Epidemiological Information Systems

2008 ◽  
pp. 235-248
Author(s):  
V. Gómez-Rubio ◽  
J. Ferrándiz-Ferragud ◽  
A. López-Quílez
Keyword(s):  
Information Systems ◽  
Epidemiological Information

Scientific and technical review: Epidemiological information systems

1992 ◽  
Vol 32 (1) ◽  
pp. 96-99
Author(s):  
P. Cowen
Keyword(s):  
Information Systems ◽  
Technical Review ◽  
Epidemiological Information

Epidemiological information systems

1992 ◽  
Vol 22 (2) ◽  
pp. 255
Author(s):  
R.W. Sutherst
Keyword(s):  
Information Systems ◽  
Epidemiological Information

Epidemiological Information Systems

1992 ◽  
Vol 23 (1) ◽  
pp. 108
Author(s):  
M.J. Delany
Keyword(s):  
Information Systems ◽  
Epidemiological Information

Epidemiological information systems

1991 ◽  
Vol 23 (4) ◽  
pp. 232-232
Author(s):  
Michael Thrusfield
Keyword(s):  
Information Systems ◽  
Epidemiological Information

Geographical Information Systems in Archaeology

2006 ◽  
Author(s):  
James Conolly ◽  
Mark Lake
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Geographical Information

Cost Containment in Information Systems

1984 ◽  
Vol 1 (1) ◽  
pp. 175-185
Author(s):  
Michael E. D. Koenig
Keyword(s):  
Information Systems ◽  
Cost Containment

Business-Function Productivity and Information Systems

1988 ◽  
Vol 6 (1) ◽  
pp. 49-61
Author(s):  
Hirohide Hinomoto
Keyword(s):  
Information Systems ◽  
Business Function

Trust in Management Information Systems (MIS)

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel
Keyword(s):  
Information Systems ◽  
Information Overload ◽  
Management Information Systems ◽  
Empirical Work ◽  
Future Research ◽  
Management Information ◽  
Trust In Management ◽  
Actual Use ◽  
Trust In Technology ◽  
The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

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