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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 purpose of this paper is to analyze a conceptual framework to identify significant benefit and cost attributes of a radio-frequency identification (RFID) system for asset tracking in healthcare facilities. Sources of value function for RFID in healthcare are categorized according to major improvement. Several cost functions are proposed to measure aspects of automated tracking implementation.

The four phases of problem definition, literature identification, assessment and analysis were used to begin the research. A cost–benefit analysis (CBA) was completed to identify the factors within healthcare with major benefits, and finally, a recommended group of items were identified to track with the CBA.

RFID to manage mobile devices increases the utilization rate, decreases annual spending, allows withdrawal of funds for underutilized assets and establishes confidence that equipment is readily available when needed. These benefits provide improved staff productivity, quicker patient turnover, higher quality of care and more cost savings. Real-time location system technologies allow hospitals to be prepared for emergencies requiring the immediate use of medical devices without delay and allow staff to determine the status, condition and location of essential equipment, leading to a decrease in patient wait time. Additional improvements were also found.

The transition from pay-for-service to pay-for-performance is taking place in an industry hampered by rising costs and limited available resources. Healthcare expenditures are estimated to grow dramatically, and various factors contribute to rising expenses, including an aging population and increased chronic conditions resulting in higher demand for care, poor quality and operational inefficiencies. Therefore, understanding benefits of new technology use like RFID is critical for improvement and efficiency in healthcare.

The literature on warehouse performance assessments is mainly focussed on the efficiency and effectiveness of an action or activity due to customer demand and tailored fulfilment, with less attention being given to the performance measurement of each function of the warehouse and its overall productivity. Therefore, this study was aimed at revising the key warehouse performance metrics to a set of productivity measurement indicators that can be adopted internationally for benchmarking productivity performance.

A literature review and semi-structured survey questionnaire were used for this study. The importance of warehouse productivity performance was reviewed to revamp the measurement indicators. Through the use of a directed content analysis and descriptive analysis, an extensive study was carried out to analyze existing warehouse productivity indicators.

The findings of this study provide comprehensive references for practitioners and academicians for improving the classification of productivity measurements from existing key performance metrics for warehousing. Also, this paper highlights the warehouse resources related to the respective warehouse operation activities.

The study was limited to productivity performance indicators adapted from Staudt et al. (2015). Furthermore, the samples for this study comprised Malaysian academicians and practitioners in the related field. The findings can be adapted on a global scale as this study implemented general warehouse operation processes.

Consequently, the contributions of this study are that it provides relevant benchmarks for key productivity performance indicators in the warehousing sector that has worldwide applicability and the developed model provides a conceptual platform from which further theoretical and empirical developments can be carried out.

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.

The Law of Industrial Dynamics ensures that if a production control system can amplify then it will surely find a way of doing so despite the best efforts of production schedulers to take corrective action. In fact, practical studies show that such human intervention frequently aggravates the situation with both stock levels and order rates fluctuating alarmingly. The solution is to design an effective system via simulation. This requires the selection of the appropriate control system structure, agreement on the test cases to be used to mimic the operating environment, and finally setting the system parameters to achieve best performance for this scenario. Demonstrates a system which has three controllers utilizing sales, inventory and work in progress (WIP) data to set production order rates. The resulting decision support system (DSS) is a generic tool that can be used by production schedulers with confidence in the knowledge that the Law of Industrial Dynamics effects may be minimized. Simulation experiments can determine the best available trade‐off in any particular situation such as achieving the lean logistics aim of minimum reasonable inventory (MRI) while retaining high customer service levels (CSL). The experimental facility available within the simulation model includes provision for assessing the impact of variable production lead times and information delays on system performance. Describes a specific application of the DSS and the specific improvements in a company’s performance. Places the DSS in the context of a case‐based reasoning environment in which a knowledge base of system structures and their dynamic properties is achieved. Outlines the opportunity of utilizing the DSS in uncertain lead‐time environments in a range of industry sectors.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

This paper identifies potential data problems when using accounting databases. To examine data errors, two commonly used accounting databases, Value Line and Compustat, are compared in their qualitative and quantitative features. Data are examined using seven variables over a period of 11 years. Substantial data differences are found, most of which are attributable to definitional discrepancies and others to direct measurement error. Finally, recommendations for dealing with these problems are presented, to preparers of databases as well as standard setters.

The purpose of this study is to propose a new dynamic model of a production-inventory control system. The objective of the new model is to maximise the flexibility of the system so that it can be used by decision makers to design inventory systems that adopt various strategies that provide a balance between reducing the bullwhip effect and improving the responsiveness of inventory performance.

The proposed production-inventory control system is modelled and analysed via control theory and simulations. The production-inventory feedback control system is modelled through continuous time differential equations. The simulation experiments design is conducted by using the state-space model of the system. The Automatic Pipeline Inventory and Order-Based Production Control System (APIOBPCS) model is used as a benchmark production-inventory control system.

The results showed that the Two Automatic Pipelines, Inventory and Order-Based Production Control System (2APIOBPCS) model outperforms APIOBPCS in terms of reducing the bullwhip effect. However, the 2APIOBPCS model has a negative impact on Customer Service Level. Therefore, with careful parameter setting, it is possible to design control decisions to be suitably responsive while generating smooth order patterns and obtain the best trade-off of the two objectives.

This research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level.

This present model is an extension and improvement to Towill’s (1982) and John et al.’s (1994) work, since it presents a new dynamic model of a production-inventory control system which utilises an additional flow of information to improve the efficiency of order rate decisions.

This study explores the intricate relationship between inventory leanness, financial constraints and digital transformation in listed Chinese manufacturing firms.

Using a large panel data collected from 2,563 Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U- shaped relationship between inventory leanness and financial constraints. Furthermore, the moderating role of digital transformation is demonstrated.

Contrary to traditional assumptions, our research uncovers a U-shaped relationship between inventory leanness and financial constraints, indicating that excessive inventory reduction can exacerbate financial constraints. Digital transformation plays a significant moderating role, particularly in highly digitalized environments.

Our findings have practical significance for top managers and policymakers. We advocate for a balanced approach to lean inventory management to mitigating financial constraints. The study emphasizes the pivotal role of digital transformation in alleviating the impact of inventory leanness on financial constraints, highlighting the need for digital transformation strategies.

This research provides a comprehensive analysis of inventory leanness, financial constraints and digital transformation dynamics. It challenges conventional thinking by revealing the nonlinear nature of the inventory leanness–financial constraints relationship. The concept of moderation highlights the moderating effect of digital transformation. This study offers practical guidance for practitioners and policymakers.