A predictive model for citizens’ utilization of open government data portals

Di Wang; Deborah Richards; Ayse Aysin Bilgin; Chuanfu Chen

doi:10.1007/978-3-030-64452-9_14

A predictive model for citizens’ utilization of open government data portals

Di Wang^*, Deborah Richards, Ayse Aysin Bilgin, Chuanfu Chen

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

Abstract

Open government data (OGD) initiatives for building OGD portals have not yet delivered the expected benefits of OGD to the whole of society. Although citizens’ reluctance to use OGD has become a key problem in the present OGD development, limited studies have been carried out to investigate citizens’ actual usage of OGD and OGD portals. In order to fill this research gap, this study primarily focuses on predicting citizens’ actual utilization of OGD portals. To find features influencing citizens’ utilization of OGD portals and to predict their actual usage of OGD portals, an experiment was designed and carried out in China. A predictive model was built with C5.0 algorithm based on data collected through the experiment, with a predictive accuracy rate of 84.81%. Citizens’ monthly income, the compatibility of OGD portals, and citizens’ attentiveness regarding their interactions with OGD portals are found to be the most important factors influencing citizens’ actual utilization of OGD portals. Positive effects of compatibility, attentiveness, and perceived usefulness on citizens’ usage of OGD portals are noticed.

Original language	English
Title of host publication	Digital Libraries at Times of Massive Societal Transition
Subtitle of host publication	22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings
Editors	Emi Ishita, Natalie Lee Pang, Lihong Zhou
Place of Publication	Cham, Switzerland
Publisher	Springer, Springer Nature
Pages	159-175
Number of pages	17
ISBN (Electronic)	9783030644529
ISBN (Print)	9783030644512
DOIs	https://doi.org/10.1007/978-3-030-64452-9_14
Publication status	Published - 2020
Event	22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020 - Kyoto, Japan Duration: 30 Nov 2020 → 1 Dec 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12504 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020
Country	Japan
City	Kyoto
Period	30/11/20 → 1/12/20

Keywords

Open data utilization
Open government data portal
Predictive model

Access to Document

10.1007/978-3-030-64452-9_14

Link to publication in Scopus

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Wang, D., Richards, D., Bilgin, A. A., & Chen, C. (2020). A predictive model for citizens’ utilization of open government data portals. In E. Ishita, N. L. Pang, & L. Zhou (Eds.), Digital Libraries at Times of Massive Societal Transition: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings (pp. 159-175). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12504 LNCS). Cham, Switzerland: Springer, Springer Nature. https://doi.org/10.1007/978-3-030-64452-9_14

Wang, Di ; Richards, Deborah ; Bilgin, Ayse Aysin ; Chen, Chuanfu. / A predictive model for citizens’ utilization of open government data portals. Digital Libraries at Times of Massive Societal Transition: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. editor / Emi Ishita ; Natalie Lee Pang ; Lihong Zhou. Cham, Switzerland : Springer, Springer Nature, 2020. pp. 159-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Open government data (OGD) initiatives for building OGD portals have not yet delivered the expected benefits of OGD to the whole of society. Although citizens’ reluctance to use OGD has become a key problem in the present OGD development, limited studies have been carried out to investigate citizens’ actual usage of OGD and OGD portals. In order to fill this research gap, this study primarily focuses on predicting citizens’ actual utilization of OGD portals. To find features influencing citizens’ utilization of OGD portals and to predict their actual usage of OGD portals, an experiment was designed and carried out in China. A predictive model was built with C5.0 algorithm based on data collected through the experiment, with a predictive accuracy rate of 84.81{\%}. Citizens’ monthly income, the compatibility of OGD portals, and citizens’ attentiveness regarding their interactions with OGD portals are found to be the most important factors influencing citizens’ actual utilization of OGD portals. Positive effects of compatibility, attentiveness, and perceived usefulness on citizens’ usage of OGD portals are noticed.",

