Ph.D. in Human Resource Management

The doctoral program in human resource management (HRM) prepares students for success in research universities as faculty members specializing in human resources. Doctoral students work closely with faculty to gain research and teaching expertise in the various functions and activities carried out as part of HRM, including the relationship between these practices and organizational strategies, cultures, and performance.

Many HRM scholars specialize or focus on more micro-level work, such as researching the impact of specific HR practices (e.g., selection or training techniques) on individual-level measures of satisfaction or performance. Alternatively, macro-level HR (i.e., “strategic HRM”) scholars study the effects of systems of HR policies and practices on organizational-level outcomes. KU faculty have expertise at both levels, as evidenced by publications in prestigious outlets.

Published faculty research

Application deadlines

Priority: January 5, 2023
Final: February 1, 2023

Admissions

Program details

Core courses

A graduate course in economics

BE 701: Business Economics OR BE 917: Advanced Managerial Economics OR ECON 700: Survey of Microeconomics

BE 917: Business Economics, is preferred. Students coming into the program directly from an undergraduate degree may consider substituting BE 701: Business Economics, or ECON 700: Survey of Microeconomics. In the event a student has taken a graduate economics course prior to enrolling as a KU doctoral student, she/he may waive the requirement and substitute either an elective doctoral content course or a statistics/research methods course for this requirement.

MGMT 905: Macro Management Research Methods

MGMT 906: Micro Management Research Methods

MGMT 916: Major Management Theories

1 of 2

Management Area HRM Content Courses (MGMT 950 or MGMT 951)

1 of 2

Management Area OB Content Courses (MGMT 953 or MGMT 954)

1 of 2

Management Area Strategy Content Courses (MGMT 956 or MGMT 957)

Concentration courses

Second Management Area Course from Student’s Area of Specialization

Elective Content or Statistics/Methods Course

Supporting courses

PSYC 790: Statistical Methods in Psychology I

PSYC 791: Statistical Methods in Psychology II

PSYC 893: Multivariate Analysis

PSYC 894: Multilevel Modeling

PSYC 896: Structural Equation Modeling I

For more information, view a detailed list of courses in the academic catalog.

Area of concentration

Most students typically will select the specific area to which they are admitted (human resources) as their concentration. However, an aspirant, with the assistance of his or her faculty advisor and the area faculty, may propose an interdisciplinary area of concentration that is a combination of the traditional business disciplines of accounting, finance, marketing, decision sciences, organizational behavior, and strategic management. An aspirant may also propose an interdisciplinary area of concentration that includes emphases such as international business, law, and economics. The aspirant must take at least five advanced courses in the area of concentration. These courses may include those offered outside the School of Business.

Supporting areas

Coursework in the area of concentration is supplemented and strengthened by study in one or two supporting areas. A supporting area is one that supplements and complements the area of concentration. The aspirant will satisfy the supporting area requirement by taking at least four advanced courses in the supporting areas (at least two courses in each of two supporting areas, or at least four courses in one supporting area). Courses recommended for preparation for the qualifiers may not be included in satisfying the supporting area requirement.

Research methodology

For successful qualifier assessment, the student’s program of study should include adequate preparation in research methodology. A sound research is always grounded on sound methodology. A doctoral student in human resources management has the opportunity to develop methodological skill in probability and statistics, optimization, uncertain reasoning, game theory, and econometrics. A typical doctoral dissertation often utilizes one or more of the following research methodology: empirical, analytical, behavioral, and computational.