{"id":81,"date":"2026-01-02T09:12:22","date_gmt":"2026-01-02T09:12:22","guid":{"rendered":"https:\/\/dataenvelopment.com\/workshop\/?page_id=81"},"modified":"2026-04-13T09:08:57","modified_gmt":"2026-04-13T09:08:57","slug":"deaw2026","status":"publish","type":"page","link":"https:\/\/dataenvelopment.com\/workshop\/","title":{"rendered":"DEA Workshop: Efficiency and Productivity Assessment in Higher Education and Public Services: DEA, Machine Learning, and AI, April 16-17, 2026, Aston University, UK"},"content":{"rendered":"\n

Program<\/strong>:<\/p>\n\n\n\n

<\/object>DEA-Workshop-2026<\/a>Download<\/a><\/div>\n\n\n\n

Submit an abstract<\/strong>: CLICK HERE<\/a> <\/s>
Register<\/strong>: CLICK HERE<\/a> [Registration will close once we reach 25 participants<\/mark>.<\/strong>]
Full details:<\/strong> Efficiency and Productivity Assessment | Aston University<\/a><\/p>\n\n\n\n

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CLICK HERE to download the program (Will be available on April 1, 2026!)<\/p>\n\n\n\n

Call for Papers\/Presentations<\/strong><\/p>\n\n\n\n

The need to improve efficiency in higher education and public services has become particularly important in the UK context, where institutions face sustained financial constraints, growing regulatory and accountability requirements, and increasing expectations to demonstrate value for money alongside educational quality. Although efficiency and productivity analysis has attracted the attention of academics and policymakers, translating analytical results into actionable insights remains challenging. These challenges stem from the complexity of modelling public service production processes, data limitations, non-market outputs, and the reliance on composite indicators and performance metrics.<\/p>\n\n\n\n

Recent advances in machine learning combined with performance analytics techniques such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) offer new opportunities to address these issues by improving model flexibility, pattern discovery, and decision support, while also raising important questions around interpretability, robustness, and policy relevance. Improving the use of public resources is not only essential for financial sustainability but also for safeguarding quality, equity, and long-term performance in higher education and other public services.<\/p>\n\n\n\n

The Workshop provides an ideal platform for presenting new methods, applications of existing techniques and advances in theoretical and empirical research from different multidisciplinary perspectives.<\/p>\n\n\n\n

This workshop is organised by the Aston Business School <\/a>and the Centre for Business Analytics in Practice<\/a> of the University of Surrey. It aims to provide a dedicated platform for researchers, practitioners, and early-career scholars to exchange ideas, share insights, and discuss recent methodological and applied advances in DEA, machine learning and AI, as well as complementary parametric approaches such as SFA, with a particular focus on applications in higher education and public services.<\/p>\n\n\n\n

Themes:<\/strong> DEA, Machine Learning and Artificial intellignece for Assessment of higher education and public services<\/p>\n\n\n\n

Submission Guidelines:<\/strong> Authors are invited to submit original research papers or presentations related to the workshop themes. Submissions should adhere to the following guidelines: <\/p>\n\n\n\n