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Recently, the French Senate approved a law that imposes a 3% tax on revenue generated from digital services by companies above a certain size. While there is a lot of political debate about economic consequences of this action, it is…
A well-established approach for inferring full displacement and stress fields from possibly sparse data is to calibrate the parameter of a given constitutive model using a Bayesian update. After calibration, a (stochastic) forward…
In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise.…
Multi-echelon parcel delivery systems using electric vehicles (EVs) are crucial for managing urban logistics complexity and promoting sustainability. In multi-echelon systems, particularly within two-stage systems, larger vehicles transport…
This paper presents an integrated algorithmic framework for minimising product delivery costs in e-commerce (known as the cost-to-serve or C2S). One of the major challenges in e-commerce is the large volume of spatio-temporally diverse…
This paper presents an online reinforcement learning based application which increases the revenue of one particular electric vehicles (EV) station, connected to a renewable source of energy. Moreover, the proposed application adapts to…
Existing language models excel at writing from scratch, but many real-world scenarios require rewriting an existing document to fit a set of constraints. Although sentence-level rewriting has been fairly well-studied, little work has…
In this work, we study a scenario where a publisher seeks to maximize its total revenue across two sales channels: guaranteed contracts that promise to deliver a certain number of impressions to the advertisers, and spot demands through an…
With the growing needs of online A/B testing to support the innovation in industry, the opportunity cost of running an experiment becomes non-negligible. Therefore, there is an increasing demand for an efficient continuous monitoring…
To alleviate traffic congestion that results from the growth of e-commerce we propose an approach in the city of Linz, Austria by relying on shared distribution centers from different companies. We develop two algorithms to find out the…
When delivering items to a set of destinations, one can save time and cost by passing a subset to a sub-contractor at any point en route. We consider a model where a set of items are initially loaded in one vehicle and should be distributed…
Plug-in electric vehicles are receiving global attention. However, large-scale plug-in electric vehicles bring challenge to charging station deployment. This paper provides a deployment evaluation method and a planning method for plug-in…
Motivated by the application of real-time pricing in e-commerce platforms, we consider the problem of revenue-maximization in a setting where the seller can leverage contextual information describing the customer's history and the product's…
Quick commerce (q-commerce) is one of the fastest growing sectors in India. It provides informal employment to approximately 4,50,000 workers, and it is estimated to become a USD 200 Billion industry by 2026. A significant portion of this…
This paper presents the behavioral study's results on willingness-to-pay the extra money by the customers for e-groceries deliveries based on crowd-shipping. The proposed methodology was tested for Ukraine, i.e., a developing country where…
We consider the problem of unsupervised domain adaptation for semantic segmentation by easing the domain shift between the source domain (synthetic data) and the target domain (real data) in this work. State-of-the-art approaches prove that…
Despite the increasing integration of the global economic system, anti-dumping measures are a common tool used by governments to protect their national economy. In this paper, we propose a methodology to detect cases of anti-dumping…
We study distributional off-policy evaluation (OPE), of which the goal is to learn the distribution of the return for a target policy using offline data generated by a different policy. The theoretical foundation of many existing work…
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…
This paper explores a GIS-based application of the conditional p-median problem (where p = 1) in last-mile delivery logistics. The rapid growth of e-commerce in Pakistan has primarily benefited logistics companies, which face the challenge…