Call for Papers: AI for Sustainable Performance Analytics, November 23-26, 2024, Doha, Qatar

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Dear Colleagues,
We cordially invite you to participate in the special track on ” AI for Sustainable Performance Analytics” as part of the 7th International Conference of Entrepreneurship for Sustainability & Impact (ESI). This conference will be held in Doha, Qatar, from November 23rd to 26th 2024. We welcome contributions from both academic and non-academic communities.

The “AI for Sustainable Performance Analytics” track encourages collaboration among researchers, practitioners, and policymakers to explore innovative approaches at the intersection of AI and sustainability analytics, emphasizing Performance Analytics. We invite contributions across theoretical frameworks, methodological advancements, case studies, and practical applications in areas like energy management, supply chain optimization, and environmental monitoring. Join us in shaping the conversation on leveraging AI for sustainable performance analytics, driving positive change towards a more resilient and environmentally conscious future.

We are especially interested in contributions that explore the integration of AI with mathematical modelling, including Data Envelopment Analysis (DEA), Best Worth Model (BWM), Analytic Hierarchy Process (AHP), machine learning algorithms, sustainability principles, decision-making unit performance, big data analytics, comprehensive sustainability assessments, synergy, practical case studies, and achieving sustainable outcomes.

Please ensure that your submissions adhere to the conference guidelines and formatting instructions provided on the conference website.

The conference will be recognizing outstanding contributions with the following awards:
Best Paper Awards: the winner will be awarded the sum of $1,500 and the runner-up will be awarded $1,000.
Best Case Study Awards: the winner will be awarded the sum of $1,500 and the runner-up will be awarded $1,000.
Outstanding PhD Dissertation-Based Paper Award: the winner will be awarded the sum of $1,000.
Best Master/MBA-Dissertation Based Paper Awards: the winner will be awarded the sum of $1,000.
Abstract submission deadline: July 15, 2024

Registration and Fees:
All paper presentations will take place in person and on-site. At least one author must register and attend the conference in person to present. Qatar University supports the ESI 2024 conference by covering the registration fees for accepted papers.
For more information and paper submission, please visit https://www.qu.edu.qa/conference/ESI2024.
We look forward to your valuable contributions and active participation in the special track on ” AI for Sustainable Performance Analytics” at ESI 2024.
Kind regards,

Ali Emrouznejad, Professor and Director of Centre for Business Analytics in Practice, Surrey Business School, University of Surrey, UK, http://emrouznejad.com/.
Ruba Al-jarallah, Professor at Arab Planning Institute, Kuwait

The following papers might be of your interest:

  • Emrouznejad, A., M. Marra, G. L. Yang, M. Michali (2023) Eco-efficiency considering NetZero and Data Envelopment Analysis: A critical literature review, IMA Journal of Management Mathematics (doi).
  • Azadi, M., R, Kazemi Matin, A. Emrouznejad, and W. Ho(2023) Evaluating Sustainably Resilient Supply Chains: A Stochastic Double Frontier Analytic Model Considering NetZero. Annals of Operations Research (doi).
  • Taleb, M., , R. Khalid, A. Emrouznejad, R. Ramli (2023). Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero. Environment, Development and Sustainability (doi).
  • Emrouznejad A., G. L. Yang and G. R. Amin (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. (doi). Production, 223 (20): 641-650. (doi).
  • Emrouznejad, A., G. L. Yang (2016) CO2 emissions reduction of Chinese light manufacturing industries: A novel RAM-based global Malmquist–Luenberger productivity index, Energy Policy 96: 397–410. (doi).
  • Emrouznejad, A., ­G. L. Yang (2016) A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries, Energy 115 (1): 840-856. (doi)