Sponsor
Portland State University. Systems Science Ph. D. Program
First Advisor
Leslie B. Hammer
Date of Publication
1-1-2011
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.) in Systems Science: Psychology
Department
Systems Science
Language
English
Subjects
Supervision of employees -- Psychological aspects, Work and family, Multilevel models (Statistics)
DOI
10.15760/etd.179
Physical Description
1 online resource (xii, 172 p.) : ill.
Abstract
There is a growing awareness that informal supports such as family-supportive supervision are critical in assuring the success of work-life policies and benefits. Furthermore, it is believed that family-supportive supervision may have positive effects regardless of the number or quality of work-life polices and benefits an organization has in place. Given this recognition, work-life experts have emphasized the need for supervisor training to increase family-supportive supervision. To date however, there has been a paucity of research on the predictors of family-supportive supervision which could be used as the target of such a training intervention. This dissertation had three major aims: 1) to investigate which supervisor-level (e.g., reward system, productivity maintenance, salience of changing workforce, belief in business case, awareness of organizational policies and benefits, role-modeling) and employee-level (e.g., support sought) factors are most strongly related to family-supportive supervision; 2) to explore whether supervisor factors moderate the relationship between support sought and family-supportive supervision; 3) and to use a multilevel design to confirm the association between family-supportive supervision and work-family conflict. This study used a cross-sectional, two-level (e.g., supervisor, and employee) hierarchical design. The data were collected from supervisors (Nurse Managers N=67) and employees (Nurses N=757) at five hospitals in the Pacific Northwest. All of the major analyses were conducted using multi-level regression in HLM. The results indicated that family-supportive supervision was higher for employees who worked for managers with a stronger belief in the business case and for employees who sought support. None of the other supervisor-level factors were found to be significant predictors of family supportive supervision. There was no evidence that supervisor-level factors moderated that relationship between support sought and family-supportive supervision. Higher levels of family-supportive supervision were related to lower work-to-family conflict. These findings suggest that organizations seeking to reduce work-family conflict and increase family supportive supervision should consider intervening at multiple levels. This dissertation reviews a rich body of evidence demonstrating the business case for offering work-life supports that could serve as a starting point for developing a training to increase supervisors' belief in the business case. In addition, strategies for organizations to increase support seeking, which has been shown to be an important coping mechanism, are discussed. The multi-level design of this dissertation also contributes to the literature by demonstrating that the largest proportion of variability in family-supportive supervision is at the employee-level. This finding suggests the importance of measuring family-supportive supervision at the employee-level and suggests that future research should focus on the employee-level predictors of family-supportive supervision.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
http://archives.pdx.edu/ds/psu/6994
Recommended Citation
Hanson, Ginger Charmagne, "A Multi-Level Study of the Predictors of Family-Supportive Supervision" (2011). Dissertations and Theses. Paper 179.
https://doi.org/10.15760/etd.179
Comments
Portland State University. Systems Science Ph. D. Program