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  4. Social media analytics in operations and supply chain management: Opportunities, challenges and paradoxes
 
Zitierlink DOI
10.26092/elib/1621

Social media analytics in operations and supply chain management: Opportunities, challenges and paradoxes

Veröffentlichungsdatum
2022-06-20
Autoren
Kinra, Aseem  
Siekmann, Fabian  
Kotzab, Herbert  
Zusammenfassung
Industrial and academic communities in the field of operations and supply chain management (OSCM) have been paying increasing attention to social media analytics (SMA). However, the disparity of social media has inspired new ways of thinking about how data are produced, organized and analyzed. This chapter addresses how OSCM is affected by this disparity and provides an overview of SMA use, applications and challenges in the domain. A directed content analysis of current, application-oriented research is carried out to review SMA in OSCM from a signaling theory perspective. In particular, we shed light on data sources, opportunities, challenges, paradoxes and current managerial issues and seek to inform research practices and policy in order to advance operations and supply chain management research. The chapter contributes to the understanding of SMA in OSCM by identifying a set of paradoxes and challenges that have not previously been identified in OSCM research. By relating SMA to social media data sources and OSCM activities, it shed light on preferred sources and application scenarios and discusses the imponderables of social media signal processing in OSCM.
Schlagwörter
social media

; 

Supply Chain Management
Institution
Universität Bremen  
Fachbereich
Fachbereich 07: Wirtschaftswissenschaft (FB 07)  
Institute
Diginomics Research Group  
Dokumenttyp
Bericht, Report
Serie(s)
Diginomics Working Paper  
Band
0018
Zweitveröffentlichung
Nein
Lizenz
https://creativecommons.org/licenses/by/4.0/
Sprache
Englisch
Dateien
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Vorschaubild
Name

Diginomics Working Paper - June 2022, No0018.pdf

Size

3.24 MB

Format

Adobe PDF

Checksum

(MD5):93b3a07c938cbca757c256d0cdcd3b3b

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