Open PhD Position in Business Information Management
The aim of the ERIM-LIS research group is to be at the forefront of the developments in its domain and to make major contributions both to management science and to management practice. The research aims to contribute significantly to the leading role of the Netherlands as a gateway to Europe and as an innovative country. Much of the research is inspired by business challenges, and by the new opportunities of innovative information and communication systems, and technologies.
The research in the ERIM-LIS program is inter-disciplinary, integrating both quantitative and empirical research methods. Around the main research themes several research centres have been built (e.g. Smart Port, Behavioural Operations, Closed Loop Supply Chains, Optimization in Public Transport, Procurement, Future Energy Business, and Data Science and Business Analytics), which are used to focus the research, to acquire external funding, and to disseminate the research findings.
Keywords
Software Agents, Advanced Decision Support Systems, Theory of Informedness, Business Information Management, Software-based Platform Ecosystems, Supply Chain and Network Management.
Topic
Business Information Management
The research in this theme aims to understand the usage and impact of advanced, next generation information systems on firm and supply chain performance. The overall supply chain performance will be partly determined by the quality (in terms of availability, reliability, timing) of information and communication of the different firms in the supply chain and their information systems.
Next generation information systems are characterized by taking into account real time and detailed data (so called big data), incorporate autonomous decision making, collaboration and learning capabilities (for example by using software agents), and explores the opportunities of new information technology concepts such as cloud computing, sentiment analysis, semantic web technology and business analytics. The focus of the research is on inter-organisational information exchange among different firms in supply chains and its impact on decision-making and performance.
Theme 1: Design of a Sustainable Smart Electricity Market
There is a growing scientific and societal interest in many aspects of future energy business. A key challenge is how to facilitate the transition from traditional to renewable energy, and how to promote and support the consumption of sustainable energy in markets with dynamic prices. Currently, most energy markets employ fixed energy tariffs, and energy consumption in such systems is relatively insensitive to the height of energy prices. Due to current developments aimed at allowing for sustainable energy resources that usually fluctuate in terms of supply, this situation is likely to fundamentally change. Flexible energy tariffs -- that fluctuate to reflect the state of the energy market at the time -- have been put forward as a means to cope with the imbalances in the future energy market. For individual households, fluctuations in energy pricing may revolutionize the ways in which they consume and deal with energy, because they may receive higher energy bills than before, or be temporary disconnected at times due to unforeseen overload, but also can move their energy consumption to time windows with a low energy demand. These developments in the energy market raise the need to design smart markets mechanisms that achieve efficient, robust, and sustainable outcomes given the collective and individual preferences of market participants and the social context. Research will be carried out in collaboration with the Power Trading Agent Competition (TAC) community, a state-of-the-art computational simulation platform for sustainable energy market research. For further information: prof.dr. Wolfgang Ketter: wketter@rsm.nl and prof.dr ir Eric van Heck: evanheck@rsm.nl
Theme 2: Next Generation Decision Support Systems in Online Markets
Because the human mind has limited cognitive capacity, humans tend to make decisions using rules of thumb, or heuristics, which stem from their own experiences. While these heuristics may be appropriate for the decision maker’s environment, they usually result in only satisfactory, rather than optimal, decisions. As such, there is ample room for improvement. An important area of study within the overlapping fields of artificial intelligence and cognitive psychology is the design and implementation of (artificially) intelligent agents (i.e., software) that can effectively assist humans with their decision-making efforts, particularly in information-rich and time critical environments like markets. This theme calls for a quantitative approach to the future trading and decision-support.
The need for real-time decision-making arises in many different domains from deciding dynamic change of parameters in online auctions to making decisions in the flower markets. In this research, we envision a novel decision support framework where highly personalized software agents gather and analyze information, and recommend or automate decisions at the discretion of human decision makers. Such intelligent agent-based decision support systems will be particularly useful in various online markets where market participants must anticipate and adapt to ever-evolving market conditions at warp-speed and will need to take into account the challenges of the next generation supply chain and logistics.
