TY - JOUR
T1 - Applying crowdsourcing techniques in urban planning
T2 - A bibliometric analysis of research and practice prospects
AU - Liao, Pinchao
AU - Wan, Yaolin
AU - Tang, Pingbo
AU - Wu, Chunlin
AU - Hu, Yumeng
AU - Zhang, Sichun
N1 - Funding Information:
This study received financial support from the National Natural Science Foundation of China (Grant Nos. 71801007 , 51878382 and 51578317 ), the MOE ( Ministry of Education of China ) Project of Humanities and Social Sciences (Grant No. 18YJCZH188 ), and the Fundamental Research Funds for the Central Universities . We would like to thank the anonymous reviewers for their invaluable comments on the earlier versions of this article.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11
Y1 - 2019/11
N2 - Urban planning requires more public involvement and larger group participation to achieve scientific and democratic decision making. Crowdsourcing is a novel approach to gathering information, encouraging innovation and facilitating group decision-making. Unfortunately, although previous research has explored the utility of crowdsourcing applied to urban planning theoretically, there are still rare real practices or empirical studies using practical data. This study aims to identify the prospects for implementing crowdsourcing in urban planning through a bibliometric analysis on current research. First, database and keyword lists based on peer-reviewed journal articles were developed. Second, semantic analysis is applied to quantify co-occurrence frequencies of various terms in the articles based on the keyword lists, and in turn a semantic network is built. Then, cluster analysis was conducted to identify major and correlated research topics, and bursting key terms were analyzed and explained chronologically. Lastly, future research and practical trends were discussed. The major contribution of this study is identifying crowdsourcing as a novel urban planning method, which can strengthen government capacities by involving public participation, i.e., turning governments into task givers. Regarding future patterns, the application of crowdsourcing in urban planning is expected to expand to transportation, public health and environmental issues. It is also indicated that the use of crowdsourcing requires governments to adjust urban planning mechanisms.
AB - Urban planning requires more public involvement and larger group participation to achieve scientific and democratic decision making. Crowdsourcing is a novel approach to gathering information, encouraging innovation and facilitating group decision-making. Unfortunately, although previous research has explored the utility of crowdsourcing applied to urban planning theoretically, there are still rare real practices or empirical studies using practical data. This study aims to identify the prospects for implementing crowdsourcing in urban planning through a bibliometric analysis on current research. First, database and keyword lists based on peer-reviewed journal articles were developed. Second, semantic analysis is applied to quantify co-occurrence frequencies of various terms in the articles based on the keyword lists, and in turn a semantic network is built. Then, cluster analysis was conducted to identify major and correlated research topics, and bursting key terms were analyzed and explained chronologically. Lastly, future research and practical trends were discussed. The major contribution of this study is identifying crowdsourcing as a novel urban planning method, which can strengthen government capacities by involving public participation, i.e., turning governments into task givers. Regarding future patterns, the application of crowdsourcing in urban planning is expected to expand to transportation, public health and environmental issues. It is also indicated that the use of crowdsourcing requires governments to adjust urban planning mechanisms.
KW - Bibliometric analysis
KW - Crowdsourcing
KW - Prospects
KW - Semantic network
KW - Urban planning
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U2 - 10.1016/j.cities.2019.05.024
DO - 10.1016/j.cities.2019.05.024
M3 - Article
AN - SCOPUS:85066427087
SN - 0264-2751
VL - 94
SP - 33
EP - 43
JO - Cities
JF - Cities
ER -