Ph.D. Research in Business Analytics in Information Systems

We are living in a highly connected world that is filled with digital technologies, social media, mobile devices, Internet-of-Things, smart cities, and connected cars. Growth of the information technologies has created new opportunities across different industries as companies innovate to meet changes in consumer demand, and has given rise to new challenges. In our Ph.D. program in Information Systems, you will be trained to conduct innovative research to address increasingly complex challenges facing digital society. Our faculty is working on a variety of projects in this area ranging from digital platforms, mobile advertising, recommendation and personalization, social networks, online piracy and privacy, and the role of AI.

We are seeking highly motivated students with demonstrated academic ability, those who possess a commitment to interdisciplinary research on significant information technology and management issues, and those who desire to pursue an academic research career in this field. You will be part of the Business Information Management (BIM) section within the Department of Technology & Operations Management at the Rotterdam School of Management, Erasmus University.

Applicants must have strong quantitative training, with preference given to candidates who have earned an MSc, MPhil or Research Master in economics, computer science, econometrics, statistics, or a related field. Successful candidates have proficiency with R, SQL, Python, or other programming languages.

As a Ph.D. student, you will gain the training and experience necessary to conduct independent research through course work in information systems, economics, econometrics, machine learning, and large-scale data analytics. You will work closely with the advisors to define, develop, and execute your own research. The Ph.D. dissertation will be defined by the student with inputs from the advisors, and thus requires creativity, self-direction, and a passion for scientific inquiry.

Keywords

Artificial intelligence, business analytics, information strategy, digital innovation, digital platforms, economics of information systems

Topic

Research Topics

The Ph.D. student will develop research topics in close collaboration with the advisors. The advisors consists of full professors (promotors) and associate/assistant professors (daily supervisors).

The promoters are: Prof. Ting Li and Prof. Eric van Heck. Prof. Ting Li is the professor of digital business and focuses on studying the economic impacts of digitization on consumer behavior and firm strategy. She is an expert in digitization and platforms, personalization, ecommerce, social media analytics, mobile marketing, and pricing and revenue management. Prof. Eric van Heck is the professor in information management and markets and an expert in digital market and enterprise architecture, big data and analytics, digital work, and energy markets. 

Depending on research topics, you will have the opportunity to collaborate with other BIM faculty. They are working on a wide-range of interdisciplinary research topics, including digital marketing and recommendation (Dr. Dimitrios Tsekouras), social networks (Dr. Rodrigo Belo), sport analytics and algorithmic accountability (Dr. Otto Koppius), energy markets and smart grid (Dr. Yashar Ghiassi), smart cities (Dr. Tobias Brandt), digital privacy and piracy (Dr. Zike Cao), crowd funding (Dr. Philipp Cornelius), digital decision making (Dr. Markus Weinmann), user generated content (Dr. Dominik Gutt), and digitization and media (Dr. Dainis Zegners). For more information on BIM faculty and research topics, you can visit: https://www.rsm.nl/research/departments/technology-and-operations-management/business-information/.

During the Ph.D., you will work in close collaboration with the advisors to:

  • Identify a consequential phenomenon that is relevant to managers or policy makers, and which has not been fully addressed in prior research;
  • Obtain data, primary or secondary, that are needed to better understand the phenomenon;
  • Use the scientific literature to understand and examine the theoretical foundations of the phenomenon;
  • Identify the fundamental variables and relationships that are most important to the phenomenon of interest, and formalize these mathematically while relating them to data;
  • Identify the main assumptions that need to be made in order to solve or estimate the model, and understand their implications;
  • Develop methods necessary to extract research results from data;
  • Present research findings at national and international conferences;
  • Document findings for publication in leading scientific journals, and ultimately, your dissertation.

To conduct research, you will be able to take advantage of our strong industry ties, institutional databases, and software development support to gain access to large-scale data sets and have the opportunity to conduct real-world field experiments.

Organization

The BIM section of the Department of Technology & Operations Management at RSM is recognized worldwide and is multi- and interdisciplinary, publishing their research in top information systems and management journals. This makes the BIM section a lively, creative, and intellectually stimulating place to conduct research. The BIM section has a large, young and highly international faculty. The 14 full-time research-active faculty members have been educated at renowned institutions in Europe, the USA, and Asia. We have a strong research and teaching tradition and an international orientation both to the academic community and the business community.

BIM offers a high-profile MSc Business Information Management, one of Europe’s largest master programmes in Information Systems with 250+ new students each year. The programme delivers in-depth knowledge from theoretical and practical perspectives. Furthermore, a Master of Business Analytics program will be launched in 2020.

Rotterdam School of Management, Erasmus University (RSM) is one of Europe’s top 10 business schools. RSM provides ground-breaking research and education furthering excellence in all aspects of management and is based in the international port city of Rotterdam – a vital nexus of business, logistics and trade. RSM’s primary focus is on developing business leaders with international careers who can become a force for positive change by carrying their innovative mindset into a sustainable future. Our first-class range of bachelor, master, MBA, PhD and executive programmes encourage them to become critical, creative, caring and collaborative thinkers and doers.

