A Dynamic Model for Managing Volunteer Engagement

Published Online:https://doi.org/10.1287/opre.2021.0419

References

  • Adusumilli KM, Hasenbein JJ (2010) Dynamic admission and service rate control of a queue. Queueing Syst. 66(2):131–154.CrossrefGoogle Scholar
  • Alwan AA, Ata B, Zhou Y (2023) A queueing model of dynamic pricing and dispatch control for Rride-hailing systems incorporating travel times. Preprint, submitted February 5, https://arxiv.org/abs/2302.02265.Google Scholar
  • AmeriCorps & Senior Corps (2019) Research – Overview statistics. AmeriCorps & Senior Corps. Accessed May 21, 2019, https://www.nationalservice.gov/serve/via/research.Google Scholar
  • Ata B (2003) Dynamic control of stochastic networks. PhD dissertation, Stanford University, Stanford, CA.Google Scholar
  • Ata B (2005) Dynamic power control in a wireless static channel subject to a quality-of-service constraint. Oper. Res. 53(5):842–851.LinkGoogle Scholar
  • Ata B (2006) Dynamic control of a multiclass queue with thin arrival streams. Oper. Res. 54(5):876–892.LinkGoogle Scholar
  • Ata B, Barjesteh N (2019) Dynamic pricing of a multiclass make-to-stock queue. Preprint, submitted October 3, https://dx.doi.org/10.2139/ssrn.3464763.Google Scholar
  • Ata B, Kumar S (2005) Heavy traffic analysis of open processing networks with complete resource pooling: Asymptotic optimality of discrete review policies. Ann. Appl. Probab. 15:331–391.CrossrefGoogle Scholar
  • Ata B, Olsen TL (2009) Near-optimal dynamic lead-time quotation and scheduling under convex-concave customer delay costs. Oper. Res. 57(3):753–768.LinkGoogle Scholar
  • Ata B, Olsen TL (2013) Congestion-based leadtime quotation and pricing for revenue maximization with heterogeneous customers. Queueing Syst. 73(1):35–78.CrossrefGoogle Scholar
  • Ata B, Shneorson S (2006) Dynamic control of an m/m/1 service system with adjustable arrival and service rates. Management Sci. 52(11):1778–1791.LinkGoogle Scholar
  • Ata B, Tongarlak MH (2013) On scheduling a multiclass queue with abandonments under general delay costs. Queueing Syst. 74(1):65–104.CrossrefGoogle Scholar
  • Ata B, Zachariadis KE (2007) Dynamic power control in a fading downlink channel subject to an energy constraint. Queueing Syst. 55(1):41–69.CrossrefGoogle Scholar
  • Ata B, Barjesteh N, Kumar S (2020) Dynamic dispatch and centralized relocation of cars in ride-hailing platforms. Preprint, submitted September 14, https://dx.doi.org/10.2139/ssrn.3675888.Google Scholar
  • Ata B, Harrison JM, Shepp LA (2005) Drift rate control of a Brownian processing system. Ann. Appl. Probab. 15(2):1145–1160.CrossrefGoogle Scholar
  • Ata B, Lee D, Sonmez E (2019) Dynamic volunteer staffing in multicrop gleaning operations. Oper. Res. 67(2):295–314.AbstractGoogle Scholar
  • Ataseven C, Nair A, Ferguson M (2018) An examination of the relationship between intellectual capital and supply chain integration in humanitarian aid organizations: A survey-based investigation of food banks. Decision Sci. J. 49(5):827–862.CrossrefGoogle Scholar
  • Bell S, Williams R (2005) Dynamic scheduling of a parallel server system in heavy traffic with complete resource pooling: Asymptotic optimality of a threshold policy. Electron. J. Probab. 10(33):1044–1115.CrossrefGoogle Scholar
  • Bell SL, Williams RJ (2001) Dynamic scheduling of a system with two parallel servers in heavy traffic with resource pooling: Asymptotic optimality of a threshold policy. Ann. Appl. Probab. 11(3):608–649.CrossrefGoogle Scholar
