Digital Brands and Web 3.0 Enterprises: Social Network Analysis and Thematic Analysis of User activities and Behavioral Patterns in Online Retailers

Main Article Content

Fatemeh Sharafi Farzad https://orcid.org/0000-0002-4568-8078
Shaghayegh Kolli https://orcid.org/0000-0002-0101-352X
Tohid Soltani https://orcid.org/0000-0002-5597-326X
Saeid Ghanbary https://orcid.org/0000-0002-6689-8488

Keywords

Web 3.0 enterprise, Social Network Analysis, Thematic analysis, E-commerce, Customer Behavioral Pattern, Digikala, Online Shopping, Twitter

Abstract





Considering the importance of web 3.0 enterprises in online retailing, this article addresses how these enterprises operate in Iranian context. DigiKala, is an online retailer that has been one of the most successful Start-ups in Iran and has gains 85-90% of the online retailers market of the country. This enterprise has started to evolve its value chain to a platform business. On the other hand, twitter as a free social networking microblogging has been one of the most important tools in online market, as customers, especially on digital markets, share their positive and negative comments in regard with their purchase experience. In this research, firstly social network analysis (SNA) method used to understand the relationships and individual nodes in the network. Then, thematic analysis method applied to analyze the sent tweets to achieve users’ behavioral patterns. Using different social media, like twitter, and sharing the feedback is also valid for Digikala as a web 3.0 enterprises. This research studied the network of tweets in a special events namely Black Friday which DigiKala offered considerable discounts for the customers. Some implications of our research are also presented at the end of this article.





Downloads

Download data is not yet available.
Abstract 1366 | PDF Downloads 577

References

Achtenhagen, L. (2017). Media Entrepreneurship—Taking Stock and Moving Forward, International Journal of Media Management, 19(1), 1-10

Amati, G., Angelini, S., Capri, F., Gambosi, G., Rossi, G., & Vocca, P. (2016a). Modelling the temporal evolution of the retweet graph. IADIS International Journal on Computer Science & Information Systems, 11(2).

Amati, G., Angelini, S., Capri, F., Gambosi, G., Rossi, G., & Vocca, P. (2016b). Twitter temppral evolution analysis: comparing event and topic driven retweet graphs. IADIS International Journal on Computer Science & Information Systems, 11(2).

Bagheri, S. K., Raoufi, P., Samandar Ali Eshtehardi, M., Shaverdy, S., Ramezani Akbarabad, B., Moghaddam, B., & Mardani, A. (2018). Using the crowd for business model innovation: the case of Digikala. R&D Management.

Bakhshizadeh, K., Haji Jafar, A., & Nasiri, H. (2018). Eliciting Mental Map of the Customers of Digikala E-Stores Using Zaltman Metaphor Elicitation Technique (ZMET). Journal of Business Management, 10(1), 49-72. doi:10.22059/jibm.2017.215675.2242

Berger, J., & Milkman, K. L. (2012). What makes online content viral?. Journal of marketing research, 49(2), 192-205.

Bulearca, M., & Bulearca, S. (2010). Twitter: a viable marketing tool for SMEs? Global business and management research, 2(4), 296.


Campbell, W. M., Dagli, C. K., & Weinstein, C. J. (2013). Social network analysis with content and graphs. Lincoln Laboratory Journal, 20(1), 61-81.

Chappuis, B., Gaffe, B., & Parvizi, P. (2011). Are your customers becoming. McKinsey Quarterly.

Cheung, C. M., & Lee, M. K. (2008). Online consumer reviews: Does negative electronic word-of-mouth hurt more? AMCIS 2008 Proceedings, 143.

Chiang, P., Hui Lo, S., & Wang, L.-H. (2017). Customer Engagement Behaviour in Social Media Advertising:Antecedents and Consequences. Contemporary Management Research.

Chiosa, A. R., & Anastasiei, B. (2017). Negative Word-of-Mouth: Exploring the Impact of Adverse Messages on Consumers’ Reactions on Facebook. Review of conomic and business studies.

Choi, D., & Kim, P. (2013, March). Sentiment analysis for tracking breaking events: a case study on twitter. In Asian Conference on Intelligent Information and Database Systems (pp. 285-294). Springer, Berlin, Heidelberg.

Choi, D., Hwang, M., Kim, J., Ko, B.-K., & Kim, P. (2014). Tracing trending topics by analyzing the sentiment status of tweets. Comput. Sci. Inf. Syst., 11(1), 157-169.

Choudary, S. P. (2015), Platform Scale: How an emerging business model helps startups build large empires with minimum investment, Platform thinking lab
Ciasullo, M. V., Troisi, O., & Cosimato, S. (2018). How Digital Platforms Can Trigger Cultural Value Co-Creation?—A Proposed Model. Journal of service science and management, 11(02), 161.

Cogburn, D. L., & Espinoza-Vasquez, F. K. (2011). From networked nominee to networked nation: Examining the impact of Web 2.0 and social media on political participation and civic engagement in the 2008 Obama campaign. Journal of Political Marketing, 10(1-2), 189-213.

Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing, 241-263.

Evangelopoulos, N., Magro, M. J., & Sidorova, A. (2012). The dual micro/macro informing role of social network sites: can Twitter macro messages help predict stock prices? Informing Science, 15.

Fuchs, C. (2017). Social media: A critical introduction: Sage.

Gallaugher, J., & Ransbotham, S. (2010). Social media and customer dialog management at Starbucks. MIS Quarterly Executive, 9(4).

González-Ibánez, R., Muresan, S., & Wacholder, N. (2011). Identifying sarcasm in Twitter: a closer look. Paper presented at the Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short Papers-Volume 2.

Hanna, R., Rohm, A., & Crittenden, V. L. (2011). We’re all connected: The power of the social media ecosystem. Business horizons, 54(3), 265-273.

Harary, F. (1994). Graph Theory: Addison-Wesley.

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.

Hornikx, J., & Hendriks, B. (2015). Consumer Tweets about Brands:A Content Analysis of Sentiment Tweets about Goods and Services. Journal of Creative Communications, 176–185.

Ibrahim, N. F., & Wang, X. (2019). Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media. Computers in Human Behavior, 96, 32-45.

Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American society for information science and technology, 60(11), 2169-2188.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68.

Khajeheian, D. (2016). Telecommunication Policy: Communication Act Update. Global Media Journal-Canadian Edition, 9(1), 135-141.

Khajeheian, D. (2017). Media entrepreneurship: A consensual definition. AD-minister, (30), 91-113.

Labafi, S., & Williams, I. (2018). Competitiveness of Small Media Firms Competitiveness in Emerging Markets (pp. 263-282): Springer.

Lennon, S. J., Johnson, K. K., & Lee, J. (2011). A perfect storm for consumer misbehavior: Shopping on Black Friday. Clothing and Textiles Research Journal, 29(2), 119-134.


Maia, M., Almeida, J., & Almeida, V. (2008). Identifying user behavior in online social networks. Paper presented at the Proceedings of the 1st workshop on Social network systems.

Malehmir, F., Maeen, M., & Jahangir, M. R. (2017). A study on the Interaction of Motivations and Online Shopping Experience in E-Commerce Success in Digikala Company. International Journal of Scientific Study, 5(5).

Marsh, K. L., Richardson, M. J., & Schmidt, R. C. (2009). Social connection through joint action and interpersonal coordination. Topics in Cognitive Science, 1(2), 320-339.

Martínez-Cañas, R., Ruiz-Palomino, P., Linuesa-Langreo, J., & Blázquez-Resino, J. J. (2016). Consumer participation in co-creation: an enlightening model of causes and effects based on ethical values and transcendent motives. Frontiers in psychology, 7, 793.

Munger, T., & Zhao, J. (2015). Identifying influential users in on-line support forums using topical expertise and social network analysis. Paper presented at the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economyand how to make them work for you: WW Norton & Company.

Puschmann, T., & Alt, R. (2016). Sharing economy. Business & Information Systems Engineering, 58(1), 93-99.

Qualman, E. (2013). Socialnomics: How Social Media Transforms the Way We Live and Do Business. New Jersey: John Wiley & Sons.

Reillier, L. C., & Reillier, B. (2017). Platform strategy: How to unlock the power of communities and networks to grow your business: Routledge.
Simpson, L., Taylor, L., O'Rourke, K., & Shaw, K. (2011). An analysis of consumer behavior on Black Friday. American International Journal of Contemporary Research.

Smith, M. A., Shneiderman, B., Milic-Frayling, N., Mendes Rodrigues, E., Barash, V., Dunne, C., ... & Gleave, E. (2009, June). Analyzing (social media) networks with NodeXL. In Proceedings of the fourth international conference on Communities and technologies (pp. 255-264). ACM.‏

Thackeray, R., Neiger, B. L., Hanson, C. L., & McKenzie, J. F. (2008). Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health promotion practice, 9(4), 338-343.

Thomas, J., Cara O, P., Emelia , H., & Robbins, K. (2012). Social media and negative word of mouth: strategies for handing unexpecting comments. Atlantic Marketing Journal, 87-108.

Wang, J. C., & Chang, C. H. (2013). How online social ties and product-related risks influence purchase intentions: A Facebook experiment. Electronic Commerce Research and Applications, 337–346.

Yadav, M. S., De Valck, K., Hennig-Thurau, T., Hoffman, D. L., & Spann, M. (2013). Social commerce: a contingency framework for assessing marketing potential. Journal of interactive marketing, 27(4), 311-323.

Yusheng, L., Shang, Y., & Yang, Y. (2017). Clustering coefficients of large networks. Information Sciences.

Zarantonello, L., Romani, S., Grappi, S., & Bagozzi, R. P. (2016). Brand hate. Journal of Product & Brand Management, 25(1), 11-25.

Zeng, X., & Wei, L. (2013). Social ties and user content generation: Evidence from Flickr. Information Systems Research, 71-87.