Lecture Content

Note: Lecture prepared for Neoscholar

1 What is Cultural Consumerism?

Example taken from Vocal Media

Image Generated with [Deep AI](https://deepai.org/machine-learning-model/cyberpunk-generator)

Image Generated with Deep AI

Image Generated with [Deep AI](https://deepai.org/machine-learning-model/cyberpunk-generator)

Image Generated with Deep AI

2 What is its connection with social media?

2.1 Does this impact affects all social media users equally?

  • Hu and Zhu (2022) argued that social media usage serves to generate users’ purchase intention on social commerce websites.

  • Importantly, users’ cultural intelligence has been found to play a significant role mediating the effects of social media usage on users’ intention to consume.

    • This means that according to Hu and Zhu (2022), the more culturally intelligent a user is, the more likely they are to be influenced by social media in their consumption choices.
  • We have to note that sample is 2,058 international college students in china (little to no external validity)

    • It is more likely that what they really found was that “social media is closely associated with individuals’ international exposure” and it is this exposure what transforms into knowledge of US-centric pop culture – rather than people’s capacities to manage cross-cultural issues in a foreign culturally novel environment, which is the original conceotualization of cultural intelligence (see Earley and Ang (2003)).
  • Then the takeaway point is that US-centric social media users are more likely to be influenced to participate in cosumeristic behaviors

2.2 In short…

  • Cultural consumerism and social media are closely intertwined.
    • Social media platforms amplify the effects of cultural consumerism by providing a space for consumers to
      • express their identities,
      • engage with brands, and
      • make purchase decisions influenced by their social media interactions.
  • This relationship between cultural consumerism and social media is shaping the landscape of modern consumer behavior.

3 What is the role of social media influencers and why?

  1. Influencer Marketing: Influencer marketing is a relationship between a brand and an influencer.
    • The influencer promotes the brand’s products or services through various media outlets such as Instagram and YouTube.
    • Influencers must be trusted figures within a niche community and retain a loyal following.
    • They typically possess knowledge or experience about what they are advertising.
  2. Trust and Authenticity: When influencers promote a brand or endorse its products, their audience perceives it as a trusted recommendation.
    • This is because successful social media influencers have nurtured relationships with their followers based on transparency, relatability, and expertise.
  3. Targeted Audience: Influencers can help reach a specific target audience.
    • The monetary value of an influencer is typically calculated by the size of their social following as well as the platform they are using.
  4. Effective Marketing Strategy: Influencer marketing can be one of the most effective ways that businesses can win new customers and grow their revenue.
    • According to Forbes, 74% of consumers say they trust the opinions they see on social media — including those from influencers — when deciding whether to purchase a product.
  5. Monetary Compensation: The brand pays the influencer to talk about the products on social media, where they have a vast network of followers who could become potential customers.
    • The price of an influencer marketing campaign varies significantly depending on the influencer and how much they charge.

4 How big is this business?

Image taken from the social media data analytics and storytelling course--methods and software used [MDCOR by @canche2023machine](https://www.sciencedirect.com/science/article/pii/S0957417422022837?via%3Dihub)

Image taken from the social media data analytics and storytelling course–methods and software used (MDCOR by González Canché 2023a)(https://www.sciencedirect.com/science/article/pii/S0957417422022837?via%3Dihub)

Image taken from the social media data analytics and storytelling course--methods and software used [MOVIE by @gonzalez2022mapping](https://journals.sagepub.com/doi/full/10.1177/20597991221119012)

Image taken from the social media data analytics and storytelling course–methods and software used (MOVIE by González Canché 2022)(https://journals.sagepub.com/doi/full/10.1177/20597991221119012)

Image taken from the social media data analytics and storytelling course--methods and software used [SSEM by @canche2023spatial](https://link.springer.com/book/10.1007/978-3-031-24857-3)

Image taken from the social media data analytics and storytelling course–methods and software used (SSEM by González Canché 2023b)(https://link.springer.com/book/10.1007/978-3-031-24857-3)

Image taken from the social media data analytics and storytelling course--methods and software used [GRATIS by @gonzalez2024graphical](https://journals.sagepub.com/doi/full/10.1177/15586898231166968)

Image taken from the social media data analytics and storytelling course–methods and software used (GRATIS by González Canché 2024)(https://journals.sagepub.com/doi/full/10.1177/15586898231166968)

5 In closing

References

Earley, P Christopher, and Soon Ang. 2003. “Cultural Intelligence: Individual Interactions Across Cultures.”
González Canché, Manuel S. 2022. “Mapping, Organizing, and Visualizing Interdependent Events (MOVIE): A Rigorous Analytic Framework and Cost-Free Software Application Designed to Model Temporal and Dynamic Complex Realist Structures in Social Research Settings.” Methodological Innovations 15 (3): 263–88.
———. 2023a. “Machine Driven Classification of Open-Ended Responses (MDCOR): An Analytic Framework and No-Code, Free Software Application to Classify Longitudinal and Cross-Sectional Text Responses in Survey and Social Media Research.” Expert Systems with Applications 215: 119265.
———. 2023b. Spatial Socio-Econometric Modeling (SSEM): A Low-Code Toolkit for Spatial Data Science and Interactive Visualizations Using r. Springer Nature.
———. 2024. “Graphical Retrieval and Analysis of Temporal Information Systems (GRATIS): An Integrative Mixed Methodology and Open-Access Software to Analyze the (Non-) Linear Chronological Evolution of Information Embedded in Textual/Qualitative Data.” Journal of Mixed Methods Research 18 (1): 71–103.
Hu, Shangui, and Zhen Zhu. 2022. “Effects of Social Media Usage on Consumers’ Purchase Intention in Social Commerce: A Cross-Cultural Empirical Analysis.” Frontiers in Psychology 13: 837752.