The Social Psychology of Organizations.

Communities have the potential to function effectively and adapt successfully in the aftermath of disasters. Drawing upon literatures in several disciplines, we present a theory of resilience that encompasses contemporary understandings of stress, adaptation, wellness, and resource dynamics. Community resilience is a process linking a network of adaptive capacities (resources with dynamic attributes) to adaptation after a disturbance or adversity. Community adaptation is manifest in population wellness, defined as high and non-disparate levels of mental and behavioral health, functioning, and quality of life. Community resilience emerges from four primary sets of adaptive capacities—Economic Development, Social Capital, Information and Communication, and Community Competence—that together provide a strategy for disaster readiness. To build collective resilience, communities must reduce risk and resource inequities, engage local people in mitigation, create organizational linkages, boost and protect social supports, and plan for not having a plan, which requires flexibility, decision-making skills, and trusted sources of information that function in the face of unknowns.

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Community Resilience as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness

This article integrates the literature on interorganizational relationships into six generalizable determinants of relationship formation, applies these determinants to the prediction of six types of interorganizational relations, and proposes hypotheses for future research that specify the conditions under which each determinant will he more likely to predict different types of relations. These determinants provide the basis for a general theory of interorganizational relationships and suggest that alternative theoretical perspectives on relationship formation provide important but only partial insights into why organizations enter into relationships with one another.

https://www.jstor.org/stable/pdfplus/258156.pdf

Determinants of Interorganizational Relationships: Integration and Future Directions

Concepts of uncertainty and information processing are used to integrate the diverse organization design/structure literatures. This approach more fully explicates the concept of congruence which lies at the heart of contingency ideas. The review suggests a contingency approach to design which develops a feasible set of structural alternatives from which the organization can choose.

Information Processing as an Integrating Concept in Organizational Design.

Current research in organizational innovation is extensive, yet, because of limitations in scope, most studies are not adequately encompassing. These studies typically relate organizational variables to innovation and control at most for the effect of one contingency factor. Because innovation depends upon a complex host of factors, such theories have limited predictive application. This study intends to develop and test theories that explain the variation in the organizational complexity-innovation relationship in greater detail. The study considers two major indicators of organizational complexity-structural complexity and organizational size. Hypotheses are proposed on the effects of 14 contingency factors on the relationships between structural complexity and innovation and organizational size and innovation. The contingency factors include environmental uncertainty, organizational size, industrial sectors, types of innovation, and stages of innovation adoption. Using a meta-analytic procedure for multivariate analysis, the hypotheses are then tested with data from published studies in organizational innovation during the last three decades. The effects of four methods variables-operational definitions of innovation, structural complexity and size, and similarity of data sources-are controlled for in testing the hypotheses. This process results in two powerful and encompassing models: 1 the association between structural complexity and innovation depends upon operational definition of complexity, environmental uncertainty, use of manufacturing organizations, use of service organizations, focus on technical innovations, focus on product innovations, and focus on implementation of innovation; and 2 the association between organizational size and innovation depends upon operational definition of size, environmental uncertainty, use of service organizations, use of for-profit organizations, focus on technical innovations, and focus on product innovations. These models suggest avenues for further theory development and research, which we discuss.

Organizational complexity and innovation: developing and testing multiple contingency models

Structural equation modelling with LISREL was used to investigate the factor structure of the Maslach Burnout Inventory (MBI). Emotional exhaustion was the most robust of the MBI's three factors, followed by depersonalization, while the personal accomplishment factor performed weakly. A new measurement model was developed in a sample of 197 nurses consisting of the emotional exhaustion and depersonalization dimensions, which were measured with five and two empirical MBI indicators, respectively. A test of invariance of the two-factor model across three samples (i.e. one calibration sample of nurses, and two validation samples consisting of hospital laboratory technicians and hospital managers with an effective sample size of 445) produced a good fit for the proposed two-factor model. Assessment of psychometric properties of the two-factor model produced (1) internal consistencies comparable to those reported in the literature for the MBI's originally specified emotional exhaustion and depersonalization sc...

A test of the Maslach Burnout Inventory in three samples of healthcare professionals

The competing values framework (CVF) formulated by Quinn and his colleagues was developed to specify the criteria of organizational effectiveness and was later used to study a wide range of organizational phenomena such as culture and change. We extend this work by using structural equations modeling (LISREL) to (a) test the CVF and (b) refine a scale that identifies the extent to which managers and other organizational constituencies use the framework’s criteria to evaluate organizational effectiveness. Based on a sample of 300 hospital managers and supervisors, with one exception, our results support the CVF. Moreover, scores on the scale developed to measure the CVF criteria yield excellent validity and reliability estimates.

A Confirmatory Factor Analysis of the Competing Values Instrument.

Poor linkage cracks are defined and identified empirically in a postdisaster service delivery network. These cracks exist when essential services are provided only by isolated or peripheral clusters of organizations. Network analysis is used to identify the isolated and peripheral clusters of organizations. Measures of experience in responding to disasters and service capacity are used to identify the organizations whose services are essential in the network. Cracks prevent the network from responding effectively in the aftermath of a disaster. Suggestions are made for using network analysis to identify cracks and to improve planning and coordination in all kinds of service networks.

Cracks in a postdisaster service delivery network

Network analysis is presented as a useful extension of conventional forms of analysis. We introduce and illustrate basic features of network analysis. Reference materials are suggested and data from a network of 80 emergency service organizations are used to illustrate a matrix approach to network analysis. Our discussion shows how network analysis can complement standard modes of analysis to broaden and deepen the application of theories to social work. We conclude that network analysis has great potential in social work research and theory.

Social Network Analysis

Baorong Guo is in the social work faculty at the University of Missouri–St Louis and she is a faculty associate at the Center for Social Development (CSD) at Washington University in St Louis. Her current research focuses on inclusion of the poor in asset-building, human service non-profits and socio-economic development. Her recent research projects include the effects of household assets on material hardships, funding streams for human service non-profits and evaluation research on asset-based policies in the USA and China. Brian Perron studies services for persons with serious mental illnesses and substance use disorders, with an emphasis on comorbidities. Dr Perron has a range of teaching interests, with his primary interests relating to his practice experience in community mental health. His training in services research was supported by fellowships from the National Institute of Mental Health (T32) and the National Institute of Drug Abuse (F31). Other areas of research/scholarly interest: treatment processes, service access and utilization, evidence-based practices. Professor Gillespie is a national expert in the area of disaster preparedness and mitigation, specifically the integration of social work and social services with emergency management. Professor Gillespie teaches social measurement and structural equation modelling at the doctoral level and organizational dynamics and disaster preparedness at the master’s level. Professor Gillespie is a member of the FOCUS St Louis Regional Disaster Preparedness Task Force—a cross-section of 30 citizen leaders representing a range of perspective and skills charged with

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David F. Gillespie

Papers

A test of the Maslach Burnout Inventory in three samples of healthcare professionals

A Confirmatory Factor Analysis of the Competing Values Instrument.

Cracks in a postdisaster service delivery network

Social Network Analysis

A Systematic Review of Structural Equation Modelling in Social Work Research