Evaluation of User Contribution Value in the Virtual Brand Community

Zhihong Li; Yanhong Zhou

doi:doi:10.11648/j.jwer.20170604.11

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Evaluation of User Contribution Value in the Virtual Brand Community

Zhihong Li, Yanhong Zhou

Received: 24 April 2017 Accepted: 3 May 2017 Published: 5 July 2017

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Abstract

Virtual brand community has become the platform for users to obtain product knowledge, share experience and interact with other members. However, integrative research that investigates the process and possible contribution of these behaviors in the virtual brand community remains limited. Based on an extensive review of literature on user behavior, we divide user contribution value into user-contributed content value and user interaction value. Then we use weighted knowledge super-network model and weighted knowledge network model to estimate the value of users. We test our model with a dataset from a Chinese virtual brand community, Millet forum. According to the different features of users, we build a two-dimensional matrix of user contribution value. Our model and findings provide important implications for better understand and manage users in the virtual brand community.

DOI	10.11648/j.jwer.20170604.11
Published in	Journal of World Economic Research (Volume 6, Issue 4, August 2017)
Page(s)	46-53
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Virtual Brand Community, User Behavior, User Contribution Value, Knowledge Network, Weighted Knowledge Super-Network

References

[1]	Algesheimer, R., U. M. Dholakia, and A. Herrmann, The Social Influence of Brand Community: Evidence from European Car Clubs. Journal of Marketing, 2005. 69 (4): p. págs. 19-34.
[2]	Arthur, G., Net gain: expanding market through virtual communities. 1997.
[3]	Bagozzi, R. P. and U. M. Dholakia, Antecedents and purchase consequences of customer participation in small group brand communities. International Journal of Research in Marketing, 2006. 23 (1): p. 45-61.
[4]	Barabasi, A. L. and R. Albert, Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509-512. Science, 1999. 286 (5439): p. 509-12.
[5]	Berge, C., Graphs and hypergraphs. 1973: North-Holland Pub. Co.;. 1307-1315.
[6]	Bretto, A. and L. Gillibert. Hypergraph-Based image representation. in Iapr International Conference on Graph-Based Representations in Pattern Recognition. 2005.
[7]	Bulte, C. V. D. and Y. V. Joshi, New Product Diffusion with Influentials and Imitators. Marketing Science, 2007. 26 (3): p. 400-421.
[8]	Chung, M., Study of impact on motives of participation and recognition of brand community over brand loyalty-an example of Fan page of Facebook.
[9]	DJ, W. and S. SH. Collectivedynamics of ’small-world’ networks. in Nature. 1998.
[10]	Dong, J. Q. and W. Wu, Business value of social media technologies: Evidence from online user innovation communities. Journal of Strategic Information Systems, 2015. 24 (2): p. 113–127.
[11]	Estrada, E., Introduction to Complex Networks: Structure and Dynamics. 2015: Springer International Publishing. 93-131.
[12]	Gale, B. T. and R. C. Wood, Managing Customer Value: Creating Quality and Service That Customers Can See. 1994: Free Press, Maxwell Macmillan Canada, Maxwell Macmillan International. 83-84.
[13]	Gallos, L. K., et al., Tolerance of scale-free networks: from friendly to intentional attack strategies. Physica A Statistical Mechanics & Its Applications, 2004. 344 (3-4): p. 504-509.
[14]	Ha, J. W., et al. Layered hypernetwork models for cross-modal associative text and image keyword generation in multimodal information retrieval. in Pacific Rim International Conference on Trends in Artificial Intelligence. 2010.
[15]	Heo, M. O., M. Kang, and B. T. Zhang, Visual Query Expansion via Incremental Hypernetwork Models of Image and Text. Lecture Notes in Computer Science, 2010. 6230: p. 88-99.
[16]	Kamat, S., F. Page, and M. Wooders. Networks and Farsighted Stability. in Econometric Society 2004 North American Winter Meetings. 2004.
[17]	Kim, J. K. and B. T. Zhang. Evolving hypernetworks for pattern classification. in Evolutionary Computation, 2007. CEC 2007. IEEE Congress on. 2007.
[18]	Liao, X., Z. Li, and Y. Xi, Discovering and Analyzing Methods on User-innovation Knowledge in Virtual Communities Based on Weighted Knowledge Network. Open Cybernetics & Systemics Journal, 2014. 8 (1): p. 976-983.
