Impact of RFID technology on supply chain decisions with inventory inaccuracies
Introduction
The Internet of Things (IoT) was first coined by MIT in the late 1990s, which refers to a ‘devices or sensors connected world’ where objects are connected, monitored, and optimized through either wired, wireless, or hybrid systems. Thus, the real world things are connected and integrated virtually and seamlessly by information technology that the real world can be more accessible when necessary (Atzori et al., 2010, Uckelmann et al., 2011). IoT has become particularly popular through some potential representatively applications such as telemedicine monitoring, and smart electric meter reading, especially in supply chain management.
Radio frequency identification (RFID) is a widely-used key technology that is regarded as a prerequisite or essential element in the IoT. It mainly consists of three elements: a tag formed by a chip connected with an antenna; a reader that emits radio signals and receives in return answers from tags; and a middleware that bridges RFID hardware and enterprise applications (Ngai et al., 2008, Sarac et al., 2010). Using radio waves, RFID technologies communicate in real time with numerous objects at a distance without any contact. This automatic identification and data capture technology can improve the product traceability and the visibility among supply chains, and it has been publicized as a promising solution to inventory inaccuracies. Therefore, it has been paid more and more attention by researchers as well as practitioners (Kok, 2008; Rekik and Sahin, 2009; Ngai et al., 2008).
Inventory inaccuracy is inevitable and prevalent in many industries, which stands for the discrepancy between inventory records and the amount of product available for sale to customers. Dehoratius and Raman (2008) examined nearly 370,000 inventory records from 37 stores of a large public retailer with annual sales of approximately $10 billion, and they found that 65% of the records were inaccurate. Kok and Shang (2007) examined a large distribution company with an average inventory of $3 billion and found that its records were inaccurate by 1.6% of the total inventory value at the end of 2004.
Where do these inventory inaccuracies arise from? Two main sources exist, namely inventory misplacement and inventory shrinkage. Inventory shrinkage (due to theft and damage) leads to permanent inventory loss, while misplacement is temporary that the inventory can be recovered by physical audit (Atali et al., 2004, Atali et al., 2006). Additionally, transaction errors could also cause inventory inaccuracies, but they affect only the inventory record, leaving the actual inventory unchanged (Rekik and Sahin, 2009).
Because inventory inaccuracy exists, retailers should increase their inventory level to buffer the added uncertainty, otherwise sales may be lost due to stock-outs (Raman et al., 2001, Dehoratius et al., 2008). It has been estimated that inventory inaccuracy results in lost sales and inventory costs, which reduces profits by more than 10% (Raman et al., 2001; Heese, 2007). Thus, this problem has heavily effected on supply chain performance. In this paper, we focus on the impact of inventory misplacement and shrinkage, and analyze the effectiveness of applying RFID technology in the IoT when the retail supply chain encounters both inaccuracies.
Since RFID adoption may eliminate or reduce inventory inaccuracies in the supply chain, several retail chains have strongly mandated their suppliers to adopt RFID. Wal-Mart implemented an RFID-based pallet-level and case-level tracking system by early 2005, and it required its top 100 suppliers to supply their products with RFID tags on cases and pallets.1 Other big retailers, such as Tesco and Metro, have followed suit.
Although RFID technology in the IoT has been verified to enable substantial efficiency gains at different stages of a supply chain, the associated costs are by no means negligible (Gaukler et al., 2007). In addition to variable tag costs, RFID adopters also must consider the upfront costs for deploying the new technology in the supply chain (Kambil and Brooks, 2002). For example, a typical consumer packaged goods manufacturer was estimated to spend between $13 million and $23 million on RFID, including fixed costs and variable costs, for shipping 50 million cases per year (Asif and Mandviwalla, 2005). As a result, the substantial cost of RFID in the IoT seems to prohibit widespread use at the item level. Therefore, the cost of RFID adoption will heavily affect supply chain decisions (Kearney, 2003, Thomas, 2004).
Motivated by the issue of RFID technology adoption, we jointly study inventory shrinkage and misplacement in both centralized and decentralized supply chains based on the Newsvendor model, in which the threshold values of fixed investment cost, tag price and shrinkage recovery rate are determined separately to identify the ordering policies and revenue. In a decentralized supply chain, the effect of RFID adoption on supply chain decisions is analyzed with a wholesale price contract between supply chain partners. It is intriguing to find that the retailer’s revenue is much more dependent on both RFID fixed investment cost and tag price than that of the supplier, though RFID technology can benefit the supply chain partners. The main reason is that the manufacturer is the Stackelberg leader, who determines the wholesale price, while the retailer is the follower, who accepts the price and determines only the order quantity. Therefore, if the cost of RFID is not shared appropriately between the supplier and the retailer, the supply chain will perform badly even with a coordinated contract.
The remainder of this paper is organized as follows. In Section 2, we provide a brief literature review of the related research. In Section 3, we study the effect of RFID adoption on a centralized supply chain where the manufacturer and the retailer are taken as an entity. In Section 4, we consider the effect of RFID adoption on a decentralized supply chain consisting of one retailer and one manufacturer. In Section 5, we conclude our paper and point out further research directions.
