Abstract
An increasing number of nonprofits are interacting with their current and prospective donors on social media. How to elicit donations effectively through social media, however, remains under-researched. This study applied the optimal matching theory to examine online interactions between nonprofit organizations and their followers. A 2 (valence of organizational post: positive vs. negative) × 2 (type of social support: emotional vs. informational) between-subjects experiment was conducted to investigate how the match between a nonprofit organization’s need and its followers’ social support impacts third-party observers’ perceived relationship satisfaction and donation intention. The mediation effect of enacted social support evaluation (i.e., perceived helpfulness, supportiveness, and sensitiveness) was also examined. It was found that organizational post valence exerted an indirect effect on third-party observers’ perceived relationship satisfaction and donation intention through perceived supportiveness and helpfulness. These mediation effects were conditional on the type of social support provided by online followers of the organization.
Similar content being viewed by others
References
Antonucci, T. C., & Jackson, J. S. (1990). The role of reprocity in social support. In B. R. Sarason, I. G. Sarason, & G. R. Pierce (Eds.), Social support: Theory, research and application (pp. 21–37). Boston, MA: Nijhoff.
Barbee, A. P., & Cunningham, M. R. (1995). An experimental approach to social support communications: Interactive coping in close relationships. In B. R. Burleson (Ed.), Communication yearbook 18 (pp. 381–413). Thousand Oaks, CA: Sage.
Barnes, M. K., & Duck, S. (1994). Everyday supportive contexts for social support. In B. R. Burleson, T. L. Albrecht, & I. G. Sarason (Eds.), Communication of social support: Messages, interactions, relationships, and community (pp. 175–194). Thousand Oaks, CA: Sage.
Bartikowski, B., & Walsh, G. (2014). Attitude contagion in consumer opinion platforms: Posters and lurkers. Electron Markets, 24, 207–217. https://doi.org/10.1007/s12525-013-0149-z.
Blouin, M. C., Lee, R. L., & Erickson, G. S. (2018). The impact of online financial disclosure and donations in nonprofits. Journal of Nonprofit & Public Sector Marketing, 30(3), 251–266.
Boren, J. P. (2014). The relationships between co-rumination, social support, stress, and burnout among working adults. Management Communication Quarterly, 28(1), 3–25. https://doi.org/10.1177/0893318913509283.
Burleson, B. R. (1994). Comforting messages: Features, functions, and outcomes. In J. A. Daly & J. M. Wiemann (Eds.), Strategic interpersonal communication (pp. 135–161). Hillsdale, NJ: Lawrence Erlbaum.
Burleson, B. R. (2009). Understanding the outcomes of supportive communication: A dual-process approach. Journal of Social and Personal Relationships, 26(1), 21–38. https://doi.org/10.1177/0265407509105519.
Burleson, B. R., & MacGeorge, E. L. (2002). Supportive Communication. In M. L. Knapp & J. A. Daly (Eds.), Handbook of interpersonal communication (pp. 34–424). Thousand Oaks, CA: Sage Publications.
Burleson, B. R., Albrecht, T. L., Goldsmith, D. J., & Sarason, I. G. (1994). The communication of social support. In B. R. Burleson, T. L. Albrecht, & I. G. Sarason (Eds.), Communication of social support: Messages, interactions, relationships, and community (pp. xi–xxx). Thousand Oaks, CA: Sage.
Campbell, D. A., Lambright, K. T., & Wells, C. J. (2014). Looking for friends, fans and followers? Social media use in public and nonprofit human services. Public Administration Review, 74(5), 655–663. https://doi.org/10.1111/puar.12261.
Cobb, S. (1976). Social support as a moderator of life stress. Psychosomatic Medicine, 38(5), 300–314. https://doi.org/10.1097/00006842-197609000-00003.
Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. https://doi.org/10.1037/0033-2909.98.2.310.
Cho, M., Schweickart, T., & Haase, A. (2014). Public engagement with nonprofit organizations on Facebook. Public Relations Review, 40(3), 565–567. https://doi.org/10.1016/j.pubrev.2014.01.008.
Cutrona, C., & Russell, D. (1990). Type of social support and specific stress: Toward a theory of optimal matching. In B. Sarason, I. Sarason, & G. Pierce (Eds.), Social support: An interactional view (pp. 319–366). New York: Wiley.
Cutrona, C. E., & Suhr, J. A. (1992). Controllability of stressful events and satisfaction with spouse support behaviors. Communication Research, 19(2), 154–174. https://doi.org/10.1177/00936509201900200.
Cutrona, C. E., Shaffer, P. A., Wesner, K. A., & Gardner, K. A. (2007). Optimal matching support and perceived spousal sensitivity. Journal of Family Psychology, 21(4), 754–758. https://doi.org/10.1037/0893-3200.21.4.754.
