Perceived usefulness of social media in financial decision-making: differences and similarities

  • 1602 Views
  • 492 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Financial decision-making through social media blogs and opinions is an area not much explored by the researchers. This study intends to understand the perceived usefulness of social media in financial decision-making amongst individuals and groups based on demographic similarities and social parameters. This paper aims to understand the perception of various subgroups in society within the large population sample. The paper applies Mann-Whitney and Kruskal-Wallis non-parametric tests to examine the proposed research questions from a dataset of 201 individuals residing in two most populated states in Northern India. The analysis reveals the differences between different groups categorized based on generation, financially dependent, educational background, occupation, and geographical location. In terms of social media’s perceived utility in financial decision-making, results suggest that segregated groups based on cohort generation and occupation have significant variations relative to others. Based on the educational context, all other segments, number of financially dependent, geographical location, were found insignificant. The novelty of the paper lies in investigating the perceived usefulness of social media in financial decision-making amongst various homogenous groups based on demographics in a developing country. The study outcomes can be useful for the financial service providers and social media platforms in comprehending consumer behavior to devise an innovative marketing strategy for financial products targeting specific segments through enhanced coordination between them.

Acknowledgment
This paper was supported by Internal Grant Agency of FaME TBU No. IGA/FaME/2019/002.

view full abstract hide full abstract
    • Table 1. Tests of normality
    • Table 2. Measurement scale
    • Table 3. Sample profile
    • Table 4. Mann-Whitney U test results
    • Table 5. Kruskal-Wallis test results
    • Conceptualization
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Data curation
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Formal Analysis
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi
    • Funding acquisition
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Investigation
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi
    • Methodology
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Project administration
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Resources
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi
    • Software
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Supervision
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi
    • Validation
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Visualization
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi
    • Writing – original draft
      Khurram Ajaz Khan, Mohammed Anam Akhtar
    • Writing – review & editing
      Khurram Ajaz Khan, Mohammed Anam Akhtar, Pankaj Kumar Tripathi