Please visit our website for more information:

Approach

As a Ph.D. student, you will gain the training and experience necessary to conduct independent research through course work in information systems, economics, econometrics, machine learning, and large-scale data analytics. You will conduct applied and theoretical research under the supervision of our research faculty. The Ph.D. dissertation will be defined by the student with inputs from the advisors, and thus requires creativity, self-direction, and a passion for scientific inquiry.

Coursework. Core coursework is designed to build methodological skills, modelling competence, and substantive depth. The Ph.D. students will develop their knowledge and research skills by taking courses during the first and second year. The courses are offered by the Tinbergen Institute (http://www.tinbergen.nl), ERIM (https://www.erim.eur.nl/), and/or other research institutes. It is relevant to economics of information systems and business analytics in information systems, including, but not limited to microeconomics (individual choice, aggregate supply and demand, equilibrium), econometrics (endogenous variables, choice modeling), statistics and probability, Bayesian modelling, machine learning, and deep learning.

Research seminars. We organize weekly BIM research seminars (www.erim.eur.nl/research/events/research-seminars) that bring leading scholars to share their knowledge and insights on cutting-edge research that is emerging in other top schools around the world. Exposure to such network helps you jump-start your careers by providing in-depth view of mainstream research in the field, key methodological concerns, and emerging views among scholars and journal editors.

Research environment. Our interdisciplinary Ph.D. program provides an unparalleled source of training for doing cutting-edge research in Information Systems. In addition to strong technical training in quantitative methods, students will also be equipped with a deep appreciation and understanding of the behavioral mechanisms and processes that influence decision making via interactions with faculty studying topics related to individual decision making in experimental paradigms. Although you are likely to work primarily with field data, you will have access to the Erasmus Behavioral Lab, which provides all the necessary facilities to conduct world-class research on consumer behavior (cubicles, group labs, video-labs, eye tracking, EEG).

Required Profile

  • Passionate about understanding the impact of digital technologies on individuals, organizations, markets, system design, public policy, and society;
  • Enthusiasm for quantitative analysis, data, programming, and science;
  • Experience in conducting and completing a research project;
  • MSc or MPhil in Econometrics, Statistics, Computer Science, Economics or a related discipline;
  • Experience developing and estimating econometric or statistical models in R, SAS, Stata, and Python;
  • Programming skills, and in particular, prior exposure to or experience with scraping structured content structured web content (HTML, XPATH, CSS, etc.) from web sites;
  • Openness, intellectual curiosity, eagerness to learn, and a willingness to be proved wrong;
  • Ambition to work towards an academic career as a world-class researcher and instructor;
  • Willingness and motivation to formulate your own research projects and carry those through to the end (i.e., publication in a top journal);
  • Eagerness to ask and answer novel questions;
  • Experience in writing scientific papers.

Application process

Interested candidates are invited to visit the ERIM PhD in Management website (http://www.erim.eur.nl/doctoral-programme/) for information about application procedures and criteria. The application deadline is January 08, 2020.

If you have any questions about the formal admission requirements, please contact the ERIM doctoral office: phd@erim.eur.nl.

Expected output

Scholar publications. You will develop research papers that can be published in top-tier information systems and management journals, such as Management Science, MIS Quarterly, and Information Systems Research. BIM faculty at RSM has a strong publication record in these journals. The final results of the Ph.D. are also published in a Ph.D. dissertation. Most BIM Ph.D. students will be able to publish multiple papers in these top journals.

Placement record. In the past five years, our graduates have accepted faculty positions at top business schools all around the world, including MIT, Northwestern University, George Washington University, Copenhagen Business School, IE Business School, University of Amsterdam, and VU Amsterdam.

Cooperation

To strengthen your international profile, we strongly encourage our Ph.D. students to go abroad for a research visit during their third or fourth year at one of the top universities for 3 to 6 months. Past destinations include MIT, University of Maryland, University of Minnesota, Carnegie Mellon University, and University of California, Berkeley.

Literature references

  • Bughin, Jacques, Laura LaBerge, and Anette Mellbye, The Case for Digital Reinvention, McKinsey Quarterly, February 2017.
  • Porter, M. E. and J.E. Heppelmann, How Smart, Connected Products are Transforming Competition, Harvard Business Review, p. 65 - 88, November 2014.
  • Vidgen, R., Shaw, S., and Grant, D.B. (2017) “Management challenges in creating value from business analytics,” European Journal of Operational Research (261), pp. 626-639.
  • Li, T., J. van Dalen & P.J. Rees (2018). More than just noise? Examining the Information Content of Stock Microblogs on Financial Markets. Journal of Information Technology.
  • S. Yang, T. Li & E. van Heck (2015). Information Transparency in Prediction Markets. Decision Support Systems, 78, 67-79.
  • Li, T., R.J. Kauffman, E. van Heck, P.H.M. Vervest & B.G.C. Dellaert (2014). Consumer Informedness and Firm Information Strategy. Information Systems Research, 25 (2), 345-363.
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