Dijkmans, C., Kerkhof, P., Buyukcan-Tetik, A., & Beukeboom, C. J. (2015). Online conversation and corporate reputation: A two-wave longitudinal study on the effects of exposure to the social media activities of a highly interactive company. Journal of Computer-Mediated Communication, 20(6), 632–648. https://doi.org/10.1111/jcc4.12132.
Erlandsson, A., Björklund, F., & Bäckström, M. (2015). Emotional reactions, perceived impact and perceived responsibility mediate the identifiable victim effect, proportion dominance effect and in-group effect respectively. Organizational Behavior and Human Decision Processes, 127, 1–14.
Erlandsson, A., Nilsson, A., & Västfjäll, D. (2018). Attitudes and donation behavior when reading positive and negative charity appeals. Journal of Nonprofit & Public Sector Marketing, 30(4), 444–474.
Erlandsson, A., Västfjäll, D., Sundfelt, O., & Slovic, P. (2016). Argument-inconsistency in charity appeals: Statistical information about the scope of the problem decrease helping toward a single identified victim but not helping toward many non-identified victims in a refugee crisis context. Journal of Economic Psychology, 56, 126–140. https://doi.org/10.1016/j.joep.2016.06.007.
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191.
France, J. L., Kowalsky, J. M., France, C. R., McGlone, S. T., Himawan, L. K., Kessler, D. A., & Shaz, B. H. (2014). Development of common metrics for donation attitude, subjective norm, perceived behavioral control, and intention for the blood donation context. Transfusion, 54(3), 839–847. https://doi.org/10.1111/trf.12471.
Gable, S. L., Gonzaga, G. C., & Strachman, A. (2006). Will you be there for me when things go right? Supportive responses to positive event disclosures. Journal of Personality and Social Psychology, 91(5), 904–917. https://doi.org/10.1037/0022-3514.91.5.904.
Gable, S. L., Reis, H. T., Impett, E. A., & Asher, E. R. (2004). What do you do when things go right? The intrapersonal and interpersonal benefits of sharing positive events. Journal of Personality and Social Psychology, 87(2), 228–245.
Goldsmith, D. J., McDermott, V. M., & Alexander, S. C. (2000). Helpful, supportive and sensitive: Measuring the evaluation of enacted social support in personal relationships. Journal of Social and Personal Relationships, 17(3), 369–391. https://doi.org/10.1177/0265407500173004.
Goodman, J. K., Cryder, C. E., & Cheema, A. (2012). Data collection in a flat world: The strengths and weaknesses of mechanical turk samples. Journal of Behavioral Decision Making, 26(3), 213–224.
Green-Hamann, S., & Sherblom, J. C. (2014). The influences of optimal matching and social capital on communicating support. Journal of Health Communication, 19(10), 1130–1144. https://doi.org/10.1080/10810730.2013.864734.
Grunig, J. E., & Huang, Y. H. (2000). From organizational effectiveness to relationship indicators: Antecedents of relationships, public relations strategies, and relationship outcomes. In J. A. Ledingham & S. D. Bruning (Eds.), Public relations as relationship management. Lawrence Erlbaum Associate: Mahwah, NJ.
Haber, M. G., Cohen, J. L., Lucas, T., & Baltes, B. B. (2007). The relationship between self-reported received and perceived social support: A meta-analytic review. American Journal of Community Psychology, 39(1–2), 133–144. https://doi.org/10.1007/s10464-007-9100-9.
Hayes, A. F. (2013). An introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press.
Hayes, A. F., & Rockwood, N. J. (2020). Conditional process analysis: Concepts, computation, and advances in modeling the contingencies of mechanisms. American Behavioral Scientist, 64(1), 19–54.
Hendrick, S. S. (1988). A generic measure of relationship satisfaction. Journal of Marriage and the Family, 50(1), 93–98. https://doi.org/10.2307/352430.
High, A. C. (2011). The production and reception of verbal person-centered social support in face-to-face and computer-mediated dyadic conversations (unpublished doctoral dissertation). University Park, PA: The Pennsylvania State University.
High, A. C., & Solomon, D. (2008). Locating computer-mediated social support within online communication environments. Conference paper presented at National Communication Association. San Diego CA.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55. https://doi.org/10.1080/10705519909540118.
Jacob, C., Gueguen, N., & Boulbry, G. (2018). How proof of previous donations influences compliance with a donation request: Three field experiments. Int Rev Public Nonprofit Mark, 15, 1–8.
Knight, M., & Carpenter, S. (2012). Optimal matching model of social support: An examination of how national product and service companies use twitter to respond to consumers. Southwestern Mass Communication Journal, 27(2), 21–25.
Ko, H.-C., Wang, L.-L., & Xu, Y.-T. (2013). Understanding the different types of social support offered by audience to A-list diary-like and informative bloggers. Cyberpsychology, Behavior and Social Networking, 16(3), 194–199. https://doi.org/10.1089/cyber.2012.0297.
