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How Citizen Demand Affects the Process of M-Government Adoption: An Empirical Study in China

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Abstract

Mobile government applications have been increasingly adopted by governments around the world, but their use by targeted clients is lower than expected and under-examined in the literature. We conceptualize citizen adoption of m-government as a dynamic process composed of three interrelated stages—awareness, current use, and future use. However, we suggest that citizen demand will affect them differently. To test this, we used recent survey data from a Chinese city to examine the antecedents of citizen adoption of an m-government application, a traffic APP. The results reveal that citizens’ commuting demands significantly affected their awareness of the APP, but did not impact their current and planned future uses, which were primarily affected by citizens’ perceptions and habits. These findings help open up the “black box” of citizen adoption, and generate policy suggestions for boosting citizen use, of m-government.

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Acknowledgement

We thank the editor and two anonymous reviewers for helpful comments and suggestions. Financial support is from the National Natural Science Foundation of China (NSFC) (No.: 71774164). The correspondence should go to Liang Ma at liangma@ruc.edu.cn.

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Authors and Affiliations

  1. Center for Chinese Public Administration Research, School of Government, Sun Yat-sen University, Guangzhou, China

    Yueping Zheng

  2. School of Public Administration and Policy, Renmin University of China, Qiushi Building, 59 Zhongguancun Avenue, Beijing, China

    Liang Ma

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Appendix

Appendix

The ordered logistic regression model estimates

Variables

Awareness

Current Use

Future Use

 

Coef

SE

Coef

SE

Coef

SE

Independent variables

      

Commuting frequency

0.10*

0.06

0.60***

0.12

0.20

0.12

Commuting distance

0.16**

0.08

0.10

0.12

−0.10

0.14

Commuting complexity

0.28***

0.06

0.08

0.10

0.12

0.10

Commuting mode (public transportation)

0.67***

0.18

1.31***

0.31

−0.38

0.33

Peak-hour commuting

0.39***

0.15

0.38

0.25

0.47*

0.28

Perceived congestion

0.11*

0.06

0.09

0.10

0.09

0.11

Parking needs

−0.02

0.06

−0.09

0.10

−0.07

0.11

Control variables

      

Awareness

  

0.87***

0.15

0.14

0.16

Current use

    

0.63***

0.16

Usability

  

0.35*

0.19

0.52**

0.21

Trust

  

−0.32*

0.17

0.31*

0.18

Perceived advantage

  

0.24

0.16

0.50***

0.18

Satisfaction

  

−0.04

0.20

0.93***

0.21

Perceived usefulness

  

0.56**

0.20

1.07***

0.22

ICT use frequency

0.01

0.08

−0.12

0.14

−0.20

0.15

ICT use skills

0.34***

0.10

0.00

0.17

0.10

0.18

New technology acceptance

0.20**

0.08

−0.01

0.15

0.21

0.15

Education

0.04

0.11

0.24

0.20

−0.20

0.21

Income

0.00

0.08

0.11

0.14

0.04

0.16

Occupation (public sectors)

0.12

0.17

−0.08

0.26

0.45

0.28

Gender (male)

−0.41**

0.15

−0.31

0.24

−0.08

0.26

Age

−0.14

0.09

0.08

0.15

0.06

0.16

Location (downtown)

0.15

0.15

−0.13

0.24

−0.11

0.27

Pseudo R-squared

0.1035

0.2110

0.3311

  1. *p < 0.1, **p < 0.05, ***p < 0.01

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Zheng, Y., Ma, L. How Citizen Demand Affects the Process of M-Government Adoption: An Empirical Study in China. Electron Commer Res 22, 1407–1433 (2022). https://doi.org/10.1007/s10660-021-09470-3

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