Business Administration Doctor of Philosophy (Ph.D.) Degree
Business Administration
Doctor of Philosophy (Ph.D.) Degree
Advancing your knowledge and practice through research and the exploration of the latest trends and biggest challenges found at the intersection of business and technological innovation.
Overview for Business Administration Ph.D.
The Ph.D. in business administration is designed to inspire and train scholars to identify, investigate, and solve novel business challenges that influence business and society, particularly, those that are triggered by technological changes. Our program has a sharp emphasis on the effects of technological innovation on discipline-based theories and research. Our faculty adopt an apprenticeship model in working with students to become independent scholars, cutting-edge researchers, and well-trained educators at research-oriented universities.
The program offers three areas of specialization:
Digital Transformation: Digital transformation emphasizes the integration of digital technologies that have altered the marketing of products and services, as well as the management of information systems. In this area of specialization, you will study the design and development of digital artifacts and their implications for interpersonal interaction, analyze the modes of human information processing in digitally transformed business contexts, and theorize the emergence of new business models and ways of organizing in digitally immersive environments.
Strategy and Innovation: A distinct feature of 21st century competition is the pivotal role played by technological innovation as a competitive advantage for organizations. In the strategy and innovation specialization, research emphasizes the growing role of technological capabilities and innovation-based products and processes as a source of competitive advantage. You will acquire knowledge and skills to address novel research questions about firm-level strategy and innovation-related challenges faced by managers and policy makers.
Finance and Accounting: The finance and accounting specialization emphasizes new challenges and research areas that have emerged from technological innovations within finance and accounting disciplines. These areas include FinTech, high-frequency trading, alternative trading systems (dark pool and ECNs), crowdfunding platforms, P2P lending platforms, blockchains, cryptocurrencies, data analytic tools in auditing and credit rating, digital transformation of SEC filings and corporate disclosures. In this area of specialization, you will study the antecedents and consequences of technology in finance and accounting.
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Featured Work
Research Insights: Food tourism, a life satisfaction factor
Muhammet Kesgin
Food tourism contributes to long-term life satisfaction and sense of well-being
Ph.D. program in business administration, Oct. 3, 2022 information session
Research Insights: Accounting conservatism and qualitative disclosures
Ashok Robin, Kean Wu
Study explores the benefits of reporting bad news early
Featured Profiles
Ph.D. student from Tehran, Iran
’23
Ph.D. student, Negin Haghi from Tehran, Iran
Ph.D. student from Delta, Nigeria
’23
Ph.D. Student, Cindy Achedu Okoh from Delta, Nigeria
Ph.D. student from Trivandrum, India
’23
Ph.D. student, Biju Babukutty Varghese from Trivandrum, India
Latest News
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September 13, 2023
![a full auditorium with the president of R I T on stage shaking his hands in the air for the American sign language sign for applause.]()
RIT president charts vision for future during State of the University Address
In his welcome to the community for the start of a new academic year, RIT President David Munson asserted the university is well positioned to thrive while laying out “challenges, opportunities, and vision” for RIT’s future.
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August 24, 2023
![college professor sitting on a small sofa-like chair.]()
Saunders College of Business at RIT launches innovative Ph.D. in business administration
Saunders College of Business is entering its first cohort of students into the college’s new Ph.D. in business administration this fall, marking the university’s inaugural social sciences doctoral program. The program is designed to inspire and train scholars to identify, investigate, and solve unique business challenges that influence business and society.
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February 1, 2023
![students wearing eyewear and microphones along with faculty members looking at computer screens.]()
Doctoral offerings keep growing
RIT is growing its Ph.D. offerings, adding one new program in the fall of 2023 and two in 2024. This fall, Saunders College of Business will offer a Ph.D. in business administration. In 2024, the College of Liberal Arts will introduce a new doctoral degree in cognitive science and the College of Science will launch a Ph.D. in physics.
Curriculum for 2023-2024 for Business Administration Ph.D.
