EURO2021 Athens

31th EUROPEAN CONFERENCE ON OPERATIONAL RESEARCH

Abstract submission deadline: March 28, 2021
Conference dates: July 11-14, 2021
Conference website: https://euro2021athens.com/

Dear Colleagues,
We are organizing the stream “Data Envelopment Analysis and Performance Measurement” at the upcoming EURO 2021 conference in Athens, July 11-14, 2021, that will take place in hybrid format.

Conference delegates will be able to choose, at the time of registration, whether they wish to participate virtually or physically attend the conference in Athens. Each timetabled session will be either virtual or physical, not mixed.

We have the great pleasure of inviting you to participate in EURO 2021 conference and submit a paper to this stream. To submit the paper, please visit https://euro2021athens.com/abstract-submission/  and use the invitation code 7982d87b

In order to submit a paper, you need to have a EURO account. If you do not have one, please visit http://www.euro-online.org/web/accounts/register/ and sign up for a new account.

If you would like to organize an invited session, please let us know via email to acamanho@fe.up.pt or giovanna.dinverno@kuleuven.be .

We will send you the information that will allow you to invite people to submit abstracts online to your session. Each session consists of four papers. Abstracts have at maximum of 1500 characters (extended deadline March 28).

Please, do not hesitate to contact us if you have any questions or if you need more information.

Looking forward to seeing you in Athens at EURO 2021!

Giovanna D’Inverno & Ana Camanho

Webinar on “Data Envelopment Analysis with PIM-DEA software”

Time: November 4, 2020 01:00 PM (UK time)

REGISTER YOUR FREE PLACE: https://lnkd.in/de58kuq

Join Ali Emrouznejad, Professor of Business Analytics, Aston University, for an introduction to Data Envelopment Analysis (DEA).
In this webinar he will share his top performance measurement tips using advanced DEA models and introduce features of the Performance Improvement Management Software (PIM-DEA).

Data Envelopment Analysis Stream at OR62, September 15-17, 2020, Online, Free to register

This stream is perfect for anyone interested in learning more about Data Envelopment Analysis (DEA). It will provide an introduction to DEA, demonstrate how DEA is used in benchmarking and regulation, and showcase how PIM-DEA software can be used in benchmarking. It is an excellent starting point for anyone looking to further their knowledge of productivity analysis or performance management.

Free registration:  CLICK HERE

Presenters:

Ali Emrouznejad will provide an introduction to DEA, before Emmanuel Thanassoulis and Srini Parthasarathy speak about DEA in regulation. The session will finish with a demonstration of how PIM-DEA software can be applied in regulation and a Q&A session.

Abstract:

The use of benchmarking in regulation with special reference to DEA

Utility companies provide services like water, energy and telecommunications etc. They have virtual monopoly power relative to clients and are therefore regulated to simulate market conditions. There is a prevailing view that markets either do not exist or are not competitive enough in the case of utilities. In essence, the Regulator is there to protect the consumer from excessive costs for the services provided by utilities.

The need for utilities to make large capital-intensive infrastructure investments, coupled with the absence of substitutes and inelastic demand, tends to generate natural monopolies. Given this market structure, governments have set up regulatory systems to control prices and incentivise investment, continuity of supply and improvement in the quality of service. The regulatory systems have largely developed in tandem with the privatisation of previously publicly owned and managed utilities such as gas, electricity, water and telecommunications.

This talk will give an overview of benchmarking and its purpose in the regulation of utilities in Europe and the UK. It will then outline how DEA has been integrated into Regulatory systems and offer insight into how DEA can be extended to improve the incentives within regulation.

Organisers & Chairs:

Ali Emrouznejad  –  a.emrouznejad@aston.ac.uk

Free registration:  CLICK HERE

IMA Journal of Management Mathematics

Special issue on:

Recent Advances in Inverse Data Envelopment Analysis

Guest editors: 

Ali Emrouznejad, Aston Business School, Aston University, Birmingham, UK
Gholam R Amin, Faculty of Business, University of New Brunswick at Saint John, Canada  

• Download: Call for Papers
• Further information: CLICK HERE
• Instructions for Authors: CLICK HERE
• Submit you paper:CLICK HERE

Data Envelopment Analysis (DEA) as developed by Charles Coopers, Rhodes (1978) is an optimization method of mathematical programming to generalize the Farrell (1957) single-input/ single-output technical efficiency measure to the multiple-input/ multiple-output case by constructing a relative efficiency score as the ratio of a single virtual output to a single virtual input.

