An analysis of how Fortune 500 companies respond to users replying to company tweets

The objective of the research was to identify statistically significant differences in selected engagement indicators on Facebook – likes and shares in relation to the different types of content that brands on this platform add to. The analysis was performed on a sample of three global companies from the top 25 most valuable brands in the world and their posts. Using quantitative statistical methods – MANOVA (Multivariate analysis of variance) and Gammes-Howell post hoc test, a total of 1,280 brand posts were analyzed in order to differentiate the liking and sharing of content types. Data collection was carried out in the first half of 2018. The findings pointed to two statistically significant differences that were also interpreted in the discussion of the research. The findings have shown that in case of liking, in two cases out of three, there is a statistically significant difference in terms of the type of content added, when photos came out as those with the greatest potential to get like from Facebook users and fans. At the same time, the same finding appeared in the case of sharing, which is an even stronger form of engagement. Likewise, photos were shown to be the most promising in terms of potential content sharing by Facebook users and fans. The study provided some clues as to where this research should go further and explore the relationship more deeply in view of the more extensive quantitative research, and also the potential qualitative approach. The future research directions include analyzing companies of different types and sizes and also taking into account the contribution from other social networks with the same or similar engagement indicators.

TikTok is increasingly influential in promoting brand awareness and boosting purchase intention. From a social media marketing perspective, brand awareness significantly influences consumers’ purchasing decisions. The primary objective of this study is to investigate and measure the factors influencing the brand awareness of TikTok users through social media marketing communications. The paper employs exploratory factor analysis, Cronbach’s Alpha test, and regression analysis to test the hypotheses. 24 observed variables were divided into six groups. Each variable was assessed using a 5-point Likert scale. The sample size includes 240 valid responses from TikTok users collected via convenience sampling. The questionnaire was distributed to TikTok users from Vietnam via the link on Google Forms. The collected data were processed by SPSS 20 software. The results suggest that six independent variables positively affect brand recognition via social media marketing on TikTok, with a 95% confidence interval at Sig. = 0.000 (0.05). Each of the six variables positively impacts initial expectations and is statistically significant at 1%. The results show that trends (Beta = 0.299) are the most decisive factors impacting brand awareness of TikTok users. Besides, electronic word of mouth (Beta = 0.242), influencer (Beta = 0.220), entertainment (Beta = 0.206), interaction (Beta = 0.200), and storytelling (Beta = 0.179) also positively affect the brand awareness of TikTok users. Limitations and further research suggest that marketers should investigate the role of artificial intelligence (AI) in the consumer’s brand awareness-constructing process.

Social media live streaming commerce is an emerging and effective online shopping channel that integrates live streaming and e-commerce through social media platforms. This trend has gained significant attention, particularly from Generation Z, who are drawn to the interactive and entertaining aspects of shopping through live streaming. This study investigates factors affecting the purchase intention of Vietnamese Generation Z consumers in live streaming commerce on social media platforms, assessing the impact of six factors: entertainment, information quality, interactivity, perceived risk, peer customer evaluations and recommendations, and streamers. Using a non-probability sampling, an online survey was conducted among 344 consumers who possess prior experience with social media live streaming commerce. Data analysis used a partial least squares structural equation modeling technique. The findings revealed that increased entertainment, higher information quality, enhanced interactivity, positive peer customer evaluations and recommendations, and a more attractive and expert streamer positively impact purchase intention. Notably, streamers exhibited the most robust influence, while information quality demonstrated the weakest effect among the influencing factors. Conversely, perceived risk did not significantly hinder purchase intention, suggesting Generation Z consumers’ confidence in online transactions and their willingness to take risks for entertainment and interactivity in live streaming commerce. In light of these results, businesses are advised to elevate consumer purchase intentions by prioritizing aspects related to entertainment, information quality, interactivity, and peer customer evaluations. Prudent selection of streamers is highlighted as a pivotal strategy for organizations to effectively shape customer purchasing intentions.

Acknowledgment
The researchers express sincere gratitude to all the participants who generously participated in this study.