User Motivations to Participate in Crowdsourcing and Contribute User-generated Content on Location-based Media: A Literature Review

Research Background and Issues

• Identified Issues: Although location-based services like Google Maps, Strava, and Pokémon GO heavily rely on user-generated content (UGC), the academic community has yet to systematically analyze users' motivations for contributing such data. Moreover, existing studies lack consistency regarding how to maintain data accuracy and the best practices for incentive mechanisms.
• Significance: UGC is central to many location-based media services. Understanding user motivations can help optimize service quality and user experience on these platforms, promoting the long-term sustainability of the UGC ecosystem.
• Research Motivation and Related Work:
  • The rapid proliferation of location-based media is driven by advancements in smartphones, cloud computing, and navigation infrastructure.
  • Existing research has explored partial motivations for UGC and crowdsourcing (e.g., gamification, monetary rewards), but lacks a comprehensive perspective specific to location-based media.
  • Research questions include: (1) theoretical frameworks suitable for incentivizing user contributions; (2) specific motivational effects of various types of UGC and crowdsourcing processes on users.

Solution

• Research Methods:
  • Conducted a literature review, integrating bibliometric analysis and systematic search strategies.
  • Included screening, data extraction, and qualitative analysis of 19 relevant studies.
  • Proposed nine methods and motivational categories for encouraging user participation in location-based UGC based on existing literature.
• Innovations:
  • Developed a comprehensive motivational classification framework, categorizing motivations into intrinsic motivations (e.g., enjoyment of activities), extrinsic motivations (e.g., badges and points), and other social motivations.
  • Explained how these theoretical motivations can be mapped to practical design elements and product features.
• Key Techniques:
  • Literature organization: Leveraged the Scopus database and optimized search efficiency using specific keywords (e.g., "motivation," "geo*," "locative media").
  • Motivation extraction and classification: Integrated literature analysis with theoretical frameworks, including Self-Determination Theory (SDT) and Maslow's hierarchy of needs.

Research Findings

• Specific Findings:
  • Identified nine key motivational dynamics, including clear goals, enjoyment of activities, sense of competence, social recognition, personal learning and development, sense of belonging, system quality, practicality of contributions, and reward mechanisms.
  • Provided clear terminology recommendations (e.g., using "Volunteered Geographic Information" to describe geospatial data).
  • Clarified design strategies for long-term user engagement, such as balancing competition and collaboration.
• Advantages:
  • Established a reliable incentive mechanism design framework through a cross-disciplinary literature review (e.g., UGC, GIS, HCI).
  • Elegantly combined academic research with practical applications, aiding product developers in designing UGC tools that align with user psychology.
• Experimental and Evaluation Results:
  • Intrinsic motivations such as "enjoyment of activities" and "sense of competence" were shown to simultaneously improve both the quantity and quality of UGC.
  • Extrinsic motivations (e.g., points and leaderboards) primarily increased quantity but could reduce contribution quality in certain scenarios.
• Limitations and Future Directions:
  • The literature sample size (19 studies) may not fully encompass all perspectives in the field.
  • Sample heterogeneity (different countries, industries, etc.) makes it challenging to delineate specific boundaries of certain motivations.
  • Proposed future research directions include:
    1. Comparing the effectiveness of motivations across applications.
    2. Investigating long-term user engagement (e.g., multi-year participation in games or platforms).
    3. Quantitatively evaluating the cost-benefit of motivational strategies like reward mechanisms.
    4. Exploring factors that inhibit contribution motivations and the psychology of non-user groups.

In summary, this study not only organizes the theories and practices of incentivizing location-based media UGC but also provides the academic and industrial communities with a clear motivational classification and design strategies. The research supports the increasingly complex UGC ecosystem and points to promising directions for future studies.