Assessing Information Quality In A RFID-Integrated Shelf Replenishment Decision Support System For The Retail Industry

Motivated by the problem of out-of-shelf (OOS) in retail industry and the emergence of RFID (Radio Frequency Identification) technology, this paper investigates the impact that the adoption of RFID has on the quality of information utilized during the shelf replenishment process and consequently on the products’ shelf availability. A RFID-integrated decision support system (DSS) with three alternative implementation scenarios is proposed to enhance the shelf replenishment process. On one hand, the impact of the three alternative solutions on the quality of the DSS information input is examined in terms of accuracy, timeliness and completeness. On the other hand, the effect of the three alternative deployment scenarios of the RFID-integrated DSS on the OOS problem is assessed through measuring the number of OOS occurrences after utilizing the DSS. The quality of the DSS information input and the products’ shelf availability are assessed for each implementation scenario by executing the DSS with input data of test cases. Test cases are generated via the business process modeling used to develop the RFIDintegrated DSS and the respective input data of the DSS during the test cases are based on case studies findings and also real data from the retailer, e.g. point-of-sales data, in order to reflect each possible event during the shelf replenishment process. An example of assessing the impact of RFID technology on the quality of DSS information input is given to present the research approach of executing DSS with input data of test cases. A cost-benefit analysis of the alternative solutions of the RFID-integrated DSS will be conducted to select that solution that provides the DSS with satisfying quality of information input and also improves the products’ shelf availability at an affordable cost. The contribution of this study is reflected on the research approach of using a DSS to assess information quality and executing it with input data of test cases based on real data and case studies.