Traffic Congestion Effects on Supply Chains: Accounting for Behavioral Elements in Planning and Economic Impact Models

As traffic volumes and congestion grows on highways and urban roadways, freight and delivery service operators become increasingly challenged to maintain dependable and reliable schedules. This affects supply chains and truck-dependent businesses both of which are of increasing importance for both public policy and private sector operators. From the public perspective, there is a need to make investment, financing and policy decisions based on an understanding of public infrastructure needs, costs and broader economic stakes involved. From the perspective of shippers and carriers, there are the day-to-day cost implications of delay and reliability as it affects supply chain management, and well as a longer-range need to assess opportunities, risks and returns associated with location, production and distribution decisions. Both perspectives need to be recognized when considering the full range of impacts that traffic congestion can have on the economy. A barrier to considering these two perspectives together is the gap that exists between theoretical simulation modeling and real world observations of business responses to congestion. A review of research literature reveals a number of theoretical models which posit that the generalized growth of traffic congestion adds to total transport costs for delivered products, causing firms to shift location and shipment size configurations to reoptimize net revenues. However, industry publications and business interviews reveal a wider variety of behavioral responses that depend on the type and timing of congestion delays (bottlenecks at specific ports, intermodal facilities, highways or urban road networks) and their frequency, leading to a range of operational responses as a hedge against both expected and unexpected delay. The nature of the affected parties, and the form of operational responses, can vary widely by industry. The impacts can span different supply chain configurations â including not only the movement of material and parts to producers and then to distributors, but also local distribution and delivery of finished goods to retail markets, and even local delivery of parts and repair services to businesses and households. For service-oriented economies, more sophisticated changes in operations â especially those that depend on efficiency of over-the-road operations â can be limited or entirely foreclosed by congestion. In a broad sense, all of these forms of movement have supply chain elements. And they share a common factor, which is that they are very much affected by the degree of of unpredictability and variation in delays associated with growing congestion

Defining the Range of Urban Congestion Impacts on Freight and their

Abstract The causes and impacts of urban traffic congestion are intrinsically tied to changes occurring in business practices and the economy. The freight delivery requirements of businesses and their sensitivity to congestion are also increasing as many types of business seek to serve wider markets and apply new logistics and production technologies with increasing reliance on just-intime supply chains, overnight courier services, intermodal facilities and international gateways. In response, regional business organizations are starting to take a leadership role in focusing attention on urban traffic congestion and its impacts on freight movement and business activity. This paper uses examples from three areas where business organizations have been working with public agencies to study the economic implications of congestion growth and the economic benefits of investing in efforts to mitigate it. It utilizes findings from those studies to develop a taxonomy of the ways in which urban traffic congestion is changing the freight delivery and operational decisions of businesses, and increasing their costs. It then identifies needs for improved transportation and economic analysis methods that are sensitive to those factors. Weisbrod and Fitzroy page

Real wages, investment and employment: New evidence from West German sectoral data

C33, E22, E24,

Wage differentials between skilled and unskilled workers

J23, J31, J41, J51,

Factors affecting cytochrome P-450 3A activity in cancer patients

Purpose: The purpose is to identify the demographic, physiologic, and inheritable factors that influence CYP3A activity in cancer patients Experimental Design: A total of 134 patients (62 females; age range, 26 to 83 years) underwent the erythromycin breath test as a phenotyping probe of CYP3A. Genomic DNA was screened for six variants of suspected functional relevance in CYP3A4 (CYP3A4*1B, CYP3A4*6, CYP3A4*17, and CYP3A4*18) and CYP3A5 (CYP3A5*3C and CYP3A5*6). Results: CYP3A activity (AUC0-40min) varied up to 14-fold in this population. No variants in the CYP3A4 and CYP3A5 genes were a significant predictor of CYP3A activity (P \u3e 0.2954). CYP3A activity was reduced by ∼50% in patients with concurrent elevations in liver transaminases and alkaline phosphatase or elevated total bilirubin (P \u3c 0.001). In a multivariate analysis, CYP3A activity was not significantly influenced by age, sex, and body size measures (P \u3e 0.05), but liver function combined with the concentration of the acute-phase reactant, α-1 acid glycoprotein, explained ∼18% of overall variation in CYP3A activity (P \u3c 0.001). Conclusions: These data suggest that baseline demographic, physiologic, and chosen genetic polymorphisms have a minor impact on phenotypic CYP3A activity in patients with cancer. Consideration of additional factors, including the inflammation marker C-reactive protein, as well as concomitant use of other drugs, food constituents, and complementary and alternative medicine with inhibitory and inducible effects on CYP3A, is needed to reduce variation in CYP3A and treatment outcome to anticancer therapy

Unions and profits : a meta-regression analysis

The effect of unions on profits continues to be an unresolved theoretical and empirical issue. In this paper, clustered data analysis and hierarchical linear meta-regression models are applied to the population of forty-five econometric studies that report 532 estimates of the direct effect of unions on profits. Unions have a significant negative effect on profits in the United States, and this effect is larger when market-based measures of profits are used. Separate meta-regression analyses are used to identify the effects of market power and long-lived assets on profits, as well as the sources of union-profit effects. The accumulated evidence rejects market power as a source of union-profit effects. While the case is not yet proven, there is some evidence in support of the appropriation of quasi-rent hypothesis. There is a clear need for further American and non-American primary research in this area.<br /