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The purpose of this paper is to examine out‐of‐stock (OOS) challenges in the independent grocery sector with a special emphasis on in‐store root causes. The analysis aims to assess the extent and root causes for OOS in the independently controlled retail sector and provide a comparison of these results with the centrally controlled chain sector in Denmark. The paper also seeks to examine the practices and challenges of store ordering and store replenishment processes in the independent sector and identify practical implications for store management and other members of the grocery channels.

The research design includes two studies. Study‐I surveys and compares the extent and root causes of OOS of 42 stores from eight chains in the two sectors. Study‐II identifies, based on qualitative interviews with 17 store managers/owners of independent stores, specific insights on store operations.

The quantitative study shows that the OOS rates in the independent sector are significantly higher than in the centrally organized sector. Furthermore, the independent grocery sector faces OOS challenges in more categories than the centrally controlled sector. The study also reveals a very large variation in the performance of independent stores. Contrary to the centrally controlled chain store sector, the major root cause for OOS in the independent sector is found in the store ordering process. The qualitative study shows that the main discriminating issues between stores with a low and a high OOS rate are: store management emphasis and commitment to OOS issues; the resulting priority and managerial guidance in store ordering and store replenishment tasks; the stability of staff and the proper planning for replenishment peaks; the store size and resulting space conditions; and the use of appropriate decision heuristics and use of inventory in store ordering.

The findings have practical implications for store management as it reveals practices to pursue and to avoid. Also, it is argued that the findings have implications for the other members of the grocery channels.

Empirically, this paper explores two issues not being dealt with in depth in previous research, i.e. the OOS challenge in the independent sector and the emphasis on store operations.

The purpose of this paper is to present a methodology to structure the problem of retail out of stock (OOS). This methodology allows investigating risk factors and barriers related to the main causes and consequences that lead to OOS occurring.

The proposed methodology to structure the OOS problem is based on the bow- ie tool, which allows better visualisation, understanding and analysis of a complete OOS scenario. This proposal comprises exploring the main causes and consequences of OOS, the barriers to prevention and mitigation, the escalation factors to control undesirable events and to define actions to eliminate or mitigate the OSS risk.

Several potential causal risk factors, related to technical, behavioural, cultural and organisational aspects, were identified with this methodology. With the analysis of the OOS scenario, it was observed that the factors that lead to the OOS risk are preventable. In order to improve existing barriers or implement new barriers, a set of actions can be recommended to reduce or eliminate OOS risk factors.

From a better understanding of hazard, the bow-tie methodology allows identifying crucial factors that could be acted upon to reduce the incidence of OSS. Thus, the value is to propose a methodology that allows establishing the preventive and protective barriers necessaries and the escalation factors related to each of these to help structure the problem and consequently reduce the OOS in retail organisations.

The objective of this paper is to examine the impact of cross-docking on the retail out of stock (OOS).

The research is based on a three-phase Delphi study consisting of a seeding/literature review phase, a pre-testing phase and a three-round Delphi study. The Delphi study used in this paper brings together leading supply chain management experts with leading academics.

The findings of the paper show that cross-docking may impact the retailers OOS drivers positively or negatively. The study demonstrates that cross-docking has a negative impact on ordering, placement, delivery, handling, DC handling and receipt. On the other hand, cross-docking has a positive effect on supplier ordering. Finally, academics and supply chain managers disagreed on the effect of cross-docking on the promotions driver. Academics consider that cross-docking has a positive impact on promotions OOS driver, while supply chain managers believe the opposite.

The Delphi study was administrated to supply chain managers from a single major FMCG company, which is a supplier of grocery retailers. By including supply chain managers from the retailers' side, more perspectives on the impact of cross-docking on the OOS drivers can be investigated.

The study develops an original instrument to investigate the impact of cross-docking on OOS drivers. This is the first scholarly work to investigate the relationship between a distribution strategy and the OOS drivers.