Current Students: See Curriculum Requirements
Business Administration, Ph.D. degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| MGIS-815 | Research Design The doctoral seminar course introduces students to the most prominent theoretical streams within the scholarly discipline of Management Information Systems. Students read, analyze, and discuss seminal research manuscripts within the field. Through these analyses, they discern underlying assumptions, philosophical/ ontological stances, and central arguments of the various works. In addition, students complete a focused exploration of the research corpus of one or more significant researchers within the discipline. Seminar 3 (Fall). |
3 |
| Choose one of the Research Methodology I courses: | 3 |
|
| ESCB-830 | Econometrics I This course is designed for doctoral students and serves as the first of a two-course sequence focused on modern econometric theory and methods. This foundational course covers essential concepts in statistics, including the theory, uses, and application of regression techniques under different conditions. The course will cover common econometric challenges in social sciences research and discuss techniques used to address them. The class adopts a hands-on approach, with students working with data to model and address econometric issues. Familiarity with basic statistics, calculus, and matrix algebra is required. (Prerequisites: MKTG-825 or equivalent course.) Seminar 3 (Spring). |
|
| MKTG-825 | Multivariate Methods and Analyses This course is designed introduce doctoral students to statistical methodology as it pertains to the study of multivariate techniques used in the behavioral sciences. The course will cover a range of statistical procedures and programs for multivariate data analysis. The focus is on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. Topics covered include multivariate data screening, analysis of variance, multi-dimensional scaling, factor analysis, OLS regression, mediation and moderation among others. Seminar 3 (Fall). |
|
| Choose one of the Research Methodology II courses: | ||
| ESCB-830 | Econometrics I This course is designed for doctoral students and serves as the first of a two-course sequence focused on modern econometric theory and methods. This foundational course covers essential concepts in statistics, including the theory, uses, and application of regression techniques under different conditions. The course will cover common econometric challenges in social sciences research and discuss techniques used to address them. The class adopts a hands-on approach, with students working with data to model and address econometric issues. Familiarity with basic statistics, calculus, and matrix algebra is required. (Prerequisites: MKTG-825 or equivalent course.) Seminar 3 (Spring). |
3 |
| ESCB-835 | Econometrics II This course is designed for doctoral students and serves as the second of a two-course sequence focused on modern econometric theory and methods. The course builds on the students’ knowledge of advanced econometric techniques used in social sciences research. Topics reviewed in foundational econometrics such as matching and causal identification, are examined in greater detail and rigor with a particular focus on issues such as censoring and selection bias. Relevant modeling techniques are reviewed with an emphasis their use in social science research. The class adopts a hands-on approach, with students working with data to model and address econometric issues. (Prerequisites: ESCB-830 or equivalent course.) Lec/Lab 3 (Fall). |
3 |
| MKTG-830 | Structural Equation Modeling This course provides a detailed look at structural equation modeling (SEM) for doctoral students. SEM is a technique for modeling the relationships among multiple latent variables. It includes models that have multiple indicators of constructs (latent variables; confirmatory factor analysis) that have directional relationships among constructs (path analysis; structural equations). The course will cover both conceptual and practical aspects of SEM, with the goal of preparing the student to use SEM in original research and to critically evaluate its use in scholarly work. Further, it introduces the student to partial least squares modeling and to Bayesian approaches in structural equations modeling. (Prerequisites: MKTG-825 or equivalent course.) Lec/Lab 3 (Spring). |
3 |
Focus Area Courses |
6 | |
Support Area Courses |
6 | |
SCB Electives |
3 | |
| Second Year | ||
| SCBI-801 | Business Administration PhD Second Year Paper Students will complete a graduate paper in their second year after all courses have been completed. Research (Fall, Spring). |
0 |
| SCBI-895 | Business Administration PhD Comprehensive Exam Students will demonstrate synthesis and integration of the theories and foundation principles of their discipline to respond to questions found in the comprehensive examination. This demonstration will apply core knowledge to problem situations to be successful students must receive a passing grade of at least 80 percent. Students will have one additional opportunity to pass this examination if their initial attempt is unsuccessful. Comp Exam (Fall, Spring). |
0 |
Focus Area Course |
9 | |
Support Area Courses |
6 | |
SCB Electives |
9 | |
| Third Year | ||
| SCBI-890 | Business Administration PhD Dissertation Research Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students must successfully pass the PhD comprehensive examination prior to enrolling in this course. Research 5 (Fall, Summer). |
10 |
| Fourth Year | ||
| SCBI-890 | Business Administration PhD Dissertation Research Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students must successfully pass the PhD comprehensive examination prior to enrolling in this course. Research 5 (Fall, Summer). |
10 |
| Fifth Year | ||
| SCBI-890 | Business Administration PhD Dissertation Research Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students must successfully pass the PhD comprehensive examination prior to enrolling in this course. Research 5 (Fall, Summer). |
10 |
| Total Semester Credit Hours | 78 |
|
Focus Areas
Students must declare a focus area in either Finance & Accounting, Strategy & Innovation or Digital Transformation. The tables below detail the courses for each focus area and corresponding support area and graduate electives.
