For the Public's Health: The Role of Measurement in Action and Accountability

Outlines a framework for the collection, analysis, and dissemination of population health data that help assess the social, economic, and environmental factors affecting health to increase clinical effectiveness and enhance government accountability

Mediating effects of broadband consumers’ behavior in India

Internet usage is rapidly growing in areas like cosmopolitan cities, semi-urban cities in India. I-enabled services offered by various government agencies, educational institutions and commercial activities force users of these services to seek superior internet access like broadband, WiMax is likely to replace traditional broadband and dial-up access soon. Interestingly, reforms in telecom sector are taking place at a rapid pace in India. Many private players started internet services affecting monopolistic public sector telecoms. The advent of private ISPs, the consumer behavior and brand choice of broadband consumers are witnessing dynamic shift in favor of private players. Cost competitiveness, transparency, paradigm shift in consumer responsiveness etc weigh in favor of Public Sector telecoms. This paper attempts to identify the factors affecting broadband consumer behavior. Further, paper studies the causes and effects, mediating effects of consumer behavior and conceptualizes a model to capture these effects. The results suggest that adoption of broadband service is playing a mediatory role in consumer satisfaction.Broadband, Adoption, Normative constructs, mediating

The Role of the Mangement Sciences in Research on Personalization

We present a review of research studies that deal with personalization. We synthesize current knowledge about these areas, and identify issues that we envision will be of interest to researchers working in the management sciences. We take an interdisciplinary approach that spans the areas of economics, marketing, information technology, and operations. We present an overarching framework for personalization that allows us to identify key players in the personalization process, as well as, the key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We review extant literature in the strategic behavior of firms, and discuss opportunities for analytical and empirical research in this regard. Next, we examine how a firm can learn a customer's preferences, which is one of the key components of the personalization process. We use a utility-based approach to formalize such preference functions, and to understand how these preference functions could be learnt based on a customer's interactions with a firm. We identify well-established techniques in management sciences that can be gainfully employed in future research on personalization.CRM, Persoanlization, Marketing, e-commerce,

Challenges for Water Researchers in Alberta in a Climate of Policy Uncertainty

A safe and plentiful supply of surface water is crucial to the well-being of every resident of Alberta. The effective and efficient use of surface water is central to economic growth and environmental sustainability. As the necessary but competing demands on surface water intensify, the awareness of its limited supply increases. This is particularly evident in southern Alberta, which has experienced significant agricultural, industrial and population growth. In addition to its use for extensive irrigation, surface water in the South Saskatchewan River basin is vital to meet drinking and sanitation needs in rural and urban communities. Management of this key resource involves many researchable issues– water supply, water treatment, water distribution, wastewater collection and processing, flood control, navigation, hydropower production, aquatic recreation – which interact with each other and with government policies. The purpose of this article is to outline the priorities for socio-economic research on surface water resource issues in light of the ever-changing legal and policy frameworks in Alberta.Resource /Energy Economics and Policy,

Unbiased Learning for the Causal Effect of Recommendation

Increasing users' positive interactions, such as purchases or clicks, is an important objective of recommender systems. Recommenders typically aim to select items that users will interact with. If the recommended items are purchased, an increase in sales is expected. However, the items could have been purchased even without recommendation. Thus, we want to recommend items that results in purchases caused by recommendation. This can be formulated as a ranking problem in terms of the causal effect. Despite its importance, this problem has not been well explored in the related research. It is challenging because the ground truth of causal effect is unobservable, and estimating the causal effect is prone to the bias arising from currently deployed recommenders. This paper proposes an unbiased learning framework for the causal effect of recommendation. Based on the inverse propensity scoring technique, the proposed framework first constructs unbiased estimators for ranking metrics. Then, it conducts empirical risk minimization on the estimators with propensity capping, which reduces variance under finite training samples. Based on the framework, we develop an unbiased learning method for the causal effect extension of a ranking metric. We theoretically analyze the unbiasedness of the proposed method and empirically demonstrate that the proposed method outperforms other biased learning methods in various settings.Comment: accepted at RecSys 2020, updated several experiment

Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices

Hybrid cloud provides an attractive solution to microservices for better resource elasticity. A subset of application components can be offloaded from the on-premises cluster to the cloud, where they can readily access additional resources. However, the selection of this subset is challenging because of the large number of possible combinations. A poor choice degrades the application performance, disrupts the critical services, and increases the cost to the extent of making the use of hybrid cloud unviable. This paper presents Atlas, a hybrid cloud migration advisor. Atlas uses a data-driven approach to learn how each user-facing API utilizes different components and their network footprints to drive the migration decision. It learns to accelerate the discovery of high-quality migration plans from millions and offers recommendations with customizable trade-offs among three quality indicators: end-to-end latency of user-facing APIs representing application performance, service availability, and cloud hosting costs. Atlas continuously monitors the application even after the migration for proactive recommendations. Our evaluation shows that Atlas can achieve 21% better API performance (latency) and 11% cheaper cost with less service disruption than widely used solutions.Comment: To appear at EuroSys 202

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations