Aug 14

Twentyfirst International Working Seminar on Production Economics

February 24-28, 2020
Innsburck, Austria

We will continue the Working Seminar on Production Economics in 2020 Innsbruck. The detailed information of the organization, paper submission, registration will come soon. For current contact, please email:

Professor Hubert Missbauer, Universität Innsbruck, Austria,

Professor, Ou Tang, Linköping University, Sweden,

Feb 13

New Industry Projects on Inventory Forecasting

Logistics Systems Dynamics Group (LSDG), and
Panalpina Centre for Maufacturing and Logistics Research at Cardiff University

Cardiff Business School has partnered with Yeo Valley, the largest organic dairy producer in the UK, on a project to streamline the company’s forecasting, planning and replenishment systems. The £220,000 two-year collaborative project is being led by Dr Laura Purvis, Professor Stephen Disney and Professor Aris Syntetos, from the School’s Logistics and Operations Management section. This new project and partnership enables the School and Yeo Valley to conduct research into flexible and resilient operations and supply chain management strategies. The project runs with the contribution of one postdoctoral research assistant, Xia Meng.

The School has also partnered with Hilti on a project co-funded by the Economic and Social Research Council (ESRC, UK) to elevate the company’s inventory forecasting performance. Hilti is a multinational company that develops, manufactures, and markets products for the construction, building maintenance, and mining industries. Dr Qinyun Li will be working for the first half of 2018 with Hilti’s global statistical forecasting team, after having been awarded an early career research fellowship grant from ESRC.



Feb 13

TU Darmstadt Department of Law and Economics – Research Assistant position

The Department of Law and Economics invites applications for a vacant position of a

Research Assistant – 75 %

at the Institute for Production and Supply Chain Management, initially limited to 3 years.

An option for increasing the coverage of the position is available – for more information please contact the head of the institute.

Applicants should have a Master or Diploma degree, comparable to a German University degree, with a focus on quantitative studies, preferably in the areas of business mathematics, business informatics, industrial and business engineering with majors in operations research/management science, logistics or industrial management/supply chain management.

Applicants with experiences in the use of mathematical optimization software, such as Mathematica, MatLab, CPlex or LINGO, will be given preference. Applicants should further be fluent in German or English; proficiency in both languages is desirable. The prospective job holder is expected to contribute to research and teaching at the institute, in particular:

•Contribute to the various research projects of the institute in the area of production and logistics
•Contribute to the preparation of (and conduct) lectures and seminars
•Supervise student theses
•Take over administrative duties

Opportunity for further qualification (doctoral dissertation) is given. The fulfillment of the research and service requirements attached to this position serve at the same time as fulfillment of the academic requirements for a candidate’s doctoral degree.

The Technische Universität Darmstadt intends to increase the number of female employees and encourages female candidates to apply. In case of equal qualifications applicants with a degree of disability of at least 50 or equal will be given preference.
Wages and salaries are according to the collective agreements on salary scales, which apply to the Technische Universität Darmstadt (TV-TU Darmstadt).

Please send your application including a CV and certificates preferably in electronic form to: or by mail to: TU Darmstadt, Prof. Dr. Christoph Glock, Fachgebiet Produktion und Supply Chain Management, Fachbereich Rechts- und Wirtschaftswissenschaften, Hochschulstr. 1, 64289 Darmstadt, Germany.

For questions and further information please do not hesitate to contact us.

Code. No. 24

Application deadline: February 15, 2018


Feb 13

Call for Papers – Machine Learning for Big Data in Industrial Processes

Special Issue on Machine Learning for Big Data Analytics in Manufacturing and Logistics Processes

Applied Mathematical Modelling invites submissions of original contributions to machine learning research for Big Data Analytics for Optimization of Manufacturing and Logistics Processes.

1. Summary and Scope

Machine learning is continuously enhancing its power in a wide range of applications and has been pushed to the forefront in recent years partly owing to the advent of big data. Thus, machine learning techniques have generated a huge societal impact in a wide range of applications such as computer vision, speech processing, natural language understanding, neuroscience, health, and Internet of Things and business process improvement. Moreover, in the context of big data, machine learning algorithms enable to uncover more fine-grained or complex patterns and make more timely and accurate predictions than ever before, e.g. for sales, marketing and tailor-made advertising applications for customers.

