In his dissertation 'Integration, Decentralization and Self-Organization: Towards Better Public Transport' Rolf van Lieshout sought to improve the planning process of public transport operators by integrating planning steps that are traditionally performed sequentially. Furthermore he investigated decentralized strategies for operating public transport, with a focus on railway systems. Such strategies could be preferable over conventional centralized and schedule-based control in various scenarios. Last, he tested decentralized dispatching of both vehicles and crew in a microscopic railway simulation.
Erasmus PhD Programme in Business and Management
ERIM’s full-time doctoral programme – the Erasmus Doctoral Programme in Business and Management – is focused on developing and nurturing international academic talent. It enables promising students to develop into ‘thought leaders’ and become top researchers at the world’s best universities and business schools. Depending on the PhD project, generous funding can be generated for four or five years; further extensions are possible.
Facts and figures
- Erasmus University Rotterdam is ranked number 3 in Business Administration and number 4 in Management (ARWU 2020)
- ERIM currently supports a community of around 250 senior researchers and 160 doctoral students
- Five research programmes spanning all areas of management research: Business Processes, Logistics & Information Systems; Organisation; Marketing; Finance & Accounting; Strategy & Entrepreneurship
- Research Initiatives which focus on specific areas of research interest
- Access to EUR’s state-of-the-art behavioural lab, extensive range of databases and excellent computing facilities.
- Strong ERIM presence in top academic journals
- More than 200 international research seminars, workshops and conferences each year
In her dissertation 'Consumers in the Age of AI: Understanding Reactions Towards Algorithms and Humans in Marketing Research' Gizem adopted a nuanced perspective on consumers’ reactions towards algorithms and humans and introduced three contextual factors that impact consumers’ reactions. Specifically, it reveals how consumers’ reactions towards algorithms and humans depends on what the outcome of the decision is, who the consumer is and on what type of complexity the decision possesses.