Research will be carried out in cooperation with FloraHolland, the leading global auction platform for flowers and potted plants. For further information: prof.dr ir Eric van Heck:<link doctoral-programme phd-in-management phd-projects detail>evanheck@rsm.nl and prof.dr. Wolfgang Ketter: wketter@rsm.nl.
Approach
The research in Business Information Management is inter-disciplinary, integrating both quantitative and empirical research methods. Research is carried out using simulation modeling, laboratory and field experiments, next to detailed case studies and surveys. Research is done in collaboration with researchers in computer science, software engineering, artificial intelligence, and economics.
Literature references
Data sources:
The research group in Business Information Management carries out its research in close cooperation with its business partners based on real-world business challenges. The real-world data that is needed for the research is provided by the business partners.
Literature:
A number of relevant papers of the research group are the following:
Bichler, M., Gupta, A. and Ketter, W. 2010. “Designing smart markets,” Information Systems Research, 20th anniversary special issue, (21:4), 688-699
Collins, J., W. Ketter, et al. (2010). "Flexible decision support in dynamic interorganizational networks." European Journal of Information Systems, (19:4), 307-318.
Ketter, W., Collins, J., Gini, M., Gupta, A., and Schrater, P. (2012). "Real-time tactical and strategic sales management for intelligent agents guided by economic regimes." Information Systems Research, (23:4), 1263-1283.
Ketter, Wolfgang, Collins, John & Reddy, Prashant (2013). Power TAC: a competitive economic simulation of the smart grid.Energy Economics, 39(September), 262-270.
Ketter, W. & Symeonidis, A. (2012). Competitive Benchmarking: Lessons learned from the Trading Agent Competition. AI Magazine, 33(2), 103-107.
Li, Ting, Kauffman, R.J., Heck, E. van, Vervest, P.H.M. & Dellaert, B.G.C. (2014).Consumer Informedness and Firm Information Strategy. Information Systems Research, 25(2), 345-363.
A reinforcement learning approach to autonomous decision-making in Smart Electricity Markets.Machine Learning, 92(1), 5-39.Peters, M., Ketter, W., Saar-Tsechansky, M. & Collins, John (2013).
Expected output
The research team in Business Information Management focuses on research that leads to publications in highly ranked scientific journals in the area of information systems, such as Information Systems Research, MIS Quarterly, Management Science, and Communications of the ACM, and in adjacent areas such as in software engineering, artificial intelligence, and energy research. The research in these Ph.D. projects also aims at a number of highly ranked publications. Moreover, the open Ph.D. project should lead to the publication of a Ph.D. thesis after 4 years. Nowadays it is usual that a Ph.D. thesis consists of a number of high quality papers that have been published already or that have been accepted for publication.
Scientific relevance
The aim of the research in the area of Business Information Management is to be at the forefront of the developments in its domain and to make major contributions to management science.
The research aims to contribute significantly to the leading role of the Netherlands in the digital transformation of firms and supply chains and networks and as an innovative country. Much of the research is inspired by business challenges in area’s such as Supply Chain Management, Logistics, Trading, and Energy and by the opportunities of innovative information and communication systems and technologies. The research group aims at carrying out high quality research that can be published in highly ranked scientific journals. The research group has an excellent publication track record in these journals.
PhD candidate profile
Candidates should have obtained a Master’s degree in Business Administration or Management, Economics, Econometrics, Computer Science, Information Management or Information Systems, Mathematics, Operations Research, Statistics or another filed that provides a sufficient background in quantitative analysis. Further, curiosity and an interest to work in an interdisciplinary environment are considered as assets.
Contact information
For academic questions only prof.dr. Wolfgang Ketter: wketter@rsm.nl and prof.dr ir Eric van Heck: evanheck@rsm.nl. For procedural questions, contact the <link doctoral-programme contact-the-doctoral-office>Doctoral Office.
Deadline
Saturday, 31 January 2015
