Impact of Blogs on Sales Revenue: Test of a Network Model

Impact of Blogs on Sales Revenue: Test of a Network Model

Guoying Zhang (Midwestern State University, USA), Alan J. Dubinsky (Midwestern State University, CALIMT Learning and Innovation Research Center and Purdue University, USA) and Yong Tan (University of Washington, USA)
DOI: 10.4018/jvcsn.2011040104
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In this study, blog data were collected and network parameters were captured to represent three common measurements of online Word-Of-Mouth: intensity, influence level, and dispersion. These parameters were then analyzed using a General Estimating Equation (GEE) model to test their effects on average weekly movie box office receipts. Findings indicated that all three parameters were significant in the model. The aggregated degree, representing WOM intensity, was positively significant, which was consistent with results from extant research. Further, diameter of a network, representing WOM dispersion, was observed to be positively significant, which validated the importance of spreading WOM as far as possible. Counter-intuitively, the aggregated size node, representing WOM influence level, was ascertained to be negatively significant, which might be explained by the possible negative stance from opinion leaders with high influence level. Applying network analysis methodology to blog entries, the present work differentiated itself from extant WOM literature that has focused chiefly on content analysis. The findings also provided managerial insights to companies interested in utilizing blogs as online WOM for marketing initiatives and implications for future research.
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Literature Review

WOM has been widely studied and considered a recognized factor in driving consumer behavior, particularly in an offline venue. One such research stream has investigated how to measure WOM. In the traditional WOM format of private conversations, in general WOM is often measured through survey instruments. For instance, Elberse and Eliashberg (2003) used previous weekly box office receipts as an indicator of WOM. Eliashberg et al. (2000) modeled WOM in two dimensions—frequency and duration—both of which follow two independent exponential distributions. Mohr and Nevin (1990) proposed four types of communication measures: frequency, direction, modality, and content, among which face-to-face (WOM) is regarded as an informal means of conveying information.

Selected Online (Non-Blog) WOM Research

Owing to burgeoning use of, and interest in, online venues, scholars have recently expended much effort toward exploring WOM in the format of online conversations, messages, and user reviews. For example, Godes and Mayzlin (2004) collected data from message posts of a popular online user forum to measure the frequency and reach of online WOM. Liu (2006) collected WOM data from the Yahoo Movies message board to focus on the dynamic patterns of WOM. Utilizing cross-sectional and panel data over a two-year period, Chevalier and Mayzlin (2006) observed that online WOM in the format of user reviews influenced the sales of and Gruen et al. (2005) investigated effects of online WOM in terms of customer knowledge exchange. Sen and Lerman (2007) examined existence of a negative effect in online WOM customer reviews. Awad and Ragowsky (2008) assessed whether the effect of online WOM in the format of customer reviews was moderated by gender. Goldenberg et al. (2001) proffered a simulation model to measure the effects of strong and weak ties conveying WOM over personal networks. Trusov et al. (2009) studied the impact of WOM marketing on member growth in a social networking site. Dwyer (2007) categorized online WOM into two distinct groups—social and informational—and introduced a metric to measure the value a community assigns to each WOM instance.

WOM Blog Research

As noted earlier, the present investigation used WOM as captured in the format of blog posts. Related work on WOM of blogs is also emerging in the marketing literature. Beyond providing a comprehensive review of online WOM using blogs, Kozinets et al. (2010) followed 83 blogs for six months to present a study of a marketing campaign. In their study, a network co-production model was also proposed as a sharp contrast to the traditional organic consumer-to-consumer model and the linear opinion leader-to-consumer model. The network co-production model is similar to the network model presented in this study; specifically, bloggers are acting as nodes in the movie network within the defined domain. In the computer science literature, some studies of blogs have also been undertaken. For example, Kumar et al. (2004) discovered that there exist time periods which have dense communication among inter-community blogs in terms of blog linkage creations. The authors proposed the concept of a time graph to capture topical and temporal features of online blog links. Gruhl et al. (2004) focused on information diffusion through blogs; they considered both blog contents (by categorizing topics into spike and chatter) and individual bloggers (by categorizing them into four types based their behavior during the life cycle of a certain topic).

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