[19]	Liao, X., Z. Li, and Y. Xi, Modeling and analyzing methods of user-innovation knowledge in enterprise communities based on weighted knowledge network. Systems Engineering-Theory & Practice, 2016.
[20]	Mak, K. T. and A. Ramaprasad, Knowledge Supply Network. Journal of the Operational Research Society, 2003. 54 (2): p. 175-183.
[21]	Mcalexander, J. H. and H. F. Koenig, Building Brand Community. Journal of Marketing, 2002. 66 (1): p. págs. 38-54.
[22]	Mcgraw, P. N. and M. Menzinger, Clustering and the synchronization of oscillator networks. Physical Review E Statistical Nonlinear & Soft Matter Physics, 2005. 72 (2): p. 19-42.
[23]	Motter, A. E., C. Zhou, and J. Kurths, Enhancing complex-network synchronization. Physics, 2004. 22 (s 13–14): p. 1820-1825.
[24]	Muniz, A. M. and T. C. O’Guinn, Brand Community. Journal of Consumer Research, 1998. 27 (4): p. 412-32.
[25]	Nagurney, A., Supernetworks: An introduction to the concept and its applications with a specific focus on knowledge supernetworks. Organization Collection, 2005. 4.
[26]	Nagurney, A. and J. Dong, Supernetworks: Decision-Making for the Information Age. 2002. 76 (2): p. 93-95.
[27]	Nambisan, S., Complementary Product Integration by High-Technology New Ventures: The Role of Initial Technology Strategy. Management Science, 2002. 48 (3): p. 382-398.
[28]	Parmentier, G. and V. Mangematin, Orchestrating innovation with user communities in the creative industries ☆. Technological Forecasting & Social Change, 2013. 83 (2): p. 40-53.
[29]	Ravald, A. and C. Grönroos, The value concept and relationship marketing. European Journal of Marketing, 1996. 30 (2): p. 19-30.
[30]	Rheingold, H., The Virtual Community: Homesteading on the Electronic Frontier. 2000: HarperTrade. 1114.
[31]	Seufert, A., G. V. Krogh, and A. Bach, Towards knowledge networking. Journal of Knowledge Management, 1999. 3 (3): p. 180-190.
[32]	Strogatz, S., Thestructure and function of complexnetworks. 2003.
[33]	Thurner, S., 2002): “Statistical mechanics of complex networks. Review of Modern Physics, 2001. 74 (1): p. xii.
[34]	Valck, K. D., G. H. V. Bruggen, and B. Wierenga, Virtual communities: A marketing perspective ☆. Decision Support Systems, 2009. 47 (3): p. 185-203.
[35]	Volpentesta, A. P., Hypernetworks in a directed hypergraph. European Journal of Operational Research, 2008. 188 (2): p. 390-405.
[36]	Woodruff, R. B., Customer Value: The Next Source for Competitive Advantage. Journal of the Academy of Marketing Science, 1997. 25 (2): p. 139-153.
[37]	Yan, E., et al., Topics in dynamic research communities: An exploratory study for the field of information retrieval. Journal of Informetrics, 2012. 6 (1): p. 140-153.
[38]	Yan, S. R., et al., A graph-based comprehensive reputation model: Exploiting the social context of opinions to enhance trust in social commerce. Information Sciences, 2015. 318: p. 51–72.
[39]	Yang, G. and X. Li, The Analysis of Model and Robustness of Regional Logistics Network Based on the Weighted Super-Network. 2009.
[40]	Yang, W. W. and X. Liu, The Empirical Research into the effect of the Value of Virtual Brand Community on Brand Loyalty. Systems Engineering, 2010. 28 (3): p. 53-58.
[41]	Yun-Jiang, X. I. and Y. Z. Dang, The Discovery and Representation Methods of Expert Domain Knowledge Based On Knowledge Network. Systems Engineering, 2005. 23 (8): p. 110-115.
[42]	Yun-Jiang, X. I. and Y. Z. Dang, Method to Analyze Robustness of Knowledge Network based on Weighted Supernetwork Model and Its Application. Systems Engineering - Theory & Practice, 2007. 27 (27): p. 134-140.
[43]	Yun-Jiang, X. I. and Y. Z. Dang, The Method to Analyze the Robustness of Knowledge Network based on the Weighted Supernetwork Model and Its Application. Systems Engineering-Theory & Practice, 2007. 27 (4): p. 134-140.

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APA Style

Zhihong Li, Yanhong Zhou. (2017). Evaluation of User Contribution Value in the Virtual Brand Community. Journal of World Economic Research, 6(4), 46-53. https://doi.org/10.11648/j.jwer.20170604.11

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ACS Style

Zhihong Li; Yanhong Zhou. Evaluation of User Contribution Value in the Virtual Brand Community. J. World Econ. Res. 2017, 6(4), 46-53. doi: 10.11648/j.jwer.20170604.11

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AMA Style

Zhihong Li, Yanhong Zhou. Evaluation of User Contribution Value in the Virtual Brand Community. J World Econ Res. 2017;6(4):46-53. doi: 10.11648/j.jwer.20170604.11

