The direct‐from‐model and tool‐less manufacturing process of 3D printing (3DP) embodies a general‐purpose technology, facilitating capacity sharing and outsourcing. Starting from a case study of a 3DP company (Shapeways) and a new market entrant (Panalpina), we develop dynamic practices for partial outsourcing in build‐to‐model manufacturing. We propose a new outsourcing scheme, bidirectional partial outsourcing (BPO), where 3D printers share capacity by alternating between the role of outsourcer and subcontractor based on need. Coupled with order book smoothing (OBS), where orders are released gradually to production, this provides 3D printers with two distinct ways to manage demand variability. By combining demand and cost field data with an analytical model, we find that BPO improves 3DP cost efficiency and delivery performance as the number of 3DP firms in the network increases. OBS is sufficient for an established 3D printer when alternatives to in‐house manufacturing are few, or of limited capacity. Nevertheless, OBS comes at the cost of reduced responsiveness, whereas BPO shifts the cost and delivery performance frontier. Our analysis shows how BPO combined with OBS makes 3DP companies more resilient to downward movements in both demand and price levels.

Purpose -The positioning of the customer order decoupling point (CODP) is an important strategic consideration for supply chains. Recently, research has focused only on the static effects of CODP positioning. The purpose of this paper is to expand the body of knowledge by describing the dynamic consequences that arise from shifting the CODP upstream or downstream. Design/methodology/approach -A generic assembly-to-order system dynamics simulation model is developed and used to evaluate the dynamic consequences of shifting the CODP. Findings -Placing the CODP downstream allows for short-term fluctuations in demand to be absorbed by the order book, leading to a stable production rate and inventory response. This benefit must, however, be weighed against any additional safety stock a CODP placed far downstream may require.Research limitations/implications -The paper demonstrates the importance of considering the dynamic aspects of CODP positioning. Further research should investigate the phenomenon for different demand scenarios and supply chain configurations. Practical implications -Downstream shifting of the CODP has been identified as a powerful way to reduce variability in assembly-to-order systems. Originality/value -This paper introduces the dynamic consequences of CODP location, providing a new perspective that should be considered when positioning the CODP.

Food waste has become a major concern globally, leading to high economic, environmental and social awareness, as well as inclusion in international policy documents. In the developed world, the retail stage has the greatest potential for waste reduction as it balances demand with supply, stimulates demand (thus affecting waste at the consumer level) and sets standards to the supply and the products (thus affecting food loss upstream). To precisely direct managerial intervention towards products with high waste-mitigation potential, the waste impact needs to be quantified. Previous studies measuring waste have examined individual metrics exclusive of each other, which affects the ranking of products. The present study proposes a method for prioritising waste based on combined monetary and environmental indicators, and it demonstrates the applicability of the method through empirical data from Scandinavian retail stores. The contribution of the proposed metric is that it results in a unique score comprising economic and environmental impacts for every single product, thus directing the managerial intervention more precisely. In addition, it enables choosing a weight for the economic and the environmental indicators, thus adding to the previous literature that looks at the products either through an economic or environmental perspective, exclusive of each other. Applying the method confirmed the previous research at a product group level that bread, meat and fruits/vegetables are the highest wasters. In addition, for some products, such as meat and fruit, the dependency between economic and environmental impacts is weaker, whereas it is stronger for others (e.g. bread and biscuits), thereby necessitating a method to gauge waste in both dimensions.

We investigate the inventory service metric known as the fill rate-the proportion of demand that is immediately fulfilled from inventory. The task of finding analytical solutions for general cases is complicated by a range of factors including; correlation in demand, double counting of backlogs, and proper treatment of negative demand. In the literature, two approximate approaches are often proposed. Our contribution is to present a new fill rate measure for normally distributed, autocorrelated, and possibly negative demand. We treat negative demand as returns. Our approach also accounts for accumulated backlogs. The problem reduces to identifying the minimum of correlated normally distributed bivariate random variables. There exists an exact solution, but it has no closed form. However, the solution is amenable to numerical techniques, and we present a custom Microsoft Excel function for practical use. Numerical investigations reveal that the new fill rate is more robust than previous measures. Existing fill rate measures are likely to cause excessive inventory investment, especially when fill rate targets are modest, a strongly positive or negative autocorrelation in demand is present, or negative demands exist. Our fill rate calculation ensures that the target fill rate is achieved without excessive inventory investments.

Production plans often span a whole week or month, even when independent production lots are completed every day and service performance is tallied daily. Such policies are said to use staggered deliveries, meaning that the production rate for multiple days are determined at a single point in time. Assuming autocorrelated demand, and linear inventory holding and backlog costs, we identify the optimal replenishment policy for order cycles of length P. With the addition of a once-per-cycle audit cost, we optimize the order cycle length P * via an inverse-function approach. In addition, we characterize periodic inventory costs, availability, and fill rate. As a consequence of staggering deliveries, the inventory level becomes cyclically heteroskedastic. This manifests itself as ripples in the expected cost and service levels. Nevertheless, the cost-optimal replenishment policy achieves a constant availability by using time-varying safety stocks; this is not the case with suboptimal constant safety stock policies, where the availability fluctuates over the cycle.