Introduction to Operations & Technology Management Research
This course consists of two equally weighted parts. In the first part, you are introduced to mathematical modelling paradigms. Mathematical modelling is a core “language” of the field and many of its insights are captured succinctly in mathematical formulae or propositions. It is therefore important for you to become conversant. The goals of the first part of the Introduction module are (i) to enable you to appreciate the gist, if not the detail, of modelling papers in the OTM literature and (ii) to introduce you to the mathematical modelling language at a level that enables you to learn more details from textbooks or take more advanced graduate courses in the university if and when required for your own research. This first part of the module is a natural methodological complement to the econometrics modules of the MPhil programme, which cover empirical methods.
The second part of this module teaches you how to write a convincing OTM research proposal with the goal of developing an academic paper for publication in a peer-reviewed journal of the field. What makes a good research question? What is a suitable research method for the question at hand? How does the proposed research relate to management practice? How does it relate to and extend the existing academic literature? You explore these questions using published papers as case studies, and you practice the writing and presenting of research proposals, which will prepare you for the PhD continuation process. This second part of the module also teaches you how to read and evaluate academic papers in an efficient manner and what distinguishes OTM papers from papers in cognate disciplines (e.g. economics or marketing).
Classics of Operations & Technology Management Research
The Classics module introduces you to landmark papers and books that have shaped the OTM field. The purpose of the module is to enable you to position your own research within the existing body of literature. We take a broad view of the OTM field and also cover aspects of cognate fields (industrial engineering, economics, sociology, psychology) that are relevant to current debates in OTM.
Fundamentals of Competitive Markets
You are introduced to the foundations necessary to conduct research in the three areas of marketing, operations & technology management, and finance, with a view to developing your own skills as researchers in these areas and in business in general. This course covers standard models of:
- individual choice under certainty and uncertainty
- production theory
- general equilibrium
- monopoly pricing, price discrimination
- information economics
- behavioural economics
The course gives you some fundamental knowledge of competitive markets, enabling you to leverage your course knowledge to do original research and write papers in your chosen field of research in a business school.
This is the first in the sequence of Econometrics modules designed for Research MPhil students who intend to use econometric methods in their PhD research at Cambridge Judge Business School. It is taught in Michaelmas Term.
This introductory module develops your capability in using linear regression and associated statistical techniques to examine causal relationships from primarily cross-sectional, observational data. By the end of the module you are to specify, estimate, test, interpret, and critically evaluate single equation regression models, with applications in subject areas of management, finance, and business economics.
The module is followed in Lent Term by Econometrics II, training you in methods and applications of Micro-econometrics. A further module on Time Series Econometrics is offered as an elective in Easter Term.
To carry out empirical research that has the potential to make an original contribution to knowledge in management, finance, business economics and similar fields, it is necessary to exploit the richness and structure of longitudinal as well as cross-sectional, individual-level data on the behaviour of individuals or firms. It is necessary to become competent in an array of micro-econometric techniques that help researchers to build into the design of their studies, a variety of complexities (in decision-making, for example) and also compensate for partial observability that is inherent in research data.
This module introduces you to research-level micro-econometric methods. It provides the background required to confidently choose techniques and methods suited to different types of data-sources and models. The focus is on how techniques relate to theory, on the insights that can be drawn from their application, and critical interpretation and appraisal of results.
You must have taken the Econometrics I course to take this course. A further module on Time Series Econometrics is offered as an elective in Easter Term.
Organisational Research Methods I & II (biennial content)
This course helps you understand a variety of predominantly quantitative research methods, as well as their embeddedness within various research designs. The course is divided into two independent content blocks, parts I and II, and is designed in such a way that part II can be attended without having attended part I previously. Upon completion you’ll have a good understanding of various research methods commonly used in management research, and will have applied this knowledge to your own research project.
Specifically, the course covers the following content areas, among others:
- Research design
- Experimental & quasi-experimental design
- Survey design & analysis
- Mediation & moderation
- Multilevel design & analysis
- Social network design & analysis
- Big data research design & analysis
The course increases your understanding of organisational research methods and your sensitivity to the practical problems in conducting organisational research, and enables you to apply organisational research methods to your own research projects and interests.
Game Theory & Information Economics (2022/23)
This course is for students who wish to pursue a research career in a business school and consists of a mix of lectures and seminar-based sessions in which you read, analyse and comment on selected papers. Following the course, you’ll be able to leverage your course knowledge to do original research and write papers in your chosen field of research.
Topics covered include:
- Static games of complete information (normal form games)
- Modelling strategic interactions
- Iterated dominance and rationalisability
- Nash equilibrium
- Application: imperfect competition
- Mixed strategies
- Dynamic games of complete information (extensive form games)
- Extensive form and Nash equilibrium
- Subgame perfect equilibrium
- Application: product differentiation
- Repeated games and one-step deviation
- Static games of incomplete information
- Bayesian Nash equilibrium
- Dynamic games of incomplete information
- Perfect Bayesian equilibrium
Consumer Behaviour (2021/22)
This seminar-based module is an overview of issues related to consumer behaviour research in marketing. The module includes readings on marketing research as well as cognate home disciplines such as psychology and behavioural economics. Two major areas are covered:
- The information processing perspective
- The behavioural decision perspective
In each session you’re required to read, analyse and comment on selected papers surrounding the key themes of that session. At least half of every session will be devoted to student presentations and group discussion. Having completed the module, you’ll possess some basic knowledge that will help you appreciate and conduct consumer behaviour research. You’ll also be able to leverage your learning experience to develop an in-depth understanding of relevant topics for a research career at a business school.
Further Econometrics: Time Series
In a large number of empirical contexts in finance and management, data are temporarily ordered in the form of time series. The Time Series Econometrics module introduces you to concepts and methods that are appropriate for empirical research in such settings, covering methods for exploratory time series analysis, estimation of dynamic causal effects and forecasting.
Individual Research Project
This module is designed for you to conduct individual research under the supervision of SMO faculty members. Research projects can consist of a thorough literature review related to a specific research question, an in-depth critique of published papers, or a specific application of a research methodology (such as a pilot study on the basis of limited data). Our goal is to familiarise you with the faculty members’ current research and bring you closer to the frontier of knowledge. The module can prepare you for the individual research that you will undertake in PhD studies, and can indeed become the starting point of future PhD research.