The data comes from different sources and in different forms and formats (i.e. structured or unstructured) such as consisting of a complex mixture of cross-media data content. For example, text, images, videos, audio, graphics, process signals, and time series sequences in logistics and manufacturing processes. The complexity, size, variety, and uncertainty (noise) in the data make it challenging to analyze the data and build models with it using traditional approaches. Machine learning methods have extensively been used in many industrial application areas such as pattern recognition, object and product identification and steering, predictive maintenance, scheduling and material flow control, predictive analytics in supply chains for logistics planning purposes using industry 4.0 environment, and statistical process control. Machine Learning is programming computers to optimize a performance criterion using example data or past experience. They are most useful when learning is needed in the absence of human expertise, or humans are unable to explain their expertise, or solution changes over time, or solution needs to be adopted in particular cases[1]

This special issue will focus on brand-new research results and shared recent advances in this research area. We solicit original contributions that have a strong emphasis on data analytics using machine learning techniques.

The list of possible topics includes, but is not limited to:

Machine learning methods for

  • Business process improvement and optimization
  • Analysis of real-time business process data
  • Real-time data analysis in a statistical process and quality control
  • Predictive analytics in supply chains
  • Machine learning methods in process optimization and quality control
  • Predictive maintenance
  • Logistics and manufacturing process optimization
  • Data analytics in manufacturing and logistics processes
  • Industrial analysis and mining applications via machine learning methods


Read the full Call for Papers >>>

Sep 27

Dr. Johannes Fichtinger: 1976 – 2017

Dr. Johannes Fichtinger


It is with our deepest regret and great sorrow to report that Dr. Johannes Fichtinger, Assistant Professor at the Institute for Production Management of  the Vienna University of Economics and Business passed away on September 1, 2017 after two years of fight against a serious illness.

As one of his last tasks he has completed, Johannes with his team organized a succesful ISIR Summer School in Vienna from August 21-25, for which our community is really grateful.

Our deepest sympathy goes out to his family, his wife Dr. Emel Arikan-Fichtinger, and his 5-year-old son, Serkan.

Read the obituary from his colleagues here.


Sep 27

Twentieth International Working Seminar on Production Economics

Innsbruck, Austria, February 19-23, 2018

Abstract submission deadline: November 1, 2017 



The Seminar Objective

The purpose of this seminar is to provide an opportunity for research scientists and practitioners to meet, present and develop their ideas on subjects within the field of Production Economics. Papers submitted will be distributed to all participants in advance. A discussant will be appointed for each paper. The intention is, that models and methods presented, and the discussion of them, will result in concrete ideas for future research and developments in this area. Participants of the Seminar are expected to act as discussants within their field of expertise.

Production Economics
focuses on scientific topics treating the interface between engineering and economics/management. The subject is interdisciplinary in nature. The ultimate objective is to create and develop knowledge for improving industrial practice and to strengthen the theoretical base necessary for supporting sound decision making. Tracing economic and financial consequences in the analysis of the problem and solution reported, belongs to the central theme.

Call for abstracts
Participants, who wish to present papers, are requested to send an abstract not exceeding 250 words (in Word format), to the Programme Committee by November 1, 2017 at the latest (by email to The conference language is English. Acceptance of abstracts will be notified to authors by ca December 1, 2017. The number of participants will be limited.
The Seminar is a Working Seminar intending to provide ample opportunities for interaction between Authors, Discussants and Audience. Participants are therefore recommended to join the sessions of the seminar for at least three of the four days. By submitting an abstract authors implicitly agree to have their paper published in the Seminar Proceedings, which means that their paper has not been published  nor is intended to be published elsewhere. 

Full papers should be submitted by January 10, 2018, in order to be included in the Pre-Prints. Papers presented will be reviewed after the seminar. Accepted papers will be printed in a proceedings issue of the International Journal of Production Ec onomics by Elsevier, Amsterdam.

Seminar location

Congress Innsbruck Rennweg 3, A-6020 Innsbruck Phone: 43-512-575600, fax: +43-512-575607

Seminar sessions
The seminar will be held in Congress Innsbruck beginning Tuesday and ending Friday in morning sessions 8.00-11.30 am and evening sessions (except Friday) 7.00-9.15 pm. Afternoons will be free for other activities. Buses will be available for participants going to skiing areas.
Reception and Registration
A reception will be held on Monday, February 19, beginning at 6 pm in Kristall Foyer, Congress Innsbruck. Registration takes place prior to the reception.

