Grocery omnichannel perishable inventories: performance measures and influencing factors

Purpose- Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures. Design/methodology/approach- The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation. Findings- Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects. Practical implications- To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products. Originality/value- This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors

A dynamic pricing policy for perishables with stochastic demand

Ankara : The Department of Industrial Engineering and The Institute of Engineering and Sciences of Bilkent Univ., 2001.Thesis (Master's) -- Bilkent University, 2001.Includes bibliographical references.III this study, we consider the pricing of perishables in an inventory system where items have a fixi'd lifetime. Unit demands come from a Poisson Process with a price-dependent rate. The instances at which an item is withdrawn from inventory due to demand constitute decision epochs for setting the sales price; the time elapsed between two such consecutive instances is called a period. The sales price at each decision epoch is taken to be a lunction of Tj denoting the remaining lifetime when tin' inventory level drops to z, i = 1,...,Q. The objective is to determine the optimal pricing policy (under the proposed class) and the optimal initial stocking level to maximize the discounted expected profit. A Dynamic Programming approach is used the solve the problem numerically. Using the backward recursion, the optimal price paths are determined for the discounted expected profit for various combinations of remaining lifetimes. Our numerical studies indicate that a single price policy results in significantly lower profits when compared with our formulation.Yıldırım, GoncaM.S

Modelo de gestión de inventarios de medicamentos para un sistema de atención pre-hospitalaria

RESUMEN: Los Servicios de Emergencias Médicas-SEM, son sistemas responsables de la estabilización y transporte pre-hospitalario de pacientes con urgencias y emergencias médicas. Para los SEM la gestión de los medicamentos es indispensable, ya que la disponibilidad y el estado de los mismos afecta costos del servicio y tienen un impacto directo en la seguridad del paciente y en la calidad del servicio. Tomando como referencia a Coomeva Emergencias Médicas, se propone un modelo de gestión de inventarios de medicamentos diseñado específicamente para SEM, el cual, considera las características y necesidades de este tipo de servicios y las características relevantes para la administración de los medicamentos. En el modelo propuesto, se separan los conceptos de reorden y revisión de inventario, y sus parámetros son determinados con base en la adaptación de un modelo de gestión de inventarios con control conjunto y revisión periódica para casos de demanda estocástica, y en revisiones sistemáticas basadas en la priorización del inventario resultante de una Clasificación Multicriterio (CM) de Medicamentos. Las revisiones sistemáticas, reducen el número de referencias de medicamentos que deben ser inspeccionadas por cada turno, generando una secuencia que garantiza la revisión de todo el inventario con base en las prioridades resultantes de la CM

An inventory model for randomly perishing goods

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 2000.Thesis (Master's) -- Bilkent University, 2000.Includes bibliographical references.In this study, we consider an (s, S) ordering policy with backordering for a continuous review inventory system, where the items have a random shelflife. Assuming zero lead time and no decay until the shelflife, we derive the exact expressions for both unit and random batch demand cases with renewal demand arrivals. We present some analytical results on the cost rate function for unit demand case. A detailed numerical analysis is also provided to investigate the performance of the model which incorporates the random shelflife and comparisons with flxed shelflife are given.Yüksel, BanuM.S

Ensuring blood is available when it is needed most

The provision of blood to patients in need is an imperative faced by all countries.  Red blood cells (RBCs) are perishable with a life of 42 days.  Inventory managers at hospitals need to know how many RBCs to order so that the probability of experiencing shortages or outdates is minimised.  This is complicated by demand for RBCs being doubly stochastic.  Both the number of patients that need RBCs and quantity of RBCs they will need are random.  For centralised blood banks not only are the orders they receive from hospitals apparently random, the supply of blood is also random. This thesis shows that, in addition to the previously mentioned sources of volatility, the structure of the supply chain induces further volatility.  This occurs due to the presence of delivery delays and negative feedback loops in two locations within the supply chain.  It is shown how this volatility can be addressed with some simple structural changes.  But simply removing system induced volatility does not imply that the supply chain is optimised.  To address optimality the problem is formulated as a Markov decision process (MDP).  A solution to this process uses Stochastic Dynamic Programming (SDP), but this results in a combinatoric explosion making the computation of an exact solution within a reasonable time impossible.  Instead, Stochastic Average Approximation (SAA) is used to derive an approximate solution.  Repeated, sequential application of this is an exercise in Discrete Time Stochastic Control.  A working control solution is provided in python.  This solution can be arranged so as to mimic the two echelon supply chain found in blood inventories.  It is general enough to apply to any discrete perishable inventory system with random demand and/or supply. The approach for blood inventories requires credible estimates of demand for RBCs.  It is shown, using hierarchical Bayesian modelling and Discrete Phase-Type (DPH) distributions, that credible estimates of demand at hospitals of any size can be derived from publicly available information.  In particular a new method for obtaining the parameters of a DPH distribution is formulated and applied to estimating transfusion quantities from publicly available sources. An application of the proposed solution is presented for RBC inventories at both hospitals and at the blood bank.  For the blood bank in particular it is shown how this can be used to determine the quantity of donors needed to meet demand within a desired probability of adequacy