Finance and Accounting Focus Area Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| ESCB-810 | Financial Economics Economics is an important foundation for business research. This course focuses on the behavior of individuals and firms in various market settings. Classical issues of demand, supply, and market equilibrium, as well as topics more germane to business research such as contracting and theory of firm are covered. Throughout, focus is on developing economic intuition, understanding applications to business research, and accumulating an in-depth understanding of useful economic theories and tools. Seminar 3 (Fall). |
3 |
| FINC-810 | Technology in Accounting and Finance This Ph.D. research seminar focuses on the two roles of technology in accounting and finance research in particular, and business research generally. First, the world of technology which includes information technology and analytics, has influenced research methods with techniques such as sentiment analysis and machine learning. Second, technology has transformed the practice of accounting and finance, through innovations such as the blockchain and has led to distinct areas of research such as fintech. This seminar will cover both aspects and has the objective of (a) allowing access to cutting edge research techniques and (b) developing research questions in tech related areas. Seminar 3 (Fall). |
3 |
| Students must choose three courses from the list below | ||
| ACCT-810 | Doctoral Seminar in Research in Financial Accounting This course introduces the landscape of financial accounting research. Three main topics will be included: 1) the use of accounting information by investors, creditors, analysts and other decision makers; 2) the preparation of accounting information by managers who may respond to economic incentives and use discretion to manage earnings; and 3) the regulation of accounting information by standard setters and other regulators who are evaluating the relevance and reliability of current and potential accounting information. (Prerequisites: ACCT-365 or ACCT-705 or equivalent course.) Seminar 3 (Fall). |
3 |
| ACCT-820 | Auditing Research Seminar This Ph.D. level course develops basic research topics in Auditing area. Focus is on developing a general understanding of the research questions tested in Auditing. Emphasis will also be placed on regulation and institutional issues affecting audit quality, auditor behavior, and audit markets. Furthermore, time will be devoted to discuss challenging research opportunities in auditing, the process of conducting audit research, and selecting the appropriate research methodology and design, which should help students to identify an important research topic and develop a sound research proposal. Seminar 3 (Fall). |
3 |
| ACCT-858 | Seminar: Special Topics in Accounting* This research seminar focuses on timely, special topics not covered in other seminars. Topics rotate based on faculty expertise (such as Financial Institutions and Markets, Behavioral Research in Accounting) and student needs as determined by the department. Seminar 3 (Biannual). |
3 |
| FINC-820 | Research Topics & Methods in Corporate Finance |
3 |
| FINC-830 | Research Topics & Methods in Investment & Asset Pricing Investment and Asset pricing theories are foundations of modern financial economics. This course focuses on the no arbitrage pricing under a general equilibrium framework. Specific topics include decisions under uncertainty, modern portfolio theories, option pricing, behavioral finance, and models with asymmetric information. Students develop a solid understanding of the Investment and Asset pricing literature and research methodologies and search for potential research topics in the area of asset pricing. Seminar 3 (Fall). |
3 |
| FINC-858 | Seminar: Special Topics in Finance* This research seminar focuses on timely, special topics not covered in other seminars. Topics rotate based on faculty expertise (such as Financial Institutions and Markets, Behavioral Research in Accounting) and student needs as determined by the department. Seminar 3 (Biannual). |
3 |
Finance and Accounting Support Area Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| Students must choose four courses from the list below | ||
| ACCT-745 | Accounting Information and Analytics The objective for this course is helping students develop a data mindset which prepare them to interact with data scientists from an accountant perspective. This course enables students to develop analytics skills to conduct descriptive, diagnostic, predictive, and prescriptive analysis for accounting information. This course focuses on such topics as data modeling, relational databases, blockchain, visualization, unstructured data, web scraping, and data extraction. (Prerequisites: ACCT-110 or ACCT-603 or equivalent course.) Lecture 3 (Fall, Summer). |
3 |
| BANA-680 | Data Management for Business Analytics This course introduces students to data management and analytics in a business setting. Students learn how to formulate hypotheses, collect and manage relevant data, and use standard tools such as Python and R in their analyses. The course exposes students to structured data as well as semi-structured and unstructured data. There are no pre or co-requisites; however, instructor permission is required for students not belonging to the MS-Business Analytics or other quantitative programs such as the MS-Computational Finance which have program-level pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
3 |
| FINC-780 | Financial Analytics This course provides a survey of financial analytics applications in contexts such as investment analysis, portfolio construction, risk management, and security valuation. Students are introduced to financial models used in these applications and their implementation using popular languages such as R, Matlab, and Python, and packages such as Quantlib. A variety of data sources are used: financial websites such as www.finance.yahoo.com, government sites such as www.sec.gov, finance research databases such as WRDS, and especially Bloomberg terminals. Students will complete projects using real-world data and make effective use of visualization methods in reporting results. There are no pre or co-requisites; however, instructor permission is required – student aptitude for quantitative work will be assessed; waived for students enrolled in quantitative programs such as the MS-Computational Finance which have pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
