Tasks of a Different Color: How Crowdsourcing Practices Differ per Complex Task Type and Why This Matters

Document Title

Tasks of a Different Color: How Crowdsourcing Practices Differ per Complex Task Type and Why This Matters

Document Information

• Subject Area: Research on Human-Computer Interaction and Crowdsourcing Work Practices
• Keywords: Crowdsourcing, Crowdfarms, Work Practices, Complex Tasks, Modular Tasks, Interwoven Tasks, Wicked Problems, Container Tasks

Research Background and Issues

• Identified Problems or Challenges:

  • The current crowdsourcing research community generally studies all complex crowdsourcing work from a unified "big task" perspective, overlooking the structural differences between various task types.
  • There is a lack of systematic analysis of work practices, especially for Chinese crowdfarms.
  • Research on wicked problems and container tasks remains unexplored, and the work practices and platform support for these task types are still unclear.

• Significance:

  • A deeper understanding of the work practices for different types of complex tasks can help optimize task allocation and workflow design, improving the quality and efficiency of crowdsourcing work.
  • Focusing on Chinese crowdsourcing practices contributes to understanding the trends of business transformation in the global crowdsourcing economy, particularly in the field of complex tasks.

• Research Motivation and Related Work:

  • Many scholars have studied the workflows of modular and interwoven tasks, proposing concepts such as "flash organizations" to facilitate collaboration on complex tasks.
  • Previous research has mostly focused on modular tasks, neglecting the work practices of workers and teams in wicked problems and container tasks.
  • Chinese crowdfarms, as a typical research subject, can provide new perspectives for the development of global crowdsourcing research.

Solutions

• Methods or Solutions:

  • Propose a systematic task classification framework based on task complexity, decomposability, and structure, dividing tasks into modular tasks, interwoven tasks, wicked problems, and container tasks.
  • Conduct in-depth research on 31 Chinese crowdfarms using structured interviews to obtain detailed work practices for different task types.
  • Study task procurement, execution, problem-solving, reputation maintenance, and workflow adjustments.

• Innovations:

  • For the first time, study crowdfarm practices based on task type classification, providing a comprehensive analysis through four distinct task categories.
  • Provide preliminary research on wicked problems and container tasks to fill gaps in the field and offer improvement suggestions.

• Implementation Steps and Key Techniques:

  • Use semi-structured interviews to investigate crowdfarm practices for different task types.
  • Employ bilingual (Chinese-English) translation and thematic analysis for data processing to ensure accuracy.
  • Use the task framework as a guide to map tasks into four categories for induction and analysis.

Research Outcomes

• Specific Findings:

  • Identified specific work practice differences among the four task types: modular tasks are efficient but homogeneous; interwoven tasks require extensive collaboration but are costly; wicked problems are difficult to undertake due to unclear structures; container tasks require cross-domain collaboration.
  • Established the advantages of Chinese crowdfarms in modular and interwoven tasks while revealing their limitations in wicked problems and container tasks.
  • Provided platform optimization suggestions, such as improving payment mechanisms, diversifying reward policies, and developing expert search engines.

• Advantages Compared to Existing Solutions:

  • Using Chinese crowdfarms as case studies fills a gap in global crowdsourcing research.
  • Offers the first empirical study on the work practices of wicked problems and container tasks, enriching the depth of understanding in this area.

• Experimental or Evaluation Results:

  • Participation in crowdfarms significantly enhances the efficiency of modular and interwoven tasks but faces significant challenges in complex tasks (e.g., wicked problems and container tasks).
  • Existing work practices primarily focus on cost control and team collaboration, with insufficient support for individual efforts in wicked problems.

• Limitations and Future Directions:

  • Limitations:

    • The sample is concentrated on crowdfarms, lacking research on individual crowdsourcing workers.
    • Primarily qualitative interviews were used, without incorporating quantitative methods like surveys to enhance data comprehensiveness.
    • The closed research context cannot be directly generalized to the global crowdsourcing market.

  • Future Directions:

    • Study the practices of individual crowdsourcing workers for different types of complex tasks.
    • Explore how individual workers collaborate with crowdfarms or teams to complete complex tasks.
    • Expand the sample to include more diverse task backgrounds, such as wicked problems and container tasks on international platforms.

Conclusion

Through an in-depth study of Chinese crowdfarms, this paper systematically identifies the differences in work practices among modular tasks, interwoven tasks, wicked problems, and container tasks for the first time. It proposes feasible optimization suggestions for crowdsourcing platforms, providing theoretical foundations and design inspiration for achieving more efficient and diverse crowdsourcing workflows.