.1002/csr.1287
Healy, K. (2004) Altruism as an organizational problem: the case of organ procurement, American Sociological Review, 69(3): 387–404. doi: 10.1177/000312240406900304
Hilbe, J.M. (2009) Logistic Regression Models, Boca Raton, FL: CRC Press.
Hrywna, M. (2015) United Way revenue ticks down, NonProfit Times, 6 October, http://www.thenonprofittimes.com/news-articles/united-way-fundraising-up-total-revenue-down/.
Huang, Z. (1998) Extensions to the k-means algorithm for clustering large data sets with categorical values, Data Mining and Knowledge Discovery, 2(3): 283–304. doi: 10.1023/A:1009769707641
Ivankova, N.V., Creswell, J.W. and Stick, S.L. (2006) Using mixed-methods sequential explanatory design: from theory to practice, Field methods, 18(1): 3–20. doi: 10.1177/1525822X05282260
Johnson, J.A. and Taylor, B.J. (2019) Academic capitalism and faculty salary gap, Innovative Higher Education, 44(1): 21–35. doi: 10.1007/s10755-018-9445-z
Jones, J.A., Pracht, D., Simonne, E., Renfrow, K. and Hunter, C. (2018) Nonprofit partnerships in extension programming: a pilot study, Journal of Extension, 56(2): 1–9.
Kalnins, A. (2018) Multicollinearity: how common factors cause type 1 errors in multivariate regression, Strategic Management Journal, 39(8): 2362–85. doi: 10.1002/smj.2783
Kaufman L. and Rousseeuw, P.J. (1987) Clustering by means of medoids, in Y. Dodge (ed) Statistical Data Analysis Based on the L1 Norm and Related Methods, Basel: Springer, pp 405–16.
Kaufman, L. and Rousseeuw, P.J. (2009) Finding Groups in Data: An Introduction to Cluster Analysis (Vol. 344), Hoboken, NJ: John Wiley & Sons.
Knight, W.E. (2004) Influences on participation in a university faculty and staff annual giving campaign, The CASE International Journal of Educational Advancement, 4(3): 221–32. doi: 10.1057/palgrave.cijea.2140002
Krijthe, J.H. (2015) Rtsne: T-distributed stochastic neighbor embedding using Barnes-Hut implementation, R package version 0.13, https://github.com/jkrijthe/Rtsne.
Kuo, I.C., Levine, R.B., Gauda, E.B., Bodurtha, J., Clements, J., Fivush, B. and Ishii, L. (2019) Identifying gender disparities and barriers to measuring the status of female faculty: the experience of a large school of medicine, Journal of Women’s Health, 28(11): 1569–75.
Leslie, L.M., Snyder, M. and Glomb, T.M. (2013) Who gives? Multilevel effects of gender and ethnicity on workplace charitable giving, Journal of Applied Psychology, 98(1): 49–62. doi: 10.1037/a0029943
Magidson, J. and Vermunt, J.K. (2002) Latent class modeling for clustering: a comparison with K-means, Canadian Journal of Marketing Research, 20(1): 37–44.
McNall, M., Reed, C.S., Brown, R. and Allen, A. (2009) Brokering community–university engagement, Innovative Higher Education, 33(5): 317–31. doi: 10.1007/s10755-008-9086-8
Melit Devassy, B., George, S. and Nussbaum, P. (2020) Unsupervised clustering of hyperspectral paper data using t-SNE, Journal of Imaging, 6(5): 29. doi: 10.3390/jimaging6050029
Millennial Impact Project (2015) Cause, influence and the next generation: the 2015 millennial report, http://www.themillennialimpact.com/research/.
Nesbit, R., Christensen, R.K. and Gossett, L. (2012) Charitable giving in the public workplace: a framework to understand employees’ philanthropic performance, Public Performance & Management Review, 35(3): 449–75. doi: 10.2753/PMR1530-9576350303
Ng, R.T. and Han, J. (2002) CLARANS: a method for clustering objects for spatial data mining, IEEE Transactions on Knowledge and Data Engineering, 14(5): 1003–16. doi: 10.1109/TKDE.2002.1033770
Osili, U.O., Hirt, D.E. and Raghaven, S. (2011) Charitable giving inside and outside the workplace: the role of individual and firm characteristics, International Journal of Nonprofit and Voluntary Sector Marketing, 16(4): 393–408. doi: 10.1002/nvsm.435
Park, H.S. and Jun, C.H. (2009) A simple and fast algorithm for K-medoids clustering, Expert Systems with Applications, 36(2): 3336–41. doi: 10.1016/j.eswa.2008.01.039
Paterlini, A.A., Nascimento, M.A. and Traina Jr, C. (2011) Using pivots to speed-up k-medoids clustering, Journal of Information and Data Management, 2(2): 221–36.