3 |
| MGIS-725 | Data Management and Analytics This course discusses issues associated with data capture, organization, storage, extraction, and modeling for planned and ad hoc reporting. Enables student to model data by developing conceptual and semantic data models. Techniques taught for managing the design and development of large database systems including logical data models, concurrent processing, data distributions, database administration, data warehousing, data cleansing, and data mining. Lecture 3 (Spring). |
3 |
| MGIS-805 | Advanced Data Analytics This Ph.D. research methodology course will introduce students to contemporary and advanced analytics techniques related to data acquisition, data preparation, data mining, and data reporting. Students will engage in hands-on experience with different techniques and will demonstrate the ability to carry a research project on their own using a combination of techniques taught in class. (Prerequisites: MGIS-650 or equivalent course.) Seminar 3 (Fall). |
3 |
Strategy & Innovation Focus Area Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| MGMT-820 | Foundations of Strategy Research This doctoral level seminar surveys the foundations of strategic management research, drawing primarily from economics, but also sociology and psychology theoretical perspectives towards understanding firm performance and related strategic issues. The main objective of the seminar is to familiarize students with the assumptions, concepts, and theories underlying the field of strategic management, as well as to help develop the skills necessary to evaluate, critique, and contribute to the field. Seminar 3 (Spring). |
3 |
| MGMT-821 | Organizational Behavior & Creativity This PhD seminar explores those topics in organizational behavior that explicate our understanding of creativity in organizations. This course draws upon trending as well as classic organizational behavior research to expose students to topics that are especially relevant to creativity, but it is not restricted to creativity literature. The objective of this course is to equip students with conceptual frameworks and analytical approaches that will serve as micro- and meso-level foundation to their understanding of organizational creativity and, ultimately, innovation. Seminar 3 (Spring). |
3 |
| MGMT-822 | Innovation This course covers foundational and advanced issues in innovation management, focusing on current trends as well as classic readings in innovation literature. This is a broad ranging seminar on the topics that undergird the organizational innovation, but excludes the individual level aggregation (i.e., creativity). The innovation seminar prepares the PhD candidate to understand conceptual frameworks and analytical approaches needed to critically evaluate and identify important issues underlying innovation in organizations. Seminar 3 (Fall). |
3 |
| MGMT-823 | Business, Technology and Society Business, Technology and Society introduces Ph.D. students to the theoretical foundations of research on the relationship between business, technology and society, including corporate social responsibility, the problems and promise of technological innovation, and the role of government policy and other institutional factors. The course will look at these issues within the context of a range of social issues. Students will be challenged to critically review seminal and emerging research, with a focus on both on theoretical arguments, research methods, and social relevance. Seminar 3 (Fall or Spring). |
3 |
| MGMT-824 | Contemporary Topics in Strategy Research Business, Technology and Society introduces Ph.D. students to the theoretical foundations of research on the relationship between business, technology and society, including corporate social responsibility, the problems and promise of technological innovation, and the role of government policy and other institutional factors. The course will look at these issues within the context of a range of social issues. Students will be challenged to critically review seminal and emerging research, with a focus on both on theoretical arguments, research methods, and social relevance. Seminar 3 (Fall). |
3 |
Strategy & Innovation Support Area Courses
Group A Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| Students must choose two courses from the list below | ||
| ESCB-835 | Econometrics II This course is designed for doctoral students and serves as the second of a two-course sequence focused on modern econometric theory and methods. The course builds on the students’ knowledge of advanced econometric techniques used in social sciences research. Topics reviewed in foundational econometrics such as matching and causal identification, are examined in greater detail and rigor with a particular focus on issues such as censoring and selection bias. Relevant modeling techniques are reviewed with an emphasis their use in social science research. The class adopts a hands-on approach, with students working with data to model and address econometric issues. (Prerequisites: ESCB-830 or equivalent course.) Lec/Lab 3 (Fall). |
3 |
| MGIS-805 | Advanced Data Analytics This Ph.D. research methodology course will introduce students to contemporary and advanced analytics techniques related to data acquisition, data preparation, data mining, and data reporting. Students will engage in hands-on experience with different techniques and will demonstrate the ability to carry a research project on their own using a combination of techniques taught in class. (Prerequisites: MGIS-650 or equivalent course.) Seminar 3 (Fall). |
