On Shelf Availability: A Literature Review & Conceptual Framework

On-Shelf Availability (OSA) is a key performance indicator for the retail industry, greatly impacting profit and customer loyalty. Strong competition in the industry causes retailers and suppliers to put heavy emphasis on improving performance in an effort to satisfy consumers and keep them coming back to their store or product. Over 40 years of research has been done on OSA and its complement, out-of stock (OOS), however very little progress has been made in improving performance in these areas, leading to the belief that gaps in extant research exist. In order to solve the OOS problem, the key drivers of OOS events must first be identified and then addressed. This paper focuses on identifying the drivers of poor OSA performance through a three step process. First, a comprehensive literature review was performed to identify the drivers of OOS addressed in existing literature. Second, interviews with industry professionals revealed potential drivers of poor OSA performance that have been explored at an industry level. Finally, the two lists were examined against each other and the potential drivers identified in the interviews that had yet to be researched were highlighted. This paper gives strategic direction for future research to help solve the OOS dilemma facing manufacturers and retailers today

An assessment of the sustainability of E-fulfilment models for the delivery of fast moving consumer goods to the home

Online retail sales are growing rapidly and have captured a significant proportion of the retail market in many countries. Although companies are under mounting pressure to reduce their environmental impact, the environmental effect of the different online distribution strategies remains unclear. Most previous studies of this subject have only included partial effects and consequences. To enable a more holistic understanding, this study proposes a more inclusive framework of environmental assessment based on life cycle analysis. This was applied to fast moving consumer goods (FMCG). Previous studies have shown that the last mile delivery contributes significantly to the environmental impact of online retailing, mainly because of the nature of the home delivery operations, including narrow time windows and short order lead times. If consumers were to buy products online on a subscription basis and give the supplier more control over the replenishment process there might be less need for fast deliveries, creating opportunities to improve the efficiency of home deliveries and reduce their environmental impact. The study classified different forms of subscription arrangement, assessed their relative attractiveness to consumers and examined their likely impact on the supply chain. Consumer views on subscriptions were surveyed by means of focus group discussions and interviews. To assess the likely supply chain impacts of subscriptions, the literature on vendor-managed inventory was consulted. A Life-Cycle Assessment (LCA) model was built to quantify and compare the environmental impact of various e-fulfilment models for FMCG products in the United Kingdom. This study reveals that the method of execution have a large influence on the environmental impact. In store-based retailing, the energy consumption within the supermarket is a significant contributor to the total greenhouse gas emissions. On the other hand, some forms of home delivery, involving for example the use of parcel networks with no pre-agreed time-slots and relatively high rates of delivery failure and customer collection, are also carbon-intensive. This contribution of consumer trips to the total footprint is much smaller in case of van-based deliveries where pre-agreed time-windows are used. Regardless of the business model, the total carbon footprint per item depends heavily on the number of items per delivery. Consequently, companies or consumers looking to decrease the environmental impact of online shopping should maximise the number of items per delivery. The study concludes with an assessment of the strengths, weaknesses and possible environmental improvements of each of the efulfilment methods, taking account of the possible role of subscriptions

A rolling horizon simulation approach for managing demand with lead time variability

[EN] This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.This work was supported by the European Commission Horizon 2020 project Diverfarming [grant number 728003].Campuzano Bolarin, F.; Mula, J.; Díaz-Madroñero Boluda, FM.; Legaz-Aparicio, Á. (2020). A rolling horizon simulation approach for managing demand with lead time variability. 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The value of nonlinear control theory in investigating the underlying dynamics and resilience of a grocery supply chain

In an empirical context, a method to use nonlinear control theory in the dynamic analysis of supply chain resilience is developed and tested. The method utilises block diagram development, transfer function formulation, describing function representation of nonlinearities and simulation. Using both ‘shock’ or step response and ‘filter’ or frequency response lenses, a system dynamics model is created to analyse the resilience performance of a distribution centre replenishment system at a large grocery retailer. Potential risks for the retailer’s resilience performance include the possibility of a mismatch between supply and demand, as well as serving the store inefficiently and causing on-shelf stock-outs. Thus, resilience is determined by investigating the dynamic behaviour of stock and shipment responses. The method allows insights into the nonlinear system control structures that would not be evident using simulation alone, including a better understanding of the influence of control parameters on dynamic behaviour, the identification of inventory offsets potentially leading to ‘drift’, the impact of nonlinearities on supply chain performance and the minimisation of simulation experiments

