Programme Structure

Trinity Business School offers PhDs on a fulltime basis with students enrolling in September.

Trinity College Dublin Entrance

Learning Goals

The PhD programme is informed by a number of key objectives:

  • Education focused on careers and business performance
  • A set of values – “put in more than you take out"
  • The personal development and well-being of our students
  • A real-business educational environment. 
  • Rigorous research that serves and critically evaluates business

    And aim to achieve five key learning objectives:
  • Identifying and developing the critical knowledge, skill, and expertise required to thrive in an international research and teaching environment that is intensive, collaborative, enjoyable, and results-oriented
  • Appreciating and critiquing the philosophical foundations, theories, and practices of social science research
  • Identifying, critiquing, and justifying the key elements of an integrated programme of research leading to the award of a higher degree by research;
  • Effectively planning, conducting, and communicating rigorous, valid, and ethical research;
  • Critically examining and evaluating ongoing or completed research projects.

Academic Supervision

Each student is assigned a principal supervisor with whom they are expected to maintain regular contact.  If it is deemed academically useful a co-supervisor may also be appointed. All principal supervisors are appointed from within Trinity Business School while co-supervisors may be appointed from other Schools throughout the University. In certain circumstances, co-supervisors may be appointed from other Universities or industry partners depending on the nature of the research being undertaken.

Each candidate is also assigned a Thesis Committee which contains a domain expert and one other person, the committee role being to oversee the annual confirmation and transfer process and to act as a external resource. 

Structured Elements of the PhD programme

Students take the structured elements in the first three or four semesters of their degree.

Every student takes the modules outlined below, each module accounts for 5 credits. All must be passed at a level of 60% of above within the first 4 semesters to allow the student to present their confirmation report at the end of Semester 4. Confirmation of PhD status must be undertaken by end of Year 2. 

  • Research Integrity and Impact in an Open Scholarship Era, delivered online and must be completed before confirmation. 
  • BUS1, BUS2, BUS3, SRMA, TM 
  • At least 2 modules from QUANT1-3 /QUAL1-3 at least one of which must be in each set – the level of the modules is agreed beforehand with the supervisor and the PhD Director. 
  • 2 optional modules, which may include quantitative/qualitative modules not already passed. Students can take additional “overload” modules if they desire, for which no credit but a certificate of completion will be given. 

Below please see a broad outline of the modules. Full syllabi, learning objectives etc are available on the course intranet:

  • Introduction to Management Research BUS1: PhD expectations and the journey, supervisor management, assessment of novelty and contribution, global v local in research, impact, dissemination channels 
  • Philosophy and Practice of Management Research BUS2: Identifying research topics and questions; the role of theory and philosophy in research design; contrasting and combining methodological approaches; replication and secondary analysis; comparisons and case studies; issues of time; multi-level research designs; knowledge exchange and the uses of research; ethics and good research practice. 
  • Publishing and Professional Practice in Management Research BUS3: types of scholarly output (journals, books etc) ; journal ecosystems; good paper design; effective communication of research findings; reviewing ; conferences and workshops; 
  • Qualitative Data Collection and Recording / Analysing Qualitative Data QUAL1-2: introduction to qualitative data and the principles of data collection, qualitative data sources including data collection and selection, interview design and transcription and data preparation 
  • Computerized qualitative data analysis QUAL3; Computerized qualitative data analysis; selection of appropriate software; coding and transcription; from output to publishable research 
  • Advanced Qualitative Methods QUAL4 ; phenomenology and case research; archival text analysis, observations, triangulation with multiple sources, exploring mixed methods. 
  • Quantitative Methods 1/ Quantitative Methods 2 QUANT1-2; Introduction to statistical methods and reasoning in management research; measuring and the nature of data; exploratory data analysis; measuring relationships between variables; multivariate statistics; nonparametric statistics; Bayesian reasoning; effective graphical communication 
  • Econometrics and Data Science QUANT3; time series modelling, ARCH/GARCH processes, Cupola and Wavelet modelling, ARCD modelling, conditional dependent variables 
  • Advanced Econometrics QUANT4: static and dynamic panel models, unbalanced panel estimators, non and semi parametric models 
  • Inferential Statistics QUANT5; ANOVA, MANOVA, Data Reduction, Variable reduction and influence, survival model, extreme values 
  • QUANT6; forecasting and model evaluation, machine learning, Bayesian analysis, discontinuities and DiD models; network models. 
  • Systemic Reviews and Meta Analytic Methods : evidence based decisions; synthesising knowledge; types of systematic reviews; conducting a systematic review; Meta analysis; creating a knowledge synthesis documents 
  • Theorising management TM : Theorising management, limits to present management theories across selected domains, testing management theories in practice.

    Optional courses: Any more advanced quantitative or qualitative module may be taken as an optional course for credit.
  • Introduction to Python for Management Research PHYBUS Introduction to Python for Business Research; intro to python - data management and wrangling - visualisation - statistics w python - web scraping - textual analysis –- Machine Learning and AI 
  • Causal Inference and Structural Equation Modelling CISEM: field experiments; discontinuity designs; directed and undirected graphs; mediation, moderation; Structured equation models; linear and nonlinear causality models 
  • Social Science and philosophy : philosophy of science; social science as a science; epistemology and ontology in management research.
  • Optional courses from the MSc roster are also available, subject to space and timetable availability. Examples of these modules might include Private Equity Finance,, Enterprise Risk Management, International Finance, Alternative Investments, Energy Finance & Trading, Decision and Risk Analysis, Global Procurement, Supply Chain Science, Operations Analytics, Researching HRM, HR Digitalisation & Analytics, Leading Change in a Complex World

To be confirmed on the PhD register, students must:

  • Have satisfactorily completed the Core Modules in the structured PhD programme; 
  • Have designed and delivered a Research Seminar; 
  • Have prepared and submitted a formal Confirmation Report, made a formal Confirmation Presentation, participated in a formal Confirmation Interview, and satisfactorily met any other requirements associated with the Confirmation Process.

In years 3 and 4 of the programme students are expected to participate in the intellectual life of the School, to attend and present at conferences, and to engage with the scholarly aspects of their discipline, such as reviewing papers and mentoring junior students. 

Supporting participation in the Graduate Teaching Practice programme, students may also elect to complete VP1017 and VP1021.

  • VP1017: Teaching & Supporting Learning as a Graduate Teaching Assistant.
  • VP1021: Adapting our Teaching for Learning  Online.

Additional programme Requirements

By agreement with the Director of Doctoral Studies and the Academic Supervisor, a PhD student may be encouraged to participate in one or more additional modules to compensate for deficiencies in their knowledge deemed essential to the proposed programme of research. Such modules may be drawn from, but not limited to, the options outlined below:

  • Modules offered as part of the suite of taught postgraduate programmes within Trinity Business School.
  • Modules offered by Business Schools in partner institutions as part of the Dublin Region Higher Education Alliance (TCD, UCD, DCU, NUIM, TUD).
  • Modules offered in the areas of research philosophy, methodology and methods offered by other Schools within the Faculty of Arts, Humanities, and Social Sciences

Enrolment in research modules offered by other Schools is subject to both the availability of places and permission to enrol.