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Applying a middle-range theorizing to premises of signaling theory and the scarcity principle, this study aims to investigate the mechanisms and effects of different patterns of post-stockout disclosures that highlight the limited supply and high quality of a durable good on consumer satisfaction with the shopping experience and purchase intention, mediated by consumer perceived product scarcity.

The hypotheses are tested with two scenario-based experiments. The first experiment—a between-subjects design—explores the effect of post-stockout disclosures on consumers' perceived scarcity, satisfaction, and purchase intention. The second experiment – a within-subject design – examines the impact of time on consumer responses to stockouts.

Results indicate that perceived product scarcity mediates the relationship between post-stockout disclosures and consumer outcomes. Specifically, post-stockout disclosures present an indirect positive effect on consumer purchase intention, despite reducing satisfaction beyond the effects of the stockout. These results are consistent when disclosures are sent through multiple channels. Results also show that consumers' perceived scarcity and purchase intention decrease over time while dissatisfaction levels remain the same when stockouts persist.

Even though consumers will be dissatisfied upon experiencing a stockout, specific patterns of post-stockout disclosures can be a valuable strategy for consumer retention and lost sales prevention.

While recent consumer-centric supply chain management literature has investigated mitigation strategies of detrimental consumer response to stockouts, such as “save-the-sale” tactics and price discounts, the mechanisms and effects of different patterns of post-stockouts disclosures highlighting the limited supply and high quality of the product are yet to be investigated.

Inventory management systems in health-care supply chains (HCSC) have been pushed to breaking point by the COVID-19 pandemic. Unanticipated demand shocks due to stockpiling of medical supplies caused stockouts, and the stockouts triggered systematic supply chain (SC) disruptions inconceivable for risk managers working individually with limited information about the pandemic. The purpose of this paper is to respond to calls from the United Nations (UN) and World Health Organization (WHO) for coordinated global action by proposing a research agenda based on a review of current knowledge and knowledge gaps on the role of collaboration in HCSCs in maintaining optimal stock levels and reinforcing resilience against stockout disruptions during pandemics.

A systematic review was conducted, and a total of 752 articles were analyzed.

Collaborative planning, forecasting and replenishment practices are under-researched in the HCSC literature. Similarly, a fragmented application of extant SC collaborative risk management capabilities undermines efforts to enhance resilience against systematic disruptions from medical stockouts. The paucity of HCSC articles in humanitarian logistics and SC journals indicates a need for more research interlinking two interdependent yet critical fields in responding to pandemics.

Although based on an exhaustive search of academic articles addressing HCSCs, there is a possibility of having overlooked other studies due to search variations in language controls, differences in publication cycle time and database search engines.

The paper relies on COVID-19's uniqueness to highlight the limitations in optimization and individualistic approaches to managing medical inventory and stockout risks in HCSCs. The paper proposes a shift from a fragmented to holistic application of relevant collaboration practices and capabilities to enhance the resilience of HCSCs against stockout ripple effects during future pandemics. The study propositions and suggestion for an SC learning curve provide an interdisciplinary research agenda to trigger early preparation of a coordinated HCSC and humanitarian logistics response to future pandemics.

This paper aims to propose a statistical method to measure the impacts of stockouts on demand, using a segmented linear regression model.

The proposed method is applied to data sets from large retail chains to measure the impacts of stockouts of an item on substitute items. The measured impacts of stockouts can be used to estimate the true demand of the sold-out item by recovering the lost demand (turned-away demand), as well as to estimate the true demand of the substitute item by reducing the extra demand.

This study found that estimated true demand by the proposed method improves sales forecasting and calculation of the annual expected revenue.

A new method to measure the impacts of stockouts on the demand of substitute items was proposed. The proposed method is practical, in that, it is conceptually simple, computationally efficient and applicable in general scenarios. Also, the proposed method is scalable for larger data sets.

The terms “inventory” and “stock” are usually seen as being synonymous and are used to describe materials which can be identified at various stages of the transformation process in organisations. It is customary to divide inventory into three categories:

The choice of mode of transport used by a shipper to move his goods does not depend solely upon relative transportation costs. It should be viewed as one part of the complex process of deciding the method of distributing a product which, apart from transport, involves materials handling and packaging, inventory control and warehousing and order processing procedures. The transport operator providing a premium system of transport such as air freight may well be able to justify its use if appropriate economies can be obtained from other distribution activities. For example, a shipper would be prepared to incur higher transport costs if he were able to reduce the size of the inventory he had to hold to meet demand. Demonstrating in numerical terms the potential benefits from any changes in the distribution system is a difficult task because of the complexity of inter‐relationships involved. A computer‐based analysis is essential. However, because the results of such analysis must be easily understood it is also necessary that the system employed is simple to use, sparing in its input requirements, with a readily assimilated output: in short, it has to be efficient in the marketing sense, as well as an accurate model of the distribution system.