Liu, J., Li, C., Carcioppolo, N., & North, M. (2016). Do our Facebook friends make us feel worse? A study of social comparison and emotion. Human Communication Research, 42(4), 619–640. https://doi.org/10.1111/hcre.12090.
Lovejoy, K., & Saxton, G. D. (2012). Information, community, and action: How nonprofit organizations use social media. Journal of Computer-Mediated Communication, 17, 337–353. https://doi.org/10.1111/j.1083-6101.2012.01576.x.
MacGeorge, E. L. (2001). Support providers’ interaction goals: The influence of attributions and emotions. Communication Monographs, 68(1), 72–97. https://doi.org/10.1080/03637750128050.
Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s mechanical Turk. Behavior Research Methods, 44(1), 1–23.
Meng, J., Martinez, L., Holmstrom, A., Chung, M., & Cox, J. (2017). Research on social networking sites and social support from 2004 to 2015: A narrative review and directions for future research. CyberPsychology, Behavior & Social Networking, 20(1), 44–51. https://doi.org/10.1089/cyber.2016.0325.
Mews, M., & Boenigk, S. (2013). Does organizational reputation influence the willingness to donate blood? Int Rev Public Nonprofit Mark, 10, 49–64.
Mittelman, R., & Rojas-Mendez, J. (2018). Why Canadians give to charity: An extended theory of planned behavior model. Int Rev Public Nonprofit Mark, 15, 189–204.
Morelli, S. A., Lee, I. A., Arnn, M. E., & Zaki, J. (2015). Emotional and instrumental support provision interact to predict well-being. Emotion, 15(4), 484–493. https://doi.org/10.1037/emo0000084.
M+R Benchmarks (2019), The 2019 M+R Benchmarks Study, available at https://mrbenchmarks.com/numbers
Nah, S., & Saxton, G. D. (2012). Modeling the adoption and use of social media by nonprofit organization. New Media & Society, 15(2), 294–313. https://doi.org/10.1177/1461444812452411.
Nonprofit tech for good (2018). 2018 global trends in giving report. Available at https://givingreport.ngo/wp-content/uploads/2018-GivingReport-English.pdf
Source, N. P. (2018). The ultimate list of charitable giving statistics for, 2018 Available at https://nonprofitssource.com/online-giving-statistics/.
Parsons, L. M. (2007). The impact of financial information and voluntary disclosure on contributions to not-for-profit organizations. Behavioral Research in Accounting, 19, 179–196.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891.
Preece, J., Nonnecke, B., & Andrews, D. (2004). The top five reasons for lurking: Improving community experiences for everyone. Computers in Human Behavior, 20(2), 201–223. https://doi.org/10.1016/j.chb.2003.10.015.
Ray, E. B., & Miller, K. I. (1991). The influence of communication structure and social support on job stress and burnout. Management Communication Quarterly, 4(4), 506–527.
Rockwood, N. J., & Hayes, A. F. (2020). Mediation, moderation, and conditional process analysis: Regression-based approaches for clinical research. In A. G. C. Wright & M. N. Hallquist (Eds.), Handbook of research methods in clinical psychology. Cambridge: University Press.
Saxton, G. D., Kuo, J.-S., & Ho, Y.-C. (2012). The determinants of voluntary financial disclosure by nonprofit organizations. Nonprofit and Voluntary Sector Quarterly, 41(6), 1051–1071. https://doi.org/10.1177/0899764011427597.
Trepte, S., Dienlin, T., & Reinecke, L. (2015). Influence of social support received in online and offline contexts on satisfaction with social support and satisfaction with life: A longitudinal study. Media Psychology, 18(1), 74–105. https://doi.org/10.1080/15213269_2013_838904.
Turner, J. W., Grube, J. A., & Meyers, J. (2001). Developing an optimal match within online communities: An exploration of CMC support communities and traditional support. Journal of Communication, 51(2), 231–251. https://doi.org/10.1111/j.1460-2466.2001.tb02879.x.
Waters, R. D., Burnett, E., Lamm, A., & Lucas, J. (2009). Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public Relations Review, 35(2), 102–106. https://doi.org/10.1016/j.pubrev.2009.01.006.
Waters, R. D., & Jamal, J. Y. (2011). Tweet, tweet, twee: A content analysis of nonprofit organizations’ twitter updates. Public Relations Review, 37(2), 321–324. https://doi.org/10.1016/j.pubrev.2011.03.002.
Xie, J., Sreenivasan, S., Korniss, G., Zhang, W., Lim, C., & Szymanski, B. K. (2011). Social consensus through the influence of committed minorities. Physical Review, 84(1), 1–9. https://doi.org/10.1103/PhysRevE.84.011130.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hong, C., Li, C. How to turn lurkers into donors? A study of online social support interactions between nonprofit organizations and their followers. Int Rev Public Nonprofit Mark 17, 527–547 (2020). https://doi.org/10.1007/s12208-020-00255-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12208-020-00255-2