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Erschienen in: Social Network Analysis and Mining 1/2022

01.12.2022 | Original Article

A framework to improve smartphone supply chain defects: social media analytics approach

verfasst von: Masoud Ramezaninia, Sajjad Shokouhyar, Seyed Hamed GhanadPour, Sayyed Mohammad Mutallebi, Sina Shokoohyar

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2022

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Abstract

Smartphones are one of the most widely used electronic devices. Their supply chain can play an essential role in enhancing their quality and associated services. Numerous studies have been conducted in recent years on supply chain waste and how to manage it to improve product quality. Discussing this issue can help solve supply chain deficiencies and improve its performance, increasing production efficiency and customer satisfaction. This study examines the issue using two valid methods. Initially, text mining on Twitter was used to extract hashtags for Apple smartphones. Then, sentiment analysis was used to distinguish between complaints and negative tweets about services or device performance. Afterward, the most frequently occurring deficiencies (23 deficiencies) that resulted in dissatisfaction were identified. Eventually, 14 deficiencies were selected after consulting with experts. These cases were attributed to various supply chain steps using the Delphi method and Apple's reports. Finally, the highest degree of agreement between the cases and supply chain steps was determined through the Delphi process, consultation with experts, and statistical methods.

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Metadaten
Titel
A framework to improve smartphone supply chain defects: social media analytics approach
verfasst von
Masoud Ramezaninia
Sajjad Shokouhyar
Seyed Hamed GhanadPour
Sayyed Mohammad Mutallebi
Sina Shokoohyar
Publikationsdatum
01.12.2022
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2022
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-022-00982-w

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