With all the hype around efficient consumer response (ECR) and the brave new world of technologies, one would believe that retail out‐of‐stocks have gone down over the last ten years. That is wrong. Retailers have been struggling with considerable out‐of‐stocks for decades – with little evidence of improvement. A similar wrong belief is that shoppers are also still unwilling to accept low service levels. In fact, increasingly, consumers switch brands when they do not find the brand they wanted. But retailers must be wary, because the results of our research show that increasingly shoppers switch stores quickly and may never come back. So, who is to blame? The supply chain. And where to tackle it? On the shop floor. Over the past two years, we have conducted a major, worldwide study of the extent, causes, and consumer responses to out‐of‐stocks in the fast‐moving consumer goods industry. In this article, we report these findings and provide insight to solving this chronic industry problem.

The purpose of this paper is to present an investigation into the causes of promotional on‐shelf‐availability (on‐shelf‐availability) shortfalls in retailing.

The research follows a multiple‐case study research design involving seven major retailers and four multinational food manufacturers operating in the UK. The data collection took the form of semi‐structured interviews with 110 practitioners across 24 sites. Observations and documentation were used as supporting evidence.

Improving promotional on‐shelf‐availability presents retailers and manufacturers with a complex set of inter‐connected problems distributed across the supply chain. This research identified 32 causes affecting on‐shelf‐availability, grouped into eight themes, six of which are generic (forecasting, collaboration, replenishment, IT, distribution and production), and two which are specific to promotions (timescales and promotional process). This classification provides practitioners with a framework to improve promotional on‐shelf‐availability and academics with a more comprehensive range of the factors affecting on‐shelf‐availability, including two new themes not previously documented.

Although the number of cases does not allow statistical analysis, the size and scope of the organizations involved helps to underpin the generalizability of the findings. The volume of data collected for retailers is significantly higher than for manufacturers, although this only reflects the importance of retailers in ensuring on‐shelf‐availability.

This paper presents a framework designed to provide a steer for further research into promotional on‐shelf‐availability and to help retail professionals to prioritize their actions towards improving promotional on‐shelf‐availability.

While on‐shelf‐availability has been the subject of much research, promotional on‐shelf‐availability has not been investigated in significant depth. This research is, to our knowledge, the first to investigate the causes of poor promotional on‐shelf‐availability and expands the knowledge of the field by highlighting the similarities and differences between traditional on‐shelf‐availability and promotional on‐shelf‐availability. Given the increasing use of promotions as a competitive strategy this area of research is both timely and important.

The purpose of this paper is to provide clear insights into the influence of product availability, and thus distribution on double jeopardy (DJ) patterns, for frequently‐purchased products (FPP). This paper also aims to provide important strategies in order to maximize the efficiency of retailers' stocking decisions and manufacturers' branding efforts by discussing distribution dynamics in a set of experiments developed in light of related theoretical discussions.

This study provides an in‐depth literature review of DJ, distribution, out‐of‐stock and consumer behavioural brand loyalty in many marketing and supply chain decisions. A practical simulation is developed to test the main hypotheses in the study in light of the theoretical discussion.

The study's results indicated that distribution might explain DJ patterns. In addition, distribution might create behavioural brand loyalty when FPP are widely available (excessive availability) in the market.

Although the study provides a simulation structure and varying experiments, more field data about FPP might also enhance the study's results.

Small brands can break their curse as indicated by the DJ phenomenon by focusing on distribution. Also, they might create some level of behavioural brand loyalty by being available everywhere in the market.

The impact of distribution on DJ has seldom been discussed in general terms previously, and has never been discussed and explored theoretically with specificity using experimental analysis. Therefore, this study provides the first evidence that distribution has a strong potential to explain the reasons behind DJ patterns and might create behavioural brand loyalty.

This paper aims to focus on the store ordering and replenishment practices which appear to be the major cause behind the problem of out‐of‐stock situations. A collaborative store replenishment practice, enabled by an internet‐based platform is examined. By enabling information and knowledge sharing between retail store managers and suppliers' salesmen, this practice leads to increased order accuracy and, as a result, to fewer out‐of‐stock situations.