3 |
| MGIS-811 | Qualitative Research Methods In this course, students learn and apply qualitative data collection and analysis methods in the context of business research. The course provides an overview of prominent qualitative research designs, including case study, field study, and ethnography. Students learn critical qualitative data collection techniques, including interviewing, field observation, and historical analysis. Finally, students explore different techniques for qualitative data analysis, including grounded theory methodology, thematic analysis, discourse analysis, and conversation analysis. Students will engage in hand-on experiences in each of the analytical methods to demonstrate skills in managing selected design, data collection, analysis and writing strategies of qualitative research. Seminar 3 (Spring). |
3 |
| MKTG-830 | Structural Equation Modeling This course provides a detailed look at structural equation modeling (SEM) for doctoral students. SEM is a technique for modeling the relationships among multiple latent variables. It includes models that have multiple indicators of constructs (latent variables; confirmatory factor analysis) that have directional relationships among constructs (path analysis; structural equations). The course will cover both conceptual and practical aspects of SEM, with the goal of preparing the student to use SEM in original research and to critically evaluate its use in scholarly work. Further, it introduces the student to partial least squares modeling and to Bayesian approaches in structural equations modeling. (Prerequisites: MKTG-825 or equivalent course.) Lec/Lab 3 (Spring). |
3 |
Group B Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| Students must choose two courses from the list below | ||
| ESCB-810 | Financial Economics Economics is an important foundation for business research. This course focuses on the behavior of individuals and firms in various market settings. Classical issues of demand, supply, and market equilibrium, as well as topics more germane to business research such as contracting and theory of firm are covered. Throughout, focus is on developing economic intuition, understanding applications to business research, and accumulating an in-depth understanding of useful economic theories and tools. Seminar 3 (Fall). |
3 |
| MGIS-810 | Societal Impacts of Digital Transformation Digital transformation refers to the widespread integration of digital technologies into almost all aspects of organizational and social interaction. This phenomenon has engendered a wide variety of new markets, ways of organizing, mechanisms for the delivery of goods and services, and modes of interpersonal exchange. In so doing, it has simultaneously engendered novel challenges to prevailing business models, organizational routines, foundational assumptions of social interaction, and traditional ethical frameworks. This doctoral seminar course explores the societal impacts engendered by the phenomenon of digital transformation. The course places a special emphasis on the implications for three facets of social interaction: (1) organizing and organizational forms, (2) consumer markets and experiences, and (3) interpersonal dynamics. Seminar 3 (Spring). |
3 |
| MGMT-825 | Seminar: Emergent Topics in Management This research seminar focuses on timely, special topics not covered in other seminars. Topics rotate based on faculty expertise (such as Creativity and Innovation, Groups and Teams, Corporate Social Responsibility) and student needs as determined by the department. Seminar 3 (Fall, Spring, Summer). |
3 |
| MKTG-805 | Psychological Foundations of Business Research This doctoral seminar course explores a range of theories and principles from the field of psychology with an eye to their applicability to contemporary business research. Critical topics explored include the study of human motivation, the nature of perception and learning, diverse models of cognition, principles of decision-making and choice, the role of personality and perceptions of the self, and group dynamics. Students will develop an understanding of the foundational role of these concepts in variety of business research disciplines. Seminar 3 (Spring). |
3 |
SCB Graduate Independent Study |
3 | |
Digital Transformation Focus Area Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| MGIS-805 | Advanced Data Analytics This Ph.D. research methodology course will introduce students to contemporary and advanced analytics techniques related to data acquisition, data preparation, data mining, and data reporting. Students will engage in hands-on experience with different techniques and will demonstrate the ability to carry a research project on their own using a combination of techniques taught in class. (Prerequisites: MGIS-650 or equivalent course.) Seminar 3 (Fall). |
3 |
| MGIS-810 | Societal Impacts of Digital Transformation Digital transformation refers to the widespread integration of digital technologies into almost all aspects of organizational and social interaction. This phenomenon has engendered a wide variety of new markets, ways of organizing, mechanisms for the delivery of goods and services, and modes of interpersonal exchange. In so doing, it has simultaneously engendered novel challenges to prevailing business models, organizational routines, foundational assumptions of social interaction, and traditional ethical frameworks. This doctoral seminar course explores the societal impacts engendered by the phenomenon of digital transformation. The course places a special emphasis on the implications for three facets of social interaction: (1) organizing and organizational forms, (2) consumer markets and experiences, and (3) interpersonal dynamics. Seminar 3 (Spring). |
3 |
