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Operational research from Taylorism to Terabytes: A research agenda for the analytics age
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- Wagner, Julia & Kontny, Henning, 2017. "Use case of self-organizing adaptive supply chain," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Digitalization in Supply Chain Management and Logistics: Smart and Digital Solutions for an Industry 4.0 Environment. Proceedings of the Hamburg Inter, volume 23, pages 255-273, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
- 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.
- Kummitha, Rama Krishna Reddy, 2019. "Smart cities and entrepreneurship: An agenda for future research," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
- Nagesh Shukla & Senevi Kiridena, 2016. "A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6984-6996, December.
- Tom Pape, 2020. "Prioritising data items for business analytics: Framework and application to human resources," Papers 2012.13813, arXiv.org.
- Taylor, Simon J.E., 2019. "Distributed simulation: state-of-the-art and potential for operational research," European Journal of Operational Research, Elsevier, vol. 273(1), pages 1-19.
- Pavla Vrabcová & Hana Urbancová, 2021. "Use of human resources information system in agricultural companies in the Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(5), pages 173-180.
- Tobias Bender, 2024. "Towards a process selection method for embedded analytics," Information Systems and e-Business Management, Springer, vol. 22(3), pages 501-525, September.
- Hahsler, Michael, 2017. "An experimental comparison of seriation methods for one-mode two-way data," European Journal of Operational Research, Elsevier, vol. 257(1), pages 133-143.
- Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
- Paula Carroll, 2023. "Analytics Modules for Business Students," SN Operations Research Forum, Springer, vol. 4(2), pages 1-20, June.
- Shiyu Liu & Ou Liu & Junyang Chen, 2023. "A Review on Business Analytics: Definitions, Techniques, Applications and Challenges," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
- Constantin Zopounidis & Michalis Doumpos & Dimitrios Niklis, 2018. "Financial decision support: an overview of developments and recent trends," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 63-76, June.
- 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.
- Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
- Crevecoeur, Jonas & Antonio, Katrien & Verbelen, Roel, 2019.
"Modeling the number of hidden events subject to observation delay,"
European Journal of Operational Research, Elsevier, vol. 277(3), pages 930-944.
- Jonas Crevecoeur & Katrien Antonio & Roel Verbelen, 2018. "Modeling the number of hidden events subject to observation delay," Papers 1801.02935, arXiv.org, revised Mar 2019.
- Ni, Ji & Chen, Bowei & Allinson, Nigel M. & Ye, Xujiong, 2020. "A hybrid model for predicting human physical activity status from lifelogging data," European Journal of Operational Research, Elsevier, vol. 281(3), pages 532-542.
- Ahi, Alan A. & Sinkovics, Noemi & Shildibekov, Yelnur & Sinkovics, Rudolf R. & Mehandjiev, Nikolay, 2022. "Advanced technologies and international business: A multidisciplinary analysis of the literature," International Business Review, Elsevier, vol. 31(4).
- 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.
- Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "Towards a business analytics capability for the circular economy," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
- Leopold-Wildburger, Ulrike & Strohhecker, Jürgen, 2017. "Strategy map concepts in a balanced scorecard cockpit improve performanceAuthor-Name: Hu, Bo," European Journal of Operational Research, Elsevier, vol. 258(2), pages 664-676.
- Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
- 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.
- 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.
- Hauser, Matthias & Flath, Christoph M. & Thiesse, Frédéric, 2021. "Catch me if you scan: Data-driven prescriptive modeling for smart store environments," European Journal of Operational Research, Elsevier, vol. 294(3), pages 860-873.
- 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.
- Mantin, Benny & Rubin, Eran, 2018. "Price volatility and market performance measures: The case of revenue managed goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 120(C), pages 35-50.
- Sanjay Kumar Tyagi & Sujeet Kumar Sharma & R. Krishankumar & K. S. Ravichandran, 2022. "An extension of interpretive structural modeling using linguistic term sets for business decision-making," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1158-1177, September.
