Managing AMI in a Just-In-Time Environment in the UK and Japan

In recent years many commentators have addressed the ‘crisis’ in manufacturing industry (Gerwin, 1982; Drucker, 1988, 1990; Hayes and Jaikumar, 1988). Some have offered cross-national comparisons on Japanese and Western management methods and techniques (Kharbanda and Stallworthy, 1991; Oliver and Wilkinson, 1987; Pascale and Athos, 1981) whilst others have concentrated on improving performance in specific fields such as management accounting (Kaplan, 1984; Cooper, 1991) or manufacturing management (Schonberger, 1982; Halt, 1983). Empirical research into managing AMT in Japan and the UK (Currie 1991a) considers some of the broader managerial issues in manufacturing. Cultural differences are common in the areas of investment appraisal, post-auditing of AMT and preventive maintenance policy. For example, in Japan JIT is perceived ‘holistically’ incorporating production management, total quality assurance (TQA) and total preventive maintenance (TPM). This is contrary to the UK in that many large manufacturing companies fail to include TPM in their manufacturing strategies (Currie and Seddon, 1991). There are few management information systems (MIS) which provide an understanding of machine performance using both non-financial and financial information. Focusing on maintenance as a central theme, the paper discusses the development of the Failure And Scheduled Maintenance Analysis (FASMA) system, which offers a practical solution to the problem of collecting and manipulating manufacturing data on the shopfloor (Seddon, 1991a). Essentially, FASMA attempts to interface both the manufacturing and management accounting functions by translating machine performance data into valuable information from which preventive maintenance policy may be improved. Using FASMA to measure machine performance at a major UK automotive manufacturer, machine down-time has averaged 61% each month over a 3-year period. By manipulating this data, performance measurement information may be utilized by management accountants. FASMA thus develops a link between manufacturing and management accounting by providing data on machine performance which can be used for cost analysis within a manufacturing environment. The paper concludes by arguing that manufacturing strategies can only be developed using appropriate management information systems (MIS) designed to enhance functional integration. This will enable a better understanding of how the ‘manufacturing jigsaw’ fits together.     

Multi-scale process modelling and distributed computation for spatial data

Statistics and Computing - Recent years have seen a huge development in spatial modelling and prediction methodology, driven by the increased availability of remote-sensing data and the reduced...     

Institutions and Policies for Pro‐poor Agricultural Growth

Global experience with pro‐poor growth and empirical work spanning India, Malawi and Zimbabwe demonstrates the importance of agricultural growth for poverty reduction in poor rural areas, while also pointing to the need for complementary non‐farm sector growth. Theoretical arguments, historical evidence and livelihoods modelling in poor medium‐potential rural economies suggest that, contrary to thinking dominating much of current development policy, subsidies to relieve critical seasonal credit and cash restraints and reduce market and input supply uncertainties need to help in ‘kick‐starting’ agricultural markets if increased smallholder productivity in food‐grains is to drive rural non‐farm growth. Establishing the base conditions for these to work, designing and implementing them to be effective, and then phasing them out are major challenges facing policymakers.     

The [R]Evolving Relationship Between Risk Assessment and Risk Management

In Science and Decisions: Advancing Risk Assessment, the National Research Council recommends improvements in the U.S. Environmental Protection Agency's approach to risk assessment. The recommendations aim to increase the utility of these assessments, embedding them within a new risk‐based decision‐making framework. The framework involves first identifying the problem and possible options for addressing it, conducting related analyses, then reviewing the results and making the risk management decision. Experience with longstanding requirements for regulatory impact analysis provides insights into the implementation of this framework. First, neither the Science and Decisions framework nor the framework for regulatory impact analysis should be viewed as a static or linear process, where each step is completed before moving on to the next. Risk management options are best evaluated through an iterative and integrative procedure. The extent to which a hazard has been previously studied will strongly influence analysts’ ability to identify options prior to conducting formal analyses, and these options will be altered and refined as the analysis progresses. Second, experience with regulatory impact analysis suggests that legal and political constraints may limit the range of options assessed, contrary to both existing guidance for regulatory impact analysis and the Science and Decisions recommendations. Analysts will need to work creatively to broaden the range of options considered. Finally, the usefulness of regulatory impact analysis has been significantly hampered by the inability to quantify many health impacts of concern, suggesting that the scientific improvements offered within Science and Decisions will fill an crucial research gap.     

Integrating risk assessment and life cycle assessment: a case study of insulation.

