Abstract: Characterizing Organizational Complexity within Private Child Welfare Agencies: An Empirical Typology Study (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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Characterizing Organizational Complexity within Private Child Welfare Agencies: An Empirical Typology Study

Wednesday, January 20, 2021
* noted as presenting author
Monia Perez Jolles, PhD, Assistant Professor, University of Southern California
Bowen McBeath, PhD, Professor, Portland State University
Emmeline Chuang, PhD, Associate Professor, University of California Berkeley, Berkeley, CA
Crystal Collins-Camargo, PhD, Professor, University of Louisville, KY
Background and Purpose. Private child welfare agencies (PCWAs) are key players in the delivery of safety net services for children and families. Yet, they face steep challenges as they strive for efficient performance and use of research evidence while navigating dynamic and unpredictable organizational environments. Some sources of organizational complexity include the need for CWAs to interface with neighboring agencies such as mental health and juvenile justice agencies, steep market competition, dwindling financial resources, evolving client needs, volatile political and institutional forces, and growing demand for efficiency and use of evidence-informed practices. Research fails to capture the complex nature of these organizational environments to better inform managerial and service delivery efforts. This paper fills this gap by applying complexity theory to characterize CWAs’ environments. Our research question was whether there are empirical typologies reflecting the multi-level sources of variation within PCWAs.

Methods. This study used a national survey of 229 PCWAs participating in a 2016 web-based survey - Improving Performance with Evidence (IPWE). The IPWE study had a goal of identifying organizational supports used by private CWAs to promote use of research and other forms of evidence and those environmental (inner and outer) factors influencing evidence use efforts. The overall response rate of the survey was 52%; state-specific response rates ranged from 45-70%. Respondents were upper management or other senior leaders. For multiple respondents within a single agency, we kept only the respondent with the highest managerial role and seniority. This approach yielded an analytical sample of n=186 agencies. Cluster analysis differentiated CWAs’ organizational complexity based on nine indicators: agency size (number of FTEs); service type (child welfare, behavioral health, and other); number of revenue sources; perceived revenue predictability, accreditation status, agency type (stand-alone vs. multi-site); and number and type of inter-organizational ties (i.e., ties with peer child welfare agencies, ties with behavioral health and juvenile justice agencies, and ties with external consortiums, networks or institutions).

Results. Despite high variation across the nine organizational complexity indicators, four distinct clusters emerged, which can be grouped into two main typologies based on their level of differentiation (convergence criterion was satisfied; about 95% of original grouped cases correctly classified). PCWAs’ organizational complexity derived from their organizational structure and from their level of inter-organizational ties. Complexity in organizational structure typology (32% of agencies, n=60) was characterized by un-accredited agencies, small sized, stand-alone status, with limited service diversity and fewer revenue sources (i.e., contracts, insurance, private or other). Complexity in organizational ties typology (68%; n=126) was characterized by agencies with low, medium and high levels of inter-organizational ties.

Conclusions and Implications. We identified two distinct typologies of PCWAs’ organizational complexity related to how these agencies operate and related to their level of inter-organizational linkages. This study has relevant implications for practice. Managers can better account for contextual complexity in their efforts to maximize evidence use by implementing strategies that are best suited for the identified typologies. Further research is warranted on drivers of these complexity typologies and pathways to outcomes.