Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data

This paper analyzes consumer choices over lunchtime restaurants using data from a sample of several thousand anonymous mobile phone users in the San Francisco Bay Area. The data is used to identify users' approximate typical morning location, as well as their choices of lunchtime restaurants. We build a model where restaurants have latent characteristics (whose distribution may depend on restaurant observables, such as star ratings, food category, and price range), each user has preferences for these latent characteristics, and these preferences are heterogeneous across users. Similarly, each item has latent characteristics that describe users' willingness to travel to the restaurant, and each user has individual-specific preferences for those latent characteristics. Thus, both users' willingness to travel and their base utility for each restaurant vary across user-restaurant pairs. We use a Bayesian approach to estimation. To make the estimation computationally feasible, we rely on variational inference to approximate the posterior distribution, as well as stochastic gradient descent as a computational approach. Our model performs better than more standard competing models such as multinomial logit and nested logit models, in part due to the personalization of the estimates. We analyze how consumers re-allocate their demand after a restaurant closes to nearby restaurants versus more distant restaurants with similar characteristics, and we compare our predictions to actual outcomes. Finally, we show how the model can be used to analyze counterfactual questions such as what type of restaurant would attract the most consumers in a given location.Marie Curie Fellowship from the European Commission (H2020 programme, grant agreement 706760)

Needs for an Expanded Ontology‐Based Classification of Adverse Drug Reactions and Related Mechanisms

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110048/1/cptclpt201241.pd

Predation on stink bugs (Hemiptera: Pentatomidae) in cotton and soybean agroecosystems

Stink bugs (Hemiptera: Pentatomidae) are significant pests of cotton and soybeans in the southeastern United States with annual control costs exceeding $14 million in these crops. Three of the most prominent stink bug pests are the southern green (Nezara viridula), brown (Euschistus servus) and green (Chinavia hilaris) stink bugs. To determine trophic linkages between generalist arthropod predators and these pests, species-specific 16S molecular markers were designed and used to detect the presence of prey DNA in predator gut-contents. Over 2700 predators were collected over two growing seasons in cotton and soybean in southern Georgia in 2011 and 2012 and screened for stink bug DNA. Trophic linkages were analyzed relative to prey availability, crop type and field location. The frequency of stink bug DNA in predator guts was negligible on E. servus (0.23%) and C. hilaris (0.09%). Overall gut content detection of N. viridula was 3.3% and Geocoris sp. (Hemiptera: Geocoridae), Orius sp. (Hemiptera: Anthocoridae) and Notoxus monodon (Coleoptera: Anthicidae) were the primary predators. This contrasts with previous studies that reported a much more diverse suite of predators consuming stink bugs with much higher frequency of gut-content positives. The discrepancy between studies highlights the need for replicating studies in space and time, especially if the goal is to implement effective and durable conservation biological control in integrated pest management

GSP with General Independent Click-Through-Rates

The popular generalized second price (GSP) auction for sponsored search is built upon a separable model of click-through-rates that decomposes the likelihood of a click into the product of a "slot effect" and an "advertiser effect" --- if the first slot is twice as good as the second for some bidder, then it is twice as good for everyone. Though appealing in its simplicity, this model is quite suspect in practice. A wide variety of factors including externalities and budgets have been studied that can and do cause it to be violated. In this paper we adopt a view of GSP as an iterated second price auction (see, e.g., Milgrom 2010) and study how the most basic violation of separability --- position dependent, arbitrary public click-through-rates that do not decompose --- affects results from the foundational analysis of GSP (Varian 2007, Edelman et al. 2007). For the two-slot setting we prove that for arbitrary click-through-rates, for arbitrary bidder values, an efficient pure-strategy equilibrium always exists; however, without separability there always exist values such that the VCG outcome and payments cannot be realized by any bids, in equilibrium or otherwise. The separability assumption is therefore necessary in the two-slot case to match the payments of VCG but not for efficiency. We moreover show that without separability, generic existence of efficient equilibria is sensitive to the choice of tie-breaking rule, and when there are more than two slots, no (bid-independent) tie-breaking rule yields the positive result. In light of this we suggest alternative mechanisms that trade the simplicity of GSP for better equilibrium properties when there are three or more slots

High-throughput next-generation sequencing technologies foster new cutting-edge computing techniques in bioinformatics

The advent of high-throughput next generation sequencing technologies have fostered enormous potential applications of supercomputing techniques in genome sequencing, epi-genetics, metagenomics, personalized medicine, discovery of non-coding RNAs and protein-binding sites. To this end, the 2008 International Conference on Bioinformatics and Computational Biology (Biocomp) – 2008 World Congress on Computer Science, Computer Engineering and Applied Computing (Worldcomp) was designed to promote synergistic inter/multidisciplinary research and education in response to the current research trends and advances. The conference attracted more than two thousand scientists, medical doctors, engineers, professors and students gathered at Las Vegas, Nevada, USA during July 14–17 and received great success. Supported by International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design (IJCBDD), International Journal of Functional Informatics and Personalized Medicine (IJFIPM) and the leading research laboratories from Harvard, M.I.T., Purdue, UIUC, UCLA, Georgia Tech, UT Austin, U. of Minnesota, U. of Iowa etc, the conference received thousands of research papers. Each submitted paper was reviewed by at least three reviewers and accepted papers were required to satisfy reviewers' comments. Finally, the review board and the committee decided to select only 19 high-quality research papers for inclusion in this supplement to BMC Genomics based on the peer reviews only. The conference committee was very grateful for the Plenary Keynote Lectures given by: Dr. Brian D. Athey (University of Michigan Medical School), Dr. Vladimir N. Uversky (Indiana University School of Medicine), Dr. David A. Patterson (Member of United States National Academy of Sciences and National Academy of Engineering, University of California at Berkeley) and Anousheh Ansari (Prodea Systems, Space Ambassador). The theme of the conference to promote synergistic research and education has been achieved successfully

