Electronic Word-of-mouth In The Context Of Third-person Effect

Companies are always in the pursuit of increasing customer satisfaction, trust, loyalty and commitment. According to the twenty-eighty rules, eighty percent of the profit is generated by only twenty percent of the customers, who are often characterized as having the traits just described above. Needless to say, there are numerous benefits of developing such customers, namely, repeat purchases, spread of positive word-of-mouth and reluctance to switch to other products and brands. Eventually, all these benefits will be realized into profits and help companies achieving its ultimate goal. Out of all the benefits, the engagement of electronic word-of-mouth or e-WOM is the most profound and influential in terms of time and scope. With the help of the Internet, the messages could reach to an unlimited number of audiences worldwide in a short period of time and with indefinite persistence.Moreover, the influence will grow stronger once the messages start to be passed along. To the companies, the engagement of e-WOM is considered to be the most efficient and effective way of marketing. Not only does it help to increase the sales dramatically, e-WOM is also the least expensive method to promote the products. However, in the case of negative e-WOM, it will also harm the companies greatly. Unfortunately, it is difficult to prevent negative or sensitive e-WOM from being articulated and passed along, especially when these e-WOM are intended to ruin competitors'image and reputation. Furthermore, given the lack of censorship on the Internet, the number of false and manipulated e-WOM is likely to proliferate as the market becomes more competitive. Therefore, it is imperative for the companies to be more equipped when confronting with these contingencies by having a better understanding of customer's perception and intentional behavior when reading different forms of e-WOM.The main objective of this thesis is to examine e-WOM in the context of third-person effect, by detecting the existence of third-person perception and exploring the relationship of third-person perception and its intentional behaviors of customers. The customers under interest are categorized into different types, in terms of their level of commitments towards the product and company.