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Reassessing the scope of OR practice: The Influences of Problem Structuring Methods and the Analytics Movement

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Cited by:

  1. Ion Georgiou & Joaquim Heck, 2021. "The emergence of problem structuring methods, 1950s–1989: An atlas of the journal literature," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(6), pages 756-796, November.
  2. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
  3. LeBlanc, Larry J. & Grossman, Thomas A. & Bartolacci, Michael R., 2019. "Ensuring scalability and reusability of spreadsheet linear programming models," Omega, Elsevier, vol. 84(C), pages 55-69.
  4. Smith, Chris M. & Shaw, Duncan, 2019. "The characteristics of problem structuring methods: A literature review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 403-416.
  5. Richard Ormerod, 2017. "Writing practitioner case studies to help behavioural OR researchers ground their theories: application of the mangle perspective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 507-520, May.
  6. Paula Carroll, 2023. "Analytics Modules for Business Students," SN Operations Research Forum, Springer, vol. 4(2), pages 1-20, June.
  7. Frans Cruijssen & Ilja van Beest & Goos Kant, 2023. "A Human Behaviour Perspective on Horizontal Collaboration to Reduce the Climate Impact of Logistics," Sustainability, MDPI, vol. 15(23), pages 1-15, November.
  8. Sobrie, Léon & Verschelde, Marijn & Hennebel, Veerle & Roets, Bart, 2023. "Capturing complexity over space and time via deep learning: An application to real-time delay prediction in railways," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1201-1217.
  9. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
  10. Johnson, Michael P. & Midgley, Gerald & Chichirau, George, 2018. "Emerging trends and new frontiers in community operational research," European Journal of Operational Research, Elsevier, vol. 268(3), pages 1178-1191.
  11. Sobrie, Léon & Verschelde, Marijn & Roets, Bart, 2024. "Explainable real-time predictive analytics on employee workload in digital railway control rooms," European Journal of Operational Research, Elsevier, vol. 317(2), pages 437-448.
  12. Osman, Ibrahim H. & Anouze, Abdel Latef & Irani, Zahir & Lee, Habin & Medeni, Tunç D. & Weerakkody, Vishanth, 2019. "A cognitive analytics management framework for the transformation of electronic government services from users’ perspective to create sustainable shared values," European Journal of Operational Research, Elsevier, vol. 278(2), pages 514-532.
  13. Isabelle Piot-Lepetit & Joseph Nzongang, 2021. "Business analytics for managing performance of microfinance Institutions: A flexible management of the implementation process," Post-Print hal-03209188, HAL.
  14. Harper, Alison & Mustafee, Navonil & Yearworth, Mike, 2021. "Facets of trust in simulation studies," European Journal of Operational Research, Elsevier, vol. 289(1), pages 197-213.
  15. Isabelle Piot-Lepetit & Joseph Nzongang, 2021. "Business Analytics for Managing Performance of Microfinance Institutions: A Flexible Management of the Implementation Process," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
  16. Kshitij Sharma & Yogesh K. Dwivedi & Bhimaraya Metri, 2024. "Incorporating causality in energy consumption forecasting using deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 537-572, August.
  17. Luoma, Jukka, 2016. "Model-based organizational decision making: A behavioral lens," European Journal of Operational Research, Elsevier, vol. 249(3), pages 816-826.
  18. Ranjan Chaudhuri & Sheshadri Chatterjee & Demetris Vrontis & Alkis Thrassou, 2024. "Adoption of robust business analytics for product innovation and organizational performance: the mediating role of organizational data-driven culture," Annals of Operations Research, Springer, vol. 339(3), pages 1757-1791, August.
  19. Burger, Katharina & White, Leroy & Yearworth, Mike, 2019. "Developing a smart operational research with hybrid practice theories," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1137-1150.
  20. Hindle, Giles A. & Vidgen, Richard, 2018. "Developing a business analytics methodology: A case study in the foodbank sector," European Journal of Operational Research, Elsevier, vol. 268(3), pages 836-851.
  21. Konrad, Renata A. & Maass, Kayse Lee & Dimas, Geri L. & Trapp, Andrew C., 2023. "Perspectives on how to conduct responsible anti-human trafficking research in operations and analytics," European Journal of Operational Research, Elsevier, vol. 309(1), pages 319-329.
  22. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
  23. Durugbo, Christopher M., 2020. "Affordance-based problem structuring for workplace innovation," European Journal of Operational Research, Elsevier, vol. 284(2), pages 617-631.
  24. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
  25. Vidgen, Richard & Shaw, Sarah & Grant, David B., 2017. "Management challenges in creating value from business analytics," European Journal of Operational Research, Elsevier, vol. 261(2), pages 626-639.
  26. Tayo Fabusuyi & Michael P Johnson, 2022. "Enhancing the quality and social impacts of urban planning through community-engaged operations research," Environment and Planning B, , vol. 49(4), pages 1167-1183, May.
  27. Franco, L. Alberto & Greiffenhagen, Christian, 2018. "Making OR practice visible: Using ethnomethodology to analyse facilitated modelling workshops," European Journal of Operational Research, Elsevier, vol. 265(2), pages 673-684.
  28. Duan, Yanqing & Cao, Guangming & Edwards, John S., 2020. "Understanding the impact of business analytics on innovation," European Journal of Operational Research, Elsevier, vol. 281(3), pages 673-686.
  29. Alexandre de A. Gomes Júnior & Vanessa B. Schramm, 2022. "Problem Structuring Methods: A Review of Advances Over the Last Decade," Systemic Practice and Action Research, Springer, vol. 35(1), pages 55-88, February.
  30. Jung, Sang Hoon & Jeong, Yong Jin, 2020. "Twitter data analytical methodology development for prediction of start-up firms’ social media marketing level," Technology in Society, Elsevier, vol. 63(C).
  31. Timonina-Farkas, Anna & Katsifou, Argyro & Seifert, Ralf W., 2020. "Product assortment and space allocation strategies to attract loyal and non-loyal customers," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1058-1076.
  32. Shaw, Duncan & Smith, Chris M. & Scully, Judy, 2017. "Why did Brexit happen? Using causal mapping to analyse secondary, longitudinal data," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1019-1032.
  33. Kraus, Mathias & Feuerriegel, Stefan & Oztekin, Asil, 2020. "Deep learning in business analytics and operations research: Models, applications and managerial implications," European Journal of Operational Research, Elsevier, vol. 281(3), pages 628-641.
  34. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
  35. Nikolas Stege & Christoph Wegener & Tobias Basse & Frederik Kunze, 2021. "Mapping swap rate projections on bond yields considering cointegration: an example for the use of neural networks in stress testing exercises," Annals of Operations Research, Springer, vol. 297(1), pages 309-321, February.
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