- Ahn, Heinz & Vazquez Novoa, Nadia, 2016. "The decoy effect in relative performance evaluation and the debiasing role of DEA," European Journal of Operational Research, Elsevier, vol. 249(3), pages 959-967.
- 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.
- Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
- Bechler, Georg & Steinhardt, Claudius & Mackert, Jochen & Klein, Robert, 2021. "Product line optimization in the presence of preferences for compromise alternatives," European Journal of Operational Research, Elsevier, vol. 288(3), pages 902-917.
- Heilig, Leonard & Lalla-Ruiz, Eduardo & Voß, Stefan, 2017. "Multi-objective inter-terminal truck routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 178-202.
- Symitsi, Efthymia & Stamolampros, Panagiotis & Daskalakis, George & Korfiatis, Nikolaos, 2021. "The informational value of employee online reviews," European Journal of Operational Research, Elsevier, vol. 288(2), pages 605-619.
- 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.
- 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.
- Benjamin T. Hazen & Joseph B. Skipper & Christopher A. Boone & Raymond R. Hill, 2018. "Back in business: operations research in support of big data analytics for operations and supply chain management," Annals of Operations Research, Springer, vol. 270(1), pages 201-211, November.
- H. Kava & K. Spanaki & T. Papadopoulos & S. Despoudi & O. Rodriguez Espindola & M. Fakhimi, 2024. "Data analytics diffusion in the UK renewable energy sector: an innovation perspective," Post-Print hal-04478933, HAL.
- Li, Han & Gupta, Ashish & Zhang, Jie & Flor, Nick, 2020. "Who will use augmented reality? An integrated approach based on text analytics and field survey," European Journal of Operational Research, Elsevier, vol. 281(3), pages 502-516.
- Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
- Feuerriegel, Stefan & Gordon, Julius, 2019. "News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions," European Journal of Operational Research, Elsevier, vol. 272(1), pages 162-175.
- Erkip, Nesim Kohen, 2023. "Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems," European Journal of Operational Research, Elsevier, vol. 308(3), pages 949-959.
- 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.
- 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.
- Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
- Galetsi, P. & Katsaliaki, K. & Kumar, S., 2019. "Values, challenges and future directions of big data analytics in healthcare: A systematic review," Social Science & Medicine, Elsevier, vol. 241(C).
- Esposito Amideo, A. & Scaparra, M.P. & Kotiadis, K., 2019. "Optimising shelter location and evacuation routing operations: The critical issues," European Journal of Operational Research, Elsevier, vol. 279(2), pages 279-295.
- Hing Kai Chan & Ewelina Lacka & Rachel W.Y. Yee & Ming K. Lim, 2017. "The role of social media data in operations and production management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5027-5036, September.
- Käki, Anssi & Kemppainen, Katariina & Liesiö, Juuso, 2019. "What to do when decision-makers deviate from model recommendations? Empirical evidence from hydropower industry," European Journal of Operational Research, Elsevier, vol. 278(3), pages 869-882.
- Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2018. "On Mathematical Optimization for the visualization of frequencies and adjacencies as rectangular maps," European Journal of Operational Research, Elsevier, vol. 265(1), pages 290-302.
- Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
- 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.
- Zelenyuk, Valentin, 2020. "Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data," European Journal of Operational Research, Elsevier, vol. 282(1), pages 172-187.
- 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).
- 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.
- 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.
- Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.
- Delen, Dursun & Zolbanin, Hamed M., 2018. "The analytics paradigm in business research," Journal of Business Research, Elsevier, vol. 90(C), pages 186-195.
- Ranyard, J.C. & Fildes, R. & Hu, Tun-I, 2015. "Reassessing the scope of OR practice: The Influences of Problem Structuring Methods and the Analytics Movement," European Journal of Operational Research, Elsevier, vol. 245(1), pages 1-13.
- Chen, Yi-Ting & Sun, Edward W. & Lin, Yi-Bing, 2020. "Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability," European Journal of Operational Research, Elsevier, vol. 281(3), pages 687-705.
- Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.
- Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.