Start Date
12-18-2013
Description
Object tracking systems track moving objects between locations and provide object positioning information. Such systems rely on tracking technologies e.g. Radio Frequency Identification (RFID). The challenge is how to ensure an adequate quality of information at a moderate infrastructure cost. We propose a framework that evaluates information quality (IQ) of object tracking systems, with respect to information completeness and accuracy. The framework models all the alternative configurations of an object tracking system and proposes quantitative metrics of accuracy and completeness as functions of the system configuration. Ultimately, it calculates IQ per configuration and employs the Crisp-Set Qualitative Comparative Analysis (CS/QCA) method to pinpoint specific design solutions that achieve high IQ. The framework is technology- and application environment-independent and may be employed for both ex-post and ex-ante IQ evaluation of object tracking systems. The framework is illustrated through the IQ assessment of a product tracking system in a retail supply chain.
Recommended Citation
Bardaki, Cleopatra; Kourouthanassis, Panos; Pramatari, Katerina; and Doukidis, Georgios, "An Information Quality Evaluation Framework of Object Tracking Systems" (2013). ICIS 2013 Proceedings. 3.
https://aisel.aisnet.org/icis2013/proceedings/ProjectManagement/3
An Information Quality Evaluation Framework of Object Tracking Systems
Object tracking systems track moving objects between locations and provide object positioning information. Such systems rely on tracking technologies e.g. Radio Frequency Identification (RFID). The challenge is how to ensure an adequate quality of information at a moderate infrastructure cost. We propose a framework that evaluates information quality (IQ) of object tracking systems, with respect to information completeness and accuracy. The framework models all the alternative configurations of an object tracking system and proposes quantitative metrics of accuracy and completeness as functions of the system configuration. Ultimately, it calculates IQ per configuration and employs the Crisp-Set Qualitative Comparative Analysis (CS/QCA) method to pinpoint specific design solutions that achieve high IQ. The framework is technology- and application environment-independent and may be employed for both ex-post and ex-ante IQ evaluation of object tracking systems. The framework is illustrated through the IQ assessment of a product tracking system in a retail supply chain.