Guest Editors: Thanos Papadopoulos and Angappa Gunasekaran
The term ‘Big Data Analytics’ (BDA) refers to those algorithmic techniques, practices, methodologies, and applications that enable businesses to analyse and make sense of critical business data to help them understand their operations and market. BDA enables businesses to predict the likelihood an event and take timely business decisions, ensuring, for instance, that they are able to meet the needs of their customers over a sustained period of time. BDA highlights the importance of data in terms of its volume (referring to the amount of data), velocity (referring to frequency or speed by which data is generated and delivered), veracity (referring to data quality) and value (referring to the benefits from the analysis and use of big data). Improved productivity, competitiveness, and efficiency are amongst the benefits of BDA within supply chain and logistics management; for instance, gaining information from unstructured customer data can generate useful insights on product placement, pricing strategies, optimization strategies, layout optimization, operational risk management, and improved product/service delivery.
It is therefore no surprise that BDA has started receiving significant attention from supply chain and logistics management and management science researchers. In response, this special issue is seeking to pull together the latest thinking in this area. Much research on BDA has been limited to conceptual frameworks, definitions, and some empirical papers. However, limited studies have focused on applying big data modelling, algorithms, and analysis within supply chain and logistics management. The aim of this special issue is to help researchers and decision makers in understanding the modelling, algorithms, strategies, tactics and implementation processes involved in applying BDA in supply chains and logistics and the performance measures and metrics related to the application of BDA.
The scope of the special issue will be to present researchers and senior managers with modelling and analysis, and application of BDA in supply chains and logistics. This should include, for instance, applications of BDA on capacity management and planning of Human Resources, carbon foot-printing of supply chains and logistics, life-cycle management and product and process development, improving energy savings, efficiency of transport, and other related areas. The prime objective of the special issue is to publish original works from around the world that demonstrate interesting applications of BDA.
All submissions should follow the official scope of Computers & Operations Research. Contributed papers may deal with but are not limited to:
Big data modeling and analysis, including applications of BDA
OR techniques with a particular emphasis on algorithms for BDA
Modeling of performance measures and metrics in BDA
Modeling of cost/benefit and risk considerations/realizations in BDA
Performance measures and models for decisions using BDA
Justification for BDA through conceptual modeling and analysis
Real case studies focusing on BDA adoption for supply chains and logistics. Illustrative examples or examples inspired by real case studies should be avoided
Use of non-parametric methods such as Fuzzy Cognitive Mapping to support quantitative management decision making
Models for studying the impact of BDA on sustainable supply chain and logistics initiatives and policies
Strategic co-operation and partnership development for supply chain and logistics through BDA.
Manuscripts should be between 5000-7000 words in length, with all contributions being subjected to a desk screening process by the guest editors. Successful papers will then be reviewed. Please review the Computers & Operations Research “Guide for Authors” at: https://www.elsevier.com/journals/computers-and-operations-research/0305-0548/guide-for-authors Manuscripts should be submitted electronically via the Journal’s online submission system. Submitted manuscripts should not have been previously published nor be currently under consideration for publication elsewhere. Please select “SI: BDA for SC and LM” as the “Article Type” during the submission process. Submitted papers will undergo a normal review process according to the high standard of Computers & Operations Research. Manuscripts must be submitted no later than October 31, 2016.
Paper Submission Due: 31 October 2016
Notification of Review Results: March 31, 2017
Revised Manuscript Due: May 31, 2017
Final Decision: July 31, 2017
For any further information, please contact one of the following guest editors:
Professor Thanos Papadopoulos
Kent Business School
University of Kent
Sail and Colour Loft, The Historic Dockyard, Chatham, Kent ME4 4TE
Tel: +44 (0) 1634 88 8494
Professor Angappa Gunasekaran
Dean, Charlton College of Business
University of Massachusetts – Dartmouth
285 Old Westport Road
North Dartmouth, MA 02747-2300
Tel: (508) 999-9187