A design guideline for non-monetary incentive mechanics in mobile health participatory sensing system
Participatory sensing emphasizes the participation of citizens and community groups in the process of sensing and documenting current events in their local environment using smart phones and mobile devices. Incentive is crucial in participatory sensing data collection to attract participants to join...
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Main Authors: | , , |
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Format: | Article |
Published: |
Research India Publications
2017
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Online Access: | http://eprints.utm.my/id/eprint/76323/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040255212&partnerID=40&md5=0732dcfd9238eefa7fd55d72d8213276 |
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Institution: | Universiti Teknologi Malaysia |
Summary: | Participatory sensing emphasizes the participation of citizens and community groups in the process of sensing and documenting current events in their local environment using smart phones and mobile devices. Incentive is crucial in participatory sensing data collection to attract participants to join in a participatory campaign, and to engage participants to use the participatory sensing application. The challenge in studies on non-monetary incentives is how this type of incentives should be represented in a participatory sensing system because they are inherent to the participants. This study proposes a design guideline which consists of set of mechanics and features associated with each incentive construct based on Self-determination Theory and Motivation 3.0. The design guideline is presented in a hierarchical system structure to illustrate dynamic operation of incentive mechanics with different components in participatory sensing system. Content analysis is performed on 283 mobile health monitoring application in the market to determine the reliability of the proposed incentive mechanic and features through descriptive analysis and inter-coder reliability analysis. The findings of the descriptive analysis show that a relatively small proportion of the mobile application (15 percent), addressed at least one feature that tapped on each of the incentive mechanics, and almost all apps contain a minimum of one intrinsic incentive mechanic feature. The findings obtained from inter-coder reliability analysis found 56 percent of the proposed incentive mechanic features with low reliability. Furthermore, the finding shows insignificant reliability degree for almost all extrinsic features. This study provides both theoretical, and practical contributions. On the theoretical aspect, this study provides validation on the incentive mechanics and their features that have been proposed in the design guideline. On the practical aspect, the design guideline may aid system developers and service providers to implement the incentive concepts into systems’ features and further help campaign organizers and service providers to focus on the best incentives strategy for improving participants’ performance in the next participant recruitment. |
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