Date of Conferral
Doctor of Business Administration (D.B.A.)
U.S. Coast Guard leaders have received feedback concerning gaps in performance management of the Marine Inspection Program (MIP) from maritime industry stakeholders, Department of Homeland Security representatives, and internal agents over the past decade. The purpose of this case study was to explore strategies to improve performance in the U.S. Coast Guard MIP. Data were gathered through a review of documentation pertinent to marine inspection (i.e., policy, requirements, analyses, reports, and job aids) and 13 semistructured interviews with personnel from 3 distinct organizational levels. Study participants represented civilian and active duty personnel from all geographical U.S. Coast Guard districts, as well as tactical, strategic, and policy levels of the MIP. The conceptual framework of the study was Fusch and Gillespie's human competence model. Data analysis was based on coding of words, phrases, and sentences from multiple sources of data to identify recurring themes through methodological triangulation. The thematic analysis of the study data revealed themes that included lack of mission clarity, limited information management resources, differences in skills and knowledge management among inspectors, and unclear requirements for selecting a marine inspector. The study framework provided a basis for additional performance management research in government entities. The recommendations from this study may lead to social change through improved U.S. Coast Guard marine inspection services, which could result in greater safety, reduced pollution, and fewer security risks in the navigable waterways of the United States.
This study earned the Walden University College of Management and Technology Doctoral Study of the Year award in 2016.
Buck, Joshua, "Strategies to Improve Marine Inspection Performance in the U.S. Coast Guard" (2016). Walden Dissertations and Doctoral Studies. 2250.
Business Administration, Management, and Operations Commons, Management Sciences and Quantitative Methods Commons