m-Government Security Response System: Predicting Citizens’ Adoption Behavior

ABSTRACT

The participation of mobile technology could be a massive development to ensure the citizen’s safety by linking various government agencies under the umbrella of the m-government (m-govt) security response system (SRS). Based on the novel phenomenon of m-govt SRS, this research provides a comprehensive theoretical model to discover citizens’ adoption intention. Our findings proved that transparency and trust mediate the influence of information quality characteristics and channel characteristics, while perceived usefulness mediate the influence of awareness on citizens’ intentions to use; which reduce uncertainty and enhance citizens’ willingness to adopt the m-govt SRS. This study proved that perceived response time is a key construct in the context of providing m-govt SRS to enhance citizens’ intention to use. The outcomes make a noteworthy contribution to theoretical literature and having practical implications regarding understanding various aspects of m-govt SRS adoption among citizens, which provide the broadest view to government agencies for successful implementation of these services.

List of abbreviations

Acronym	=	Details
OBOR	=	One belt, one road
CPEC	=	China-Pakistan Economic Corridor
ETIM	=	East Turkestan Islamic Movement
SSD	=	Special Security Division
STF	=	Security Task Force
AIIB	=	Asian infrastructure investment bank
e-govt	=	Electronic government
m-govt	=	Mobile government
ICT	=	Information communication technology
SRS	=	Security Response System
PDA	=	Personal digital assistant
MoU	=	Memorandum of understanding
GAM	=	eGovernment Adoption Model
URT	=	Uncertainty reduction theory
TAM	=	Technology acceptance model
UTAUT	=	Unified Theory of Acceptance and Use of Technology
AW	=	Awareness
PC	=	Perceived Compatibility
PU	=	Perceived usefulness
AR	=	Availability of resources
AC	=	Accuracy
Comp	=	Completeness
Trans	=	Transparency
T	=	Trust
Conv	=	Convenience
P	=	Personalization
PRT	=	Perceived response time
ITU	=	Intention to use
EFA	=	Exploratory factor analysis
CFA	=	Confirmatory factor analysis
CR	=	Composite reliability
AVE	=	Average variance extracted
PCA	=	Principal component analysis

Additional information

Notes on contributors

Fakhar Shahzad

Fakhar Shahzad is a doctoral student at the School of Economics & Management, Harbin University of Science and Technology, China. His current research interest relates to the fields of diffusion of the information system, human-computer interaction, and social media research. He has published work in international academic journals (Technology in Society, International Journal of Commerce, and Management).

GuoYi Xiu

GuoYi Xiu is a Professor and Ph.D. Director of School of Economics and Management, Harbin University of Science and Technology, China. He is also working as Vice President of Heilongjiang Provincial Economics Association, Vice President of Heilongjiang Management Institute and Senior Member of China Technology Economy Research Association. His research area represents an information system adoption, management innovation and engineering, and virtual enterprise system management.

Imran Khan

Imran Khan is Lecturer at Department of Management Sciences, The Islamia University of Bahawalpur, Pakistan. He attained his Ph.D. from the School of Management, Harbin Institute of Technology, China. His research interests include the social media marketing, digital consumer behavior, information system and e-health. His work has appeared in ASLIB Journal of Information Management, Journal of Global Information Technology Management and presented at International Conference on Complex Information Systems (COMPLEXIS).

Jian Wang

Jian Wang is a doctoral student at the School of Economics & Management, Harbin University of Science and Technology, China. Her current research area is technological innovation and diffusion, e-commerce, and information system adoption. She has published work in Technology in Society.