The C.A.L.L. to Action Model of Community Engagement: examining how communication, alliance, leadership, and leverage combined to end chronic homelessness among veterans in Maricopa County, Arizona

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Description
This dissertation sought to understand how leaders in a public-private strategic alliance collaboratively address complex community problems. The study responded to the gap in academic research of leadership and public relations in alliances to solve complex social issues, as well

This dissertation sought to understand how leaders in a public-private strategic alliance collaboratively address complex community problems. The study responded to the gap in academic research of leadership and public relations in alliances to solve complex social issues, as well as the scant scholarly attention to alliance leaders' communications with stakeholders. Its findings corresponded to framing theory, stakeholder theory, SWOT (strengths/weaknesses/opportunities/threats) theory, complexity theory, and the subtopic of complex leadership -- all through the lens of public relations. This investigation culminated in the introduction of the C.A.L.L. to Action Model of Community Engagement, which demonstrates the confluence of factors that were integral to the alliance's success in eliminating chronic homelessness among veterans in Maricopa County, Arizona -- Communication, Alliance, Leadership, and Leverage. This qualitative case study used the method of elite or in-depth interviews and grounded theory to investigate the factors present in a community engagement that achieved its purpose. It served as a foundation for future inquiry and contributions to the base of knowledge, including 1) additional qualitative case studies of homeless alliances in other communities or of other social issues addressed by a similar public-private alliance; 2) quantitative methods, such as a survey of the participants in this alliance to provide triangulation of the results and establish a platform for generalization of the results to a larger population.
Date Created
2015
Agent