EWEPA is a major biennial conference on the topics of productivity, efficiency and performance analysis. We expect a very large number of participants to attend, from a wide international community. Presentations are invited on the theory and application of economics, econometrics, statistics, management science and operational research to various problems in the areas of productivity and efficiency. All popular techniques and methodologies will be represented, including stochastic frontier analysis, data envelopment analysis, bootstrapping approaches, and many more. We also welcome papers on broader issues related to measuring, understanding, incentivising and improving the productivity and performance of firms, public services and industries.

The INFORMS 2016 Annual Meeting will take place in the Music City Center, the state-of-the-art convention center recently built, and the adjacent Omni Nashville Hotel. The conference will feature plenaries and keynotes; panel discussions; tutorials; and thousands of oral and poster presentations from leading academics, industry experts, students, and representatives of government agencies. This Annual Meeting will provide the attendees numerous opportunities to share expertise and experiences; find prospective employers and employees; and build professional networks by meeting new people and reconnecting with colleagues.

The College-Industry Council on Material Handling Education (CICMHE) held its bi-annual business meeting October 15th and 16th in Tucson, Arizona. CICHME is an academic/industry council of the Material Handling Industry (MHI) that promotes increased awareness of material handling and logistics through a variety of educational and research activities. The council is organized into two working committees: Events and Projects.

The Conference on Advances in Big Data Modeling, Computation and Analytics was held at Texas A&M University on September 23 and 24 featuring a variety of academic and industry talks. A highlight of the event was a keynote talk by Michael Jordan, the abstract is included below.

On Computational Thinking, Inferential Thinking and Data Science
Michael I. Jordan, University of California, Berkeley

ABSTRACT
The rapid growth in the size and scope of datasets in science and technology has created a need for novel foundational perspectives on data analysis that blend the inferential and computational sciences. That classical perspectives from these fields are not adequate to address emerging problems in “Big Data” is apparent from their sharply divergent nature at an elementary level—in computer science, the growth of the number of data points is a source of “complexity” that must be tamed via algorithms or hardware, whereas in statistics, the growth of the number of data points is a source of “simplicity” in that inferences are generally stronger and asymptotic results can be invoked. On a formal level, the gap is made evident by the lack of a role for computational concepts such as “runtime” in core statistical theory and the lack of a role for statistical concepts such as “risk” in core computational theory. I present several research vignettes aimed at bridging computation and statistics, including the problem of inference under privacy and communication constraints, and ways to exploit parallelism so as to trade off the speed and accuracy of inference.

The Texas Research Data Center (RDC) hostied the 2016 FSRDC Research Conference on September 15, 2016. The Texas RDC is supported by a multi-university consortium involving Texas A&M University, Texas A&M University System, Baylor University, Rice University, The University of Texas at Austin and The University of Texas at San Antonio. The conference was a day of concurrent paper and poster sessions and a keynote presentation. Sessions were based on current or recent research using data from the nationwide network of RDCs. Themes include, research topics from the fields of economics, business and management, demography, and health and developments in data sets. Papers and posters involved statistical analyses on nonpublic versions of data sets available from the U.S. Census Bureau, the National Center for Health Statistics, the Agency for Healthcare Research and Quality, and other federal statistical agencies.

The Doctoral dissertation of M.Sc. Xiaofeng Dai in the field of Quantitative Methods of Economics and Management Science “Adapting image processing and clustering methods to productive efficiency analysis and benchmarking: A cross disciplinary approach” was publicly examined at the Aalto University School of Business on Friday, 26 August 2016. The defense of dissertation will be held in Chydenia building (address: Runeberginkatu 22-24, Helsinki, Finland), Stora Enso Hall (3rd floor) starting at 12 o’clock.

Opponent: Professor Andrew Johnson, Texas A&M University
Custos: Professor Timo Kuosmanen, Aalto University School of Business

Xiaofeng Dai comes from Beijing, where she currently works as Associate Professor of bioinformatics at Jiangnan University, China.

The 7th Helsinki Workshop on Efficiency and Productivity Analysis, Helsinki, Finland, August 2016.

The summer workshop of Operations Research and Supply Chain Management (OR/SCM) is regularly held annually in Taiwan. This year was the 8th workshop since 2009. Typically three or four invited guest speakers will give us a 3 or 6-hour lecture about the cutting-edge research topics in OR or SCM. This year Andrew Johnson was one of the speakers and talked about, Production Function Estimation: An application of shape constrained functional estimation.

The list of the topics and guest speakers in 2014 and 2015 are summarized as follows:

The 6th workshop (2014)
Prof. Chung-Yee Lee (Dep. of IELM, HKUST)
Topic: Ocean container transport logistics: Making global supply chain effective
Prof. Loo Hay Lee (Dep. of ISE, NUS)
Topic: Simulation optimization and its application
Prof. Che-Lin Su (Booth School of Business, The University of Chicago)
Topic: Constrained optimization approaches to estimation of structural models: methods and applications
Prof. Ruey-Lin Sheu (Dep. of Math, NCKU)
Topic: From Farkas theorem to the S-lemma-Hidden convexity inside the nonconvex

The 7th workshop (2015)
Prof. Gangshu (George) CAI (Operations Management & Information Systems Department, Leavey School of Business, Santa Clara University)
Title: Modeling Multichannel Supply Chain Competition with Marketing Mixes
Prof. Shih-Fen CHENG (School of Information Systems, Singapore Management University)
Title: Applied Game Theory: An Introduction for Business and Engineering Applications
Prof. Hsiao-Hui Lee (Faculty of Business and Economics, the University of Hong Kong)
Topic 1: Supply chain management using game theoretical models
Topic 2: Supply chain management using empirical models