Internet access
Internet is accessible in the Congress Hall by wireless connection. Conference fee The basic fee for the seminar is € 695.00 (Paperback PrePrints, USB stick and CD), or € 600.00 (PrePrints on USB stick and CD), including VAT. The fee covers reception, morning and evening coffees, PrePrints and Farewell Cocktails. The fee is to be paid into Tiroler Sparkassen AG, Innsbruck: IBAN: AT9120 5030 3300 415746, BIC: SPIHAT22XXX, Account: PRODECO, by January 10, 2018.
Please identify your name with the payment. Payment can also be made by credit card (Visa or MasterCard) on the attached Application Form. Payment into Tiroler Sparkasse is the preferred option for participants from the eurozone.
Accompanying family members are not requested to pay any basic fee.

Programme Committee

M. Bogataj, University of Ljubljana

D. Çelebi, Istanbul Technical University

A. Chikán, Corvinus University, Budapest

H. Ding, Beijing Jiaotong University

A. Dolgui, Ecole des Mines de Saint-Étienne

G. Fandel, Fern-Universität Hagen

L. Gelders, Katholieke Universiteit, Leuven

R. F. Hartl, Universität Wien

G. Lo Nigro, Università di Palermo

H. Matsukawa, Keio University, Yokohama

S. Minner, Technische Universität München

Ch. O’Brien, Nottingham University

C. Pappis, University of Piraeus

L. Peccati, Università Commerciale Luigi Bocconi, Milan

J.E. Rowcroft, University of New Brunswick

R.H. Teunter, Rijksuniversiteit Groningen

M. Tuominen, Lappeenranta University of Technology

S.M. Wagner, Eidgenössige Technische Hochschule, Zürich

D.C. Whybark, University of North Carolina, Chapel Hill Organisation Committee

R.W. Grubbström, Linköping Institute of Technology

H.H. Hinterhuber, Universität Innsbruck

J. Lundquist, Linköping Institute of Technology

A. Mayr, Universität Innsbruck

Official mailing address and Web Site

Organisation Committee,

Att: Professor Hans H. Hinterhuber, Falkstrasse 16, A-6020 Innsbruck, Austria. e-mails:, Fax: +43 512 582414.

Web site:

Social Programme

A Social Programme for participants and their accompanying family members will be arranged, including a Tyrolean dinner, a tour of Innsbruck art galleries, a visit to Swarovski Crystal Worlds, the Ski Jump, the Nordpark Cable Railway, and several other activities.

Download the Flyer. 


Sep 27

Report on the 13th ISIR Summer School

13th ISIR Summer School on “Competitive Advantage through Resource Efficiency”

21‐25 August, 2017

WU Vienna University of Economics and Business, Wien, Austria

Download the Summary Report of 13th ISIR Summer School.

Apr 24

Decision Sciences – Call for Papers: Special Issue on “Information and Operational Decision Sciences



Call for Papers: Special Issue on “Information and Operational Decision Sciences: The Interplay of Information Technology and Operational Decision Sciences”


Guest Editors

Jose Benitez, Rennes School of Business, Rennes, France & University of Granada, Spain, email:
Xin Luo, University of New Mexico, USA, email:
Gyula Vastag, Szechenyi Istvan University, Hungary,

Special Issue Theme and Scope: Information and Operational Decision Sciences
The theme of the Special Issue is “Information and Operational Decision Sciences: The Interplay of Information Technology and Operational Decision Sciences”. Information technology (IT) capabilities enable firms to digitally transform their business processes to achieve business flexibility, quality, and innovation activities, thus improving the firms’ operational performance. Operational capabilities and performance are the heart of the firm’s business model to survive in the long run. Firms’ ability in using and leveraging innovative IT resources may facilitate the development of operational capabilities to increase firm performance.

As two separate fields in many Business Schools [i.e., Information Systems (IS) and Operations Management (OM)], sometimes it seems as IT is from Mars and OM comes from Venus. The Decision Sciences community and Decision Sciences are the ideal platforms to pursue a “transdisciplinary” approach (that is looking for the unity of knowledge beyond disciplines) to develop high quality and innovative research work growing out of these two fields. Because in the interplay of IT and operational decision making the whole is more than the sum of its parts, this Special Issue calls for original research on the interplay of IT and operational decision making.

This Special Issue welcomes the best submissions of the 8th Annual Conference of the European Decision Sciences Institute (EDSI 2017), as well as other high-quality submissions of other relevant conferences in 2017 (including but not restricted to DSI 2017, EURO 2017, EurOMA 2017, INFORMS 2017, and ICIS 2017).

