کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6837706 618426 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Perceived derived attributes of online customer reviews
ترجمه فارسی عنوان
ویژگی های مشتق شده از بررسی مشتریان آنلاین درک شده است
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
The influence of online customer reviews (OCRs) on customers' purchase intention has recently gained considerable attention, in both academic and business communities. Technology allows customers to freely and easily post their comments and opinions online about any product or service; this type of customer review can have a significant effect on customers' purchase decisions. Previous studies, however, have mainly focused on the influence of the virtual attributes of OCRs such as volume and valence on consumers' intentions, while limited attention has been paid to understanding the effects of the derived attributes. This study, thus, aims to understand the impact of the perceived derived attributes of OCRs on customer trust and intention. This study develops a - Perceived Derived Attributes (PDA) - model, based on the inclusion of perceived control from the Theory of Planned Behaviour (TPB) with the Technology Acceptance Model (TAM), in order to investigate the effects of OCRs on customers' purchasing intention. A total of 489 responses to a survey were collected from users of amazon.com. The findings from this study suggest that customer trust in an e-vendor and their intention to shop online are significantly affected by perceived usefulness, perceived ease of use and perceived enjoyment of OCRs. Furthermore, the sense of control derived from OCRs significantly affects customer intention and significantly affects customer trust in e-vendors, particularly for customers who frequently check OCRs before making a purchase. Clearly, those attributes of OCRs are linked to the development of the shopping environment, which consequently can affect sales.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Human Behavior - Volume 56, March 2016, Pages 306-319
نویسندگان
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