Monitoring and Pay: An Experiment on Employee Performance under Endogenous Supervision

We present an experimental test of a shirking model where monitoring intensity is endogenous and effort a continuous variable. Wage level, monitoring intensity and consequently the desired enforceable effort level are jointly determined by the maximization problem of the firm. As a result, monitoring and pay should be complements. In our experiment, between and within treatment variation is qualitatively in line with the normative predictions of the model under standard assumptions. Yet, we also find evidence for reciprocal behavior. Our data analysis shows, however, that it does not pay for the employer to solely rely on the reciprocity of employees

Risk factors for delay in symptomatic presentation: a survey of cancer patients

Background: Delay in symptomatic presentation leading to advanced stage at diagnosis may contribute to poor cancer survival. To inform public health approaches to promoting early symptomatic presentation, we aimed to identify risk factors for delay in presentation across several cancers. Methods: We surveyed 2371 patients with 15 cancers about nature and duration of symptoms using a postal questionnaire. We calculated relative risks for delay in presentation (time from symptom onset to first presentation >3 months) by cancer, symptoms leading to diagnosis and reasons for putting off going to the doctor, controlling for age, sex and deprivation group. Results: Among 1999 cancer patients reporting symptoms, 21% delayed presentation for >3 months. Delay was associated with greater socioeconomic deprivation but not age or sex. Patients with prostate (44%) and rectal cancer (37%) were most likely to delay and patients with breast cancer least likely to delay (8%). Urinary difficulties, change of bowel habit, systemic symptoms (fatigue, weight loss and loss of appetite) and skin symptoms were all common and associated with delay. Overall, patients with bleeding symptoms were no more likely to delay presentation than patients who did not have bleeding symptoms. However, within the group of patients with bleeding symptoms, there were significant differences in risk of delay by source of bleeding: 35% of patients with rectal bleeding delayed presentation, but only 9% of patients with urinary bleeding. A lump was a common symptom but not associated with delay in presentation. Twenty-eight percent had not recognised their symptoms as serious and this was associated with a doubling in risk of delay. Embarrassment, worry about what the doctor might find, being too busy to go to the doctor and worry about wasting the doctor’s time were also strong risk factors for delay, but were much less commonly reported (<6%). Interpretation: Approaches to promote early presentation should aim to increase awareness of the significance of cancer symptoms and should be designed to work for people of the lowest socioeconomic status. In particular, awareness that rectal bleeding is a possible symptom of cancer should be raised

Pricing in Online Auction Procurement: A Review of Empirical Methods and Current Understandings

The online auction has become an important channel for procurement and sourcing management. As firms often expect lower procurement prices through online auctions, how the prices are determined in online auctions should be of major interest to procurement managers and supply chain researchers. Despite the abundant empirical studies on online auction prices, an aggregated view is still absent. This study fills this gap with a review of extant studies. More specifically, this study provides summaries of all major theories behind online auction pricing, defines and analyzes often encountered econometric issues, and discusses how the treatments of these issues have been operationalized. Towards the end, existing findings on determinants of online auction prices are integrated and examined. The purpose of this study is to provide a convenient and precise package of current studies for researchers and professional

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine

Testing for Complementarity: Glyphosate Tolerant Soybeans and Conservation Tillage

Many decisions in agriculture are made over combinations of inputs and/or practices that may form a technology system linked through complementarity. The presence of complementarity among producer decisions can have far-reaching implications for market outcomes and for the effectiveness of policies intended to influence them. Identifying complementarity relations, however, is made difficult by the presence of unobserved heterogeneity. Drawing on recent methodological advances, in this paper we develop a test for complementarity between glyphosate tolerant soybeans and conservation tillage that overcomes certain limitations of previous studies. Specifically, we develop a structural discrete choice framework of joint soybean-tillage adoption that explicitly models both complementarity and the correlation induced by unobserved heterogeneity. The model is estimated with a large unbalanced panel of farm-level choices spanning the 1998–2011 period. We find that glyphosate tolerant soybeans and conservation tillage are complementary practices. In addition, our estimation shows that farm operation scale promotes the adoption of both conservation tillage and glyphosate tolerant seed, and that all of higher fuel prices, more droughty conditions, and soil erodibility increase use of conservation tillage. We apply our results to simulate annual adoption rates for both conservation tillage and no-tillage in a scenario without glyphosate tolerant soybeans available as a choice. We find that the adoption of conservation tillage and no-tillage have been about 10% and 20% higher, respectively, due to the advent of glyphosate tolerant soybeans