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Designing Incentives for Community-Based Mobile Crowdsourcing Service Architecture

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Database and Expert Systems Applications (DEXA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8645))

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Abstract

Good design strategies for designing social media are important for their success, but current designs are usually ad-hoc, relying on human intuition. In this paper, we present an overview of three community-based mobile crowdsourcing services that we have developed as case studies. In community-based mobile crowdsourcing services, people voluntarily contribute to help other people anytime and anywhere using mobile phones. The task required is usually trivial, so people can perform it with a minimum effort and low cognitive load. This approach is different from traditional ones because service architecture designers need to consider the tradeoff among several types of incentives when designing a basic architecture. We then extract six insights from our experiences to show that motivating people is the most important factor in designing mobile crowdsourcing service architecture. The design strategies of community-based mobile crowdsourcing services explicitly consider the tradeoff among multiple incentives. This is significantly different from the design in traditional crowdsourcing services because their designers usually consider only a few incentives when designing respective social media. The insights are valuable lessons learned while designing and operating the case studies and are essential to successful design strategies for building future more complex crowdsourcing services.

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Sakamoto, M., Tong, H., Liu, Y., Nakajima, T., Akioka, S. (2014). Designing Incentives for Community-Based Mobile Crowdsourcing Service Architecture. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8645. Springer, Cham. https://doi.org/10.1007/978-3-319-10085-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-10085-2_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10084-5

  • Online ISBN: 978-3-319-10085-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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