  • Berenguer G, Shen Z-JM (2020) Challenges and strategies in managing nonprofit operations: An operations management perspective. Manufacturing Service Oper. Management 22(5):888–905.LinkGoogle Scholar
  • Brayko CA, Houmanfar RA, Ghezzi EL (2016) Organized cooperation: A behavioral approach. Behav. Soc. Issues 25:77–98.CrossrefGoogle Scholar
  • Budhiraja A, Ghosh AP, Lee C (2011) Ergodic rate control problem for single class queueing networks. SIAM J. Control Optim. 49(4):1570–1606.CrossrefGoogle Scholar
  • Bussell H, Forbes D (2002) Understanding the volunteer market: The what, where, who and why of volunteering. Internat. J. Nonprofit Volunt. Sect. Marketing 7:244–257.CrossrefGoogle Scholar
  • Chevalier P, Wein L (1993) Scheduling of network of queues: Heavy traffic analysis of a multistation closed network. Oper. Res. 41(4):743–758.LinkGoogle Scholar
  • Clary EG, Snyder M, Ridge RD, Miene PK, Haugen JA (1994) Matching messages to motives in persuasion: A functional approach to promoting volunteerism. J. Appl. Psych. 24(13):1129–1149.Google Scholar
  • Cnaan RA, Cascio TA (1998) Performance and commitment. J. Soc. Serv. Res. 24:1–37.CrossrefGoogle Scholar
  • Crabill TB (1972) Optimal control of a service facility with variable exponential service times and constant arrival rate. Management Sci. 18(9):560–566.LinkGoogle Scholar
  • Crabill TB (1974) Optimal control of a maintenance system with variable service rates. Oper. Res. 22(4):736–745.LinkGoogle Scholar
  • Csorgo M, Horvath L (1993) Weighted Approximations in Probability and Statistics (Wiley, Hoboken, NJ).Google Scholar
  • Einolf C (2018) Evidence-based volunteer management: A review of the literature. Volunt. Sector Rev. 9(2):153–176.CrossrefGoogle Scholar
  • Eisner D, Grimm R Jr, Maynard S, Washburn S (2009) The new volunteer workforce. Stanf. Soc. Innov. Rev. 7(Winter):32–37.Google Scholar
  • Ellis S (2010) From the Top Down: The Executive Role in Successful Volunteer Involvement (Energize Inc., Philadelphia).Google Scholar
  • Foster-Bey J, Grimm R Jr, Dietz N (2007) Keeping baby boomers volunteering. Corporation for National and Community Service, Washington, DC. Accessed July 5, 2019, https://www.nationalservice.gov/pdf/07_0307_boomer_report_summary.pdf.Google Scholar
  • Gallus J (2017) Fostering public good contributions with symbolic awards: A large-scale natural field experiment at Wikipedia. Management Sci. 63(12):3999–4015.LinkGoogle Scholar
  • Gazley B (2012) Predicting a volunteer’s future intentions in professional associations: A test of the penner model. Nonprofit Volunt. Sector Q. 42(6):1245–1267.CrossrefGoogle Scholar
  • George JM, Harrison JM (2001) Dynamic control of a queue with adjustable service rate. Oper. Res. 49(5):720–731.LinkGoogle Scholar
  • Ghamami S, Ward AR (2013) Dynamic scheduling of a two-server parallel server system with complete resource pooling and reneging in heavy traffic: Asymptotic optimality of a two-threshold policy. Math. Oper. Res. 38(4):761–824.LinkGoogle Scholar
  • Ghosh AP, Weerasinghe AP (2007) Optimal buffer size for a stochastic processing network in heavy traffic. Queueing Syst. 55(3):147–159.CrossrefGoogle Scholar
  • Ghosh AP, Weerasinghe AP (2010) Optimal buffer size and dynamic rate control for a queueing system with impatient customers in heavy traffic. Stochastic Process. Appl. 120(11):2103–2141.CrossrefGoogle Scholar
