A decision-making approach for investigating the potential effects of near sourcing on supply chain

Purpose - Near sourcing is starting to be regarded as a valid alternative to global sourcing in order to leverage supply chain (SC) responsiveness and economic efficiency. The present work proposes a decision-making approach developed in collaboration with a leading Italian retailer that was willing to turn the global store furniture procurement process into near sourcing. Design/methodology/approach - Action research is employed. The limitations of the traditional SC organisation and purchasing process of the company are first identified. On such basis, an inventory management model is applied to run spreadsheet estimates where different purchasing and SC management strategies are adopted to determine the solution providing the lowest cost performance. Finally, a risk analysis of the selected best SC arrangement is conducted and results are discussed. Findings - Switching from East Asian suppliers to continental vendors enables a SC reengineering that increases flexibility and responsiveness to demand uncertainty which, together with decreased transportation costs, assures economic viability, thus proving the benefits of near sourcing. Research limitations/implications - The decision-making framework provides a methodological roadmap to address the comparison between near and global sourcing policies and to calculate the savings of the former against the latter. The approach could include additional organisational aspects and cost categories impacting on near sourcing and could be adapted to investigate different products, services, and business sectors. Originality/value - The work provides SC researchers and practitioners with a structured approach for understanding what drives companies to adopt near sourcing and for quantitatively assessing its advantage

Myopic inventory policies using individual customer arrival information

We investigate optimality of myopic policies using the single-unit decomposition approach in inventory management. We derive, under certain conditions, closed-form replenishment decisions, which we call a base-probability policy. That is, the order associated with a given customer is placed if and only if its arrival probability within the lead-time is higher than a threshold.inventory management; base-stock policies; myopic policies;

Capacity Reservation under Spot Market Price Uncertainty

The traditional way of procurement, using long-term contract and capacity reservation, is competing with the escalating global spot market. Considering the variability of the spot prices, the flexibility of combined sourcing can be used to benefit from occasional low short-term spot price levels while the long-term contract is a means to hedge the risk of high spot market price incidents. This contribution focuses on the cost-effective management of the combined use of the above two procurement options. The structure of the optimal combined purchasing policy is complex. In this paper we consider the capacity reservation - base stock policy to provide a simple implementation and comparison to single sourcing options. Our analysis shows that in case of large spot market price variability the combined sourcing is superior over spot market sourcing even in case of low average spot market price and also superior over long-term sourcing even in case of high average spot market price.Capacity reservation; spot market; purchasing policy; supply chain contracts; stochastic inventory control

Dynamic Product Assembly and Inventory Control for Maximum Profit

We consider a manufacturing plant that purchases raw materials for product assembly and then sells the final products to customers. There are M types of raw materials and K types of products, and each product uses a certain subset of raw materials for assembly. The plant operates in slotted time, and every slot it makes decisions about re-stocking materials and pricing the existing products in reaction to (possibly time-varying) material costs and consumer demands. We develop a dynamic purchasing and pricing policy that yields time average profit within epsilon of optimality, for any given epsilon>0, with a worst case storage buffer requirement that is O(1/epsilon). The policy can be implemented easily for large M, K, yields fast convergence times, and is robust to non-ergodic system dynamics.Comment: 32 page

MRP-based negotiation in customer-supplier relationship

In the present uncertain context, increasing the performance of the supply chains requires to define cooperative processes between partners aiming at providing a better answer to the final customer, with a risk shared between partners. Based on an analysis of real practices, we suggest in this communication to take the MRP process as a basis for defining what could be such a cooperative process

Why markdown as a pricing modality?

Markdown as a pricing modality is ubiquitous in retail whereas everyday low price (EDLP) remains relatively rare (despite its several advantages, such as simplicity). This paper explores whether and why retailers can use either of these pricing modalities as an effective defense against a competitor entering the market with the alternative pricing modality. Various studies have shown that consumers are strategic and heterogeneous in their valuation of a product. Consumers are also shown to be regret-prone, and anticipation of regret affects their purchase decisions. Consumers experience availability regret when they are unable to purchase products due to stockouts and high-price regret when they miss an opportunity to purchase products at low prices. Considering such factors, consumers decide whether, when, and from which retailer to purchase the product. In such a market environment, we find that the possible entry of a competitor should deter retailers from using the EDLP pricing modality but not markdown. We also identify a new reason for the markdown retailer to ration stock (in addition to the reason for discouraging consumers to wait for the markdown). In particular, we show that the markdown retailer can use inventory rationing to preclude a cutthroat competition and bankruptcy after the entry of an EDLP retailer. We also quantify how consumer regret affects both retailers' decisions and resulting profits. In particular, in a competitive market, the EDLP retailer cannot simply disregard consumers' availability and high-price regret (even when it stocks ample inventory and does not discount prices). We show that high-price regret and availability regret have complementary effects on the markdown retailer's rationing strategy and the EDLP retailer's price decision. Finally, using a proprietary price data set from a large department store, we show that ignoring regret factors causes the markdown retailer to leave up to 20% of its profits on the table. In addition, in a competitive market, the markdown retailer rations too aggressively when regret is ignored and, as a result, leaves some of the forgone profit to its competitor-the EDLP retailer. The retail industry is often characterized by its slim profit margins. In such an environment, the aforementioned results also suggest that retailers should seriously consider investing in developing the capacity to estimate and quantify the role of regret in consumers' purchase decisions

Determination of recovery effort for a probabilistic recovery system under various inventory control policies

In this study we investigate the desired level of recovery under various inventory control policies when the success of recovery is probabilistic. Recovery process is modelled as a single stage operation and recovery effort is represented by the expected time spent for it. The effect of increasing recovery effort on the success probability together with unit cost of the operation is included by assuming general forms of dependencies. The desired level of recovery is investigated under four inventory control policies for a wide range of system parameters. In this article, we present our computational results and their managerial implications.inventory control;probabilistic recovery

End-of-Life Inventory Decisions for Consumer Electronics Service Parts

We consider a consumer electronics (CE) manufacturer’s problem of controlling the inventoryof spare parts in the final phase of the service life cycle. The final phase starts when thepart production is terminated and continues until the last service contract or warranty periodexpires. Placing final orders for service parts is considered to be a popular tactic to satisfy demandduring this period and to mitigate the effect of part obsolescence at the end of the servicelife cycle. To satisfy demand for service in the final phase, previous research focuses on repairingdefective products by replacing the defective parts with properly functioning spare ones.However, for consumer electronic products there is a remarkable price erosion while repaircosts may stay steady over time. As a consequence, this introduces the idea that there mightbe a point in time at which the unit price of the product is lower than repair associated costs.Therefore, it would be more cost effective to adopt an alternative policy to meet demands forservice such as offering customers a replacement of the defective product with a new one orgiving a discount on the next generation of the product. This paper examines the cost trade-offsof implementing alternative policies for the repair policy and develops an exact formulation forthe expected total cost function. Based on this developed cost function we propose policies tosimultaneously find the optimal final order quantity and the time to switch from the repair toan alternative replacement policy. Numerical analysis of a real world case study sheds lightover the effectiveness and advantage of these policies in terms of cost reduction and also yieldsinsights into the quantitative importance of the various cost parameters.consumer electronics;end-of-life inventory control;service parts