Study
Doctoral study
The Centre for Decision Research in Leeds University Business School is keen to encourage applications from students wishing to undertake a PhD in the area of decision making, and would be interested in discussing potential projects with students who would like to study here. Proposals are welcomed in any area of decision research, but at this time the example topic areas listed for potential supervisors in CDR in the list below are of particular interest. To get a broader idea of each supervisors' areas of interest look at our publications page or their profile page (links in the list below).
Details of research degree study at Leeds University Business School can be found here: https://business.leeds.ac.uk/research-degrees. This includes links to details on how to apply, and fees and scholarships (in the PhD tab of "In this Section").
Scholarships currently open for application, which could be used to support study with CDR are:
Leeds Opportunity Research Scholarships available to Black and Asian Home (UK) fee-rated applicants (deadline 03/04/2023)
** Additional Scholarhip Opportunity - Measuring life quality from digital footprints for informed policy decision making - deadline 27 Feb 2023
This project, in collaboration with Leeds City Council and CitizenMe Ltd, aims to develop new measures of life quality from digital footprints (ie internet and social media data). Recent breakthrough in social data science and machine learning allow easily accessible digital footprints to estimate personal attributes, including their feelings and their psychological and behavioural traits (eg satisfaction, mental health). Citizens’ social wellbeing, like perceived safety and happiness, which is a straight reflection of life quality, is possible to measure through digital footprint data. This provides policymakers with an additional way to look beyond economic statistics and surveys to identify which policies are effective in a timely manner. The project will employ interdisciplinary approaches from psychology, management and data science to examine the changing nature of data usage and how emerging digital data can help track and monitor policy influence. It will generate new methodologies for mining open social media data, which will help the understanding of the society in social wellbeing inequalities.
Details on how to apply are here
Supervisors in CDR
- Effects of Computer Aided Decision Support
- Use of archival sports data to study choice behaviour
- Mitigating the hypothetical bias in stated preference surveys
- New revealed preference data sources for non-market valuation
- Development and evaluation of new decision support systems for real industrial problems
- Development and utilisation of new analytical techniques to support industry decision-making
- Risk perception and communication in applied contexts (e.g. medicine, natural hazards, food safety, product safety)
- Understanding and communication of weather and climate information
- Effects of source reliability and confidence on judgement and decision-making
- Food-related decision making, sustainability-related decision making
- Developing risk (benefit) communications, and other interventions in relation to food and sustainability
- Influence of heuristics, mental accounting, and bounded rationality on financial decision-making, and their implications for consumer welfare.
- Consumer behaviour, status-seeking and herd behaviour, income inequality, and their relationship to subjective well-being.
- Topics within the behavioural household finance literature (saving, borrowing and investment decisions)
- Eliciting preferences from decision makers using machine learning and multi-criteria decision analysis
- Mining association rules from large data sets using dominance-based rough analysis
- Investigating ways of structuring decision-making problems
- Influencer marketing and consumer attitudes
- Online information and cryptocurrencies
- Individual decision making, particularly in the areas of finance and health, considering cognitive and/ or emotional perspectives
- The effect of time pressure and other stressors on judgment and decision making
- Risk perception and communication, with particular interest in environmental risks (e.g. weather, climate, geohazards)
- Weather and climate information services for decision support
- The role of emotion in judgement and decision making
- Unstructured multimodal data mining: texts, images...
- Understanding and identifying human traits : faces, expressions, personalities, intelligence, confidence...
- Employing those computational techniques to improve business and management practice
- Individual differences in personality, identity status, decision-making, & risk-taking
- Lifespan perspective on decision-making, including identity status, longitudinal assessment of decision-making skills
- Risk perceptions, with a focus on health behaviors and financial behaviors (e.g., food safety, behavioural addictions such as gambling, problematic gaming)
Find out more about postgraduate research at Leeds University Business School.
MSc Business Analytics and Decision Sciences
The MSc Business Analytics and Decision Sciences programme delivers the knowledge and understanding of how business analytics can provide evidence to support management decision-making.
Dr Sajid Siraj, Director MSc Business Analytics and Decision Science
Full details of the programme and how to apply can be found here.
The MSc Business Analytics and Decision Sciences was ranked in the 2022 QS Master in Business Analytics rankings:
- 9th in the UK overall
- 6th for Thought Leadership
- 8th for Diversity
- 10th for Alumni Outcomes
Welcome to our 2019/20 Cohort for MSc Business Analytics & Decision Sciences (BADS)
We are happy to welcome more students to the programme this year (184) giving them the chance to develop skills valued by employers. This year students have the chance to take our new module on Machine Learning in Practice, giving them experience with this technology to take to the workplace.
Highlights from the 2014/15 cohort
The Premier Farnell Leadership Challenge
Students on CDR's MSc Business Analytics & Decision Sciences took part in a “Leadership Challenge” with Premier Farnell organised by Jo Lumb, Engagement Manager in the Business School’s Management Division.
Saptarshi Ray of the MSc explained “We are taking part in the leaders' challenge with one of the finest e-commerce companies in the world; Premier Farnell. We have got the challenge of demonstrating how big data analytics can help the company to improve their revenue and organisational efficiencies. We will be working as consultants for one month and will provide our suggestions to them.
“With the guidance of our Programme Director, Professor Alan Pearman, we undertook research on the company background and their business policy before going to the company and meeting their top personnel. Premier Farnell gave us a short presentation about their company and also briefed us on their current challenges and what they expect from us. We were given the opportunity to ask key questions to help with the challenge.
“It is a great experience for us to work as real life analytics consultants, which most of the students on our course aspire to be in their future career. We are grateful to Premier Farnell and the University of Leeds for providing us with this opportunity.”
The student group's analysis of the company's position was very well received and they subsequently were invited to make a full presentation to senior UK and US managers.
The team at Premier Farnell with Professor Barbara Summers
Presenting at EURO2015
Euro2015 is a major academic conference in the Operations Research area. Two MSc students, Saptarshi Ray and Ryzky Yudha presented papers:
Saptarshi Ray presented a talk titled “Association rules mining and cross correlation using Apriori algorithm to the financial market: The case with respect to UK Stock market and Global cues” and Ryzky Yudha presented a talk titled “Matching Critical Success Factors of Employee Performance to Help the Recruitment Process in Analysing Candidate Profiles by Incorporating Social Media Analytics”
Staff from the Centre for Decision Research also presented papers:
- Simon McNair, Alan Pearman, Ken-Ichi Shimomura and Barbara Summers, An experimental exploration of behaviour patterns in a mixed strategy two-person game
- Michele Lundy, Sajid Siraj and Salvatore Greco, Addressing weaknesses in pairwise comparison based prioritization methods – can the spanning tree approach help?
- Richard Hodgett, ChemDecide – a MCDA software for the chemical-using industries