| Summary: | Insufficient datasets due to a lack of data contribution from participants is a longstanding problem for data collection in participatory sensing. Empirical evidence has shown that non-monetary incentives can be a strong motivator to enhance participants' contributions. The purpose of this paper is to examine the influence of non-monetary incentives for data collection in participatory sensing. Sequential explanatory design is employed where the study integrates both quantitative and qualitative data analysis. The study uses a partial least squares structural equation modeling (PLS-SEM) analysis for quantitative data, in which a survey (N=301) of respondents attempted to identify the non-monetary incentives that influence data collection performance. The quantitative findings are further analyzed in the qualitative study using thematic analysis. Quantitative findings show that all four non-monetary incentives significantly influence participatory sensing data collection. A follow-up qualitative study suggests a convergence of the quantitative findings where inverse influence exists between the intrinsic incentives (autonomy and mastery) and the extrinsic incentives (purpose, social) toward data collection performance. Quantitative and qualitative findings show that an intrinsic incentive is more important than an extrinsic one in participatory sensing. This paper contributes to the study of participatory sensing by proposing the non-monetary incentive for participatory sensing (NMIPS) framework for participatory sensing data collection. The use of a sequential explanatory research design in the study demonstrates the ability of the proposed framework, which covers a broad spectrum of non-monetary incentives and is able to explain the contradiction between intrinsic and extrinsic incentives in participatory sensing. Moreover, the framework offers practical contributions for various stakeholders. It aids system developers, campaign organizers, and public health officials by improving incentive design, participant recruitment, and program evaluation. © 2013 IEEE.
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