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Perceived as an antidote to poor execution, interest in radio frequency identification (RFID)-enabled visibility has grown. The purpose of this paper is to examine whether and how RFID-enabled visibility with item-level tagging improves store execution.

The authors conducted three field-based experiments in collaboration with two Fortune 500 retailers.

RFID-enabled visibility resulted in a sizable decrease in inventory record inaccuracy and out-of-stocks for inventory held in both the backroom and on the sales floor. The decrease in inventory record inaccuracy and out-of-stocks was even greater among products stored primarily on the sales floor suggesting the benefits from increased visibility accrue to sales floor inventory management processes. In contrast, the authors found no significant improvement in inventory record inaccuracy and no substantive improvement in out-of-stocks among products stored primarily in the backroom suggesting that increased visibility does not improve backroom management processes.

The authors recommend retailers focus on sales floor inventory management when seeking to improve store execution through the adoption of RFID-enabled visibility. In the context, only partial evidence exists that backroom inventory management improves with RFID-enabled visibility.

Retailers seeking to invest in RFID technology must estimate potential performance improvements before making firm-specific cost-benefit analyses. They must also understand where and how these performance improvements will accrue. This research uniquely presents the results of a three field experiments that quantify the changes in retail execution associated with RFID adoption.

Information distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.

A simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.

The bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.

Information sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.

Colored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

The purpose of this paper is to explore the effect of inventory record inaccuracy due to behavioral aspects of workers on the order and inventory variance amplification.

The authors adopt a continuous-time analytical approach to describe the effect of inbound throughput on the inventory and order variance amplification due to the workload pressure and arousal of workers. The model is numerically solved through simulation and results are analyzed with statistical general linear model.

Inventory management policies that usually dampen variance amplification are not effective when inaccuracy is generated due to workers’ behavioral aspects. Specifically, the psychological sensitivity and stability of workers to deal with a given range of operational conditions have a combined and multiplying effect over the amplification of order and inventory variance generated by her/his errors.

The main limitation of the research is that the authors model workers’ behavior by inheriting a well-known theory from psychology that assumes a U-shaped relationship between stress and errors. The authors do not validate this relationship in the specific context of inventory operations.

The paper gives suggestions for managers who are responsible for designing order and inventory policies on how to take into account workers’ behavioral reaction to work pressure.

The logistics management literature does not lack of research works on behavioral decision-making causes of order and inventory variance amplification. Contrarily, this paper investigates a new kind of behavioral issue, namely, the impact of psycho-behavioral aspects of workers on variance amplification.

This research aims to consider the impact of common inventory system inaccuracies that occur in retail outlets on the inventory levels, fill rate, and service level of those outlets by simulating daily customer demand and random error in the inventory system.

The simulation experiments vary the amount of inventory system error, the frequency of inventory record error correction, the size of the daily demand, the number of days in the replenishment system's review interval, and the replenishment system's customer service level.

Inventory system error and the frequency with which the error is corrected are statistically significant for fill rate and service level. Thus, inaccuracies in inventory levels affect a retail outlet's ability to service its customers, though at the single SKU level, the results do not indicate a practical impact due to countervailing effects.

Retail outlets must be aware that error exists and can influence the behavior of their replenishment systems, but the overall impact may not be as significant as it might appear.

This research extends prior work on the effects of inventory inaccuracies and clarifies the debate pertaining to their ultimate effects on retail performance outcomes.

The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

This paper aims to explore the impact of inventory system inaccuracies on the benefits of collaborative supply chain practices under various supply chain scenarios. To achieve this purpose, two popular collaboration initiatives are considered in a four‐stage supply chain. The first practice is a vendor managed inventory program where the distributor takes the full responsibility of managing the retailer's inventory. The second practice is a collaborative planning, forecasting, and replenishment program where all members work together to plan, forecast, and replenish the product.

The study utilizes Monte Carlo computer simulation in an experimental design.

The analysis suggests that while the inaccurate inventory records result in significant performance reductions for all supply chain configurations, their impact is substantially greater for the supply chains where members collaborate more closely on key supply chain management activities. In addition, the author also realize that the adverse impact of inaccurate inventory information is stronger under the conditions where lead times are shorter and/or where demand uncertainty in market place is lower.