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Replenishment support decision model for a try­-before-you-­buy retail fashion e­commerce

A try before you buy business model is a type of sales strategy in which customers are allowed to test a product before making a purchase. As the try before you buy online business model is a topic on which there is limited public scholarly research, the purpose of this research is to provide an initial approach to the subject by presenting a tool to support the replenishment strategy of Curve Catch, a fashion e­commerce retailer. A simulation engine characterized by two main components has been built: replenishment and a demand generator. Model development is built on artificially generated data based on real data of Curve Catch. Based on the literature inherent to inventory management and through the use of simulation ­optimization, the model provides managerial guidance on how to manage r,Q policy in a system where most goods shipped to customers are returned. The tool highlights the need to optimize the use of reorder point and economic order quantity to achieve better business performance. This is because conventional formulas, if not adjusted to the specific setting, perform sub optimally. The model also provides insights into the levels of lost sales due to out stocking and the quality of service provided to customers. Studying the relationships among these three KPIs provides insight into what trade­offs are relevant in planning a continuous review replenishment strategy.Um modelo de negócio de "experimentar antes de comprar" é um tipo de estratégia de vendas onde os clientes têm a possibilidade de testar um produto antes de fazer a sua compra. Uma vez que este modelo de negócio online é um tópico sobre o qual não existe nenhuma pesquisa académica pública, o objetivo desta estudo é fornecer uma abordagem inicial ao assunto, fornecendo uma ferramenta para apoiar a estratégia de reposição da Curve Catch, um e ­ commerce de moda. Foi construído um motor de simulação caracterizado por dois componentes principais: reposição e gerador de procura. O desenvolvimento do modelo baseia ­se em dados gerados artificialmente com base em dados reais da Curve Catch. Com base na literatura inerente à gestão de stocks e através do uso de simulação­otimização, o modelo fornece orientação empresarial sobre como gerir a política r, Q em um sistema onde a maioria dos produtos enviados para os clientes é devolvido. A ferramenta destaca a necessidade de otimizar o uso do ponto de reordenação (reorder point) e da quantidade de encomenda económica (economic order quantity), para alcançar um melhor desempenho do negócio. Isso ocorre dado que as fórmulas convencionais, se não forem ajustadas para o ambiente específico, serão desempenhadas de maneira subaproveitada. Para além disso, o modelo fornece insights sobre os níveis de vendas perdidas devido ao esgotamento e a qualidade do aten dimento ao cliente. O estudo das relações entre essas três métricas­chave fornece insights sobre quais trade­offs são relevantes no planeamento de uma estratégia de reposição de revisão contínua.

How can customer experience improve retail operations sustainability?

Trabalho apresentado em 3rd International Conference on Quality Innovation and Sustainability – ICQIS2022, 3-4 maio 2022, Aveiro, Portugal.Consumer needs drive supply chains, so they are arguably the main actors in the process. Nonetheless, consumers are unaware of their ability to con tribute to stock management and the sustainability of retail operations, from the reduction of stockouts and waste to the minimization of energy-environmental impacts, through the centralization of stock in distribution and consolidation of last mile delivery in pooling systems. For this to happen, companies must provide channels that allow consumers to actively participate in the process and negotiate delivery times and prices through sustainable purchase options, through a crowdsourcing strategy in phygital stores. This paper explores two alternative strategies, maintaining or changing the current physical retail business model, based on the increase in online commerce and the use of mobile devices and ap plications in the purchase process. The first is applied in physical stores in a gam ing context through a consumer-facing augmented reality mobile application that rewards users for identifying stockouts and informing the need to replace prod ucts in the shelves. The second involves the transformation of physical stores into a showroom format, where desired products are read through a QR Code or using artificial intelligence through a mobile application, in which virtual shopping carts are created and deliveries can be fulfilled via home distribution centers, col lection points or drive-inN/