Brand Reputation and Trust: The Impact on Customer Satisfaction and Loyalty for the Hewlett-Packard Brand

Fatma Yiğit Açikgöz, Mehmet Kayakuş (), Bianca-Ștefania Zăbavă () and Onder Kabas
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Fatma Yiğit Açikgöz: Department of Marketing and Advertising, Social Sciences Vocational School, Akdeniz University, Antalya 07058, Türkiye
Mehmet Kayakuş: Department of Management Information Systems, Faculty of Social and Human Sciences, Akdeniz Unversity, Antalya 07800, Türkiye
Bianca-Ștefania Zăbavă: Department of Biotechnical Systems, Faculty of Biotechnical Systems Engineering, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Onder Kabas: Department of Machine, Technical Science Vocational School, Akdeniz University, Antalya 07070, Türkiye

Sustainability, 2024, vol. 16, issue 22, 1-17

Abstract: Reputation is shaped depending on factors such as the quality of products and services offered by a brand to its stakeholders, its reliability, and its innovative aspect in the eyes of stakeholders. The sustainability of a brand reputation depends on the brand creating a positive perception by fulfilling its social responsibilities and maintaining this perception in the long term. In this study, the brand reputation of Hewlett-Packard (HP) computers is evaluated through customer reviews. The data set in the study consists of 2012 customer reviews obtained from Hepsiburada, one of the most widely used e-commerce platforms in Turkey. Sentiment analysis and text mining artificial intelligence methods were used in the study. For sentiment analysis, the Naive Bayes method, which is one of the machine learning methods, was used, and the comments were divided into three groups as positive, negative, and neutral. In the study, 82% of the customer comments were positive, 11% were negative, and 7% were neutral. The fact that most of the comments consist of positive sentiments shows that HP Computer has a positive reputation in the eyes of stakeholders consisting of customers. Comments consisting of negative and neutral emotions show the aspects that the brand needs to improve. In the study, the text mining method emphasises the prominent features of the brand in the comments. This study makes an important contribution to the reputation assessment of brands and to ensuring sustainable brand reputation.

Keywords: sustainable reputation; e-commerce; public relations; sentiment analysis machine learning; text mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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