Ph.D. in Technology Management

The School of Business Ph.D. in Technology Management program defines itself at the intersection of three research domains: Information Systems (IS), Technology & Innovation Management (TIM) and Social Computing (SocCom). These three research domains are strongly represented by the faculty of the Business School and provide different perspectives on the management of technology.

The design of the Ph.D. program is based on the assumption that novel research ideas often occur at the intersection of different knowledge domains. The unique combination of these three research domains and their integrated discussion will lead to creative and innovative research questions within and across these domains. The combination will also encourage the development of the interdisciplinary skill sets necessary to conduct innovative research. The majority of Ph.D. programs focus on theory and analytical skills. The integration of IS, TIM and SocComp complements this fundamental skill set with the skills necessary for creating and applying this knowledge. Our students are challenged to create new technologies for analyzing relevant research questions related to important problems we face today.           

Students of the program will chose one of the three research domains as their research focus and they will study aspects of the other two domains in the mandatory courses of the program. Because of the specific integration of the knowledge domains the program offers a truly interdisciplinary experience. This is achieved by the selection of courses and by the syllabus of each individual course. Every course, no matter of its primary research domain, will include at least one topic related to the other research domains. (Please see Research Domain Integration below.)

Degree Requirements: The Ph.D. program in Technology Management consists of 36 credits of coursework (11 seminars and one individual study) and 18 research credits.

Admission Requirements:  The Ph.D. program is designed for the exceptional student possessing a strong quantitative background and a degree in management or related topics.  Students who are interested in joining the program must fulfill the following requirements:

• Students must have earned a 4-year undergraduate degree from an accredited college or university.
• Students must have earned a master’s degree in Business or MIS or related field.
• Students must have attained a basic knowledge of statistics comparable to MGT620 Statistical Models.
• Students must have completed undergraduate course work in mathematics including the equivalent of two semesters of calculus and one semester of linear algebra, or they must complete MGT 752.

International students for whom English is a second language must demonstrate English language proficiency by submitting the results of a TOEFL or an IELTS test.

All students are required to submit GMAT or GRE test scores.

Admissions decisions are made beginning in January for the following fall semester. Students are encouraged to apply at any time during the year. 

Prerequisites: Students without a basic knowledge of statistics must complete the non-credit course MGT620 Statistical Models.  Students without the required mathematics must complete MGT752 Mathematical Methods in Management for no credit.

Depending on the student’s background, several non-credit business, information technology and social computing foundation courses may also be required.

STRUCTURE OF THE Ph.D.  PROGRAM

Course work (36 credits).  All courses are worth 3 credits unless otherwise specified.)

• MGT 718 Multivariate Analysis
• MGT 719 Quantitative Research Methods & Design and Analysis of Experiments
• MGT 736 Economic Foundations of Management
• MGT 721 Qualitative Research Methods & Theory Building
• MGT 753 Theory in Management Research (New Title: Mgt. Theories)
• MGT 711 Entrepreneurship & Innovation Management Research
• MIS 722   Business Process Management & Innovation
• TBD         Design Science
• TBD         Social Network Analysis
• TBD         Statistical Learning and Analytics
• TBD         PhD. Research Colloquium Series (every spring semester)
•                Special Method Workshops (SEM, Conjoint Measurement etc.)
• MGT 960 Dissertation/ Research (18 credits)

The 11 required seminars and the individual study for the Ph.D. are the prerequisite for the program’s qualifying exam. This exam is usually taken after finishing the 4^th semester of full-time study.

A proposal for the student’s PhD dissertation is usually defended at the end of the third year of full-time study.

The final PhD dissertation is usually defended at the end of the fourth year of full-time study.

PROGRAM LEARNING OBJECTIVES

The program’s learning objectives are to prepare students to pursue an academic or industry research career.

The program’s course work will introduce students to the foundations of the three research domains and equip them with the knowledge required to conduct independent research.

The courses, with their domain specific origins, are differently positioned to develop skills in understanding and analyzing as well as in creating and applying.

• Understanding and analyzing skills are addressed by discussing the theoretical foundations of the domains and fundamental methods.
• Creating and applying skills are developed by theory building and developing tools to analyze specific social and economic phenomena.

Corresponding Courses

Skill Sets

Understand & Analyze

• Mgt 718 Multivariate Analysis
• Mgt711Entrepreneurship & Innovation Management Research
• Mgt 753 Theory in Management Research
• MIS 722 Business Process Management & Innovation
• Social Network Analysis

Create & Apply

• Mgt 721 Qualitative Research Methods & Theory Building 
• Mgt 726 Design Science
• Statistical Learning & Analytics
• Social Network Analysis
• Mgt 719 Quantitative Research Methods & Design and Analysis of Experiments

The above list indicates which skills are developed in the different courses. The skills and the corresponding courses are not meant to be complete, but illustrative. For the specific content of each individual course please refer to the individual syllabus.