  • Goheen M (2018) Personal Communications (Volunteer Engagement Manager, Three Square, Las Vegas, NV).Google Scholar
  • Harrison JM (1988) Brownian models of queueing networks with heterogeneous customer populations. Fleming W, Lions P-L, eds. Stochastic Differential Systems, Stochastic Control Theory and Applications (Springer, Berlin, Heidelberg), 147–186.CrossrefGoogle Scholar
  • Harrison JM (1996) The BIGSTEP approach to flow management in stochastic processing networks. Kelly FP, Zachary S, Ziedins I, eds. Stochastic Networks Theory Applications (Oxford University Press, Oxford, UK), 147–186.Google Scholar
  • Harrison JM (1998) Heavy traffic analysis of a system with parallel servers: Asymptotic optimality of discrete-review policies. Ann. Appl. Probab. 8(3):822–848.CrossrefGoogle Scholar
  • Harrison JM (2000) Brownian models of open processing networks: Canonical representation of workload. Ann. Appl. Probab. 10(1):75–103.CrossrefGoogle Scholar
  • Harrison JM, Wein LM (1989) Scheduling networks of queues: Heavy traffic analysis of a simple open network. Queueing Syst. 5(4):265–279.CrossrefGoogle Scholar
  • Harrison JM, Wein LM (1990) Scheduling networks of queues: Heavy traffic analysis of a two-station closed network. Oper. Res. 38(6):1052–1064.LinkGoogle Scholar
  • Harrison J, Williams R, Chen H (1990) Brownian models of closed queueing networks with homogeneous customer populations. Stochast. Stochast. Rep. 29(1):37–74.CrossrefGoogle Scholar
  • Haski-Leventhal D, Hustinx L, Handy F (2011) What money cannot buy: The distinctive and multidimensional impact of volunteers. J. Community Pract. 19(2):138–158.CrossrefGoogle Scholar
  • Henderson AC, Sowa J (2019) Volunteer satisfaction at the boundary of public and nonprofit: Organizational- and individual-level determinants. Public Perform. Management Rev. 42(1):162–189.CrossrefGoogle Scholar
  • Hewitt M, Nowak M, Gala L (2015) Consolidating home meal delivery with limited operational disruption. Eur. J. Oper. Res. 243(1):281–291.CrossrefGoogle Scholar
  • Kogan Y, Lipster R (1993) Limit non-stationary behavior of large closed queueing networks with bottlenecks. Queueing Syst. 14(1–2):33–55.CrossrefGoogle Scholar
  • Krichagina E, Puhalskii A (1986) Gaussian diffusion approximation of closed Markov model of computer networks. Probl. Inform. Transm. 22:38–51.Google Scholar
  • Krichagina E, Puhalskii A (1997) A heavy-traffic analysis of a closed queueing system with a gi/∞ service center. Queueing Syst. 25:235–280.CrossrefGoogle Scholar
  • Kumar R, Lewis ME, Topaloglu H (2013) Dynamic service rate control for a single-server queue with Markov-modulated arrivals. Naval Res. Logist. 60(8):661–677.CrossrefGoogle Scholar
  • Maglaras C (1999) Dynamic scheduling in multiclass queueing networks: Stability under discrete-review policies. Queueing Syst. 31(3–4):171–206.CrossrefGoogle Scholar
  • Maglaras C (2000) Discrete-review policies for scheduling stochastic networks: Trajectory tracking and fluid-scale asymptotic optimality. Ann. Appl. Probab. 10(3):897–929.CrossrefGoogle Scholar
  • Manshadi V, Rodilitz S (2022) Online policies for efficient volunteer crowdsourcing. Management Sci. 68(9):6572–6590.LinkGoogle Scholar
  • McBride AM, Lee Y (2012) Institutional predictors of volunteer retention: The case of AmeriCorps national service. Admin. Soc. 44(3):343–366.CrossrefGoogle Scholar
