Ambient Taxes Under m-Dimensional Choice Sets, Heterogeneous Expectations, and Risk-Aversion

We consider the design of ambient taxes forrisk-neutral and risk-averse polluters whenpolluters and the regulatory agency haveasymmetric information about environmentalrelationships and probabilities associatedwith random events. Unlike prior work, we showthat under these conditions, optimal ambienttaxes must be firm-specific, and accompaniedby additional incentives to influencepolluters' choices of abatement techniques.     

中国投资者进军美国市场将获新途径

中国股市从不久前的辉煌之巅急转直下，而与此同时，这个全球第一人口大国的投资者们又将获得新的渠道进军包括美国在内的海外股市。     

Age-test Markov chains for drug testing and detection

Random urinalysis strategies stratified by time since the last test are characterized with a set of Markov chain models. The probability of a person being tested depends on the amount of time since the person's last test. The Nuclear Regulatory Commission (NRC) has proposed a two strata drug testing strategy based on time since last test. The proposal included a high testing rate for people not yet tested in a given time period and a low testing rate for people testing negative in a given time period. Southern California Edison has implemented a variation of the NRC proposal. These strategies can be modeled within a Markov chain framework. Time to detection is calculated as a function of testing probabilities and drug usage levels. Drug user gaming strategies are discussed with illustrations. These models are implemented as part of a U.S. Navy drug policy analysis system.     

Estimating Willingness to Pay for Improved Water Quality in the Presence of Item Nonresponse Bias

This article deals with the problem of item nonresponse in contingent valuation surveys using a payment-card method, by applying a grouped-data sample-selection estimation technique that is capable of imputing the missing values conditional upon a respondent's decision to answer a willingness-to-pay question. The advantage of the technique lies in its ability to utilize all of the information in the sample, permitting a more efficient estimation in the presence of item nonresponse bias. The major determinants of willingness to pay appear to be household income, number of children, education, perception of existing water quality, and identification with environmental issues.     

B‐TO‐B E‐COMMERCE: A CONTENT ANALYTICAL ASSESSMENT OF MOTOR CARRIER WEBSITES

An Internet presence is a critical early component in the process of building towards a fully operational and unified e‐commerce strategy. E‐commerce has significantly impacted logistics/supply chain strategies and the development and implementation of a website have become key issues for many firms within the transportation industry. This study provides an overview of website content within the motor carrier industry. Content analysis was used to assess the site design, informational content, and the interactive content of 152 motor carrier websites, and to compare the features offered on the Top 100 motor carrier firm websites with those offered on the sites of smaller carrier firms.     

RELATIONSHIP MAGNITUDE AND ITS ROLE IN INTERORGANIZATIONAL RELATIONSHIP STRUCTURE

Close relationships between and among supply chain members are becoming more prevalent. However, there is lack of agreement in the literature and in practice concerning the characteristics of different interorganizational relationships. The resultant confusion is an obstacle to the progression of research and could cause problems among firms in a supply chain. Based on previous research and an exploratory study conducted with company executives responsible for supply chain management activities, this article seeks to introduce the concept of relationship magnitude (i.e., the extent or degree of closeness or strength of the relationship) and differentiate it from relationship type (i.e., classes of relationships that share common traits). Implications for managers and opportunities for future research are provided.     

The Lowry Model Revisited: Incorporating a Multizonal Input-Output Model into an Urban Land Use Allocation Model

This paper formulates a new generation of Lowry-style models that combine a multizonal input-output model and an urban land use allocation model. Three different types of models are proposed: 1) an unconstrained model, 2) a primal of a linear programming approach that includes land supply constraints, and 3) a modified dual of the linear programming approach that allocates land based on additional conditions of economic efficiency. The modified dual formulation improves upon the limitations of Lowry models and their derivatives. First, the proposed model has sound theoretical underpinnings that incorporate the production theory of input-output models and the behavioral theory of optimization models. Second, the proposed model allocates land on the basis of economic efficiency by imposing a procedure that equalizes shadow prices. And third, the proposed model is an optimization model that fully accounts for the spatial and sectoral relationships of multiplier effects determining land use demand.