- Log In/Sign Up
- E-ISSN2233-5382
- KCI
E-ISSN : 2233-5382
A Study on Switching Intention of Broadcasting Service to MCN Service by Migration Theory
Abstract
Purpose - The Millennial Generation, which grew in the wake of the spread of the Internet and rapid changes in the media environment, is rapidly moving from the traditional broadcasting environment to the Internet-broadcasting environment in terms of content acceptance. With the emergence of UGC (User-generated content), the change in the status of single-person content creators enables the growth of multi-channel networks (MCN), a new content-distribution platform and an agency concept for single creators. Youtube-based MCN produces multiple single star producers and casts and provides its own video series through Youtube. It is also emerging as a major M&A target for global media providers in terms of providing content to a wide range of consumers with the same interests and consumption characteristics. In addition, for the Millennials generation, which are part of their lives, MCN is becoming the most suitable media for TGIF (Twitter, Google, i-phone, Facebook). Accordingly, this study defines newly emerging MCNs and analyzes the factors for accepting MCN-produced content based on the push-pull-mooring (PPM) model. Research design, data, and methodology - An empirical analysis is performed through a questionnaire survey. For this purpose, 204 people who have experience of watching MCN were studied. Collected data is processed through analysis of a structural equation model using R to test the hypothesis. Results - For the MCN service to become an alternative to existing media, it is necessary to continuously promote cultural diversity and diversity of attempts that conventional media cannot provide. It is the attractiveness of the alternative that has the greatest influence on the intention to switch to a MCN service. When we look at MCN content so far, certain patterns such as game progress, introduction, food, and chat rooms have already appeared. We need to overcome this and develop a completely new conceptual content that we have never seen before. This requires a more generous viewer perception of the topics covered. For diversity, linguistic and verbal violence should be tolerant in common sense to provide a foundation for securing cultural diversity. Conclusions - In this study, we tried to develop a comprehensive approach to the substitution effect of MCN. In terms of academic achievement, the PPM model is used to enhance the utilization of media and broadcasting. Practical implications are to provide an analytical framework for verifying alternative or complementary effects when viewers switch to MCN.
- keywords
- MCN(Multi-Channel Network), Migration Theory, PPM(Pull-Push-Mooring), Switching Intention
Reference
Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working partnerships. the Journal of Marketing, 54(1), 42-58.
Ayeh, J. K. (2015). Travellers’ acceptance of consumergenerated media: An integrated model of technology acceptance and source credibility theories. Computers in Human Behavior, 48, 173-180.
Bansal, H. S., & Taylor, S. F. (2002). Investigating interactive effects in the theory of planned behavior in a service‐provider switching context. Psychology & Marketing, 19(5), 407-425.
Bansal, H. S., Taylor, S. F., & James, Y. S. (2005). “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors. Journal of the Academy of Marketing Science, 33(1), 96-115.
Bolton, R. N., Kannan, P. K., & Bramlett, M. D. (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the academy of marketing science, 28(1), 95-108.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Colgate, M., & Hedge, R. (2001). An investigation into the switching process in retail banking services. International Journal of Bank Marketing, 19(5), 201-212.
Colgate, M., & Lang, B. (2001). Switching barriers in consumer markets: An investigation of the financial services industry. Journal of consumer marketing, 18(4), 332-347.
Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. Akron, OH: University of Akron Press.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 18(3), 382-388.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. the Journal of Marketing, 56(1), 6-21.
Ganesh, J., Arnold, M. J., & Reynolds, K. E. (2000). Understanding the customer base of service providers:an examination of the differences between switchers and stayers. the Journal of marketing, 64(3), 65-87.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (Vol. 6). Upper Saddle River, NJ: Pearson Prentice Hall.
Halim, R. E., & Christian, F. (2013). The Effect of perception and attitude toward consumer complaint behavior. Journal of Distribution Science, 11(9), 17-24.
Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of service research, 13(3), 311-330.
Herrero, Á., & San Martín, H. (2017). Explaining the adoption of social networks sites for sharing user-generated content: A revision of the UTAUT2. Computers in Human Behavior, 71, 209-217.
Hou, A. C., Chen, Y. C., Shang, R. A., & Chern, C. C. (2012). The post adoption switching of social network service: A human migratory model. In PACIS 2012Proceedings Paper, 174.
