LEADERSHIP, CONTRIBUTION, LANGUAGE AND SHARED CONTENT AS METRICS IN MALAYSIAN MILLENNIALS’ DECISION MAKING
DOI:
https://doi.org/10.32770/jbfem.vol2153-162Keywords:
Malaysia, opinion leader, influencers, decision making, social mediaAbstract
Millennials have purchasing power second only to ‘baby boomers’. This generation grew up in a time of immense and fast-paced technological change. The study aims to investigate how this particular group of consumers made the decision based on their influencers, share content and common language in a virtually connected environment. A positivist paradigm to amass data from different business undergraduates who are familiar with the various social media and online purchases were used. Results revealed positive correlations between the constructs in and also indicated that ‘factors in communicating’, ‘Influencers recommendations’, ‘opinion leaders advice’, and ‘agreements with reference partner’ were statistically significant, making a unique contribution of prediction to the decision-making process. The limitations apply to a country-specific context, small sample size and a specific type of respondent. Studies in other contexts and with different respondents may yield different results. Whilst the study has confirmed and reinforced the importance of social media as a potent force in communication to and within Millennial groups, the study has highlighted that ‘collective intelligence’ in the purchase decision-making process has emerged as a result of the coalescing of social media with other complex individual factors like methods of advice and agreement with opinion leaders.
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References
Bhattacherjee. A. (2012). Social science research: Principles, methods, and practices. 2nd edition. University of South Florida Scholar Commons.
Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of computational science, 2(1), 1-8.
Bonabeau, E. (2009). Decisions 2.0: The power of collective intelligence. MIT Sloan management review, 50(2), 45-52.
Brönnimann, L. (2013). Multilanguage sentiment-analysis of Twitter data on the example of Swiss politicians. Available at: http://www.twitterpolitiker.ch/Paper _Swiss_Politicians_On_Twitter.pdf. (accessed 12 March 2017).
Bryman, A., & Bell, E. (2007). Business research methods. 2nd edition. Oxford University Press.
Burns, Alvin C., & Bush, R.F. (2010). Marketing research, textbook and instructor’s manual. 6th edition. Pearson Education Inc.
Carter, S., & Yeo, A. C. M. (2018). Internet-enabled collective intelligence as a precursor and predictor of consumer behaviour. Economics, Management and Financial Markets, 13(4), 11-38.
Castro, J., Lu, J., Zhang, G., Dong, Y., & Martínez, L. (2017). Opinion dynamics-based group recommender systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 99, 1-13.
Chen, J., Teng, L., Yu, Y., & Yu, X. (2016). The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence. Journal of Business Research, 69(2), 467-475.
Cho, Y., Hwang, J., & Lee, D. (2012). Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach. Technological Forecasting and Social Change, 79(1), 97-106.
Chung, S., & Liu, S. (2011). Predicting stock market fluctuations from twitter. Berkeley, California. Available at stat.berkeley.edu. (accessed 10 January 2017).
Denscombe, M. (2014). The good research guide: for small-scale social research projects. UK: McGraw-Hill Education.
Devellis, R. (2012). Scale development theory and applications. New York: Sage Publications.
Dong, Y., Zhan, M., Kou, G., Ding, Z., & Liang, H. (2018). A survey on the fusion process in opinion dynamics. Information Fusion, 43, 57-65.
Dörnyei, Z. (2007). Research methods in applied linguistics. New York: Oxford University Press.
Elshendy, M., Colladon, A. F., Battistoni, E., & Gloor, P. A. (2018). Using four different online media sources to forecast the crude oil price. Journal of Information Science, 44(3), 408-421.
Esmaeili, L., & Hashemi G, S. A. (2019). A systematic review on social commerce. Journal of Strategic Marketing, 27(4), 317-355.
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82-89.
Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social networks, 1(3), 215-239.
Gloor, P. A. (2017). Sociometrics and human relationships: Analyzing social networks to manage brands, predict trends, and improve organizational performance. UK, Bradford: Emerald Publishing Limited.
Gloor, P. A. (2017). Swarm leadership and the collective mind: Using collaborative innovation networks to build a better business. UK, Bradford: Emerald Publishing Limited.
Heylighen, F. (1999). Collective Intelligence and its Implementation on the Web: algorithms to develop a collective mental map. Computational & Mathematical Organization Theory, 5(3), 253-280.
Ignatow, G., Evangelopoulos, N., & Zougris, K. (2016). Sentiment analysis of polarizing topics in social media: News site readers’ comments on the Trayvon Martin controversy. In Robinson, L., Schulz, J., Cotten, S. R., Hale, T. M., Williams, A. A., and Hightower, J. L. (eds.). Communication and Information Technologies Annual: [New] Media Cultures (259-284). Emerald Group Publishing Limited.
Pallant, J. (2013). SPSS survival manual. 5th edition. UK: McGraw Hill.
Ritterman, J., Osborne, M., & Klein, E. (2009, November). Using prediction markets and Twitter to predict a swine flu pandemic. In 1st international workshop on mining social media (Vol. 9, 9-17). ac. uk/miles/papers/swine09. Pdf. Accessed 10 October 2017).
Saif, H., He, Y., a&nd Alani, H., (2012). Semantic sentiment analysis of Twitter. In the 11th International Semantic Web Conference, The Open University, Milton Keynes. Available at: http://oro.open.ac.uk/34929/1/76490497.pdf. Acesssed 10 October 2017.
Salem, M. Z. (2018). Effects of perfume packaging on Basque female consumers purchase decision in Spain. Management Decision, 56(8), 1748-1768.
Salminen, J. (2012). Collective intelligence in humans: A literature review [online], MIT, Collective Intelligence. http://arxiv.org/abs/1204.3401
Song, T., Yi, C., & Huang, J. (2017). Whose recommendations do you follow? An investigation of tie strength, shopping stage, and deal scarcity. Information & Management, 54(8), 1072-1083.
Stevens, J. (1996). Applied multivariate statistics for social sciences. 3rd edition. Mahwah, NJ: Lawrence Erlbaum.
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. 6th edition. Boston: Pearson Education.
Trigo, P., & Coelho, H. (2011). Collective-intelligence and decision-making. In Computational Intelligence for Engineering Systems (61-76). Springer, Dordrecht.
Vernette, E. (2004). Targeting women's clothing fashion opinion leaders in media planning: an application for magazines. Journal of Advertising Research, 44(1), 90-107.
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