This annual award is to recognise and honour the outstanding quality of the Master thesis. The winner of the award is selected by an academic committee consisting of the academic directors and thesis coordinators of the master programmes. Prof. Jo van Nunen (1945-2010) was Professor of Operations Research and Information Systems and is considered one of the founding fathers of Rotterdam School of management, Erasmus University. He was well known for his energy and enthusiasm for bridging management science and management practice. He inspired – and will continue to inspire – many generations of students, faculty, alumni, managers, and entrepreneurs.

2017 winners 

Business Information Management

The nominated theses were assessed by Prof Eric van Heck, Dr Ting Li and Dr. Marc Boons. Based on theoretical contribution, methodological rigor, and managerial impact they awarded two winners. The winners of the thesis awards are Christian Sitepu with his thesis entitled "A blockchain based ecosystem Blueprint for International Trade" and Dirk de Raaff with his thesis entitled "The effect of personalized referral policies: A randomised field experience".

Innovation Management

The nominated theses were assessed by Jan vd Ende, Daan Stam, Henk de Vries and Murat Tarakci based on theoretical contribution, methodological rigor, and managerial impact. The winner of the thesis award is Violetta Rodopoulou. Her thesis entitled "Innovation and Technical Efficiency of Crowdsourcing Ideas: A Multimethod Study of the My Starbucks Idea Platform" is about a very important and novel research topic: the difficulty of evaluating and selecting new ideas. In her thesis, Violetta introduces and tests the concept of"idea efficiency" - how much input is necessary to implement a particular idea and what is the expected output once an idea is implemented? 

Supply Chain Management

This year’s winner of the Jo van Nunen award for Supply Chain Management is Christian Kaps for his thesis “Towards better warehouse efficiency distinction through cross-efficiency measurement“. This thesis was awarded the exceptionally high grade of 9.5. The thesis presents several new DEA cross-efficiency measures that can be used for benchmarking and comparing decision making units. it applies the methods on a new panel data set of 102 warehouses and ranks and compares the measures on various properties. In a subsequent step the warehouses are benchmarked over time using this measure leading to interesting insights on how warehouse performance depends on size, automation and management practice.