Research Topics
This Special Issue calls research submissions about “Information and Operational Decision Sciences” using novel theories and/or methods as well as research contexts that make a significant contribution to knowledge in Decision Sciences. Submissions that focus on the interplay of IT and operational decision-making are especially welcome. Topics of interest include but are not limited to the following:

 Interplay of IT and operational decision making,
 Business value of IT,
 IT-enabled organizational capabilities,
 IT and innovation activities,
 Business value of social media,
 Social media and business activities,
 Social media and customer value proposition,
 Social media and innovation activities,
 Big data and operational decision making,
 Big data and business analytics.
 Supply chain management and value creation,
 Innovation management,
 Supply chain management and open innovation,
 Globalization of manufacturing operations,
 Quality management,
 Triple bottom line, operations management, and IT,
 Behavioral aspects of operations management,
 Decision making in public organizations.

Submission Instructions
Inquiries should be directed to the Guest Editors. Manuscripts should be submitted online directly. Please see instructions on the Journal’s website: Please select article type “Special Issue” and “Information and Operational Decision Sciences” while uploading your paper. Please indicate any of the Special Issue Guest Editors (Jose Benitez, Xin Luo, or Gyula Vastag) as your Senior Editor. All submitted papers will go through the rigorous peer-review system of the Decision Sciences Journal.

Tentative schedule
Initial paper submission deadline: January 1, 2018.
First round author notification: March 1, 2018.
Invited revisions deadline: May 1, 2018.
Second round author notification: July 1, 2018.
Final revision deadline: August 1, 2018.
Final author notification: September 1, 2018.
Projected publication: Fall 2018 or Spring 2019

Guest Editors’ Bios
Jose Benitez is an Associate Professor of IS at the University of Granada, Spain. He will be appointed in June 2017 as Full Professor of IS at Rennes School of Business, Rennes, France. Dr. Benitez is also a Visiting Professor of IS at the University of Twente, The Netherlands, and an Instructor of Partial Least Squares (PLS) Path Modeling at the PLS School. His research interests cover the study of how the firm’s portfolio of IT capabilities affects organizational capabilities and firm performance, and the development of PLS path modeling in the field of IS. His research has been published or is forthcoming in leading IS journals such as MIS Quarterly, European Journal of Information Systems, Information & Management, and Journal of Information Technology. He currently serves as Associate Editor for European Journal of Information Systems, and Information & Management.

Xin Luo is an Endowed Regent’s Professor and Associate Professor of IS and Information Assurance in the Anderson School of Management at the University of New Mexico, USA. He is the Associate Director of Center for Information Assurance Research and Education at the University of New Mexico. He received his Ph.D. in IS from Mississippi State University, USA. He has published research papers in leading journals including Decision Sciences, Decision Support Systems, European Journal of Information Systems, Communications of the ACM, Journal of the AIS, Journal of Strategic Information Systems, Information Systems Journal, Information & Management, and Computers & Security. He is currently serving as an Ad Hoc Associate Editor for MIS Quarterly and an Associate Editor for European Journal of Information Systems, Electronic Commerce Research, Journal of Electronic Commerce Research, and International Conference on Information Systems. His research interests center around information assurance, innovative technologies for strategic decision-making, and global IT management.

Gyula Vastag is Professor and Director of the Management Ph.D. Program at Szechenyi University (Győr, Hungary) and at the National University of Public Service (Budapest, Hungary). He co-authored five books (by Elsevier and Pearson), wrote eight business cases, contributed chapters to about 20 books, and published papers in a variety of peer-reviewed academic and professional journals in the United States and in Europe including – among others – Decision Sciences, Journal of Operations Management, Production and Operations Management, European Journal of Operational Research, European Management Journal, International Journal of Production Economics, and International Journal of Production Research. Gyula received several research awards: New Central Europe Distinguished Senior Researcher Scholarship (2014), Best Applications Paper Award by Alpha Iota Delta – The International Honor Society in Decision Sciences and Information Systems (2012), and Award for Research Excellence from Corvinus University (2009). He was the Founding Editor of the Pannon Management Review, is Associate Editor of Decision Sciences and serves on the editorial boards of the Central European Business Review, Business Research, Logistics Research, and International Journal of Quality Innovation. Currently, Gyula serves as President-Elect of the European Decision Sciences Institute and as Board Member of the European Operations Management Association.

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