A Study on the Practical Use of UCC Tourism Information (UCC 관광정보의 활용방안 연구)
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- The Journal of the Korea Contents Association
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- v.9 no.11
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- pp.416-423
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- 2009
From marketing perspectives, WOM(Word-of-Mouth) is one of the communication methods for travelers. It can be an instrument of the effect on tourist decision. The growing predominance of internet use has further highlighted the need for understanding of UCC(User-created contents) tourism information such as travel experience and travel recommendation. This paper was to examine usage patterns of UCC tourism information using experimental design and contents analysis. The result indicated that there were qualities of UCC tourism information. That is useful implication to tourism information-related marketers in destination marketing.
In this paper, we explore the information diffusion mechanism under social network environments by investigating the effect of message characteristics on the volume and speed of retweeting in Twitter, a popular online social media service. To this end, we select eight main keywords (i.e., '무상급식', '반값등록금', '나가수', '평창', '김연아', '박태환', '아이폰', '갤럭시') that have been popular on online social media in recent days. Each keyword represents various social aspects of Korea that recently grab people's attention such as political issues, entertainment, sports celebrities, and the latest digital products, and eventually holds distinctive message characteristics. Analyzing the frequency and velocity of retweeting for each keyword, we find that more than half of the sample messages posted on Twitter contain personal opinions for the certain keyword, but we also find that the tweets which include objective messages with hyperlink are the fastest ones when being retweeted by other followers. In overall, when being retweeted, the group of messages related to the certain keyword present distinctive diffusion patterns and speed according to message characteristics. From academic perspective, the findings in the study broaden our theoretical knowledge of information diffusion mechanism over online social media. For practitioners, the results also provide managerial implications regarding how to strategically utilize online social media for marketing communications with customers.
Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center.