Electronic Word of-Mouth (eWOM) helps consumers evaluate product quality and reduces decision risk without physical trials, and makes their purchase decision. More and more firms are embracing and applying eWOM marketing strategy as a complementary strategy for advertising to increase sales. However, little has been known regarding the mechanism underlying the eWOM effect on online consumer behavior and purchase decision. The paper is to examine the effect of eWOM to provide practitioners insightful guidance on service systems design and the allocation of firm resources to more effectively develop eWOM marketing strategies. This article seeks to shed light on eWOM effect from the empirical study. Consumers are increasingly using online consumer reviews to evaluate product quality. It is paramount for marketers to understand what makes online consumer reviews helpful to consumers and how this evaluation affects their decisions. Dual-process theory has been adopted in this study to investigate the factors and its links with consumers' purchase intention.This article examines how the electronic word of mouth (eWOM) information attitude (positive vs. negative), website's reputation, motivation to process information, consumer reviews, product evaluations, information quantity and source credibility contribute to the eWOM effect. The article also describes a study on the moderating role of the product type. The empirical study also examines the effects of electronic word-of-mouth (e-WOM) on consumer consideration and choice of an product.The survey results from 652 participants of an online survey. The study consisted of an online survey that was conducted on a survey website in 2015. All measurement items were measured using 7-point Likert scales. In order to provide greater insight into the results, several iterations of factor and reliability analyses were undertaken to determine a reduced set of composite dimensions. Principal component analyses and reliability analyses were used to simplify and purify the factors by removing variables with less loadings. The proposed model was analyzed by using the maximum likelihood method (i.e., ML), with structural equations analyses (LISREL 8). This study highlights that consumers’ reliance on online user reviews to choose products is significantly influenced by the quantity of products available. This study also proposes a more robust hierarchical structure to model the interaction effect between online user reviews and product quantity. This article further studies the impact of eWOM across brand reputation websites on consumers’ purchasing decisions. In parallel with the eWOM available on the Internet, consumers are able to reach almost every piece of eWOM brand reputation relevant to their interested products. The effect of eWOM motivation may influence consumers’ search costs for product information and affect their final decisions.

• Chih-Wen Wu(National Chung Hsing University, Taiwan)