The standard DEA models measure the relative efficiency of decision-making units (DMUs). They do not reveal the level of inputs and outputs that would allow a business firm to realize a given efficiency target. This requires solving an inverse problem which is beyond the scope of DEA models and requires appropriate mathematical models relate to inverse optimisation to be developed.

Recent years have seen the potential of inverse DEA (InvDEA) in solving different decision-making problems in the areas such as environmental efficiency, greenhouse gas emissions optimization, resource allocation, firms restructuring, and mergers’ gains estimation. Despite the wide range applicability of DEA, there are few applications of InvDEA in the literature.

In this issue, we consider state-of-the-art papers spanning all areas of analytical and empirical research related to new developments in InvDEA models and applications of performance and efficiency analysis in the real world as long as the article provides significant new insights to advance the practices of InvDEA.

Specifically, this special issue aims to invite scholars and practitioners to develop theory and application of InvDEA in the areas such as climate change, environmental efficiency, pollution minimization, carbon tax policy, firms restructuring, resource allocation, as well as potential merger and acquisition application of InvDEA for the post-Coronavirus market. 

References:

• Amin, G.R. Emrouznejad, A. and Gattoufi, S. (2017). Modelling generalized firms’ restructuring using inverse DEA. Journal of Productivity Analysis, 48(1), 51-61.
• Emrouznejad, A. Yang, G. and Amin, G.R. (2019). A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries. Journal of the Operational Research Society, 70(7), 1079-1090.
• Gattoufi, S. Amin, G.R. and Emrouznejad, A. (2014). A new inverse DEA method for merging banks. IMA Journal of Management Mathematics, 25(1), 73-87.
• Wegener, M. and Amin, G.R. (2019). Minimizing Greenhouse Gas Emissions using Inverse DEA with an Application in Oil and Gas. Expert Systems with Applications, 122, 369–375.

Important Dates

Guest Editors

• Dr Ali Emrouznejad
  Professor and Chair in Business Analytics, Aston Business School, Aston University, UK, A.Emrouznejad@aston.ac.uk
• Dr Gholam R Amin Faculty of Business, University of New Brunswick at Saint John, Saint John,  Canada,  gamin@unb.ca

List of Editors’ related paper on “Inverse DEA”: 

• Amin, G.R., and Ibn Boamah, M. (2020). A new inverse DEA cost efficiency model for estimating potential merger gains: A case of Canadian banks, Annals of Operations Research, 1-16, in press.
• Wegener, M., and Amin, G.R. (2019). Minimizing Greenhouse Gas Emissions using Inverse DEA with an Application in Oil and Gas, Expert Systems with Applications, 122, 369–375.
• Emrouznejad, A., Yang, G., and Amin, G.R. (2019). A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries. Journal of the Operational Research Society, 70(7), 1079-1090.
• Amin, G.R., Al-Muharrami, S., and Toloo, M. (2019). A combined goal programming and inverse DEA method for target setting in mergers, Expert Systems with Applications, 115, 412-417.
• Amin, G.R., and Oukil, A. (2019). Flexible target setting in mergers using inverse data envelopment analysis, International Journal of Operational Research, 35(3), 301-317.
• Amin, G.R., and Saeed Al-Muharrami (2018). A new inverse DEA model for mergers with negative data, IMA Journal of Management Mathematics, 29(2), 137-149.
• Amin, G.R., Emrouznejad, A., and Gattoufi, S. (2017). Modelling Generalized Firms’ Restructuring using Inverse DEA, Journal of Productivity Analysis, 48(1), 51-61.
• Amin, G.R., Emrouznejad, A., and Gattoufi, S. (2017). Minor and Major Consolidations in Inverse DEA: Definition and Determination, Computers and Industrial Engineering, 103(1), 193-200.
• Gattoufi, S., Amin, G.R., and Emrouznejad, A. (2014). A new inverse DEA method for merging banks, IMA Journal of Management Mathematics, 25(1): 73-87.
• Amin, G.R., and Emrouznejad, A. (2007). Inverse forecasting: A new approach for predictive modeling. Computers & Industrial Engineering, 53(3):491–498.
• Amin, G.R., and Emrouznejad, A. (2007). Inverse linear programming in DEA. International Journal of Operations Research, 4(2):105-109.

