Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.     

Development of a scale to measure skepticism toward electronic word-of-mouth

In recent years, electronic word-of-mouth (eWOM) has become an influential factor affecting Internet users' perceptions and behaviors (Chatterjee 2001; Lee et al. 2009). However, as more evidence demonstrating the utilization of fake eWOM has been discovered (Forrest and Cao 2010; Malbon 2013), Internet users' trust of eWOM may have been severely undermined, and they may have developed skepticism about this kind of communication in general. Current measurement scales for evaluating Internet users' suspicions/distrust toward eWOM messages are adopted from the marketing discipline and developed for advertising skepticism, which is contextually different from skepticism toward eWOM. The purpose of this study is to create a new measurement scales for eWOM skepticism. Using data from a preliminary survey, new measurement items for eWOM skepticism were established. Then, the new items were validated using a second survey dataset. The reliability and validity of the new scales suggested that the new instrument is suitable for measuring eWOM skepticism. This study contributes to the eWOM literature by highlighting the importance of investigating eWOM situations from the perspective of suspicion and distrust.     

Perceived derived attributes of online customer reviews

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.     

The power of eWOM: A re-examination of online student evaluations of their professors

Over the past few years, a number of studies have examined the impact of the Rate My Professors (RMP) website (RateMyProfessors.com) on higher education. The focal area of examination is whether students’ evaluations of their professors on RMP are valid. The current study attempts to push the RMP discussions to a deeper level through two studies. Study 1 illustrates that students rely on the valence of review information on RMP to make their course selection decisions without considering its validity. Study 2 shows that students’ decision-making process tends to be biased as a result of review information available. The results of both studies suggest it is necessary for institutions to test new teaching evaluation models online.     

The effect of online reviews on product sales: A joint sentiment-topic analysis

This research examines the business impact of online reviews. It empirically investigates the influence of numerical and textual reviews on product sales performance. We use a Joint Sentiment-Topic model to extract the topics and associated sentiments in review texts. We further propose that numerical rating mediates the effects of textual sentiments. Findings not only contribute to the knowledge of how eWOM impacts product sales, but also illustrate how numerical rating and textual reviews interplay while shaping product sales. In practice, the findings help online vendors strategize business analytics operations by focusing on more relevant aspects that ultimately drive sales.     

Persuasive Electronic Word-of-Mouth Messages in Social Media

Despite the influence of electronic word-of-mouth (eWOM) messages in decision-making processes, few studies have tested the determinants of persuasive eWOM messages among social media users. Although most of the researches focused on western and eastern cultural convergence or divergence of online communications, little attention has been paid on the validity and applicability of cultural orientations in countries with perceived inherent similar values. This study examines how Chinese and Malaysian users process eWOM messages and decide on continuing their overseas study. The significance of the study is to identify critical factors that influence Chinese and Malaysian users’ attitudes and behavior when processing persuasive eWOM messages. Results revealed that Facebook is the most used social networking site (SNS) for Malaysian users, while QQ Qzone for Chinese counterparts. This study found that argument quality, source credibility, source attractiveness, source perception, and source style exerted varying influences on Chinese and Malaysian users’ attitudes and intentions to continue their study abroad.     

The long tail or the short tail: The category-specific impact of eWOM on sales distribution

This paper investigates the impact of electronic word of mouth (eWOM) on sales distribution and challenges the conventional wisdom of the long tail theory. As customers refer to eWOM to evaluate products, and each product type entails a different scheme of evaluation standards, the impact of eWOM may differ by product type. Thus, we propose a new type of product categorization based on evaluation standard objectivity and hypothesize that this categorization gradually differentiates sales distribution patterns, some of which refute the long tail phenomenon. To validate the hypothesis, we collect data from Amazon.com, compare the distribution of eWOM among various product types, and conduct the Wilcoxon signed rank test for statistical significance. All the test results show adequate levels of significance; thus, the three hypotheses are supported. This study sheds new light on eWOM research by developing a new approach to product categorization and by proposing a different use of eWOM in searching for products to explain the different effects of eWOM on sales distribution.     

Consumer's decision to shop online: The moderating role of positive informational social influence

While much of the current literature tends to focus on the direct effect of social influence on consumer online shopping behavior, our study drew heavily on social influence theory and argued for an alternative theory focusing on the moderating role of social influence. In particular, we explored how positive messages in online discussion forums may affect consumers’ decisions to shop online. We used a laboratory experiment in which the treatment group was required to read positive messages about online shopping experience in an online discussion forum. Positive social influence was found to reinforce the relationship between beliefs about and attitude toward online shopping, as well as the relationship between attitude and intention to shop. We believe our alternative theory provides new insight into the complex processes through which social influence is brought to bear on consumers’ online shopping decisions. Implications of our work are discussed.     

Impact of Tweets on Box Office Revenue: Focusing on When Tweets are Written

This study investigates the impact of tweets on box office revenue. Specifically, the study focuses on the times when tweets were written by examining the impact of pre‐ and post‐consumption tweets on box office revenue; an examination that is based on Expectation Confirmation Theory. The study also investigates the impact of intention tweets versus subjective tweets and the impact of negative tweets on box office revenue. Targeting 120 movies released in the US between February and August 2012, this study collected tweet information on a daily basis from two weeks before the opening until the closing and box office revenue information. The results indicate that the disconfirmation that occurs in relation to the total number of pre‐consumption tweets for a movie has a negative impact on box office revenue. This premise suggests that the formation of higher expectations of a movie does not always result in positive results in situations where tweets on perceived movie quality after watching spread rapidly. This study also reveals that intention tweets have stronger effects on box office revenue than subjective tweets.