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Social Networking Sites as a Multimedia Tool for Brand Popularity – An Exploratory Study

Affiliations

  • Department of Management Studies, IIT (ISM), Dhanbad - 826004, Jharkhand, India

Abstract


Objectives: To identify the role of content richness (video, photo and link) and time frame of the brand publication (time and date) as factors of brand posts popularity. Methods/Statistical Analysis: The data of 1488 brand posts were collected from the Face book brand pages of five international mobile companies popular in India. For analyzing the data, multiple regressions were used as tool using SPSS software. Findings: The result showed that image has the highest impact on the brand popularity in terms of likes and comments and shares. On the other hand, the video contents significantly increase the volume of likes and shares but fail to attract more comments. Similarly, the provision of the link in the content shows significant but has a negative impact on likes as it carries users to another page. But the link is significant in terms of attracting shares. The time of brand post- publication (non-working hour) is significant in terms of likes but has got negative influence. On the other hand, it has no impact on comments and shares. Finally, the result shows that the day of the brand posts publication (workdays) significantly increases the volume of comments, whereas, for likes and shares, the study did not find any support. Application/Improvements: This paper suggests strategies for brand posts popularity on Facebook which might be helpful for the Indian marketers and contributes to the existing literature on the management of marketing strategies for consumer engagement on social networking sites.

Keywords

Brand Popularity, Multimedia Tool, Social Networking Sites.

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References


  • Hennig-Thurau T, Gwinner KP, Walsh G, Gremler DD. Electronic word of mouth via consumer opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing. 2004; 18(1):38–52.
  • Solomon M, Bamossy G, Askegaard S, Hogg M. Consumer behavior: Buying: A European Perspective. 4th ed. Financial Times Press; 2010.
  • Huang JH, Chen YF. Herding in online product choice. Psychology and Marketing. 2006; 23(5):413–28.
  • Dellarocas C. The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science. 2003; 49(10):1407–24.
  • Chakradeo SN, Abraham RM, Rani BA, Manjula R. Data mining: Building Social Network. Indian Journal of Science and Technology. 2015 Jan; 8(S2):1–5.
  • Goldsmith RE. Electronic word-of-mouth. Encyclopedia of E-Commerce, E-Government and Mobile Commerce. Khosrow-Pour M. editor. Hershey, PA: Idea Group Publishing; 2006. p. 408–12.
  • Raamakirtinan S, Livingston LMJ. Identifying influential users in Facebook - A sentiment based approach. Indian Journal of Science and Technology. 2016 Mar; 9(10):1–9.
  • Chua AY, Banerjee S. Marketing via Social Networking Sites: A study of brand-post popularity for brands in Singapore. Proceedings of the International Multi Conference of Engineers and Computer Scientists; 2015. p. 1.
  • Sinclaire JK, Vogus CE. Adoption of Social Networking Sites: An exploratory adaptive structuration perspective for global organizations. Information Technology and Management. 2011; 12(4):293–314.
  • Huang JH, Chen YF. Herding in online product choice. Psychology and Marketing. 2006; 23(5):413–28.
  • Ramesh N, Andrews J. Personalized search engine using social networking activity. Indian Journal of Science and Technology. 2015 Feb; 8(4):1–6.
  • Number of social network users in India from 2012 to 2018 (in millions). 2015. Available from: http://www.statista.com/statistics/278407/number-of-social-network-users-in-india/
  • Dhamodaran S, Sachin KR, Kumar R. Big data implementation of natural disaster monitoring and alerting system in real time social network using Hadoop technology. Indian Journal of Science and Technology. 2015 Sep; 8(22):1–4.
  • UnSeok A. A study on the effects of Facebook brand fan page value proposition on brand engagement. Indian Journal of Science and Technology. 2016 Jul; 9(26):1–7.
  • Chua AY, Banerjee S. How businesses draw attention on Facebook through incentives, vividness and interactivity. IAENG International Journal of Computer Science. 2015; 42(3):275–81.
  • De Vries L, Gensler S, Leeflang PS. Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing. 2012; 26(2):83–91.
  • 9 brands with brilliant Facebook marketing. 2016. Available from: http://blog.hubspot.com/marketing/facebook-marketing-examples#sm.00002c96ts30hdhcq2r1wetkhirs7
  • Sabate F, Berbegal-Mirabent J, Canabate A, Lebherz PR. Factors influencing popularity of branded content in Facebook fan pages. European Management Journal. 2014; 32(6):1001–11.
  • Cvijikj IP, Michahelles F. Online engagement factors on Facebook brand pages. Social Network Analysis and Mining. 2013; 3(4):843–61.
  • The Social Habit 2011. 2016. Available from: http://www.edisonresearch.com/the_social_habit_2011
  • Electronics and Information Technology. Annual report 2015-16. 2016. Available from: http://deity.gov.in/content/annual-plans-reports
  • Bernoff J, Li C. Harnessing the power of the oh-so-social web. MIT Sloan Management Review. 2008; 49(3):36.
  • Li W, Darban A. The impact of online social networks on consumers' purchasing decision: The study of food retailers. 2012.
  • Evans M, Jamal A, Foxall G. Consumer behavior. 2nd ed. John Wiley and Sons Ltd; 2009.
  • Steuer J. Defining virtual reality: Dimensions determining telepresence. Journal of Communication. 1992; 42(4):73–93.
  • Daft RL, Lengel RH. Organizational information requirements, media richness and structural design. Management Science. 1986; 32(5):554–71.
  • Coyle JR, Thorson E. The effects of progressive levels of interactivity and vividness in web marketing sites. Journal of Advertising. 2001; 30(3):65–77.
  • Kumar S, Jacob VS, Sriskandarajah C. Scheduling advertisements on a web page to maximize revenue. European Journal of Operational Research. 2006; 173(3):1067–89.
  • Golder SA, Wilkinson DM, Huberman BA. Rhythms of social interaction: Messaging within a massive online network. Communities and Technologies; London: Springer; 2007. p. 41–66.
  • Rutz OJ, Bucklin RE. From generic to branded: A model of spillover in paid search advertising. Journal of Marketing Research. 2011; 48(1):87–102.
  • Zhang L, Peng TQ, Zhang YP, Wang XH, Zhu JJ. Content or context: Which matters more in information processing on microblogging sites. Computers in Human Behavior. 2014; 31:242–9.
  • Baltas G. Determinants of internet advertising effectiveness: An empirical study. International Journal of Market Research. 2003; 45(4):505–15.
  • Fan Page Karma. 2015. Available from: http://www.fanpagekarma.com/facebook
  • Greene WH. Econometric analysis. Upper Saddle River, NJ: Prentice Hall; 2003.

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