Pérez-Ortega, J., Almanza-Ortega, N.N., Adams-López, J., González-Gárcia, M., Mexicano, A., Saenz-Sánchez, S. and Rodríguez-Lelis, J.M. (2017) Improving the efficiency of the K-medoids clustering algorithm by getting initial medoids, in Á. Rocha, A. Correia, H. Adeli, L. Reis and S. Costanzo (eds) Recent Advances in Information Systems and Technologies, Advances in Intelligent Systems and Computing, vol 569, Cham: Springer.
Rimes, H., Nesbit, R. and Christensen, R.K. (2019) Giving at work: exploring connections between workplace giving campaigns and patterns of household charitable giving in the USA, VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 30(4): 828–40. doi: 10.1007/s11266-019-00125-4
Romney-Alexander, D. (2002) Payroll giving in the UK: donor incentives and influences on giving behavior, International Journal of Nonprofit and Voluntary Sector Marketing, 7(1): 84–92. doi: 10.1002/nvsm.169
Schervish, P.G. and Havens, J. (1997) Social participation and charitable giving: a multivariate analysis, VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations, 8(3): 235–60. doi: 10.1007/BF02354199
Scull, S. and Cuthill, M. (2010) Engaged outreach: using community engagement to facilitate access to higher education for people from low socioeconomic backgrounds, Higher Education Research & Development, 29(1): 59–74.
Shaker, G.G. and Christensen, R.K. (2019) I give at the office: a review of workplace giving research, theory, and practice, International Journal of Nonprofit Voluntary Sector Marketing, 24(1): e1628. doi: 10.1002/nvsm.1628
Shaker, G.G., Borden, V.M., Kienker, B.L. (2016) Workplace giving in universities: a U.S. case study at Indiana University, Nonprofit and Voluntary Sector Quarterly, 45(1): 87–111. doi: 10.1177/0899764014565468
Shaker, G.G., Christensen, R.K. and Bergdoll, J.J. (2017) What works at work? Toward an integrative model examining workplace campaign strategies, Nonprofit Management & Leadership, 28(1): 25–46. doi: 10.1002/nml.21270
Shaker, G.G., Kienker, B.L. and Borden, V.M. (2014) The ecology of internal workplace giving at Indiana University: a case study of academic and non-academic staff campus campaign fundraising, International Journal of Nonprofit and Voluntary Sector Marketing, 19(4): 262–76. doi: 10.1002/nvsm.1501
Straub, J.D. (2003) Fundraising and Crowd-Out of Charitable Contributions: New Evidence from Contributions to Public Radio, College Station, TX: Texas A&M University.
Swarndeep Saket, J. and Pandya, D.S. (2016) An overview of partitioning algorithms in clustering techniques, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 5(6): 1943–46.
Van der Maaten, L. (2014) Accelerating t-SNE using tree-based algorithms, The Journal of Machine Learning Research, 15(1): 3221–45.
Van der Maaten, L. and Hinton, G. (2008) Visualizing data using t-SNE, Journal of Machine Learning Research, 9: 2579–605. https://www.jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf?fbclid=IwA
Van der Maaten, L. and Hinton, G. (2012) Visualizing non-metric similarities in multiple maps, Machine learning, 87(1): 33–55. doi: 10.1007/s10994-011-5273-4
Walker, C. and Pharoah, C. (2002) A Lot to Give: Trends in Charitable Giving for the 21st Century, London: Hodder and Stoughton.
Wiepking, P. (2007) The philanthropic poor: in search of explanations for the relative generosity of lower income households, Voluntas, 18(4): 339–58. doi: 10.1007/s11266-007-9049-1
Wiepking, P. and Bekkers, R. (2012) Who gives? A literature review of predictors of charitable giving. Part two: gender, marital status, income, and wealth, Voluntary Sector Review, 3(2): 217–45. doi: 10.1332/204080512X649379
Wiepking, P. and Handy, F. (eds) (2015) The Palgrave Handbook of Global Philanthropy, Houndmills: Palgrave Macmillan.
Wooldridge, J.M. (2016) Introductory Econometrics: A Modern Approach, Toronto, Canada: Nelson Education.
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