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Insights on next-generation manufacturing of smart devices using text analytics

With the mass expansion in technological user-friendly products, there is an increasing demand for smart devices, resulting in a highly competitive novel market. To ensure sustainable success, these products must remain robust and be perceived positively by customers. With the development of Web 2.0...

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Detalles Bibliográficos
Autores principales: Rajendran, Suchithra, Pagel, Emily
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385452/
https://www.ncbi.nlm.nih.gov/pubmed/32743099
http://dx.doi.org/10.1016/j.heliyon.2020.e04491
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author Rajendran, Suchithra
Pagel, Emily
author_facet Rajendran, Suchithra
Pagel, Emily
author_sort Rajendran, Suchithra
collection PubMed
description With the mass expansion in technological user-friendly products, there is an increasing demand for smart devices, resulting in a highly competitive novel market. To ensure sustainable success, these products must remain robust and be perceived positively by customers. With the development of Web 2.0, individuals are able to make knowledgeable purchasing decisions, specifically with the availability of millions of online customer reviews. Companies manufacturing smart devices can utilize this unstructured data to analyze the customers' perceptions of their products and identify potential improvements. To the best of our knowledge, this paper is the first to propose next-generation manufacturing insights for companies producing smart devices by determining the current strengths, weaknesses, opportunities, and threats (SWOT) of these gadgets using text analytics. A three-stage methodology is utilized, consisting of bigram and trigram examination, topic identification, and SWOT analysis. After online review extraction, comments for each smart device are separated into positive, neutral, and negative categories, based on the customer ratings. Text analytic tools are then used to determine the most frequently occurring bigrams and trigrams to provide topics for conducting the SWOT analysis. Using the SWOT technique results, numerous next-generation smart device manufacturing recommendations are presented.
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spelling pubmed-73854522020-07-30 Insights on next-generation manufacturing of smart devices using text analytics Rajendran, Suchithra Pagel, Emily Heliyon Article With the mass expansion in technological user-friendly products, there is an increasing demand for smart devices, resulting in a highly competitive novel market. To ensure sustainable success, these products must remain robust and be perceived positively by customers. With the development of Web 2.0, individuals are able to make knowledgeable purchasing decisions, specifically with the availability of millions of online customer reviews. Companies manufacturing smart devices can utilize this unstructured data to analyze the customers' perceptions of their products and identify potential improvements. To the best of our knowledge, this paper is the first to propose next-generation manufacturing insights for companies producing smart devices by determining the current strengths, weaknesses, opportunities, and threats (SWOT) of these gadgets using text analytics. A three-stage methodology is utilized, consisting of bigram and trigram examination, topic identification, and SWOT analysis. After online review extraction, comments for each smart device are separated into positive, neutral, and negative categories, based on the customer ratings. Text analytic tools are then used to determine the most frequently occurring bigrams and trigrams to provide topics for conducting the SWOT analysis. Using the SWOT technique results, numerous next-generation smart device manufacturing recommendations are presented. Elsevier 2020-07-23 /pmc/articles/PMC7385452/ /pubmed/32743099 http://dx.doi.org/10.1016/j.heliyon.2020.e04491 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Rajendran, Suchithra
Pagel, Emily
Insights on next-generation manufacturing of smart devices using text analytics
title Insights on next-generation manufacturing of smart devices using text analytics
title_full Insights on next-generation manufacturing of smart devices using text analytics
title_fullStr Insights on next-generation manufacturing of smart devices using text analytics
title_full_unstemmed Insights on next-generation manufacturing of smart devices using text analytics
title_short Insights on next-generation manufacturing of smart devices using text analytics
title_sort insights on next-generation manufacturing of smart devices using text analytics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385452/
https://www.ncbi.nlm.nih.gov/pubmed/32743099
http://dx.doi.org/10.1016/j.heliyon.2020.e04491
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