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author = "Di Wang and Deborah Richards and Bilgin, {Ayse Aysin} and Chuanfu Chen",

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Wang, D, Richards, D , Bilgin, AA & Chen, C 2020, A predictive model for citizens’ utilization of open government data portals. in E Ishita, NL Pang & L Zhou (eds), Digital Libraries at Times of Massive Societal Transition: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12504 LNCS, Springer, Springer Nature, Cham, Switzerland, pp. 159-175, 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Kyoto, Japan, 30/11/20. https://doi.org/10.1007/978-3-030-64452-9_14

A predictive model for citizens’ utilization of open government data portals. / Wang, Di; Richards, Deborah ; Bilgin, Ayse Aysin; Chen, Chuanfu.

Digital Libraries at Times of Massive Societal Transition: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. ed. / Emi Ishita; Natalie Lee Pang; Lihong Zhou. Cham, Switzerland : Springer, Springer Nature, 2020. p. 159-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12504 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

TY - GEN

T1 - A predictive model for citizens’ utilization of open government data portals

AU - Wang, Di

AU - Richards, Deborah

AU - Bilgin, Ayse Aysin

AU - Chen, Chuanfu

PY - 2020

Y1 - 2020

N2 - Open government data (OGD) initiatives for building OGD portals have not yet delivered the expected benefits of OGD to the whole of society. Although citizens’ reluctance to use OGD has become a key problem in the present OGD development, limited studies have been carried out to investigate citizens’ actual usage of OGD and OGD portals. In order to fill this research gap, this study primarily focuses on predicting citizens’ actual utilization of OGD portals. To find features influencing citizens’ utilization of OGD portals and to predict their actual usage of OGD portals, an experiment was designed and carried out in China. A predictive model was built with C5.0 algorithm based on data collected through the experiment, with a predictive accuracy rate of 84.81%. Citizens’ monthly income, the compatibility of OGD portals, and citizens’ attentiveness regarding their interactions with OGD portals are found to be the most important factors influencing citizens’ actual utilization of OGD portals. Positive effects of compatibility, attentiveness, and perceived usefulness on citizens’ usage of OGD portals are noticed.

AB - Open government data (OGD) initiatives for building OGD portals have not yet delivered the expected benefits of OGD to the whole of society. Although citizens’ reluctance to use OGD has become a key problem in the present OGD development, limited studies have been carried out to investigate citizens’ actual usage of OGD and OGD portals. In order to fill this research gap, this study primarily focuses on predicting citizens’ actual utilization of OGD portals. To find features influencing citizens’ utilization of OGD portals and to predict their actual usage of OGD portals, an experiment was designed and carried out in China. A predictive model was built with C5.0 algorithm based on data collected through the experiment, with a predictive accuracy rate of 84.81%. Citizens’ monthly income, the compatibility of OGD portals, and citizens’ attentiveness regarding their interactions with OGD portals are found to be the most important factors influencing citizens’ actual utilization of OGD portals. Positive effects of compatibility, attentiveness, and perceived usefulness on citizens’ usage of OGD portals are noticed.

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KW - Open government data portal

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DO - 10.1007/978-3-030-64452-9_14

M3 - Conference proceeding contribution

SN - 9783030644512

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 159

EP - 175

BT - Digital Libraries at Times of Massive Societal Transition

A2 - Ishita, Emi

A2 - Pang, Natalie Lee

A2 - Zhou, Lihong

PB - Springer, Springer Nature

CY - Cham, Switzerland

ER -

Wang D, Richards D , Bilgin AA, Chen C. A predictive model for citizens’ utilization of open government data portals. In Ishita E, Pang NL, Zhou L, editors, Digital Libraries at Times of Massive Societal Transition: 22nd International Conference on Asia-Pacific Digital Libraries, ICADL 2020, Proceedings. Cham, Switzerland: Springer, Springer Nature. 2020. p. 159-175. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-64452-9_14