Estimating a Model of Strategic Store-Network Choice

Competition among multi-store chains is common in retail industries. This paper proposes a method for eliminating a model of strategic store-network choices by two chains. In contrast to previous studies, I allow chains to not only choose which markets to enter but also how many stores to open in each of those markets. I use lattice-theoretical results to deal with the huge number of possible network choices. I show that a chain's net trade-off between costs and benefits from clustering their stores in a market can be either positive or negative while still enduring the existence of an equilibrium. By doing so, the model provides a way to freely estimate this within-market effect from the data. Incorporating revenue data allows us to interpret parameters in monetary units and to decompose the within-market effect into cost savings from clustering stores (economics of density) and lost revenues from competition with one's own stores (own-chain business-stealing effect). I apply the technique to a new data set from the convenience-store industry in Okinawa, Japan. Parameter estimates confirm that own chain business-stealing is an important consideration for a chain. I then use the estimated structural model to perform two counterfactual analyses. First, I consider a hypothetical merger of two chains and find that the merger would decrease the number of stores and total sales, and raise the acquirer's profits thereby reallocating surplus from consumers to the acquirer. Second, I examine how eliminating the zoning regulation introduced in Japan in 1968, which has been at the forefront of urban policy debates, affects store-network choices

Estimating a Model of Strategic Store-Network Choice

Competition among multi-store chains is common in retail industries. This paper proposes a method for eliminating a model of strategic store-network choices by two chains. In contrast to previous studies, I allow chains to not only choose which markets to enter but also how many stores to open in each of those markets. I use lattice-theoretical results to deal with the huge number of possible network choices. I show that a chain's net trade-off between costs and benefits from clustering their stores in a market can be either positive or negative while still enduring the existence of an equilibrium. By doing so, the model provides a way to freely estimate this within-market effect from the data. Incorporating revenue data allows us to interpret parameters in monetary units and to decompose the within-market effect into cost savings from clustering stores (economics of density) and lost revenues from competition with one's own stores (own-chain business-stealing effect). I apply the technique to a new data set from the convenience-store industry in Okinawa, Japan. Parameter estimates confirm that own chain business-stealing is an important consideration for a chain. I then use the estimated structural model to perform two counterfactual analyses. First, I consider a hypothetical merger of two chains and find that the merger would decrease the number of stores and total sales, and raise the acquirer's profits thereby reallocating surplus from consumers to the acquirer. Second, I examine how eliminating the zoning regulation introduced in Japan in 1968, which has been at the forefront of urban policy debates, affects store-network choices

A City and Countywide Summit to Advance Healthy Homes & Healthy Communities in Chicago and Cook County, Illinois

The home serves many purposes besides a place of residency. The home is where we begin and finish our day, where families and their children live, play, and grow for years, and where people have a sense of comfort and safety. Unfortunately, the home is a place where many known and unknown environmental toxins cause health hazards that affect residents on a daily basis. Indoor environmental hazards in the home harm millions of children and families each year. Scientists have long recognized that indoor toxic hazards can pose far greater risks to children’s health than outdoor exposures because of the concentrated levels in enclosed, poorly ventilated spaces. The following report outlines the initial efforts of a collaborative effort to develop an initial blueprint to adequately respond to these challenges in Chicago and Cook County. Participants include representatives from local, county, state, and federal agencies; community groups, private industry, and academia; and public health, housing, and child advocates. Implementing this blueprint will help to ensure that our children and families have homes that support good health and good living

Maximum Allowed Solvent Accessibilites of Residues in Proteins

Matthew Z. Tien, Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, Illinois, United States of AmericaAustin G. Meyer, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas, United States of AmericaAustin G. Meyer, Dariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of AmericaDariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of AmericaDariya K. Sydykova, Stephanie J. Spielman, Claus O. Wilke, Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of AmericaThe relative solvent accessibility (RSA) of a residue in a protein measures the extent of burial or exposure of that residue in the 3D structure. RSA is frequently used to describe a protein's biophysical or evolutionary properties. To calculate RSA, a residue's solvent accessibility (ASA) needs to be normalized by a suitable reference value for the given amino acid; several normalization scales have previously been proposed. However, these scales do not provide tight upper bounds on ASA values frequently observed in empirical crystal structures. Instead, they underestimate the largest allowed ASA values, by up to 20%. As a result, many empirical crystal structures contain residues that seem to have RSA values in excess of one. Here, we derive a new normalization scale that does provide a tight upper bound on observed ASA values. We pursue two complementary strategies, one based on extensive analysis of empirical structures and one based on systematic enumeration of biophysically allowed tripeptides. Both approaches yield congruent results that consistently exceed published values. We conclude that previously published ASA normalization values were too small, primarily because the conformations that maximize ASA had not been correctly identified. As an application of our results, we show that empirically derived hydrophobicity scales are sensitive to accurate RSA calculation, and we derive new hydrophobicity scales that show increased correlation with experimentally measured scales.This work was supported by National Institutes of Health (http://nih.gov/) grant R01 GM088344 to COW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Center for Computational Biology and BioinformaticsIntegrative BiologyEmail: [email protected]