Competitive location and pricing on networks

In this paper we consider a location and pricing model for a retail firm that wants to enter a spatial market where a competitor firm is already operating as a monopoly with several outlets. The entering firms seeks to determine the optimal uniform mill price and its servers' locations that maximizes profits given the reaction in price of the competitor firm to its entrance. A tabu search procedure is presentedto solve the model together with computational experience.

Audit of the Recreational Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Recreational Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Ice Arena Facility Revenue Note Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Ice Arena Facility Revenue Note Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Audit of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology (Iowa State University) as of and for the year ended June 30, 2007

Do agglomeration economies reduce the sensitivity of firm location to tax differentials?

Low corporate taxes can help attract new firms. This is the main mechanism underpinning the standard 'race-to-the-bottom'view of tax competition. A recent theoretical literature has qualified this view by formalizing the argument that agglomeration forces can reduce firms' sensitivity to tax differentials across locations. We test this proposition using data on firm startups across Swiss municipalities. We find that, on average, high corporate income taxes do deter new firms, but that this relationship is significantly weaker in the most spatially concentrated sectors. Location choices of firms in sectors with an agglomeration intensity at the twentieth percentile of the sample distribution are estimated to be twice as responsive to a given difference in local corporate tax burdens as firms in sectors with an agglomeration intensity at the eightieth percentile. Hence, our analysis confirms the theoretical prediction: agglomeration economies can neutralize the impact of tax differentials on firms' location choices.

New ideas need new space

We develop a setting with weak intellectual property rights, where firms' boundaries, location and knowledge spillovers are endogenous. We have two main results. The first one is that, if communication costs increase with distance, entrepreneurs concerned about information leakage have a benefit from locating away from the industry center: distance is an obstacle to collusive trades between members andnon-members. The second result is that we identify a trade-off for the entrepreneur between owning a facility (controlling all its characteristics) and sharing a facility with a {\it non-member} (an agent not involved in production), therefore losing control over some of its characteristics. We focus on ``location" as the relevant characteristic of the facility, but location can be used as a spatial metaphor for other relevant characteristics of the facility. For theentrepreneur, sharing the facility with non-members implies that the latter, as co-owners, know the location (even if they do not have access to it). Knowledge of the location for the co-owners facilitates collusion with employees, what increases leakage. The model yields a benefit for new plants from spatial dispersion (locating at the periphery of the industry), particularly so for new plants of new firms.We relate this result with recent empirical findings on the dynamics of industry location.

Supermarket key attributes and location decisions: A comparative study between British and Spanish consumers

The Maximum Capture problem (MAXCAP) is a decision model that addresses the issue of location in a competitive environment. This paper presents a new approach to determine which store s attributes (other than distance) should be included in the newMarket Capture Models and how they ought to be reflected using the Multiplicative Competitive Interaction model. The methodology involves the design and development of a survey; and the application of factor analysis and ordinary least squares. Themethodology has been applied to the supermarket sector in two different scenarios: Milton Keynes (Great Britain) and Barcelona (Spain).

Location of hubs in a competitive environment

We offer a formulation that locates hubs on a network in a competitiveenvironment; that is, customer capture is sought, which happenswhenever the location of a new hub results in a reduction of thecurrent cost (time, distance) needed by the traffic that goes from thespecified origin to the specified destination.The formulation presented here reduces the number of variables andconstraints as compared to existing covering models. This model issuited for both air passenger and cargo transportation.In this model, each origin-destination flow can go through either oneor two hubs, and each demand point can be assigned to more than a hub,depending on the different destinations of its traffic. Links(``spokes'' have no capacity limit. Computational experience is provided.