  • Nesbit R, Christensen RK, Brudney JL (2018) The limits and possibilities of volunteering: A framework for explaining the scope of volunteer involvement in public and nonprofit organizations. Public Admin. Rev. 78(4):502–513.CrossrefGoogle Scholar
  • Reed J, Ward A, Zhan D (2013) On the generalized Skorokhod problem in one dimension. J. Appl. Probab. 50(1):16–26.CrossrefGoogle Scholar
  • Rehnberg SJ (2009) Strategic volunteer engagement: A guide for nonprofit and public sector leaders. RGK Center for Philanthropy & Community Service. Accessed June 19, 2019, https://www.volunteeralive.org/docs/Strategic%20Volunteer%20Engagement.pdf.Google Scholar
  • Rubino M, Ata B (2009) Dynamic control of a make-to-order, parallel-server system with cancellations. Oper. Res. 57(1):94–108.LinkGoogle Scholar
  • Sampson SE (2006) Optimization of volunteer labor assignments. J. Oper. Management 24(4):363–377.CrossrefGoogle Scholar
  • Simmonds C (2014) Quality volunteers are vital and are becoming part of charity workforce. The Guardian (June 12), https://www.theguardian.com/voluntary-sector-network/2014/jun/12/volunteering-charity-value-quality-ability.Google Scholar
  • Smorodinskii AV (1986) Asymptotic-distribution of the queue length in a queueing system. Automation and Remote Control 8(2):230–237.Google Scholar
  • Snyder M, Omoto A (2008) Volunteerism: Social issues perspectives and social policy implications. Soc. Issues Policy Rev. 2(1):1–36.CrossrefGoogle Scholar
  • Stidham S, Weber RR (1989) Monotonic and insensitive optimal policies for control of queues with undiscounted costs. Oper. Res. 37(4):611–625.LinkGoogle Scholar
  • Tang F, Morrow-Howell N, Songiee H (2009) Institutional facilitation in sustained volunteering among older adult volunteers. Soc. Work Res. 33(3):172–182.CrossrefGoogle Scholar
  • Three Square (2021) Three square overview. Three Square. Accessed May 23, 2019, https://www.threesquare.org/about-us/three-square-overview.Google Scholar
  • Urban Institute (2004) Volunteer management capacity in America’s charities and congregations: A briefing report. Urban Institute. Accessed July 5, 2019, http://webarchive.urban.org/UploadedPDF/410963_VolunteerManagment.pdf.Google Scholar
  • Urrea G, Pedranza-Martinex AJ, Besiou M (2019) Volunteer management in charity storehouses: Experience, congestion and operational performance. Production Oper. Management 28(10):2653–2671.CrossrefGoogle Scholar
  • Vecina ML, Chacón F, Sueiro M, Barrón A (2012) Volunteer engagement: Does engagement predict the degree of satisfaction among new volunteers and the commitment of those who have been active longer? Appl. Psych. 61(1):130–148.CrossrefGoogle Scholar
  • Wilson N, Wansink B, Swigert J, Waxman E (2015) Hunger relief programs and behavioral economics: An introduction. Paper Presented at 2015 AAEA Annual Meeting, San Francisco CA, 26–28 July.Google Scholar
  • Wisner P, Stringfellow A, Youngdahl W, Parker L (2005) The service volunteer – Loyalty chain: An exploratory study of charitable not-for-profit service organizations. J. Oper. Management 23(2):143–161.CrossrefGoogle Scholar
  • Wymer WW Jr, Starnes BJ (2001) Conceptual foundations and practical guidelines for recruiting volunteers to service in local nonprofit organizations: Part I. J. Nonprofit Public Sect. Marketing 9:63–96.CrossrefGoogle Scholar
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