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The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.

This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.

This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.

This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.

This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

Inventory is a crucial part of a systematic supply chain of a business. Small firms mostly neglect inventory management (IM) by accumulating excessive inventory for a time. The study aims to examine the IM practices of small and medium enterprises (SMEs) in Bangladesh.

The study applied a qualitative case study design. Data were collected from ten SME owners in Bangladesh. The study employed a purposive sampling technique to collect data. This study used semi-structured interviews to generate data. The NVivo software was used to analyze the data.

The findings show that most SME business owners collect raw materials from the local market. Along with the local sources, they collect raw materials from international markets. Some SME entrepreneurs collect raw materials throughout the country as they dealt with recycled products. Frequently, they used digital technologies and online media to manage raw materials. SME owners could not buy many raw materials due to financial crisis, wastage, and damage, leading to a ratio of 10–15% losses.

This research contributes greatly to the government, SME Foundation, and trade associations concerning the SME IM system. The study recommends the government should reduce the tax rate on importing SME raw materials and inventories and exporting SME products.

This is the first study that focuses on the IM systems of SMEs in Bangladesh.

The weapon system of The Navy is the small quantity producing system on multiple kinds. It is consisted of various equipment and the subordinate parts of those which can repair the damaged part. The operating procedure concerning warship's repair parts managed under these systems is as follows. Firstly, if demand of repair parts occurs from warship which is the operating unit of weapon, then the Fleet(the repair & supply support battalion) is in charge of dealing with these requests. If certain request from warship is beyond the battalion's capability, it is delivered directly to the Logistic Command. In short, the repair and supply support system of repair parts can be described as the multi-level support system. The various theoretical researches on inventory management of Navy's repair parts and simulation study that reflects reality in detail have been carried out simultaneously. However, the majority of existing research has been conducted on aircraft and tank's repairable items, in that, the studies is woefully deficient in the area concerning Navy's inventory management. For that reason, this paper firstly constructs the model of consumable items that is frequently damaged reflecting characteristics of navy's repair parts inventory management using ARENA simulation. After that, this paper is trying to propose methodology to analyze optimal inventory level of each supply unit through OptQuest, the optimization program of ARENA simulation.

Inventory accumulation is a major problem for any organization, as it not only occupies the valuable storage space, but it also blocks the company's capital, leaving the owners with less cash to run the company's business. Aggregation of inventory in any organization contributes to inventory carrying cost; it affects labor productivity, increases equipment expenses and creates a loss of opportunity associated with it. Therefore, it is essential for any organization to come up with a solution to deal with the stockpile of inventory.

This research aims to examine the potential causes of inventory aggregation in an organization. First, the potential factors for the build-up of inventory are identified from survey data collection, such as questionnaire approach and discussion with industry experts, and then weights are assigned to attributes to study the effects for these factors. After the identification of probable causes, they are analyzed through a multi-criterion decision-making (MCDM) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) to prioritize the severity of these causes toward the accumulation of inventory and take corrective actions to prevent their disruptive effect on the business.

The top three causes identified from the TOPSIS analysis are sales and forecasting error, defects and quality related issues and communication gap between departments. Firstly, we focus on these major contributors and prioritize them using the TOPSIS analysis. Then, we proceed further toward other factors. The main reasons identified for the accumulation of inventory are (1) forecasting error, (2) bulk purchase, (3) data entry error, (4) communication gaps, (5) quality-related issues, (6) product category not traceable and (7) wrong material being procured.

To carry out the data analysis in this research paper, first survey data collection is done. Then, discussions with managers and executives in the particular domain are carried out, and weights are assigned to the attributes and the criteria to study the effects of the identified factors. After that root cause analysis (RCA) is performed to get to the genesis of the problem and to take necessary corrective action, for carrying out this study, a total of seven potential causes were identified and the contribution of these seven causes on five attributes or criteria, i.e. quantity (in tons), holding and carrying cost, effect on labor productivity, loss of opportunity cost and storage space were studied.

This research paper is the author’s original work, and all the analyses carried out are from the discussion with experts in the field and through the in-depth analysis carried out. This research aims to examine the potential causes of the accumulation of inventory in organizations and their contribution toward factors like inventory carrying cost, labor productivity, and opportunity loss and excessive storage space have been analyzed. This research provides great value to the readers in the respective domain.

For the supply chain to be responsive in the age of globalization, the firm needs to adopt strategies to enable them to meet the changing market needs. Thus, it is essential to adopt automatic replenishment programmes such as vendor-managed inventory (VMI). This study sought to examine the relationship between VMI and operational performance (OP) and the moderation roles of leadership and digitization in the mining sector.

A quantitative approach was used, including primary data collected from industry players in the mining sector in Ghana. A total of 97 industry players were included in the study. Data gathered was analysed using SPSS and LISREL (8.5).

The results indicate that VMI significantly affects OP. However, both digitization and leadership failed to moderate the relationship between VMI and OP.

The study offers mining companies an understanding of VMI applications in their industry. The knowledge will stimulate and improve inventory management practices in the mining industry.

