How to optimize container withholding decisions for reuse in the hinterland?

This study investigates how a hinterland consignee (importer) makes decisions regarding the storage of empty containers for reuse by a shipper (exporter). The system is modeled as a double-ended queue with non-zero matching times, limited truck resources, and both consignee and shipper having fixed withholding capacities. The consignee's withholding threshold is strategically set to minimize overall transport and detention costs. We derive closed-form expressions for performance measures in the case of a single storage facility at the shipper, utilizing a matrix-based approach. We extend this methodology numerically to the general case. Additionally, we present an accurate fixed-point approximation facilitating the determination of performance measures and optimal threshold. Our findings show the importance of withholding decisions in import and balanced areas for cost reduction. In export areas, a policy of full reuse proves nearly optimal. Analyzing dynamic state-dependent consignee decisions via a Markov decision process, we establish that the optimal policy involves withholding thresholds increasing with stored quantity at the shipper. While optimal, state-dependent thresholds yield limited cost savings compared to a fixed threshold, suggesting minimal impact from consignee-shipper information sharing. Additionally, we examine the influence of variability in matching and production times, observing decreased costs with reduced variability, particularly in export areas, but with minor impacts on withholding decisions.</p

Performance evaluation of stochastic systems with dedicated delivery bays and general on-street parking

As freight deliveries in cities increase due to retail fragmentation and e-commerce, parking is becoming a more and more relevant part of transportation. In fact, many freight vehicles in cities spend more time parked than they are moving. Moreover, part of the public parking space is shared with passenger vehicles, especially cars. Both arrival processes and parking and delivery processes are stochastic in nature. In order to develop a framework for analysis, we propose a queueing model for an urban parking system consisting of delivery bays and general on-street parking spaces. Freight vehicles may park both in the dedicated bays and in general on-street parking, while passenger vehicles only make use of general on-street parking. Our model allows us to create parsimonious insights into the behavior of a delivery bay parking stretch as part of a limited length of curbside. We are able to find explicit expressions for the relevant performance measures, and formally prove a number of monotonicity results. We further conduct a series of numerical experiments to show more intricate properties that cannot be shown analytically. The model helps us shed light onto the effects of allocating scarce urban curb space to dedicated unloading bays at the expense of general on-street parking. In particular, we show that allocating more space to dedicated delivery bays can also make passenger cars better off

On-demand last-mile distribution network design with omnichannel inventory

E-commerce delivery deadlines are getting increasingly tight, driven by a growing ‘I-want-it-now’ instant gratification mindset of consumers and the desire of online and omnichannel retailers to capitalize on the growth of on-demand e-commerce. On-demand deliveries with delivery deadlines as tight as one or two hours force companies to rethink their last-mile distribution network, since tight delivery deadlines require decentralization of order picking and inventory holding to ensure close proximity to consumers. This fundamentally changes the strategic design process of last-mile distribution networks. We study the impact of incorporating inventory order-up-to level decisions into the strategic design process of last-mile distribution networks with tight delivery deadlines. We develop an approximate inventory model by including an estimate of the cost of late delivery and additional transportation due to local stock-outs in a newsvendor formulation. Such local stock-outs require an order to be delivered from a more distant facility, which may lead to late delivery and additional transportation cost. We integrate our approximate inventory model and a location-allocation mixed-integer program that determines optimal facility locations, associated order-up-to inventory levels, and fleet composition, into a metamodel simulation-based optimization approach. Our numerical analyses demonstrate that pooling the additional online inventory with brick-and-mortar (B&amp;M) inventories leads to cannibalization by the B&amp;M network and higher B&amp;M service levels. However, the pooling benefits to the online network outweigh the cost of inventory cannibalization. Furthermore, we show under which circumstances omnichannel retailers may have an incentive to consolidate online inventory in specific B&amp;M facilities

Should I endorse a third party? Authorization strategies for brand manufacturers in a refurbishing market

Original equipment manufacturers (OEM) may have little or no control over third-party (3P) refurbishing firms. With the rapid growth of the refurbished market for electronic products, we study whether it is beneficial for an OEM to cooperate with a 3P via authorization schemes that boost an OEM’s brand reputations, increase their sales, and strengthen consumer acceptance of authorized 3P’s refurbished products. We examine the conditions under which both the OEM and the 3P benefit from the authorization strategy, studying the trade-off between the indirect benefit of authorizing a 3P to increase market share and the downside of cannibalizing new-product sales. To estimate our model’s behavioral parameters, we conduct an extensive experiment on MTurk to capture consumer preferences and cannibalization effects. The experimental study examines the price-perceived quality relationship along with brand value, seller identity (OEM, 3P), and product condition; its results show that the discount and seller identity play a large role in consumer choice and that cannibalization is generally linear in price. We subsequently construct a revenue maximizing model that incorporates this linear cannibalization effect, along with the authorization fees. We show that refurbished products offered by authorized 3Ps have higher demand than those that are not authorized and that it is beneficial for 3Ps to participate in these schemes despite the authorization fees. We conclude that authorization can be a win–win strategy for OEMs and 3Ps, especially when low-end consumer demand and average reduction of refurbishing costs are relatively high, and the level of cannibalization is relatively low. To achieve win–win solutions, it is important for OEMs and 3Ps to consider brand recognition, consumer behavior related to refurbished products, and remanufacturable supply.</p