Section snippets
Literature review
Generally, our work is related to three streams of research: inventory inaccuracy, RFID application and coping with supply chain problems by means of RFID technology.
The first stream is inventory inaccuracy in a retail supply chain, which is widely discussed (Fleisch and Tellkamp, 2005, Thiel et al., 2010). Classic inventory models are based mainly on the assumption of accurate inventory information however, inventory inaccuracies are inevitable. Rekik (2011) provided a general framework to
The centralized supply chain model
In this paper, we examine a single product with seasonal demand variations. We study a supply chain with inventory inaccuracies, containing both shrinkage and misplacement. In this section, we focus on a centralized supply chain to investigate the optimal inventory control policy; the next section is devoted to decisions in a decentralized supply chain.
The decentralized supply chain model
In a decentralized supply chain, individual partners along the chain can make their own decisions aimed at maximizing respective profits. In this section, we consider the decentralized supply chain with inventory inaccuracies. First, we characterize the supply chain partners’ decisions on optimal order quantities and wholesale prices in both the non-RFID and RFID cases. Wholesale price contract is applied, as it is the most simple and widely-used pricing scheme between supply chain partners.
Conclusions
In this paper, we focus on how supply chain decisions are influenced by applying RFID technology to reduce the inefficiency of inventory inaccuracies in the era of IoT. Misplacement and shrinkage are jointly considered in both centralized and decentralized supply chains, consisting of one retailer and one manufacturer and selling one product in a single season. To investigate the impact of RFID technology on the supply chain analytically and specifically, the demand is assumed to be uniformly
Acknowledgments
The authors wish to acknowledge the helpful comments provided by anonymous referees. This work was supported by the National Natural Science Foundation of China (71431004, 71171082, 71201059 and 71001039), Program for New Century Excellent Talents in University (NCET-11-0637), and the Fundamental Research Funds for the Central Universities.
References (35)
- et al.
The internet of things: a survey
Comput. Networks
(2010) - et al.
RFID-enabled shelf replenishment with backroom monitoring in retail stores
Decis. Support Syst.
(2012) - et al.
Analysis of reducing inventory shrinkage with RFID technology
Int. J. Prod. Econ.
(2014) - et al.
Inventory inaccuracies and supply chain performance: a simulation study of a retail supply chain
Int. J. Prod. Econ.
(2005) An investment evaluation of supply chain RFID technologies: a normative modeling approach
Int. J. Prod. Econ.
(2010)- et al.
The impact of false-negative reads on the performance of RFID-based shelf inventory control policies
Comput. Oper. Res.
(2013) - et al.
RFID in the warehouse: a literature analysis (1995–2010) of its applications, benefits, challenges and future trends
Int. J. Prod. Econ.
(2013) - et al.
RFID research: an academic literature review (1995–2005) and future research directions
Int. J. Prod. Econ.
(2008) - et al.
Implementing an RFID-based manufacturing process management system: lessons learned and success factors
J. Eng. Technol. Manage.
(2012) - et al.
Inventory inaccuracies in retail stores due to theft: an analysis of the benefits of RFID
Int. J. Prod. Econ.
(2009)
Analysis of impact of RFID on reducing product misplacement errors at retail stores
Int. J. Prod. Econ.
Inventory inaccuracies in the whole sale supply chain
Int. J. Prod. Econ.
Assessing the impact of inventory inaccuracies within a Newsvendor framework
Eur. J. Oper. Res.
A literature review on the impact of RFID technologies on supply chain management
Int. J. Prod. Econ.
Impact of inventory inaccuracies on service-level quality in (Q,R) continuous-review lost-sales inventory models
Int. J. Prod. Econ.
RFID and operations management: technology, value, and incentives
Prod. Oper. Manage.
Integrating the supply chain with RFID: a technical and business analysis
Commun. Assoc. Inf. Syst.
Cited by (147)
Enhancing innovativeness and performance of the manufacturing supply chain through datafication: The role of resilience
2024, Computers and Industrial EngineeringEffect of service factors and buy-online-pick-up-in-store strategies through an omnichannel system under an agricultural supply chain management
2023, Electronic Commerce Research and ApplicationsIs RFID adoption a double-edged sword? The impacts of a capital-constrained manufacturer
2023, Computers and Industrial EngineeringRFID adoption strategy in a retailer-dominant supply chain with competing suppliers
2022, European Journal of Operational ResearchCitation Excerpt :This is referred to as ‘a retailer-dominant supply chain’, and such supply chains have been widely discussed because of the increasing prevalence of retail giants (Cachon & Kok, 2010; Xiao, Choi & Cheng, 2014). Despite their dominance, retailers are still plagued by a very difficult problem: inventory inaccuracies, i.e., discrepancies between the quantity of products available in warehouses and the records in the inventory management system (Fan, Tao, Deng & Li, 2015). Since many key operations, such as ordering, replenishing and forecasting, are premised on having correct inventory records, it is important and beneficial for firms to ensure that such records are accurate (Hardgrave, Aloysius & Goyal, 2013; Çakıcı, 2020).
Identifying and analyzing the barriers of Internet-of-Things in sustainable supply chain through newly proposed spherical fuzzy geometric mean
2022, Computers and Industrial Engineering