The chart shows the distribution of publications by all Research.com ranked scientists in the field of Business and Management in 2026. The highlighted bar marks where David L. Olson sits on this spectrum.
This scientist: 390 publications — 96th percentile
96% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 436 publications or more.
The chart shows the D-index (discipline H-index) distribution of Business and Management scientists ranked by Research.com in 2026. The highlighted bar marks where David L. Olson sits on this spectrum.
This scientist: 65 D-Index — 87th percentile
87% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 89 D-Index or more.
David L. Olson is affiliated with the University of Nebraska-Lincoln in the United States. Their research spans multiple areas within business, management, and computer science, focusing particularly on management information systems, artificial intelligence, and operations research.
Their recent scholarly contributions include papers such as Data Analytics for Operational Risk Management (2020) published in Decision Sciences, Role of Analytics for Operational Risk Management in the Era of Big Data (2020) also in Decision Sciences, Technologies and applications of Industry 4.0: insights from network analytics (2021) in the International Journal of Production Research, Financing with preferential credit to coordinate the capital-constraint supply chain (2021) in the International Journal of Production Research, and Who should finance the supply chain? Impact of accounts receivable mortgage on supply chain decision (2023) in the International Journal of Production Economics.
These works underline a consistent engagement with operational risk management, supply chain finance, Industry 4.0 technologies, and big data analytics.
Olson frequently collaborates with other researchers. Some of the most common coauthors include:
The scientist's publications appear primarily in these venues:
David L. Olson has contributed to the field through various book publications, primarily with Springer International Publishing. Notable titles include TOPSIS and its Extensions: A Distance-Based MCDM Approach (2022), Enterprise Risk Management Models (2020 and 2023 editions). They have also published with Springer Nature, authoring Pandemic Risk Management in Operations and Finance (2020), and with Springer Science+Business Media, producing Data Mining and Analytics in Healthcare Management (2023).
Their research covers major topics such as:
This diverse portfolio demonstrates a focus on both theoretical and applied aspects of risk, supply chains, artificial intelligence, and data analytics within business and management contexts. Their work integrates methodologies from artificial intelligence and information systems to address complex challenges in operational and financial management.
David L. Olson;Dursun Delen
Sang M. Lee;David L. Olson;Silvana Trimi
D. L. Olson
James R. Evans;David Louis Olson
David L. Olson
David L. Olson
Desheng Wu;David L. Olson
David L. Olson;Dursun Delen;Yanyan Meng
Jijun Zhang;Desheng Wu;D. L. Olson
Yanhong Li;David L. Olson;Zheng Qin
Desheng Dash Wu;Desheng Dash Wu;Yidong Zhang;Dexiang Wu;David L. Olson
Benito E. Flores;David L. Olson;V. K. Dorai
David L. Olson;Desheng Dash Wu
Bongsug K. Chae;David Olson;Chwen Sheu
Bongsug (Kevin) Chae;Chenlung Yang;David Olson;Chwen Sheu
Desheng Dash Wu;Shu-Heng Chen;David L. Olson
DonHee Lee;Sang M. Lee;David L. Olson;Soong Hwan Chung
Desheng Dash Wu;David Olson
John Mote;Ishwar Murthy;David L. Olson
Ozgur Merih Araz;Tsan Ming Choi;David L. Olson;F. Sibel Salman
David L. Olson
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