HEC Montréal

About: HEC Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Vehicle routing problem & Corporate governance. The organization has 1221 authors who have published 5708 publications receiving 196862 citations. The organization is also known as: Ecole des Hautes Etudes Commerciales de Montreal & HEC Montreal.

How Logistics Can Service Healthcare

Abstract: The impact of supply chain integration has been well documented in numerous industries. Healthcare is no exception: Efficient Healthcare Consumer Response> (EHCR) in the late 90s projected US$11 billion in savings in supply chain related costs in the United States alone. However, we believe that external supply chain integration initiatives are drawing most of the attention, while the internal supply chain of hospitals remains the sore spot or weak link in supply chain integration. In view of the many pressures worldwide to reduce the cost of healthcare, as well as the difficulties of adapting healthcare systems to meet the growing needs of an aging population, new illnesses and cures and a severe shortage of nursing staff, this paper offers new management ideas based on case study research of leading international practices to better understand the role and impact of logistics in healthcare. It also presents examples of how to better integrate logistics activities through a unique combination of reengine...

Tenure in Office and Public Procurement

Abstract: We study the impact of politicians' tenure in office on the outcomes of public procurement. To this purpose, we match a data set on the politics of Italian municipal governments to a data set on the procurement auctions they administered. In order to identify a causal relation, we apply two different identification strategies. First, we compare elections where the incumbent mayor barely won another term, with elections where the incumbent mayor barely lost and a new mayor took over. Second, we cross-validate these estimates using a unique quasi-experiment determined by the introduction of a two-term limit on the mayoral office in March 1993. This reform granted one potential extra term to mayors appointed before the reform. The main result is that an increase in the mayor's tenure is associated with ``worse' outcomes: fewer bidders per auction, a higher cost of procurement, a higher probability that the winner is local and that the same firm is awarded repeated auctions. Taken together, our estimates are informative of the possibility that time in office progressively leads to collusion between government officials and a few favored local bidders. Other interpretations receive less support in the data.

Investigating sponsorship effectiveness: Do less familiar brands have an advantage over more familiar brands in single and multiple sponsorship arrangements?

Abstract: Using a human associative memory (HAM) framework, the authors assessed the influence of single and multiple sponsorship arrangements on consumers' attitudes and purchase intentions In addition, the authors investigated the role of familiarity with the sponsoring brand in sponsorship effectiveness Using different levels of sponsoring brand familiarity (high versus low) and sponsorship conditions (single versus multiple), a between-subjects experimental design revealed that the effects of sponsorship on attitudes and purchase intentions were greater for low familiarity sponsoring brands than for high familiarity sponsoring brands Moreover, the impact of sponsorship on attitudes and purchase intentions was not diluted in the case of multiple sponsorships compared to a single sponsorship Implications and directions for further research are discussed

The early explanatory power of NDVI in crop yield modelling

Abstract: The objective of this paper is to study, on a weekly basis, the explanatory power of one satellite-based measurement, the Normalized Difference Vegetation Index (NDVI), for wheat yield modelling in 40 census agricultural regions (CAR) in the Canadian Prairies during the whole growing season using 16 years of NOAA AVHRR satellite data (between 1987 and 2002). We also explore the relative value of NDVI compared with a land-based measurement, the Cumulative Moisture Index (CMI). By developing a series of weekly wheat yield models over the course of the growing season, we are able to determine the accuracy of different models. Our findings indicate that NDVI possesses explanatory power 4 weeks earlier in the season than CMI.

Session-based Social Recommendation via Dynamic Graph Attention Networks

Abstract: Online communities such as Facebook and Twitter are enormously popular and have become an essential part of the daily life of many of their users. Through these platforms, users can discover and create information that others will then consume. In that context, recommending relevant information to users becomes critical for viability. However, recommendation in online communities is a challenging problem: 1) users' interests are dynamic, and 2) users are influenced by their friends. Moreover, the influencers may be context-dependent. That is, different friends may be relied upon for different topics. Modeling both signals is therefore essential for recommendations. We propose a recommender system for online communities based on a dynamic-graph-attention neural network. We model dynamic user behaviors with a recurrent neural network, and context-dependent social influence with a graph-attention neural network, which dynamically infers the influencers based on users' current interests. The whole model can be efficiently fit on large-scale data. Experimental results on several real-world data sets demonstrate the effectiveness of our proposed approach over several competitive baselines including state-of-the-art models.