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Stakeholder sentiment in service supply chains: big data meets agenda-setting theory
With growing reluctance to store and disseminate sensitive data throughout a supply chain network, there is a need to understand sentiment of big data and ways of control to achieve greater economic viability in the service-oriented supply chain which reflect a greater focus on knowledge sharing fro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864136/ http://dx.doi.org/10.1007/s11628-021-00437-w |
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author | Cao, Ray Qing Schniederjans, Dara G. Gu, Vicky Ching |
author_facet | Cao, Ray Qing Schniederjans, Dara G. Gu, Vicky Ching |
author_sort | Cao, Ray Qing |
collection | PubMed |
description | With growing reluctance to store and disseminate sensitive data throughout a supply chain network, there is a need to understand sentiment of big data and ways of control to achieve greater economic viability in the service-oriented supply chain which reflect a greater focus on knowledge sharing from traditional supply chains. Social network data were collected after referencing a focal corporate media (CM) document. This study provides causal inference by first conducting a CM document search and then a social network post web scrape of postings that reference the CM document while controlling for time and other demographic variables. This study finds salience of the big data topic positively impacts stakeholder sentiment but not when future applications are discussed. |
format | Online Article Text |
id | pubmed-7864136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-78641362021-02-09 Stakeholder sentiment in service supply chains: big data meets agenda-setting theory Cao, Ray Qing Schniederjans, Dara G. Gu, Vicky Ching Serv Bus Empirical Article With growing reluctance to store and disseminate sensitive data throughout a supply chain network, there is a need to understand sentiment of big data and ways of control to achieve greater economic viability in the service-oriented supply chain which reflect a greater focus on knowledge sharing from traditional supply chains. Social network data were collected after referencing a focal corporate media (CM) document. This study provides causal inference by first conducting a CM document search and then a social network post web scrape of postings that reference the CM document while controlling for time and other demographic variables. This study finds salience of the big data topic positively impacts stakeholder sentiment but not when future applications are discussed. Springer Berlin Heidelberg 2021-02-05 2021 /pmc/articles/PMC7864136/ http://dx.doi.org/10.1007/s11628-021-00437-w Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Empirical Article Cao, Ray Qing Schniederjans, Dara G. Gu, Vicky Ching Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title | Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title_full | Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title_fullStr | Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title_full_unstemmed | Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title_short | Stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
title_sort | stakeholder sentiment in service supply chains: big data meets agenda-setting theory |
topic | Empirical Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864136/ http://dx.doi.org/10.1007/s11628-021-00437-w |
work_keys_str_mv | AT caorayqing stakeholdersentimentinservicesupplychainsbigdatameetsagendasettingtheory AT schniederjansdarag stakeholdersentimentinservicesupplychainsbigdatameetsagendasettingtheory AT guvickyching stakeholdersentimentinservicesupplychainsbigdatameetsagendasettingtheory |