Increasing residential insulation can decrease energy consumption and provide public health benefits, given changes in emissions from fuel combustion, but also has cost implications and ancillary risks and benefits. Risk assessment or life cycle assessment can be used to calculate the net impacts and determine whether more stringent energy codes or other conservation policies would be warranted, but few analyses have combined the critical elements of both methodologies In this article, we present the first portion of a combined analysis, with the goal of estimating the net public health impacts of increasing residential insulation for new housing from current practice to the latest International Energy Conservation Code (IECC 2000). We model state-by-state residential energy savings and evaluate particulate matter less than 2.5 microm in diameter (PM2.5), NOx, and SO2 emission reductions. We use past dispersion modeling results to estimate reductions in exposure, and we apply concentration-response functions for premature mortality and selected morbidity outcomes using current epidemiological knowledge of effects of PM2.5 (primary and secondary). We find that an insulation policy shift would save 3 x 10(14) British thermal units or BTU (3 x 10(17) J) over a 10-year period, resulting in reduced emissions of 1,000 tons of PM2.5, 30,000 tons of NOx, and 40,000 tons of SO2. These emission reductions yield an estimated 60 fewer fatalities during this period, with the geographic distribution of health benefits differing from the distribution of energy savings because of differences in energy sources, population patterns, and meteorology. We discuss the methodology to be used to integrate life cycle calculations, which can ultimately yield estimates that can be compared with costs to determine the influence of external costs on benefit-cost calculations.     

IDENTIFYING THE EFFECTS OF MONETARY POLICY SHOCKS ON EXCHANGE RATES USING HIGH FREQUENCY DATA

This paper proposes a new approach to identifying the effects of monetary policy shocks in an international vector autoregression. Using high‐frequency data on the prices of Fed Funds futures contracts, we measure the impact of the surprise component of the FOMC‐day Federal Reserve policy decision on financial variables, such as the exchange rate and the foreign interest rate. We show how this information can be used to achieve identification without having to make the usual strong assumption of a recursive ordering. (JEL: C32, E52, F30)     

Determinants of Priority for Risk Reduction: The Role of Worry

One hundred twenty-two members (experts) of the Society for Risk Analysis completed a mailed questionnaire and 150 nonexperts completed a similar questionnaire on the World Wide Web. Questions asked included those about priorities on personal and government action for risk reduction, badness of the risk, number of people affected, worry, and probabilities for self and others. Individual differences in mean desire for action were largely explained in terms of worry. Worry, in turn, was largely affected by probability judgments, which were lower for experts than for nonexperts. Differences across risks in the desire for action, within each subject, were also determined largely by worry and probability. Belief in expert knowledge about the risk increased worry and the priority for risk reduction. A second study involving 91 nonexperts (42 interviewed and 49 on the Web) replicated the main findings for nonexperts from the first study. Interviews also probed the determinants of worry, attitudes toward government versus personal control, and protective behaviors.     

A Field Study of RFID Deployment and Return Expectations

Radio Frequency Identification (RFID) technology promises to transform supply chain management. Building on previous research in information systems and supply chain management, this paper proposes a theoretical framework for RFID adoption and benefits, and tests the framework using data on u. s. firms. Our analysis suggests that there is a positive association between information technology (IT) application deployment and RFID adoption. We find that RFID implementation spending and partner mandate are associated with an expectation of early return on RFID investment, and a perceived lack of industry‐wide standards is associated with an expectation of delayed return on RFID investment. These results suggest that firms with broad IT application deployment and a critical mass of RFID implementation spending are more likely to report early returns from RFID deployments. This paper extends previous research to understand the relationship between organization characteristics and adoption and expected benefits of the emerging RFID technology.     

Characterizing Dose-Response Relationships in Multiple Cancer Bioassays

In the evaluation of chemical compounds for carcinogenic risk, regulatory agencies such as the U.S. Environmental Protection Agency and National Toxicology Program (NTP) have traditionally fit a dose-response model to data from rodent bioassays, and then used the fitted model to estimate a Virtually Safe Dose or the dose corresponding to a very small increase (usually 10(-6)) in risk over background. Much recent interest has been directed at incorporating additional scientific information regarding the properties of the specific chemical under investigation into the risk assessment process, including biological mechanisms of cancer induction, metabolic pathways, and chemical structure and activity. Despite the fact that regulatory agencies are currently poised to allow use of nonlinear dose-response models based on the concept of an underlying threshold for nongenotoxic chemicals, there have been few attempts to investigate the overall relationship between the shape of dose-response curves and mutagenicity. Using data from an historical database of NTP cancer bioassays, the authors conducted a repeated-measures Analysis of the estimated shape from fitting extended Weibull dose-response curves. It was concluded that genotoxic chemicals have dose-response curves that are closer to linear than those for nongenotoxic chemicals, though on average, both types of compounds have dose-response curves that are convex and the effect of genotoxicity is small.