• Title/Summary/Keyword: Seoul Innovation Park

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The Relationships among Social Influence, Use-Diffusion, Continued Usage and Brand Switching Intention of Mobile Services (사회적 영향력과 모바일 서비스의 사용-확산, 그리고 지속적 사용 및 상표 전환의도 간의 관계에 대한 연구)

  • Sang-Hoon Kim;Hyun Jung Park;Bang-Hyung Lee
    • Asia Marketing Journal
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    • v.12 no.3
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    • pp.1-24
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    • 2010
  • Typically, marketing literature on innovation diffusion has focused on the pre-adoption process and only a few studies explicitly examined consumers' post-adoption behavior of innovative mobile services. Besides, prior use diffusion research has considered the variables that determine the consumers' initial adoption in explaining the post adoption usage behavior. However, behavioral sciences and individual psychology suggest that social influences are a potentially important determinant of usage behavior as well. The purpose of this study is to investigate into the effects of network factor and brand identification as social influences on the consumers' use diffusion or continued usage intention of a mobile service. Network factor designates consumer perception of the usefulness of a network, which embraces the concept of network externality and that of critical mass. Brand identification captures distinct aspects of social influence on technology acceptance that is not captured by subjective norm in situations where the technology use is voluntary. Additionally, this study explores the effect of the use diffusion on the brand switching intention, a generally unexplored form of post-adoption behavior. There are only a few empirical studies in the literature addressing the issue of IT user switching. In this study, the use diffusion comprises of rate of use and variety of use. The research hypotheses are as follows; H1. Network factor will have a positive influence on the rate of use of mobile services. H2. Network factor will have a positive influence on variety of use of mobile services. H3. Network factor will have a positive influence on continued usage intention. H4. Brand identification will have a positive influence on the rate of use. H5. Brand identification will have a positive influence on variety of use. H6. Brand identification will have a positive influence on continued usage intention. H7. Rate of use of mobile services are positively related to continued usage intention. H8. Variety of Use of mobile services are positively related to continued usage intention. H9. Rate of use of mobile services are negatively related to brand switching intention. H10. Variety of Use of mobile services are negatively related to brand switching intention. With the assistance of a marketing service company, a total of 1023 questionnaires from an online survey were collected. The survey was conducted only on those who have received or given a mobile service called "Gifticon". Those who answered insincerely were excluded from the analysis, so we had 936 observations available for a further stage of data analysis. We used structural equation modeling and overall fit was good enough (CFI=0.933, TLI=0.903, RMSEA=0.081). The results show that network factor and brand identification significantly increase the rate of use. But only brand identification increases variety of use. Also, network factor, brand identification and the use diffusion are positively related to continued usage intention. But the hypotheses that the use diffusion are positively related to brand switching intention were rejected. This result implies that continued usage intention cannot guarantee reducing brand switching intention.

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Participation Level in Online Knowledge Sharing: Behavioral Approach on Wikipedia (온라인 지식공유의 참여정도: 위키피디아에 대한 행태적 접근)

  • Park, Hyun Jung;Lee, Hong Joo;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.97-121
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    • 2013
  • With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.