Information Quality Evaluation of Object Tracking Systems in the Internet of Things: an Analytical Approach Applied in the Supply Chain
PhD Thesis Description
This doctoral research contributes to the Information Systems, Information Quality and Supply Chain Management research fields. It proposes an analytical information quality (iq) evaluation model of object tracking systems in the Internet of Things. An analytical model of the alternative configurations of object tracking systems is developed as a function of specific configuration parameters. Then, based on probability and graph theory, analytical metrics of two dimensions, accuracy and completeness, of information quality of object tracking systems are devised as a function of the system configuration and independently of the system application context. Finally, the effect of the system configuration on the information quality of object tracking systems is empirically tested through experiment on alternative product tracking systems in the retail supply chain. The proposed analytical model may be applied to perform two distinct types of information quality assessment of object tracking systems. On the one hand, during an a priori (or ex ante) evaluation, the model may be employed to assess the IQ requirements of a given monitored context and guide pertinent design decisions. On the other hand, during an a posteriori (or ex post) assessment, the model may be applied to assess the IQ of object tracking systems and identify areas of improvement based on design best practices of other similar system instantiations.
Dr. Cleopatra Bardaki
|Office phone:||+30 2108203663|
|Address:||Evelpidon 47-A & Lefkados 33 Room 907, GR-11362, Athens, Greece|
Dr. Katerina Pramatari