A new collaboration with Alphabet's Wing will only deliver sandwiches. It demonstrates the tricky parts of taking to the sky. Starting today, eager customers of the US pizza restaurant chain Papa Johns living in one corner of southern North Carolina will have the opportunity to receive their food from the sky, thanks to a new collaboration with Alphabet's drone company, Wing . But Papa Johns' signature pizzas won't be on offer. Instead, drone-loving North Carolinians will have to choose between three kinds of sandwiches, a newer product for the fast-food chain: Philly cheesesteak, chicken bacon ranch, or steak and mushroom varieties.

Home delivery failures, traffic congestion, and relatively large handling times have a negative impact on the profitability of last-mile logistics. These external factors contribute to up to $28\%$ of the overall costs and $25\%$ of emissions for the home delivery supply chain. A potential solution, showing annual growth rates up to $36\%$, is the delivery to parcel lockers or parcel shops, denoted by out-of-home (OOH) delivery. In the academic literature, models of customer behavior with respect to OOH delivery were so far limited to deterministic settings, contrasting with the stochastic nature of actual customer choices. We model the sequential decision-making problem of which OOH location to offer against what incentive for each incoming customer, taking into account future customer arrivals and choices. We propose Dynamic Selection and Pricing of OOH (DSPO), an algorithmic pipeline that uses a novel spatial-temporal state encoding as input to a convolutional neural network. We demonstrate the performance of our method by benchmarking it against three state-of-the-art approaches. Our extensive numerical study, guided by real-world data, reveals that DSPO can save $20.8\%$ in costs compared to a situation without OOH locations, $8.1\%$ compared to a static selection and pricing policy, and $4.6\%$ compared to a state-of-the-art demand management benchmark. We provide comprehensive insights into the complex interplay between OOH delivery dynamics and customer behavior influenced by pricing strategies. The implications of our findings suggest practitioners to adopt dynamic selection and pricing policies as OOH delivery gains a larger market share.

Many e-commerce marketplaces offer their users fast delivery options for free to meet the increasing needs of users, imposing an excessive burden on city logistics. Therefore, understanding e-commerce users' preference for delivery options is a key to designing logistics policies. To this end, this study designs a stated choice survey in which respondents are faced with choice tasks among different delivery options and time slots, which was completed by 4,062 users from the three major metropolitan areas in Japan. To analyze the data, mixed logit models capturing taste heterogeneity as well as flexible substitution patterns have been estimated. The model estimation results indicate that delivery attributes including fee, time, and time slot size are significant determinants of the delivery option choices. Associations between users' preferences and socio-demographic characteristics, such as age, gender, teleworking frequency and the presence of a delivery box, were also suggested. Moreover, we analyzed two willingness-to-pay measures for delivery, namely, the value of delivery time savings (VODT) and the value of time slot shortening (VOTS), and applied a non-semiparametric approach to estimate their distributions in a data-oriented manner. Although VODT has a large heterogeneity among respondents, the estimated median VODT is 25.6 JPY/day, implying that more than half of the respondents would wait an additional day if the delivery fee were increased by only 26 JPY, that is, they do not necessarily need a fast delivery option but often request it when cheap or almost free. Moreover, VOTS was found to be low, distributed with the median of 5.0 JPY/hour; that is, users do not highly value the reduction in time slot size in monetary terms. These findings on e-commerce users' preferences can help in designing levels of service for last-mile delivery to significantly improve its efficiency.

You might say that when it comes to delivery, Amazon is flooding the zone. With Walmart and Target nipping at its heels, the e-commerce giant is determined to win the delivery wars by dropping off packages wherever, and whenever, a shopper might want to receive them. For the first time, this year, Amazon delivered items to Coachella. On a business trip but didn't pack your tie? Hilton Hotels are among the locations where you can have one shipped to an Amazon locker. In Snohomish County, Washington, a robot may bring packages to your door.

The automated aircraft are planned to work alongside Domino's current delivery fleet and will be integrated into its online ordering and GPS systems, according to the firm. Domino's Group CEO and Managing Director, Don Meij, said the company's growth in recent years had led to a "significant increase" in the number of deliveries it needs to make. "With the increased number of deliveries we make each year, we were faced with the challenge of ensuring our delivery times continue to decrease and that we strive to offer our customers new and progressive ways of ordering from us," he said. Research into different delivery methods led Domino's to Flirtey, whose success within the airborne delivery space has been "impressive", the CEO added. The two companies demonstrated their drone pizza delivery service in Auckland, New Zealand, yesterday – an event attended by the country's Civil Aviation Authority and its Minister of Transport Simon Bridges.