The Cost–Benefit Models for RFID Investments

Abstract

RFID technology does not require line of sight and provides fast and accurate reading from a great distance without human intervention. Albeit RFID is superior to other identification systems, such as barcode, complicated cost and benefit structure inhibits worldwide adoption. As a response, there is a wide range of cost–benefit models used by both industry and academy. The aim of this chapter is to review RFID cost and benefit factors and provide a comprehensive overview of RFID cost–benefit models. Besides hardware and middleware cost, service cost factors, including compliance cost, training cost, and transition cost makes up for the total RFID system cost structure. Benefit factors are more complex than cost factors as the limited pilot studies or studies from other application areas are unable to reveal the full set of benefits. Also, intangible benefit factors such as increased customer satisfaction or increased supply chain collaboration are not easily quantifiable. RFID cost–benefit models are classified as conventional models, uncertainty-based models, and decision-making models. Conventional models include return on investment models, break-even models, internal rate of return and net present value analysis. Although practical enough to help during the initial stages of investment analysis, these models are static, rely on oversimplifying assumptions, and ignore the variability of the system. Uncertainty-based models, such as simulation or real options models generate more accurate results, but require extensive modeling and data gathering effort. Decision-making models, on the other hand, facilitate selection among alternatives or help to visualize the underlying structure of decision-making process of RFID investment. Considering the limitations of each model, analysts should take caution when introducing a single type of model and rather utilize a group of different models together.