Uncertainty Modelling in Information Management and Decision Making.
(eBook)

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Published
: Emerald Publishing Limited, 2013.
Format
eBook
ISBN
9781783506491
Physical Desc
1 online resource (89 pages)
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Language
English

Notes

Description
This ebook incorporates excellent 'quality' submissions that focus on providing a mixture of theoretical and practical contributions. The research work presented in these papers highlights that social media are playing a rapidly expanding role in both companies and in teaching and learning. The aim of this ebook is to provide a broad understanding of the significance that uncertainty modelling, in the context of managing information resources and decision-making process, plays. The techniques for uncertainty modelling and analysis in engineering presents appropriate analytical and useful tools for current and future analysts and practitioners to understand the fundamentals of knowledge, how to model and analyse uncertainty, and how to select these tools for particular problems.
Local note
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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Citations

APA Citation, 7th Edition (style guide)

Kahraman, C., Öztaysi, B., & Kabak, O. (2013). Uncertainty Modelling in Information Management and Decision Making . Emerald Publishing Limited.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Kahraman, Cengiz, Basar. Öztaysi and Özgür. Kabak. 2013. Uncertainty Modelling in Information Management and Decision Making. Emerald Publishing Limited.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Kahraman, Cengiz, Basar. Öztaysi and Özgür. Kabak. Uncertainty Modelling in Information Management and Decision Making Emerald Publishing Limited, 2013.

MLA Citation, 9th Edition (style guide)

Kahraman, Cengiz., Basar Öztaysi, and Özgür Kabak. Uncertainty Modelling in Information Management and Decision Making Emerald Publishing Limited, 2013.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID
a3b63eac-f426-b91f-99cb-4aac1a995154-eng
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Grouping Information

Grouped Work IDa3b63eac-f426-b91f-99cb-4aac1a995154-eng
Full titleuncertainty modelling in information management and decision making
Authorkahraman cengiz
Grouping Categorybook
Last Update2023-03-28 17:59:37PM
Last Indexed2024-05-21 02:03:07AM

Book Cover Information

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First LoadedAug 23, 2023
Last UsedMar 26, 2024

Marc Record

First DetectedMar 28, 2023 06:04:26 PM
Last File Modification TimeMar 28, 2023 06:04:26 PM

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4901 |a Journal of Enterprise Information Management: Volume 27, Issue 3
5050 |a Cover -- Editorial review board -- Editorial -- A fuzzy integrated approach for project selection -- Analyzing relationship between ERP utilization and lean manufacturing maturity of Turkish SMEs -- An intelligent group decision-support system and its application for project performance evaluation -- A fuzzy analytic hierarchy process methodology for the supplier selection problem -- Providing an effective group-buying aggregation service:a data-driven approach -- A fuzzy expert system design for forecasting return quantity inreverse logistics network.
520 |a This ebook incorporates excellent 'quality' submissions that focus on providing a mixture of theoretical and practical contributions. The research work presented in these papers highlights that social media are playing a rapidly expanding role in both companies and in teaching and learning. The aim of this ebook is to provide a broad understanding of the significance that uncertainty modelling, in the context of managing information resources and decision-making process, plays. The techniques for uncertainty modelling and analysis in engineering presents appropriate analytical and useful tools for current and future analysts and practitioners to understand the fundamentals of knowledge, how to model and analyse uncertainty, and how to select these tools for particular problems.
588 |a Description based on publisher supplied metadata and other sources.
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7001 |a Öztaysi, Basar.
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