This study is among the first few attempts to understand VMI in the mining industry, especially in the Sub-Saharan Africa context. It presents a detailed understanding of VMI and opportunities for future research.

The future retirement of US Air Force (USAF) legacy weapon systems (WSs) removes their associated funding from within the Air Force Working Capital Fund and their parts from its organic supply chain inventory. The trending outsourcing of product support to contracted logistics support and its potential long-term consequences to the USAF government-owned, government-operated, organic supply chain and the reconstitution capabilities it enables in the USAF’s organic industrial base, suggests the need to assess its risks. Although there is an existing body of research into the risks of outsourcing the USAF’s industrial repair, and federal legislation such as Core 50/50 laws enacted to institutionalize its risk management, there is comparatively little research into the outsourcing risks to the long-term viability of the supply chain on which that repair capability is dependent. The aim of this research is to fill that research gap by assessing and modeling those risks. This research concludes by providing several future research directions that may be evaluated to provide more detail.

Leveraging a conceptual model derived from research and a multi-criteria analysis framework to assess supply chain risk. Quantifying the predicted impact of retirements on funding and inventories of unique parts. Modeling the potential risk due to WS retirement.

Results indicated long term enterprise risks to the Air Force’s supply chain correlated to the retirement of WSs and their associated funding and spare parts inventory.

This research provides an in-depth evaluation of the USAF’s supply chain to assess the holistic risk of product support outsourcing and its long-term impacts on viability by using resource-based view and contingency theory as theoretical underpinnings. In addition, insights and implications for defense supply chain managers and decision-makers.

The objective of this study is to mitigate the risks of a blood shortage. The authors designed two simulation studies to identify the superior methodology that can decrease the impact of a massive national donor shortage.

The simulation designs are triggered by the COVID-19 pandemic. The first simulation examines the company’s choice of strategic partners (regionally and nationally), and the second inspects creating a national coordinated effort to organize a pooled blood inventory that would require blood centers to contribute a small percentage of their monthly donations to become a member.

The results indicate that both methods can significantly manage the risk of stockouts regardless of the availability of safety inventory in a blood center; however, although more effective in reducing the number of shortages per month, creating a national blood pool causes the shortages to be recognized earlier than desired.

The authors contribute to the literature by focusing on the potential risk of blood shortage because it directly impacts healthcare, hospitals’ costs and their ability to provide care. Though a handful of researchers have targeted the study of the blood supply chain, there is not any article that is similar to this study.

The purpose of this study aims to investigate the relationship between employees’ personality traits and their job performances (including task performance and contextual performance) of Taiwanese freight forwarders by using responses from a NEO Personality Inventory-Revised Form (NEO-PI-R) questionnaire survey.

One of the most popular personality trait model is the five-factor model (FFM), which includes the big five domains, namely, openness, conscientiousness, extraversion, agreeableness and neuroticism (OCEAN). Each of these five domains includes six facets. Previous researchers have used OCEAN factors to describe the relationship between human personality and job performance. NEO Personality Inventory is a professional psychological assessment instrument published by psychological assessment resources. Multivariate analysis technique and regression technique are used to analyze surveyees’ responses.

Research results reveal the following four issues. The seniority of employees in a company has a positive relationship with their conscientiousness. Employees with higher score on the facets of the neuroticism domain have a negative correlation with their task performance and contextual performance. The relationship between employees’ openness to experience and job performance (both task performance and contextual performance) is not significant. Employees’ seniority has a positive correlation with both their task performance and contextual performance. In a nutshell, freight forwarding industry in Taiwan can use the facets in the neuroticism domain to screen and recruit appropriate job applicants. In addition, retaining senior employees could increase a forwarder’s task performance and contextual performance by their high degree of conscientiousness.

FFM model is a psychological theory dealing with the personality traits and human behavior. Freight forwarding is a labor-intensive business and is one of the most important sectors in the logistics industry. According the authors’ knowledge, the application of FFM on the logistics industry is simply not existed.

Low read rates are a general problem in library inventories. The purpose of this study is to examine the factors that contribute to the success of library inventory by means of a radio-frequency identification (RFID) inventory taker. The factors investigated were tag position, tag orientation, book thickness, tag density (related to thickness of a sequence of books) and position on the shelf.

A total of 210 books were placed in eight random permutations on three fixed book shelves. For each configuration, the RFID tags were read forty times. The resulting data were analysed by means of a generalized linear model, relating the combined contribution of tag position, tag orientation, book thickness and position on the bookshelf to the read rate.

The tags positioned directly next to the spine were always read, but those near the opening of the book (far from the spine and inventory reader) were not always read. Considering only books with tags near the opening, tag orientation and position on the shelf appeared not to be related to the read rate, while book thickness, thickness over three books and spine tag density appeared to have a small positive contribution to the read rate.

Low read rates during a library inventory can be prevented by placing the tags near the book spine – the other book specific factors (listed in the previous paragraph) are of little influence. When not scanned during a first sweep, repeated scanning can increase the read rate with 0.15.

This paper is one of the first to analyse the influence of tag location and book specific factors on the read rate of RFID tags in library books. The experimental approach sets an example for future work.