| MGIS-812 | Management Information Systems: Theories and Perspectives** The doctoral seminar course introduces students to the most prominent theoretical streams within the scholarly discipline of Management Information Systems. Students read, analyze, and discuss seminal research manuscripts within the field. Through these analyses, they discern underlying assumptions, philosophical/ ontological stances, and central arguments of the various works. In addition, students complete a focused exploration of the research corpus of one or more significant researchers within the discipline. Seminar 3 (Fall). |
3 |
| MGMT-822 | Innovation This course covers foundational and advanced issues in innovation management, focusing on current trends as well as classic readings in innovation literature. This is a broad ranging seminar on the topics that undergird the organizational innovation, but excludes the individual level aggregation (i.e., creativity). The innovation seminar prepares the PhD candidate to understand conceptual frameworks and analytical approaches needed to critically evaluate and identify important issues underlying innovation in organizations. Seminar 3 (Fall). |
3 |
| MKTG-805 | Psychological Foundations of Business Research This doctoral seminar course explores a range of theories and principles from the field of psychology with an eye to their applicability to contemporary business research. Critical topics explored include the study of human motivation, the nature of perception and learning, diverse models of cognition, principles of decision-making and choice, the role of personality and perceptions of the self, and group dynamics. Students will develop an understanding of the foundational role of these concepts in variety of business research disciplines. Seminar 3 (Spring). |
3 |
| MKTG-810 | Marketing Theory** This doctoral-level seminar course provides students with an introduction to the research literature in the marketing discipline. The purpose of this course is to learn about marketing theory, analyze the literature and allow students and faculty to expose their work to others, receive feedback, and foster knowledge diffusion. In this course, students will read and discuss recent articles in top marketing journals. This course offers: (1) In-depth discussion of important topics in marketing by PhD students and faculty; (2) Exposure to existing theory/ literature of marketing for conducting research in those areas; and (3) The opportunity to experience on-going research being presented and discussed, rather than just experiencing finished-and-polished research products through manuscripts or publications. Seminar 3 (Spring). |
3 |
Digital Transformation Support Area Courses
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| Choose one from the following: | ||
| ESCB-830 | Econometrics I This course is designed for doctoral students and serves as the first of a two-course sequence focused on modern econometric theory and methods. This foundational course covers essential concepts in statistics, including the theory, uses, and application of regression techniques under different conditions. The course will cover common econometric challenges in social sciences research and discuss techniques used to address them. The class adopts a hands-on approach, with students working with data to model and address econometric issues. Familiarity with basic statistics, calculus, and matrix algebra is required. (Prerequisites: MKTG-825 or equivalent course.) Seminar 3 (Spring). |
3 |
| MGIS-811 | Qualitative Research Methods In this course, students learn and apply qualitative data collection and analysis methods in the context of business research. The course provides an overview of prominent qualitative research designs, including case study, field study, and ethnography. Students learn critical qualitative data collection techniques, including interviewing, field observation, and historical analysis. Finally, students explore different techniques for qualitative data analysis, including grounded theory methodology, thematic analysis, discourse analysis, and conversation analysis. Students will engage in hand-on experiences in each of the analytical methods to demonstrate skills in managing selected design, data collection, analysis and writing strategies of qualitative research. Seminar 3 (Spring). |
3 |
| Choose three courses from the following: | ||
| ESCB-835 | Econometrics II This course is designed for doctoral students and serves as the second of a two-course sequence focused on modern econometric theory and methods. The course builds on the students’ knowledge of advanced econometric techniques used in social sciences research. Topics reviewed in foundational econometrics such as matching and causal identification, are examined in greater detail and rigor with a particular focus on issues such as censoring and selection bias. Relevant modeling techniques are reviewed with an emphasis their use in social science research. The class adopts a hands-on approach, with students working with data to model and address econometric issues. (Prerequisites: ESCB-830 or equivalent course.) Lec/Lab 3 (Fall). |
3 |
| FINC-810 | Research Seminar: Technology in Accounting & Finance This Ph.D. research seminar focuses on the two roles of technology in accounting and finance research in particular, and business research generally. First, the world of technology which includes information technology and analytics, has influenced research methods with techniques such as sentiment analysis and machine learning. Second, technology has transformed the practice of accounting and finance, through innovations such as the blockchain and has led to distinct areas of research such as fintech. This seminar will cover both aspects and has the objective of (a) allowing access to cutting edge research techniques and (b) developing research questions in tech related areas. Seminar 3 (Fall). |
3 |
| MGMT-820 | Foundations of Strategy Research This doctoral level seminar surveys the foundations of strategic management research, drawing primarily from economics, but also sociology and psychology theoretical perspectives towards understanding firm performance and related strategic issues. The main objective of the seminar is to familiarize students with the assumptions, concepts, and theories underlying the field of strategic management, as well as to help develop the skills necessary to evaluate, critique, and contribute to the field. Seminar 3 (Spring). |
