What Makes Consumer Perception of Online Review Helpfulness: Synthesizing the Past to Guide Future Research

Abstract

A growing body of academic research has aimed to investigate the helpfulness of online customer reviews (OCRs) given their prevalence and the need to better understand their appraisal mechanisms. However, past studies have applied varied methods and reported conflicting findings. This study aims to improve the understanding of the contributors to OCR helpfulness by synthesizing past studies on the topic. Based on a systematic literature review, a summary of the precursors to OCR helpfulness is provided. We decipher both the consistent and conflicting results and discuss the possible explanations for these mixed findings. By summarizing past studies, the review also points out possible directions for future research.

Quantifying the effects of online review content structures on hotel review helpfulness

“…Positive and negative sentiments' role in shaping online review helpfulness is less straightforward. Indeed, previous studies have reached conflicting conclusions about this role (Fan, 2021; Lee et al , 2017; Salehan and Kim, 2016; Siering and Muntermann, 2013). For instance, Lee et al (2017) demonstrated that negative reviews are considered more helpful than positive reviews.…”

“…Star ratings' quadratic terms were included to account for the nonlinear relationship between rating and helpfulness (Mudambi and Schuff, 2010). Readability was calculated using the automated readability index (Smith and Senter, 1967), a method of determining written material's difficulty (Fan, 2021; Korfiatis et al , 2012). The operationalization of the variables used in this study is presented in Table 4.…”

“…Researchers studying online customer reviews tend to shift their focus from directly observed factors to textual content-derived properties, such as sentiment and emotion, and various types of linguistic features (Fan, 2021). For instance, past studies have shown that review content and reviewer characteristics affect the perceived helpfulness of online customer reviews (Fang et al , 2016; Liu and Park, 2015).…”

“…Earlier studies' inconclusive findings have emphasized a need to understand review content structures in more detail (Fan, 2021). For instance, a review may contain both sentences that express strong emotions and sentences that do not contain emotional words or phrases.…”

Tüketi̇ci̇ Mobi̇l Öz Yeterli̇li̇ği̇ni̇n Ve Çevri̇mi̇çi̇ Tüketi̇ci̇ Yorumlarinin Çevri̇mi̇çi̇ Satin Alma Ni̇yeti̇ İle İli̇şki̇si̇

“…Milyonlarca tüketici, satın alma kararları için diğer tüketiciler tarafından üretilen derecelendirme ve yorumları değerlendirmekte ve bunlara güvenmektedir (İktisadi İş birliği ve Gelişme Teşkilatı [OECD], 2019, s. 6). Çevrimiçi tüketici yorum ve incelemeleri; ticari olmayan nitelikleri, içeriklerinin zenginliği ve tüketicilerin karar alma süreçlerine olan etkisi nedeniyle önem kazanmıştır (Fan, 2021(Fan, , s. 2738. Senecal ve Nantel'in (2004, s. 167) ifade ettiği üzere, çevrimiçi değerlendirme kaynaklarının tüketicilerin seçimlerini etkileyebilecek ürünleri tavsiye ettiklerinde söz konusu ürünlerin iki kat oranında daha fazla tercih edildiği bilinmektedir.…”