Mining Product Reviews for Important Product Features of Refurbished iPhones

Problem: Remanufacturers want to increase consumer interest in refurbished products, which motivates the need to understand which product features are important to buyers of refurbished products such as mobile phones. Research Questions: This study addresses two questions. First, which product featu...

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Main Authors: Atefeh Anisi, Gül E. Okudan Kremer, Sigurdur Olafsson
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Information
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Online Access:https://www.mdpi.com/2078-2489/16/4/276
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author Atefeh Anisi
Gül E. Okudan Kremer
Sigurdur Olafsson
author_facet Atefeh Anisi
Gül E. Okudan Kremer
Sigurdur Olafsson
author_sort Atefeh Anisi
collection DOAJ
description Problem: Remanufacturers want to increase consumer interest in refurbished products, which motivates the need to understand which product features are important to buyers of refurbished products such as mobile phones. Research Questions: This study addresses two questions. First, which product features are most important for buyers of refurbished iPhones? Second, how do those preferences differ from the preferences of buyers of new iPhones? Methods: Online reviews of iPhones are obtained and converted into a document–term matrix. Using this text model, three subsets of features are identified using statistical analysis of frequency of mention: most frequent, average, and least frequent. A logistic regression (LR) model is then used to identify which features are most predictive of whether a review is for a new or refurbished phone. Results: Buyers of refurbished phones mention battery health, screen/display, shell condition, and brand significantly more often than other features. Directly contrasting reviews of refurbished versus new phones shows that shell condition, brand, speaker, and charger are found to be the most predictive product features indicated in reviews for refurbished phones. Of those, the shell condition is significantly more predictive than the others. Implications: The results identify product features that remanufacturers of iPhones can emphasize to increase customer demand.
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spelling doaj-art-e021e06a799d47b182922505aa83da492025-08-20T03:13:51ZengMDPI AGInformation2078-24892025-03-0116427610.3390/info16040276Mining Product Reviews for Important Product Features of Refurbished iPhonesAtefeh Anisi0Gül E. Okudan Kremer1Sigurdur Olafsson2Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA 50011, USACollege of Engineering, University of Dayton, Dayton, OH 45469, USADepartment of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA 50011, USAProblem: Remanufacturers want to increase consumer interest in refurbished products, which motivates the need to understand which product features are important to buyers of refurbished products such as mobile phones. Research Questions: This study addresses two questions. First, which product features are most important for buyers of refurbished iPhones? Second, how do those preferences differ from the preferences of buyers of new iPhones? Methods: Online reviews of iPhones are obtained and converted into a document–term matrix. Using this text model, three subsets of features are identified using statistical analysis of frequency of mention: most frequent, average, and least frequent. A logistic regression (LR) model is then used to identify which features are most predictive of whether a review is for a new or refurbished phone. Results: Buyers of refurbished phones mention battery health, screen/display, shell condition, and brand significantly more often than other features. Directly contrasting reviews of refurbished versus new phones shows that shell condition, brand, speaker, and charger are found to be the most predictive product features indicated in reviews for refurbished phones. Of those, the shell condition is significantly more predictive than the others. Implications: The results identify product features that remanufacturers of iPhones can emphasize to increase customer demand.https://www.mdpi.com/2078-2489/16/4/276refurbished mobile phonesfeature preferencesproduct reviewstext mining
spellingShingle Atefeh Anisi
Gül E. Okudan Kremer
Sigurdur Olafsson
Mining Product Reviews for Important Product Features of Refurbished iPhones
Information
refurbished mobile phones
feature preferences
product reviews
text mining
title Mining Product Reviews for Important Product Features of Refurbished iPhones
title_full Mining Product Reviews for Important Product Features of Refurbished iPhones
title_fullStr Mining Product Reviews for Important Product Features of Refurbished iPhones
title_full_unstemmed Mining Product Reviews for Important Product Features of Refurbished iPhones
title_short Mining Product Reviews for Important Product Features of Refurbished iPhones
title_sort mining product reviews for important product features of refurbished iphones
topic refurbished mobile phones
feature preferences
product reviews
text mining
url https://www.mdpi.com/2078-2489/16/4/276
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AT guleokudankremer miningproductreviewsforimportantproductfeaturesofrefurbishediphones
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