Original Research

Incentive theory for a participatory crowdsourcing project in a developing country

Elizabeth Bosha, Liezel Cilliers, Stephen Flowerday
SA Journal of Information Management | Vol 19, No 1 | a739 | DOI: https://doi.org/10.4102/sajim.v19i1.739 | © 2017 Elizabeth Bosha, Liezel Cilliers, Stephen Flowerday | This work is licensed under CC Attribution 4.0
Submitted: 10 February 2016 | Published: 23 January 2017

About the author(s)

Elizabeth Bosha, Department of Information Systems, University of Fort Hare, South Africa
Liezel Cilliers, Department of Information Systems, University of Fort Hare, South Africa
Stephen Flowerday, Department of Information Systems, University of Fort Hare, South Africa


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Abstract

Background: Urbanisation has put enormous strain on the limited resources and services provided by city management. This means that the city must find new ways to manage their resources more effectively. One option is to collect data in a smart city from the citizens in order to make better decisions about resource management.

Objectives: The aim of this study was to provide a participatory crowdsourcing incentive model that can be used by the city of East London, South Africa, to collect information continuously from citizens in order to improve public safety in the city.

Method: This study made use of a quantitative approach to gather and analyse data. Data were collected using a questionnaire sent to all 91 East London citizens who had registered on the project website. The response rate was 81.3%.

Results: A model was proposed that can be used by the city to increase the participation rate of citizens in smart city projects. Three factors: intrinsic, internalised-extrinsic and extrinsic, were identified as central to the incentive model.

Conclusion: The recommendation of the study is that city management can use the crowdsourcing participatory incentive model to ensure citizen participation in smart city projects.


Keywords

smart city; participatory crowdsourcing; incentive theory; public safety

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Crossref Citations

1. A survey of incentive engineering for crowdsourcing
Conor Muldoon, Michael J. O’Grady, Gregory M. P. O’Hare
The Knowledge Engineering Review  vol: 33  year: 2018  
doi: 10.1017/S0269888918000061