Most managers are aware that inventory cannot exist without costs being incurred. In the absence of an accurate indication of what these costs are the decision on the level of stocks to be held becomes very subjective. The result is that in some instances stock levels are too low whereas in other instances the reverse is the case. This article seeks to demonstrate that it is possible to achieve significant savings through quantitative analysis which can be comprehended by managers who do not have specific mathematical skills.

Effects of stockouts on purchase decisions have been examined from a variety of perspectives; little is yet known about how consumers react to stockouts in online shopping contexts. The present study investigates how stockout reactions depend on a consumer's mindset and familiarity with a website and investigates the role of negative affect in determining a consumer's stockout reaction.

Shopping mindsets (deliberative vs. implemental) and website familiarity (high vs. low) were manipulated in an online experiment consisting of a simulated shopping task at an existing website which next was presented as having a stockout. The study observed the participants' switching responses and measured their negative affect.

Findings indicate that when encountering an online stockout, consumers in an implemental mindset are more likely to switch away from the website than those in a deliberative mindset and are more likely to search for additional items at a competing site. Consumers who are more familiar with the website where they encounter the stockout display a higher likelihood of defecting to a competing site; however, when they are in an implemental mindset, their inclination to defect decreases. The study also shows that the strength of negative emotions affects OOS responses in that buyers that experience more negative emotions are more likely to defect from the site.

The study's findings provide suggestions as to how retailers can manage and minimize defection behaviours associated with online stockouts. In designing operational and marketing strategies retailers need to pay close attention to how consumers' individual mindsets may vary by trait or circumstance and how they hence may respond differently to stockouts.

The authors introduce a novel perspective to the literature on stockout induced reactions and contribute by furthering investigation into previously unexplored specific consumer characteristics and intricacies of stockouts that drive particular stockout reactions.

The purpose of this paper is to investigate the direct and interaction effects of shelf space, case pack quantity, and consumer demand on shelf stockouts, i.e. stockouts at the shelf level when inventory is available in the backroom of a retail store.

This study uses discrete‐event simulation based on data collected from the ready‐to‐eat breakfast cereal category with multiple stockkeeping units (SKUs) to model a retail supply chain consisting of a supplier, a retailer, and consumers.

The results indicate that shelf space and case pack quantity have direct effects on shelf stockouts. Furthermore, evidence is found for interactions among shelf space, case pack quantity and consumer demand. Though many retailers adopt simple heuristics for shelf space allocation, such as a multiple of case pack quantity, this study suggests that such heuristics tend to over‐ or underestimate shelf space requirements when consumer demand is ignored.

This study suggests that managers should allocate shelf space for SKUs on the basis of not only case pack quantity but also consumer demand.

In calculations of inventory control costs, the effects of stockouts are often assumed or avoided because of the lack of accounting data for reasonable measurements. The authors describe the development of stockout cost models incorporating decisions made by consumers in an actual retail situation. Equations for calculating the revenue differences are based on the consumer decision alternatives. The results of a consumer survey, combined with retail prices for the product lines in question, enable the financial effects of stockouts to be calculated.

This paper aims to investigate the effect of retailers’ consumer communications in prompting the choice of an in-stock alternative to an out-of-stock first-choice product.

Four between-subjects experiments assessed the extent to which the likelihood of a retail customer switching to a similarly-priced alternative when a first choice was out-of-stock was affected by messages concerning stockout status (Studies 1a and 1b). They further examined the interaction effects on participants’ preference of messages comparing the available versus unavailable options and stating stockout status (Study 2) and those giving information on the reasons for the stockout and on its status (Study 3).

Participants maintained their original preference for an out-of-stock product unless an external restriction on choice prompted them to forsake it or they perceived a strong reason to opt for an in-stock alternative. There was a greater tendency to switch if the alternative offered a potential “gain” or the reasons given for a stockout were irrelevant to product performance, whether the participant was expecting imminent re-stocking. Switching was triggered when the available alternative was directly comparable to the original or the retailer’s explanation related to an attribute judged trivial, but only if short supply was expected to continue.

The studies add to current understanding of how shoppers respond to unavailability of a first-choice product by examining the effect on switching behavior of messages about the stockout situation that are communicated deliberately or inadvertently by retailers.