Keynote Address [pdf] Optimising services - strategy, tactics and control Mark Wallace Clayton School of Information Technology Monash University, Australia In the service industry, only one thing is certain - next year will be different from this year. Every service operation must therefore continually reallocate resources, reconfigure and reoptimise. Strategy is about where to invest - balancing capital investment against future operating costs. With the resources more or less fixed, the tactical question is how best to allocate and schedule them. Finally, on the day of operation, resources must be reconfigured to meet client requirements, typically imbalanced by various disruptions. Though strategy, tactics and operational control are often handled quite separately, they are mutually interdependent. We discuss ways in which operational control impacts medium term tactical planning, which in turn impacts long term strategy. We show by example how this understanding can improve overall customer service and minimise costs. Biodata Mark Wallace is a Research Professor in the Faculty of Information Technology,Monash University, and he has been appointed a National ICT Australia (NICTA) fellow. His research interests span artificial intelligence, operations research and the separation of problem modelling from problem solving. He has a particular interest in applications in industry and commerce. He is an editor for the Constraints Journal, Journal of Heuristics Study on the Group-buying auction Jian CHEN School of Economics and Management, Tsinghua University Beijing, 100084, China With the development of electronic commerce, online auction plays an important role in the electronic market. The group-buying auction (GBA) is a new kind of dynamic pricing mechanism on the Internet. It makes the bidders as a group through Internet to get the volume discounts, i.e., the more bidders bid, the lower the price of the object being auctioned becomes. In this talk, we first analyze the group-buying auction under some assumptions such as that IPVs (Independent Private Values) model applies and bidders are risk neutral and symmetric, etc., and build an incomplete information dynamic game model to illustrate the bidders’ bidding process. It proves that for the bidders there exists a weakly dominant strategy S, i.e., no matter when a bidder arrives at the auction and what the bidding history is, the highest permitted bid price that is no greater than his value to the object is always his optimal bid price, but may not be the unique one. Then, we analyze the seller's pricing strategy with the GBA. Based on the bidders' optimal strategy, the sellers' optimal price curve of the GBA in the uniform unit cost case and in some supply chain coordination contracts are explored. We find that the best discount rate is zero, which implies the optimal GBA is equivalent to the optimal fixed pricing mechanism (FPM). Furthermore, we compare the GBA with the FPM in two special cases, the economies of scale and risk-seeking seller, and find that in both cases the GBA outperforms the FPM. The collusion of bidders in traditional auctions is generally forbidden because it is harmful to the interests of sellers. However, we find that collusion in the GBA results in higher bidding, leading to market expansion that benefits both bidders and sellers. Furthermore, the group-buying auction with collusion (GBAC) is weakly dominant of the fixed price mechanism (FPM) for the seller. As collusion in the GBA is a win-win strategy for all traders, the GBA is a suitable form of online auctions, which are more vulnerable to collusion. Finally, we extend our study to B2B commerce, i.e., consider a supply chain with one supplier and several retailers in their respective independent market, where the supplier offers a new pricing mechanism based on the GBA, while the retailers attempt to cooperate with each other to exploit the pricing mechanism so as to optimize their total profits. A simple mechanism for profit redivision is employed, under which the retailers’ optimal order strategy is obtained. Biodata Chen Jian received the B.Sc. degree in Electrical Engineering from Tsinghua University, Beijing, China, in 1983, and the M.Sc. and the Ph.D. degree both in Systems Engineering from the same University in 1986 and 1989, respectively. He is EMC Professor and Chairman of Management Science Department, Director of Research Center for Contemporary Management, Tsinghua University. His main research interests include supply chain management, E-commerce, decision support systems, modeling and control of complex systems. Dr. Chen has published over 100 papers in refereed journals and has been a principal investigator for over 30 grants or research contracts with National Science Foundation of China, governmental organizations and companies. He has been invited to present several plenary lectures. He is the recipient of Ministry of Education Changjiang Scholars, Fudan Management Excellence