Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design

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 pape...

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Published in:IEEE Access
Main Author: Anawar S.; Adnan W.A.W.
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204185024&doi=10.1109%2fACCESS.2024.3459000&partnerID=40&md5=56596ecd67fa25436758d3d6cf4677bc
id 2-s2.0-85204185024
spelling 2-s2.0-85204185024
Anawar S.; Adnan W.A.W.
Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
2024
IEEE Access


10.1109/ACCESS.2024.3459000
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204185024&doi=10.1109%2fACCESS.2024.3459000&partnerID=40&md5=56596ecd67fa25436758d3d6cf4677bc
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.
Institute of Electrical and Electronics Engineers Inc.
21693536
English
Article
All Open Access; Gold Open Access
author Anawar S.; Adnan W.A.W.
spellingShingle Anawar S.; Adnan W.A.W.
Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
author_facet Anawar S.; Adnan W.A.W.
author_sort Anawar S.; Adnan W.A.W.
title Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
title_short Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
title_full Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
title_fullStr Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
title_full_unstemmed Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
title_sort Non-monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design
publishDate 2024
container_title IEEE Access
container_volume
container_issue
doi_str_mv 10.1109/ACCESS.2024.3459000
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204185024&doi=10.1109%2fACCESS.2024.3459000&partnerID=40&md5=56596ecd67fa25436758d3d6cf4677bc
description 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.
publisher Institute of Electrical and Electronics Engineers Inc.
issn 21693536
language English
format Article
accesstype All Open Access; Gold Open Access
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