Gottschlich, Jörg (2016)
Decision Support in Social Media and Cloud Computing.
Technische Universität Darmstadt
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
This cumulative dissertation examines applications of decision support in the field of social media and cloud computing. By the advent of Social Media, Big Data Analytics and Cloud Computing, new opportunities opening up in the field of decision support due to availability and ability to process new types of data sets. In this context, this dissertation introduces systems for the use of social media data for decisions and an approach for decision support in choosing a cloud computing provider. In this dissertation, the benefits of different Facebook profile data for use in product recommender systems will be analyzed. Two experiments are carried out, in which the recommendation quality is determined by user survey. In another part of this dissertation, structured stock recommendations of an online community are used to automatically derive and update a stock portfolio. So investment decisions in the stock market are supported by a regular recalculation of the community rating for individual stocks. An succeeding article on this topic develops a formalized model for the description of investment strategies to enable a portfolio management system that automatically follows a strategy parameterized by an investor. Finally, a cloud broker model is presented which offers price / performance-based decision support in identifying an appropriate IaaS provider on the market for public cloud services. In a fundamental part of the thesis an IT architecture design is proposed which allows the parallel use and evaluation of different solution approaches in an operative IT system. Statistical tests are used to identify the best performing approach(es) and prefer them quickly while in operation. Overall, this cumulative dissertation consists of an introduction and five published articles.
Typ des Eintrags: | Dissertation | ||||
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Erschienen: | 2016 | ||||
Autor(en): | Gottschlich, Jörg | ||||
Art des Eintrags: | Erstveröffentlichung | ||||
Titel: | Decision Support in Social Media and Cloud Computing | ||||
Sprache: | Englisch | ||||
Referenten: | Hinz, Prof. Dr. Oliver ; Buxmann, Prof. Dr. Peter | ||||
Publikationsjahr: | 1 März 2016 | ||||
Ort: | Darmstadt | ||||
Datum der mündlichen Prüfung: | 9 Juni 2016 | ||||
URL / URN: | http://tuprints.ulb.tu-darmstadt.de/5509 | ||||
Kurzbeschreibung (Abstract): | This cumulative dissertation examines applications of decision support in the field of social media and cloud computing. By the advent of Social Media, Big Data Analytics and Cloud Computing, new opportunities opening up in the field of decision support due to availability and ability to process new types of data sets. In this context, this dissertation introduces systems for the use of social media data for decisions and an approach for decision support in choosing a cloud computing provider. In this dissertation, the benefits of different Facebook profile data for use in product recommender systems will be analyzed. Two experiments are carried out, in which the recommendation quality is determined by user survey. In another part of this dissertation, structured stock recommendations of an online community are used to automatically derive and update a stock portfolio. So investment decisions in the stock market are supported by a regular recalculation of the community rating for individual stocks. An succeeding article on this topic develops a formalized model for the description of investment strategies to enable a portfolio management system that automatically follows a strategy parameterized by an investor. Finally, a cloud broker model is presented which offers price / performance-based decision support in identifying an appropriate IaaS provider on the market for public cloud services. In a fundamental part of the thesis an IT architecture design is proposed which allows the parallel use and evaluation of different solution approaches in an operative IT system. Statistical tests are used to identify the best performing approach(es) and prefer them quickly while in operation. Overall, this cumulative dissertation consists of an introduction and five published articles. |
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Alternatives oder übersetztes Abstract: |
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Freie Schlagworte: | Entscheidungsunterstützung, Social Media, Cloud Computing, Empfehlungssysteme | ||||
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URN: | urn:nbn:de:tuda-tuprints-55091 | ||||
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 300 Sozialwissenschaften > 330 Wirtschaft 300 Sozialwissenschaften > 380 Handel, Kommunikation, Verkehr 600 Technik, Medizin, angewandte Wissenschaften > 650 Management |
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Fachbereich(e)/-gebiet(e): | 01 Fachbereich Rechts- und Wirtschaftswissenschaften 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete > Fachgebiet Electronic Markets |
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Hinterlegungsdatum: | 03 Jul 2016 19:55 | ||||
Letzte Änderung: | 03 Jun 2018 21:27 | ||||
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Referenten: | Hinz, Prof. Dr. Oliver ; Buxmann, Prof. Dr. Peter | ||||
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 9 Juni 2016 | ||||
Schlagworte: |
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