Howell, J. M., & Higgins, C. A. (1990). Champions of technological innovation. Administrative science quarterly, 35(2), 317-341.
Jackson, J. A. (1986). Migration–Aspects of modern sociology. London, UK: Longman.
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of Retailing, 76(2), 259-274.
Keaveney, S. M., & Parthasarathy, M. (2001). Customer switching behavior in online services: An exploratory study of the role of selected attitudinal, behavioral, and demographic factors. Journal of the Academy of Marketing Science, 29(4), 374-390.
Kim, E. J., Ju, M. J., & Lee, Y. K. (2016). Impact of Instrumental Factors on Dissatisfaction and Complaint Behaviors: Moderating Role of Expected Profitability. Journal of Distribution Science, 14(9), 95-110.
Lattin, J. M., & McAlister, L. (1985). Using a varietyseeking model to identify substitute and complementary relationships among competing products. Journal of Marketing Research, 22(3), 330-339.
Lee, E. S. (1966). A theory of migration. Demography, 3(1), 47-57.
Longino, C. F. Jr. (1992). The forest and the trees:Micro-level considerations in the study of geographic mobility in old age. In Rogers, A, Elderly migration and population redistribution (pp.23-34), London, UK:Bellhaven Press.
Moon, B. (1995). Paradigms in migration research:exploring ‘moorings’ as a schema. Progress in Human Geography, 19(4), 504-524.
Mattila, A. S., & Ro, H. (2008). Discrete negative emotions and customer dissatisfaction responses in a casual restaurant setting. Journal of Hospitality &Tourism Research, 32(1), 89-107.
Morgan, R. M., & Hunt, S. D. (1994). The commitmenttrust theory of relationship marketing. the Journal of marketing, 58(3), 20-38.
Oliver, C. (1997). Sustainable competitive advantage:Combining institutional and resource-based views. Strategic Management Journal, 18(9), 697-713.
Park, S. H. (2015). Single content creators stand on the world stage through DiaTV. ZDNet Korea, Retrieved October 12, 2018 from http://www.zdnet.co.kr/news/news_view.asp?artice_id=20150507175810
Ping, R. A. (1993). The effects of satisfaction and structural constraints on retailer exiting, voice, loyalty, opportunism, and neglect. Journal of retailing, 69(3), 320-352.
Porter, M. E. (2004). Competitive strategy: Techniques for analyzing industries and competitors (Vol. 198). New York, NY: Free press.
Putrevu, S., & Lord, K. R. (1994). Comparative and noncomparative advertising: Attitudinal effects under cognitive and affective involvement conditions. Journal of Advertising, 23(2), 77-91.
Ravenstein, E. G. (1885). The laws of migration. Journal of the Statistical Society of London, 48(2), 167-235.
Sharma, N., & Patterson, P. G. (2000). Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional, consumer services. International Journal of Service Industry Management, 11(5), 470-490.
Spangler, T. (2014). Netflix remains king of bandwidth usage, while YouTube declines. Variety. Retrieved October 12, 2018 from https://variety.com/2014/digital/news/netflix-youtube-bandwidth-usage-1201179643/
Stimson, R. J., & Minnery, J. (1998). Why people move to the'sun-belt': A case study of long-distance migration to the Gold Coast, Australia. Urban Studies, 35(2), 193-214.
Strabase. (2015, March 12). The reason for the largescale investment of venture capital in an MCN supporting single content creator. TrendWatch. Retrieved October 12, 2018 from http://www.strabase.com/contents/view. php?num=17754
Won, J. S. (2013). A Critical Review on Behavioral Economics with a Focus on Prospect Theory and EBA Model. Journal of Distribution Science, 11(5), 63-76.
Zeelenberg, M., & Pieters, R. (2004). Beyond valence in customer dissatisfaction: A review and new findings on behavioral responses to regret and disappointment in failed services. Journal of business Research, 57(4), 445-455.
Zengyan, C., Yinping, Y., & Lim, J. (2009). Cyber migration: An empirical investigation on factors that affect users' switch intentions in social networking sites. In System Sciences, 2009. HICSS'09. 42nd Hawaii International Conference (pp. 1-11). Retrieved October 12, 2018 from https://www.computer.org/csdl/proceedings/hicss/2009/3450/00/07-08-08.pdf
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations