Executive Doctorate of Business Administration (DBA)

This course is designed to help DBA students to understand better their career choices and/or broaden their perspective of career possibilities, with the executive DBA degree. Different disciplinary perspectives from Accounting, Analytics, Economics, Finance, Management, and Marketing will be shared. Alumni of DBA programs from Dolan School and other business schools will be invited as guest speakers to share their experiences and reflections. Students will be evaluated based on their participation, a career portfolio and sharing of their own career aspirations after completing the DBA degree.

This course introduces students to the art of university teaching and Ignatian pedagogy (IP) which encourages education of the whole student (cura personalis). Students will learn the Ignatian Pedagogy Paradigm (IPP), which speaks to the continuous nature of the cycle of learning. Faculty and alumni, who are experts in this area, will be invited as guest speakers to share their experiences and reflections. Students will be evaluated based on their participation in classes, sharing of reflection on university teaching, and a course design project.

Since the Executive DBA program is designed to produce practicing scholars, this course aims to develop student’s understanding of the importance of disseminating knowledge and ways to do so. These include academic and trade publications, digital media platforms, and other effective means. Experts familiar with the process of scholarly writing and different publication avenues will be invited to share their expertise and experiences. Students will be evaluated based on their participation in class and a written assignment detailing their plan of disseminating their dissertation work.

Understanding the theoretical framework of how firm operates, is essential to identify new areas of study for the modern organization. In order to maintain effectiveness and competitiveness in the fast-paced national, global and local environment, a firm needs to continuously examine in external and internal environment and evolve through dynamic capabilities of adapting to the changes. This course examines the dynamics of complex, global organizations through the lenses of foundational theory of firms. These include strategic management; theory of organizations and industries; and behavior of individuals, groups, and organizations in global settings.

This course brings together contemporary research topics across the major functional areas of business. Topics include leadership, ethics and social justice, innovation, entrepreneurship, international business, artificial intelligence, technology, human capital. The course focus on how to approach these issues in new ways and discover research opportunities. Students will learn to build on this foundational research by formulating new research questions that address emerging issues and challenges for the modern organization.

Quantitative research methods fall into two categories: exploration and testing. This first course in quantitative research methods focuses on the tools, techniques, and approaches of exploratory data analysis for the purpose of discovering patterns and conjecturing new explanations. Students will learn the fundamentals of data collection, cleaning, and management, visualization, and exploration. Topics include sampling considerations, missing data, data integrity, normalization, correlation analysis, principle component analysis, clustering techniques, standard charts and graphs, advanced visualization techniques to display as much of the data as possible, and data interpretation. Students will have guided reading of both classic and state-of-the-art articles. Cases will be used to illustrate these techniques and datasets will be used by students to in their hands-on projects to learn these techniques including: normality violations, multi-collinearity, and missing data.

This second course in quantitative research methods focuses on the tools, techniques, and approaches of hypothesis testing for the purpose of testing competing explanations based on the observed outcomes and interpretation of results. Students will learn the relationship between null and alternative hypotheses, design of experiments, p-values and rejection regions, metrics of fit for both classification and regression problems, multivariate linear and logistic regression analysis, and introduction to time series analysis and structural equation modelling. Students will test datasets for potential violations of the assumptions needed for these methods, including non-normality and multi-collinearity. Students will have guided reading of both classic and state-of-the-art articles. The discussion of the readings will emphasize model development and application. Cases with included datasets will be used for students in projects to formulate and then test multiple possible hypotheses.

Qualitative research seeks to answer questions about the ‘what,’ ‘why,’ and ‘how’ of social phenomena within their natural settings. In this course, graduate students will understand the principles of qualitative research that will cover research design, data collection, data analysis, inferences for problem solving, theory building and presentation of findings. Philosophical approaches from various business disciplines will be discussed. Students will learn a variety of qualitative techniques such as case studies, in-depth interviews, focus groups, ethnography, content analysis and others through grounded theory building and thematic analysis. Particular attention will be given to the ethics of research, the role of the researcher, relationships within the context researched, and the quality criteria for qualitative research.

In this one-on-one seminar course led by the dissertation chair, students will examine a curated selection of discipline-specific, peer-reviewed journal articles important to and representative of the discipline. A unique list of articles will be pre-set for each discipline but can be adjusted by the dissertation chair based on student interest. At the end of the semester, students will identify their subfield of interest for dissertation research and, with consultation from the dissertation chair, produce a reading list to be examined in Research Seminar II. Students will be evaluated on the understanding and presentation of the selected papers, identification of the dissertation research topic area, and the quality and content of the reading list for Research Seminar II.

In this instructor led seminar, students will conduct a focused literature review based on the reading list generated at the end of Research Seminar I. They will synthesize and find their dissertation research question from this reading list. Throughout the semester, students will present to their peers. With consultation from the dissertation chair and guidance from the course instructor, this work will culminate in a written literature review that concludes with a more focused area from which the dissertation topic will evolve. The goal of this course is to finish the draft of the literature review section of the dissertation. Research paper generated from this seminar will be part of the dissertation. The instructor will design the class to achieve the goals of the seminar through structured steps, assignments, directional advice, and a peer-learning and supportive community. Students will be evaluated based on the quality and timely completion of the write-up of the literature review related to the dissertation research question.Research Seminar III: Hypotheses & Theory Development    

Under the guidance of the dissertation chair, each student will work independently to identify and learn about the methodologies appropriate for their dissertation topic and hypothesis testing. Students will collect or secure the data needed to test the hypotheses identified in Research Seminar III. Students will be evaluated based on the appropriateness of the methodologies to be used and whether the required data to test the hypotheses have been secured.