ANOR- Annals of Operations Research

Special issue on:

Blockchain in Operations and Supply Chain Management

Guest editors: 

Ali Emrouznejad, Soumyadeb Chowdhury, Prasanta Dey, Aston University, United Kingdom

Click HERE for details

Blockchain technology (BCT) has emerged as an enabling technology that can provide traceability, provenance and transparency in business operations, across complex global supply chain ecosystems, where leanness, agility, and speed are crucial, in addition to achieving social sustainability. It is considered one of the most disruptive technologies representing decentralised environment for transactions, self-executing digital contracts (smart contracts) and intelligent asset management over the Internet, providing a single-view to the entities (users) involved in the transaction. Therefore, the key characteristics of BCT will significantly impact the organisational governance, supply-chain relationships, operations strategy, digital transformation pathway and existing supply-chain business models. BCT when integrated with other technologies such as the Internet of Things, big data analytics, and artificial intelligence, will help to increase the efficiency of supply chain through agile data-driven decision-making based on high quality data (stored in Blockchain) and further facilitating supply chain transparency that will also afford product traceability, authenticity and legitimacy, and enhance sub-supplier transparency that will alleviate social sustainability problem in multi-tier supply networks.

Despite the potential of BCT for the field of Operations and Supply Chain Management (OSCM), it has thus far received extremely limited attention in the OSCM literature, except for a few studies reporting a systematic review of literature reflecting on the characteristics of the technology, potential drivers in a business environment and technical challenges to deploy it. However, empirical evidence and research on developing new models and contemporary tools to assess several elements related to the technology, including and not limited to, performance, organisational readiness, risk assessment, operations strategy, integration with existing ERP systems and supply chain business models, will facilitate deeper understanding of the benefits offered by the technology that in-turn will help managers and relevant decision-makers to systematically assess the impact of BCT on their respective organisation and supply chain model. Furthermore, research into application of BCT within OSCM literature will require examining the relevance of existing theories and either developing new theories or extending existing theories that will facilitate better understanding of this contemporary phenomenon and its impact on supply chain relationships, operations strategy, workforce management, business partnerships, value creation, social legislations and business transparency.

For this special issue, we expect original research papers reporting empirical evidence, models and tools, and developing new theories contributing to the application of BCT in OSCM.

The main topics of interest include but are not limited to:

• Impact of BCT on supply chain relationships
• BCT and trust in OSCM
• Blockchain adoption and risk assessment
• Blockchain adoption and performance measurement
• Blockchain and supply chain sustainability
• Blockchain and social sustainability
• Blockchain and OSCM theories
• Blockchain and operations strategy
• Blockchain and supply chain intelligence
• Blockchain readiness models and empirical assessment
• Blockchain analytics for business operations
• Blockchain and data-driven decision making
• Smart contracts in OSCM – feasibility , use-cases and business performance
• Smart contract rules and governance
• Blockchain – managerial/business perspectives
• New business/supply chain models using BCT
• Blockchain – consumer perspectives
• Blockchain and sustainability development goals in OSCM

Instructions for Authors can be found at:

https://www.springer.com/journal/10479/submission-guidelines

Authors should submit a cover letter and a manuscript by September 31, 2020, via the Journal’s online submission site. Manuscripts submitted after the deadline may not be considered for the special issue and may be transferred, if accepted, to a regular issue.

Please see the Author instructions on the web site if you have not yet submitted a paper through Springer’s web-based system, Editorial Manager. When prompted, please select the special issue’s title, Blockchain in Operations and Supply Chain Management, to ensure that it will be reviewed for this special issue.

Papers will be subject to a strict review process under the supervision of the Guest Editors, and accepted papers will be published online individually, before print publication.

Important Dates

Guest Editors

Ali Emrouznejad (Managing Guest Editor), A.Emrouznejad@aston.ac.uk, 
Professor Business Analytics, Operations and Information Management Department, Aston Business School, Aston University

Soumyadeb Chowdhury, S.chowdhury5@aston.ac.uk, 
Lecturer Information and Communication Technology, Operations and Information Management Department, Aston Business School, Aston University

Prasanta Dey, deypk@aston.ac.uk, 
Professor in Operations and Information Management, Aston Business School, Aston University