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@article{10.11648/j.jwer.20170604.11,
  author = {Zhihong Li and Yanhong Zhou},
  title = {Evaluation of User Contribution Value in the Virtual Brand Community},
  journal = {Journal of World Economic Research},
  volume = {6},
  number = {4},
  pages = {46-53},
  doi = {10.11648/j.jwer.20170604.11},
  url = {https://doi.org/10.11648/j.jwer.20170604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jwer.20170604.11},
  abstract = {Virtual brand community has become the platform for users to obtain product knowledge, share experience and interact with other members. However, integrative research that investigates the process and possible contribution of these behaviors in the virtual brand community remains limited. Based on an extensive review of literature on user behavior, we divide user contribution value into user-contributed content value and user interaction value. Then we use weighted knowledge super-network model and weighted knowledge network model to estimate the value of users. We test our model with a dataset from a Chinese virtual brand community, Millet forum. According to the different features of users, we build a two-dimensional matrix of user contribution value. Our model and findings provide important implications for better understand and manage users in the virtual brand community.},
 year = {2017}
}

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TY  - JOUR
T1  - Evaluation of User Contribution Value in the Virtual Brand Community
AU  - Zhihong Li
AU  - Yanhong Zhou
Y1  - 2017/07/05
PY  - 2017
N1  - https://doi.org/10.11648/j.jwer.20170604.11
DO  - 10.11648/j.jwer.20170604.11
T2  - Journal of World Economic Research
JF  - Journal of World Economic Research
JO  - Journal of World Economic Research
SP  - 46
EP  - 53
PB  - Science Publishing Group
SN  - 2328-7748
UR  - https://doi.org/10.11648/j.jwer.20170604.11
AB  - Virtual brand community has become the platform for users to obtain product knowledge, share experience and interact with other members. However, integrative research that investigates the process and possible contribution of these behaviors in the virtual brand community remains limited. Based on an extensive review of literature on user behavior, we divide user contribution value into user-contributed content value and user interaction value. Then we use weighted knowledge super-network model and weighted knowledge network model to estimate the value of users. We test our model with a dataset from a Chinese virtual brand community, Millet forum. According to the different features of users, we build a two-dimensional matrix of user contribution value. Our model and findings provide important implications for better understand and manage users in the virtual brand community.
VL  - 6
IS  - 4
ER  -

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Author Information

Zhihong Li

Department of Business Administration, South China University of Technology, Guangzhou, China
Yanhong Zhou

Department of Business Administration, South China University of Technology, Guangzhou, China

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APA Style

Zhihong Li, Yanhong Zhou. (2017). Evaluation of User Contribution Value in the Virtual Brand Community. Journal of World Economic Research, 6(4), 46-53. https://doi.org/10.11648/j.jwer.20170604.11

Copy | Download

ACS Style

Zhihong Li; Yanhong Zhou. Evaluation of User Contribution Value in the Virtual Brand Community. J. World Econ. Res. 2017, 6(4), 46-53. doi: 10.11648/j.jwer.20170604.11

Copy | Download

AMA Style

Zhihong Li, Yanhong Zhou. Evaluation of User Contribution Value in the Virtual Brand Community. J World Econ Res. 2017;6(4):46-53. doi: 10.11648/j.jwer.20170604.11

Copy | Download

@article{10.11648/j.jwer.20170604.11,
  author = {Zhihong Li and Yanhong Zhou},
  title = {Evaluation of User Contribution Value in the Virtual Brand Community},
  journal = {Journal of World Economic Research},
  volume = {6},
  number = {4},
  pages = {46-53},
  doi = {10.11648/j.jwer.20170604.11},
  url = {https://doi.org/10.11648/j.jwer.20170604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jwer.20170604.11},
  abstract = {Virtual brand community has become the platform for users to obtain product knowledge, share experience and interact with other members. However, integrative research that investigates the process and possible contribution of these behaviors in the virtual brand community remains limited. Based on an extensive review of literature on user behavior, we divide user contribution value into user-contributed content value and user interaction value. Then we use weighted knowledge super-network model and weighted knowledge network model to estimate the value of users. We test our model with a dataset from a Chinese virtual brand community, Millet forum. According to the different features of users, we build a two-dimensional matrix of user contribution value. Our model and findings provide important implications for better understand and manage users in the virtual brand community.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Evaluation of User Contribution Value in the Virtual Brand Community
AU  - Zhihong Li
AU  - Yanhong Zhou
Y1  - 2017/07/05
PY  - 2017
N1  - https://doi.org/10.11648/j.jwer.20170604.11
DO  - 10.11648/j.jwer.20170604.11
T2  - Journal of World Economic Research
JF  - Journal of World Economic Research
JO  - Journal of World Economic Research
SP  - 46
EP  - 53
PB  - Science Publishing Group
SN  - 2328-7748
UR  - https://doi.org/10.11648/j.jwer.20170604.11
AB  - Virtual brand community has become the platform for users to obtain product knowledge, share experience and interact with other members. However, integrative research that investigates the process and possible contribution of these behaviors in the virtual brand community remains limited. Based on an extensive review of literature on user behavior, we divide user contribution value into user-contributed content value and user interaction value. Then we use weighted knowledge super-network model and weighted knowledge network model to estimate the value of users. We test our model with a dataset from a Chinese virtual brand community, Millet forum. According to the different features of users, we build a two-dimensional matrix of user contribution value. Our model and findings provide important implications for better understand and manage users in the virtual brand community.
VL  - 6
IS  - 4
ER  -

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