3 |
| MGMT-821 | Organizational Behavior & Creativity This PhD seminar explores those topics in organizational behavior that explicate our understanding of creativity in organizations. This course draws upon trending as well as classic organizational behavior research to expose students to topics that are especially relevant to creativity, but it is not restricted to creativity literature. The objective of this course is to equip students with conceptual frameworks and analytical approaches that will serve as micro- and meso-level foundation to their understanding of organizational creativity and, ultimately, innovation. Seminar 3 (Spring). |
3 |
| MGMT-825 | Seminar: Emergent Topics in Management This research seminar focuses on timely, special topics not covered in other seminars. Topics rotate based on faculty expertise (such as Creativity and Innovation, Groups and Teams, Corporate Social Responsibility) and student needs as determined by the department. Seminar 3 (Fall, Spring, Summer). |
3 |
SCB Graduate Electives
Please discuss with your advisor about which electives aligns with the focus area
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| BANA-780 | Advanced Business Analytics This course provides foundational, advanced knowledge in the realm of business analytics. Advanced topics such as machine learning, analysis of structured data, text mining, and network analysis are covered. Industry standard tools such as R and Python are extensively used in completing student projects. (Prerequisite: BANA-680 or equivalent course.) Lecture 3 (Spring). |
3 |
| MGIS-725 | Data Management and Analytics This course discusses issues associated with data capture, organization, storage, extraction, and modeling for planned and ad hoc reporting. Enables student to model data by developing conceptual and semantic data models. Techniques taught for managing the design and development of large database systems including logical data models, concurrent processing, data distributions, database administration, data warehousing, data cleansing, and data mining. Lecture 3 (Spring). |
3 |
| MGIS-735 | Design and Information Systems Students who complete this course will understand the principles and practices employed to analyze information needs and design appropriate IT-based solutions to address business challenges and opportunities. They will learn how to conduct requirements analysis, approach the design or redesign of business processes, communicate designs decisions to various levels of management, and work in a project-based environment. Lecture 3 (Spring). |
3 |
| MGIS-745 | Information Systems Development Systems development provides MBA students with the fundamental techniques and concepts necessary for programming in a modern programming language. Emphasis will be placed on object-oriented programming concepts. By the end of the course, students will demonstrate core programming concepts, and will be able to write simple business applications. Lecture 3 (Fall, Spring). |
3 |
| MGIS-760 | Integrated Business Systems This course focuses on the concepts and technologies associated with Integrated Business Information Systems and the managerial decisions related to the implementation and ongoing application of these systems. Topics include business integration and common patterns of systems integration technology including enterprise resource planning (ERP), enterprise application integration (EAI) and data integration. The key managerial and organizational issues in selecting the appropriate technology and successful implementation are discussed. Hands-on experience with the SAP R/3 system is utilized to enable students to demonstrate concepts related to integrated business systems. (familiarity with MS Office suite and Internet browsers) Lecture 3 (Spring). |
3 |
| MGIS-811 | Qualitative Research Methods In this course, students learn and apply qualitative data collection and analysis methods in the context of business research. The course provides an overview of prominent qualitative research designs, including case study, field study, and ethnography. Students learn critical qualitative data collection techniques, including interviewing, field observation, and historical analysis. Finally, students explore different techniques for qualitative data analysis, including grounded theory methodology, thematic analysis, discourse analysis, and conversation analysis. Students will engage in hand-on experiences in each of the analytical methods to demonstrate skills in managing selected design, data collection, analysis and writing strategies of qualitative research. Seminar 3 (Spring). |
3 |
| MKTG-763 | Buyer Behavior The course reviews the major theories that frame the understanding of both consumer (end-user) and business buying behavior. Topics include the buying decision process, the impact of emotion, product knowledge, and product involvement on purchasing decisions. In addition, behavioral, social and psychological perspectives will be discussed. All perspectives will be applied to designing marketing strategy. (Prerequisites: MKTG-761 or equivalent course.) Lecture 3 (Fall). |
3 |
| MKTG-768 | Marketing Analytics This course provides an overview of marketing analytics in the context of marketing research, product portfolios, social media monitoring, sentiment analysis, customer retention, clustering techniques, and customer lifetime value calculation. Students will be introduced to, mathematical and statistical models used in these applications and their implementation using statistical tools and programming languages such as SAS, SPSS, Python and R. Multiple data sources will be used ranging from structured data from company databases, scanner data, social media data, text data in the form of customer reviews, and research databases. Students will complete guided projects using real time data and make effective use of visualization to add impact to their reports. There are no listed pre or co-requisites; however, instructor permission is required – student aptitude for quantitative work will be assessed; waived for students enrolled in quantitative programs such as the MS-Computational Finance which have pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Spring). |
