Skip to main content

News

Search results for “”

Results 21 to 30 of 180

David Palma – Seminar at the the Department of Transport Engineering and Logistic, Universidad Católica, Chile

Date

David gave a seminar entitled “A discrete-continuous approach for simultaneous modelling of time-use and expenditure" Abstract: Interest in time-use modelling has increased significantly during the last few years, especially as activity-based modelling becomes the dominating approach for large-scale transport modelling. The objective of time-use modelling is to understand and predict people’s engagement in activities throughout...

CDR's MSc Business Analytics and Decision Sciences – 9th in the UK

Date

In the QS Business Master’s Ranking: Business Analytics, the MSc Business Analytics and Decision Sciences programme at Leeds has been ranked 9th in the UK ( 71st-80th globally). The programme was also placed 6th in the UK for ‘thought leadership’, 8th for ‘diversity’ and 10th for ‘alumni outcomes’.

Dr Jooyoung Jeon from KAIST visited CDR

Date

The Korea Advanced Institute of Science and Technology (KAIST) (https://www.kaist.ac.kr/en/) was founded in 1971 and is one of Korea's most prestigious universities. Dr Jooyoung Jeon from the Predictive Analytics Lab (https://sites.google.com/view/jyjeon/) in the Graduate School of Future Strategy in KAIST, visited the Centre for Decision Research (CDR) for the ESRC project ‘Climate change, social inequality...

Barbara Summers & colleagues - Ethical Reasoning in Tax Practice: Law or is There More?

Date

Private sector tax practitioners are often accused of unethical behavior in developing contrived tax avoidance arrangements. Such arrangements usually comply with the letter of the law but contravene its underlying (often unstated) ‘spirit’. Prior research comparing the ethical reasoning of private sector tax practitioners, government revenue tax practitioners and a non-tax (control) group in both...

Romain Crastes dit Sourd & colleagues – Linking health worker motivation with their stated job preferences: A hybrid choice analysis in Ethiopia

Date

Our paper on the link between health workers motivation and job preferences has been accepted for publication in Social Science & Medicine (ABS4). Understanding health worker job preferences can help policymakers better align incentives to retain a motivated workforce in the public sector. However, in stated preference choice modelling, health worker motivation to do their...

Panagiotis Stamolampros - Employee treatment, financial leverage, and bankruptcy risk

Date

Using employee online reviews as a proxy of employee treatment and well-being for tourism and hospitality firms, this study extrapolates the association of employee satisfaction with financial leverage and bankruptcy risk. Consistent with theoretical expectations and empirical evidence, we find that firms ranked high on employee treatment have lower levels of market and book leverage....

A Successful End to a KTP with Clipper Logistics

Date

The £276k Innovate UK funded Knowledge Transfer Partnership (KTP) project (awarded in 2019) with Clipper Logistics, a logistics service provider finished in February 2022. The project was a success, receiving an award of “very good” from Innovate UK making the project eligible for entering the KTP “best of the best” awards. The project was to...

David Palma - Extending the Multiple Discrete Continuous (MDC) modelling framework to consider complementarity, substitution, and an unobserved budget

Date

There are many tools available for demand forecasting at the individual level: discrete choice models to forecast what is bought, and linear regression to forecast how much of it is bought. Multiple-Discrete-Continuous (MDC) models can forecast both what and how much is purchased simultaneously, but they have historically being limited by a lack of complementarity...

New KTP - Enhancing digital manufacturing in the steel industry

Date

Richard Hodgett, Sajid Siraj and Alan Choicharoon are involved in a new Knowledge Transfer Parternship. The project, led by Richard, aims to develop and commercialise a first-in-sector software for condition monitoring of continuous casting process in steel making using advanced data analytics, machine learning and decision sciences approaches. The software will have inbuild diagnostic and...