Award(3rd), Science and Technology Progress Awards of Beijing Municipal Government; the Outstanding Contribution Award of IEEE Systems, Man and Cybernetics Society; Science and Technology Progress Award of the State Educational Commission; Science & Technology Award for Chinese Youth. He has also been elected to IEEE Fellow. He serves as Chairman of the Service Systems and Organizations Technical Committee of IEEE Systems, Man and Cybernetics Society, Vice President of Systems Engineering Society of China, Vice President of China Society for Optimization and Overall Planning, a member of the Standing Committee of China Information Industry Association. He is the editor of “the Journal of Systems Science and Systems Engineering”, an area editor of “Electronic Commerce Research and Applications”, an associate editor of “IEEE Transactions on Systems, Man and Cybernetics: Part A”, “IEEE Transactions on Systems, Man and Cybernetics: Part C”, and “Asia Pacific Journal of Operational Research” and serves on the Editorial Board of “International Journal of Electronic Business”, International Journal of Information Technology and Decision Making” and “Systems Research and Behavioral Science”. Complex Service Systems: Integration and Adaptation James M. Tien, Ph.D., NAE, Distinguished Professor and Dean, College of Engineering University of Miami, Coral Gables, Florida From a Venn diagram perspective, there are seven possible venues to consider when one looks at possible mixtures of services, integration and adaptation. Individually, we can have 1) a services system domain, 2) a spatially integrated system, and 3) a temporally adaptive system. When combined two at a time, we can have 4) an integrated service system, 5) an adaptive service system, and 6) a complex – integrated and adaptive – system. When all three combined, we can have 7) a complex – integrated and adaptive – service system. All seven venues are appropriately considered. In fact, the management of services must recognize the fact that any service system is actually a complex system of human-centered systems that is increasingly dependent on information technology. In general, a service system can be considered to be a combination or recombination of three essential components – people (characterized by behaviors, attitudes, values, etc.), processes (characterized by collaboration, customization, etc.) and products (characterized by software, hardware, infrastructures, etc.); thus, services management is about managing an integrated set of people, processes and products. Furthermore, in as much as a service system is an integrated system, it is, in essence, a system of systems which objectives are to enhance its efficiency (leading to greater interdependency), effectiveness (leading to greater usefulness), and adaptiveness (leading to greater responsiveness in the co-production framework). The integrative methods include a component’s design, interface and interdependency; a decision’s strategic, tactical and operational orientation; and an organization’s data, modeling and cybernetic consideration. A number of insights are also provided, including an alternative system of systems management view of services; the increasing complexity of systems (especially service systems), with all the attendant life-cycle design, human interface, and system integration issues; the increasing need for real-time, adaptive decision making within such systems of systems; and the fact that modern systems are also becoming increasingly more human-centered, if not human-focused – thus, products and services are becoming more complex and more personalized or customized. Biodata Dr. James M. Tien is currently the Dean of the College of Engineering at the University of Miami, Coral Gables, Florida. He received the BEE from Rensselaer Polytechnic Institute and the SM, EE and PhD from the Massachusetts Institute of Technology. He has held leadership positions at Bell Telephone Laboratories, at the Rand Corporation, and at Structured Decisions Corporation (which he co-founded in 1974). He joined the Department of Electrical, Computer and Systems Engineering at Rensselaer in 1977, became Acting Chair of the department, joined a unique interdisciplinary Department of Decision Sciences and Engineering Systems as its founding Chair, and twice served as the Acting Dean of Engineering. Dr. Tien’s areas of research interest include the development and application of computer and systems analysis techniques to information and decision systems. He has published extensively, been invited to present many plenary lectures, and been honored with both teaching and research awards, including being elected a Fellow in IEEE, INFORMS and AAAS and being a recipient of the IEEE Joseph G. Wohl Outstanding Career Award, the IEEE Major Educational Innovation Award, the IEEE Norbert Wiener Award, and the IBM Faculty Award. Dr. Tien is also an elected member of the U. S. National Academy of Engineering. jmtien@miami.edu