3 |
| MKTG-772 | Internet Marketing: Strategy & Tactics This course examines the impact that the internet has on traditional and contemporary business-to-consumer marketing activities. It explores these implications in both strategic and tactical terms to enhance organizations' levels of competitiveness. The course identifies the use of the internet in enhancing value for consumers and considers the leverage of the latest technologies, trends, e-culture and innovation through the medium of the internet. (Prerequisites: MKTG-761 or equivalent course.) Lecture 3 (Fall, Spring). |
3 |
| MKTG-776 | Product and Brand Management An essential element of corporate success is the management of products and brands. Firms in both consumer and commercial industries often manage their marketing strategies and tactics through the activities of their product and brand managers. This course will examine the role of product and brand managers in the development and execution of strategies that deliver value to targeted customers and grow the business. The role of product and brand managers will be examined through all phases of the firm's product and brand life cycle. The course emphasizes the decisions that firms expect product and brand managers to make to achieve market share and financial objectives. (Prerequisites: MKTG-761 or equivalent course.) Lecture 3 (Fall, Spring). |
3 |
| MKTG-778 | Commercialization and Marketing of New Products This course emphasizes the marketing and product strategy-related activities required to create, develop, and launch successful new products. Topics covered include identifying the market opportunity for new products, defining the product strategy, understanding customer requirements, developing and updating the product business plan, marketing's role in the firm's product development process, developing the marketing plan for launching new products, and managing the product life cycle. The course emphasizes best practices in marketing-related activities required for successful new product commercialization. (Prerequisites: MKTG-761 or equivalent course.) Lecture 3 (Spring). |
3 |
| MKTG-825 | Multivariate Methods and Analyses This course is designed introduce doctoral students to statistical methodology as it pertains to the study of multivariate techniques used in the behavioral sciences. The course will cover a range of statistical procedures and programs for multivariate data analysis. The focus is on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. Topics covered include multivariate data screening, analysis of variance, multi-dimensional scaling, factor analysis, OLS regression, mediation and moderation among others. Seminar 3 (Fall). |
3 |
| MKTG-830 | Structural Equation Modeling This course provides a detailed look at structural equation modeling (SEM) for doctoral students. SEM is a technique for modeling the relationships among multiple latent variables. It includes models that have multiple indicators of constructs (latent variables; confirmatory factor analysis) that have directional relationships among constructs (path analysis; structural equations). The course will cover both conceptual and practical aspects of SEM, with the goal of preparing the student to use SEM in original research and to critically evaluate its use in scholarly work. Further, it introduces the student to partial least squares modeling and to Bayesian approaches in structural equations modeling. (Prerequisites: MKTG-825 or equivalent course.) Lec/Lab 3 (Spring). |
3 |
SCB Graduate Courses 700 level or higher with advisor approval |
3 | |
* Students can take either ACCT-858 or FINC-858, not both
** Students can take either MGIS-812 or MKTG-81, not both
Admissions and Financial Aid
This program is available on-campus only.
| Offered | Admit Term(s) | Application Deadline | STEM Designated |
|---|---|---|---|
| Full‑time | Fall | January 15 priority deadline, rolling thereafter | No |
Full-time study is 9+ semester credit hours. International students requiring a visa to study at the RIT Rochester campus must study full‑time.
Application Details
To be considered for admission to the Business Administration Ph.D. program, candidates must fulfill the following requirements:
- Complete an online graduate application.
- Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
- Hold a baccalaureate degree (or US equivalent) from an accredited university or college.
- A recommended minimum cumulative GPA of 3.0 (or equivalent).
- Submit a current resume or curriculum vitae.
- Submit a statement of purpose for research which will allow the Admissions Committee to learn the most about you as a prospective researcher.
- Submit two letters of recommendation.
- Entrance exam requirements: GMAT or GRE required. No minimum score requirement.
- Writing samples are optional.
- Submit English language test scores (TOEFL, IELTS, PTE Academic), if required. Details are below.
English Language Test Scores
International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver.
| TOEFL | IELTS | PTE Academic |
|---|---|---|
| 94 | 7.0 | 66 |
International students below the minimum requirement may be considered for conditional admission. Each program requires balanced sub-scores when determining an applicant’s need for additional English language courses.
How to Apply Start or Manage Your Application
Cost and Financial Aid
An RIT graduate degree is an investment with lifelong returns. Ph.D. students typically receive full tuition and an RIT Graduate Assistantship that will consist of a research assistantship (stipend) or a teaching assistantship (salary).