We propose a modeling framework for the data generating process of waste disposal in recyclable waste containers. It is based on a discrete mixture of count data models representing populations depositing dierent quantities in the containers, thus reflecting a realistic underlying behavior. It is tested on real data coming from ultrasound sensors mounted inside the containers and exhibits better in- and out-of-sample performance compared to a simple count data model assuming only one deposit quantity. The purpose of the mixture model is to forecast container waste levels at a future date when collection will take place. It thus becomes the first-step ingredient in a framework for ecient waste collection optimization.
We consider a mix transportation problem, which allows to combine a multi-modal public and a ride-sharing transports, in a dynamic environment. The main idea of our approach consists in labelling interesting nodes of a geographical map with information about either riders or drivers, in so-called buckets. Based on the information contained in these buckets, we compute admissible ride-sharing possibilities. To restrict the needed amount of memory, among the different stops along a public transportation path, we only consider the transshipment nodes, where travellers have to make a change between two modes. Each of those stops are potential pick-up or drop-off stops for ride-sharing. We consider a drivers’ maximal waiting time, as well as the maximal driving detour time depending on the actual drive. Each new drive activates a search for new ride-sharing of existing riders. Each new ride activates another process which searches for potential drivers. Among all admissible ride-sharing possibilities, only those which best improve the earliest arrival time are selected. We provide numerical results using real road network of the Lorraine region (FR) and real data provided by a local company. Our numerical experiment shows a running time of a few seconds, suitable for a new real-time transportation application.
This article describes a multi-modal routing problem, which occurs each time a user wants to travel from a point A to a point B, using either ride-sharing or public transportation. The main idea is to start from an itinerary using public transportation, and then substitute part of this itinerary by ride-sharing. We first define a closeness estimation between the user’s itinerary and available drivers. This allows to select a subset of potential drivers. We then compute sets of driving quickest paths, and design a substitution process. Finally, among all admissible solutions, we select the best one based on the earliest arrival time. We provide numerical results using benchmarks based on geographical maps, public transportation timetabling and simulated requests and driving paths. Our numerical experiment shows a running time of a few seconds, suitable for a new real-time transportation application.
Policy makers have an increasing interest in designing appropriate public R&D policy programs to stimulate national innovativeness and competitiveness. First, this study investigates the effects of public R&D subsidies on firms’ R&D investments accounting for the collaboration pattern of the subsidized firms. Second, this representative analysis further puts light on the effectiveness of the publicly induced R&D investment, and examines if the policy-induced investments translate into higher innovation performance, thereby disentangling between radical and incremental innovation. The treatment effects analysis uses firm level data from five waves (1999, 2002, 2005, 2008, and 2011) of the Swiss innovation survey. The findings show that on average the receipt of an R&D subsidy translate into higher firm R&D investments. While the results do not exhibit any additional systemic positive support for collaboration in the presence of a subsidy, the publicly induced R&D investment mainly foster radical innovation output.
This paper proposes a `re-construction' of organization studies in order to deal with the chronic incommensurability that characterizes the discipline. The paper begins by discussing the issue of incommensurability between organization studies schools of thought, arguing that it represents a significant problem with which the field must cope. Ambiguity of the key constructs that form the building blocks of organization studies schools is identified as one major reason for persistent inter-school incommensurability. To help deal with the problem, we recommend the creation of a dictionary that would include democratically produced definitions of key organization studies constructs. The procedures used by the Financial Accounting Standards Board to develop new accounting standards are presented as a possible model for the dictionary-building process. The role of the dictionary in reducing inter-school incommensurability is discussed, and possible disadvantages considered. While the need to formally create construct definitions is symptomatic of the low paradigm development of organization studies, the dictionary is envisioned as a tool for increasing the future paradigm development of the field.
