Factors which influence client satisfaction with the services of community development corporations

Abstract

The primary purpose of this study was to determine factors which influence client satisfaction with the services of community development corporations (CDCs) in metropolitan regions of Louisiana. The CDCs were evaluated based on five specific criteria: housing, social services, workforce development, educational enrichment, and community outreach. The objectives addressed were: description of clients, levels of client satisfaction, and relationships between satisfaction and selected demographic characteristics. The instrument used in this study was a researcher-designed survey questionnaire used to collect client information. It was comprised of two sections – demographics and client satisfaction. The target population for this study was adult clients of at least 18 years of age who participated in housing programs operated by CDCs in the state of Louisiana. This study focused on selected CDCs which provided housing in the cities of Baton Rouge and New Orleans, Louisiana. The entire population of 458 Louisiana CDC clients in Baton Rouge and New Orleans was surveyed. Data were collected by mailed questionnaire. After two mailings, a telephone contact, and on-site follow-up, the researcher received a 45.2% usable response rate. The population studied included clients serviced by CDCs from the year 1994 through the present, who currently reside in a housing development of the CDC. Variables examined included: age, race, gender, marital status, household income, education level, number of children, household members over the age of 18, length of participation in CDC, and client region. Findings of the study revealed that household income and education could be determining factors in promoting client satisfaction with the services of CDCs. A model was identified using multiple regression analysis which explained 18.1% of the variance in the extent to which client’s overall satisfaction can be explained by the data. Five variables, household income, education, number of children under 18, gender, and race were identified in the model.