Call for Papers

Requirements and guidance for abstract, full paper or poster submission

EDSI 2022

Presentations at the conference will be based on submission and acceptance of an abstract (up to 250 words), Following abstract acceptance, delegates will have the option to submit a full paper, addressing the review comments. All accepted abstracts and papers will be available in the Conference Proceedings. English is the official language of the conference. We welcome abstract, paper and poster submissions. prospective authors are invited to submit original research abstracts/papers/posters (NOT submitted or published or under consideration anywhere in other conferences/journal).

Abstract

You can submit an abstract alone, or optionally a full paper following abstract acceptance. Abstracts should be submitted using our submission system.

Abstracts should be submitted through Ex Ordo HERE by the deadline of January 14th 2022 February 7th 2022 (extended).

Notifications of acceptance with review comments will be communicated by February 14th 2022. 

Poster (Optional)

Alternatively you can submit a poster to our poster session. If you choose to submit a poster, an abstract should be submitted using our submission system.

Poster abstracts should be submitted through Ex Ordo HERE by the deadline of January 14th 2022 February 7th 2022 (extended).

Notifications of acceptance with review comments will be communicated by February 14th 2022.

Full Paper (Optional)

Following abstract acceptance, you will have the option to submit a full paper addressing review comments.

Full papers should be submitted through Ex Ordo HERE by the deadline of April 1st 2022.

Submissions should be created using the EDSI 2022 full paper template (please download it HERE)

Topics

EDSI 2022 invites contributions from across the full spectrum of disciplines relevant to the decision sciences, including analysis, modeling, and qualitative studies. Topics include but are not limited to:
  • Accounting Analytics
  • Behavioral Operations
  • Data Analytics
  • Decision Making in a Pandemic
  • Decision Making in Public Organizations
  • Decision Support Systems
  • Decision Sciences in Practice
  • Decision Theory
  • Digitalization in Operations and Supply Chains
  • Digital Business Transformations
  • Global Operations and Plant Location
  • Healthcare Operations
  • Humanitarian Operations and Disaster Management
  • Industry 4.0
  • Information Systems in Operations and Supply Chains Innovation
  • Innovative Teaching Methods
  • Interfaces between Functional Areas
  • Logistics and Transportation
  • Operations Planning and Control
  • Operations Strategy
  • Performance Measurement and Management
  • Project Management
  • Purchasing, Procurement and Rightsourcing
  • Quality Management and Lean Operations
  • Risk Management
  • Service Operations
  • Strategy
  • Supply Chain Management
  • Supply Networks
  • Sustainability and CSR
  • Technology Management

 

Special Streams

Stream 1: Analytics for Operations Planning under Uncertainty

Ciara Heavin, S. Armagan Tarim
Cork University Business School, UCC, Ireland

Fierce competition in today’s global markets, the introduction of products with short life
cycles and increased customer expectations have forced businesses to focus their attention on
operations planning. Further, the Covid-19 Pandemic has created a new impetus for
organisations to be flexible, as they adapt to changing internal (e.g., availability of staff) and
external environmental factors (e.g., changing public health guidelines, Brexit etc).

Operations planning is concerned with assigning appropriate resources to activities and
coordinating these activities promoting greater transparency and equity in decision making,
while minimising multiple and possibly conflicting costs. These activities span a large
spectrum of decisions, such as distribution network configuration, production scheduling,
staff rostering, inventory control, integration of inventory and transportation, risk
management, etc. Most of these planning problems have at their core difficult combinatorial
problems and involve uncertainty.

In the literature it is well-established that our inability to effectively address uncertainty in
operations planning is an increasingly critical limitation and is a significant inhibitor in the
use of research results in practice. Operations management research, to be relevant, must
tackle large-scale stochastic decision problems. However, the corresponding models often
pose serious computational challenges for even small sized problems.
With the advancements of data acquisition and processing capabilities, artificial intelligence
(AI), machine learning (ML), and operations research (OR) have significantly boosted the
accuracy of data-driven predictions and optimisation in operations management. While
notable progress has been made, much work remains to be done. In this session, recent
research results will be presented. These studies will highlight the application of AI/ML/OR
methods and techniques to operations planning under uncertainty with the potential to impact
competitive performance, innovativeness, as well as inclusion and community building.

Best Paper Awards

Two best paper prizes will be awarded – one for the best theory-oriented paper and one for the best applications-oriented paper presented at the conference. Prizes will also be awarded for the best PhD student presentation and best poster. Note that papers can only be submitted to one prize category.

Evaluation: The EDSI Board will convene the best papers nomination panel.