The research presented in this paper has been empirical in nature, involving a field experiment with a major retailer and several suppliers in Greece. Pre‐ and post‐experiment measurements were conducted and the quantitative results were statistically analyzed in order to assess the impact of collaborative store ordering on shelf availability. The quantitative measurements were repeated over several years, offering a longitudinal view on the experiment. Qualitative findings from the field experiment are also discussed.

The empirical results from the field experiment show a reduction in out‐of‐stock situations by more than 50 percent combined with no significant statistical variation in total observed inventory levels. Qualitative findings regarding the practical aspects of the process as well as organizational issues are also acquired.

Low shelf availability and the respective sales loss is one of the major issues retailers and suppliers face today. This paper examines a new replenishment process, involving supplier‐retailer collaboration supported by daily information sharing of POS data and other information over an internet platform, which leads to increased shelf availability by addressing one of its major causes. Thus, the empirical results presented in the paper have important implications for practitioners. In addition, the paper contributes from a methodological perspective to the academic community, by describing the way the field experiment was conducted and the quantitative results were analyzed as a means to evaluate a new business practice and Internet‐based collaboration platform.

The purpose of this paper is to propose an artificial intelligence-based framework to support decision making in wholesale distribution, with the aim to limit wholesaler out-of-stocks (OOSs) by jointly formulating price policies and forecasting retailer’s demand.

The framework is based on the cascade implementation of two artificial neural networks (ANNs) connected in series. The first ANN is used to derive the selling price of the products offered by the wholesaler. This represents one of the inputs of the second ANN that is used to anticipate the retailer’s demand. Both the ANNs make use of several other input parameters and are trained and tested on a real wholesale supply chain.

The application of the ANN framework to a real wholesale supply chain shows that the proposed methodology has the potential to decrease economic loss due to OOS occurrence by more than 56 percent.

The combined use of ANNs is a novelty in supply chain operation management. Moreover, this approach provides wholesalers with an effective tool to issue purchase orders according to more dependable demand forecasts.

The purpose of this paper is to: first, provide a systematic review of the drivers of retail on-shelf availability (OSA) that have been scrutinized in the literature; second, identify areas where further scrutiny is needed; and third, critically reflect on current conceptualizations of OSA and suggest alternative perspectives that may help guide future investigations.

A systematic approach is adopted wherein nine leading journals in logistics, supply chain management, operations management, and retailing are systematically scanned for articles discussing OSA drivers. The respective journals’ websites are used as the primary platform for scanning, with Google Scholar serving as a secondary platform for completeness. Journal articles are carefully read and their respective relevance assessed. A final set of 73 articles is retained and thoroughly reviewed for the purpose of this research. The systematic nature of the review minimizes researcher bias, ensures reasonable completeness, maximizes reliability, and enables replicability.

Five categories of drivers of OSA are identified. The first four – i.e., operational, behavioral, managerial, and coordination drivers – stem from failures at the planning or execution stages of retail operations. The fifth category – systemic drivers – encompasses contingency factors that amplify the effect of supply chain failures on OSA. The review also indicates that most non-systemic OOS could be traced back to incentive misalignments within and across supply chain partners.

This research consolidates past findings on the drivers of OSA and provides valuable insights as to areas where further research may be needed. It also offers forward-looking perspectives that could help advance research on the drivers of OSA. For example, the authors invite the research community to revisit the pervasive underlying assumption that OSA is an absolute imperative and question the unidirectional relationship that higher OSA is necessarily better. The authors initiate an open dialogue to approach OSA as a service-level parameter, rather than a maximizable outcome, as indicated by inventory theory.

As the flourish of today’s supply chain, the traditional model of replenishment will cause accumulation of excessive inventory to the retailers and customers, or cause shortages and inability to meet the demands. To solve this problem, Theory of Constraints (TOC) proposed the replenishment model of demand‐pull, combined with the establishment of factory‐warehouse to achieve performance improvement. In the absence of empirical research, this study applied the Bean Game developed by Dr. Goldratt to design a supply chain system for different scenarios, in order to allow players and managers better understanding and supporting the TOC replenishment method through the operations of the game.