This analysis provides a means for practitioners to realize the importance of inventory accuracy to successful adaptation of collaborative supply chain practices. Moreover, this research also helps in understanding the supply chain conditions where the attempts of eliminating or reducing errors in inventory information are more crucial and more beneficial.

Although there is a range of research focusing on collaborative practices, none of these studies considered the errors in inventory information. This is the first study to investigate the impact of inaccurate inventory information on the benefits of collaborative practices.

This paper aims to explore and describe the impact of radio frequency identification (RFID) technology on inventory accuracy within a production and assembly plant, and to propose a model for assessing the impact of the technology on inventory accuracy.

The empirical investigation, based on case study research, focuses on an RFID implementation at a supplier of injection‐moulded, surface‐treated plastic to the automotive industry. This implementation is one of the few item‐level, open‐loop RFID implementations in the automotive industry.

The empirical paper provides insights into, how inventory accuracy has been improved and made attainable in practice by implementing RFID, and indicates that the technology ensures inventory inaccuracy will be kept at a minimum. As a result, an analytical model is presented which identifies the impact of RFID technology on inventory accuracy.

The case study and context need to be considered when generalising upon the findings. Furthermore, it is hoped future research could further develop the model presented and test it against implementation practice.

RFID technology provides practitioners with the opportunity to eliminate waste, and improve production and assembly performance. The research provides practitioners with experience of, and insights into how a production and assembly plant has improved inventory accuracy by implementing RFID technology. In particular, practitioners are provided with a model which enables them to assess the impact of RFID on inventory accuracy.

This paper contributes to the RFID community by providing empirical insights into the impact of RFID technology on inventory accuracy, but also more broadly into logistics and operations management research.

Ensuring high on-shelf availability at low inventory costs remains an important challenge in retailing. Inaccurate inventory records, i.e. discrepancies between the stock records displayed in the inventory system and the stock quantity actually found in the retail store, have been identified as one of the most important drivers of retail stockouts in the past. The purpose of this work is to investigate the causes of positive inventory discrepancies in retailing, i.e. where there is more inventory on-hand than identified by the inventory system.

Based on input from retailers, the authors develop a simulation model of a retail store that considers various error-prone processes and study in a full factorial test design how the different operational errors may drive inventory discrepancies, paying special attention to the sources of positive inventory record inaccuracies.

This makes it possible to gain insights into the process parameters retailers need to adjust to avoid inventory records becoming inaccurate. In addition, the authors analyze how positive inventory discrepancies relate to stockouts to further our understanding of the role so-called phantom products may play in a retailing context.

While negative inventory discrepancies (where the stock that is available in the store is less than what the system displays) and their sources (theft, shrinkage, etc.) have been discussed quite frequently in the literature, the causes of positive inventory discrepancies (where the available inventory exceeds the system inventory) have received much less attention.

The combination of the latest advancements in information and communication technologies with the latest developments in AutoID technologies, especially radio frequency identification (RFID), brings the possibility of high-resolution, item-level visibility of the entire supply chain. In the particular case of retail, visibility of both the stock count and item location in the shop floor is crucial not only for an effective management of the retail supply chain but also for physical retail stores to compete with online retailers. The purpose of this paper is to propose an autonomous robot that can perform stock-taking using RFID for item-level identification much more accurately and efficiently than the traditional method of using human operators with RFID handheld readers.

This work follows the design science research methodology. The paper highlights a required improvement for an RFID inventory robot. The design hypothesis leads to a novel algorithm. Then the cycle of development and evaluation is iterated several times. Finally, conclusions are derived and a new basis for further development is provided.

An autonomous robot for stock-taking is proven feasible. By applying a proper navigation strategy, coupled to the stream of identifications, the accuracy, precision, consistency and time to complete stock-taking are significantly better than doing the same task manually.

The main limitation of this work is the unavailability of data to analyze the actual impact on the correction of inventory record inaccuracy and its subsequent implications for the supply chain management. Nonetheless, it is shown that figures of actual stock-tacking procedures can be significantly improved.

This paper discloses the potential of deploying an inventory robot in the supply chain. The robot is called to be a key source of inventory data conforming supply chain management 4.0 and omnichannel retail.

The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios.

The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009.

Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data.

In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer’s inventory performance against its competitors.

The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.