Assessing Engineering Resilience for Systems with Multiple Performance Measures

Recently, efforts to model and assess a system's resilience to disruptions due to environmental and adversarial threats have increased substantially. Researchers have investigated resilience in many disciplines, including sociology, psychology, computer networks, and engineering systems, to name a few. When assessing engineering system resilience, the resilience assessment typically considers a single performance measure, a disruption, a loss of performance, the time required to recover, or a combination of these elements. We define and use a resilient engineered system definition that separates system resilience into platform and mission resilience. Most complex systems have multiple performance measures; this research proposes using multiple objective decision analysis to assess system resilience for systems with multiple performance measures using two distinct methods. The first method quantifies platform resilience and includes resilience and other “ilities” directly in the value hierarchy, while the second method quantifies mission resilience and uses the “ilities” in the calculation of the expected mission performance for every performance measure in the value hierarchy. We illustrate the mission resilience method using a transportation systems‐of‐systems network with varying levels of resilience due to the level of connectivity and autonomy of the vehicles and platform resilience by using a notional military example. Our analysis found that it is necessary to quantify performance in context with specific mission(s) and scenario(s) under specific threat(s) and then use modeling and simulation to help determine the resilience of a system for a given set of conditions. The example demonstrates how incorporating system mission resilience can improve performance for some performance measures while negatively affecting others.     

Corporate social responsibility,financial performance and risk in times of economic instability

Journal of Management and Governance - This article examines the relationship between the social performance of companies and their financial performance, analyzed from the systematic risk...     

Stakeholder value disclosures: anchoring on primacy and importance of financial and nonfinancial performance measures

In the growing debate about stakeholder values, there has been little discussion about information overload or whether the requested disclosures can be effectively used. Stakeholder advocates call for complicated and massive environmental and related social disclosures while not considering how information overload might affect the discourse about corporate performance. Stakeholders, including shareholders, plead for more transparency in financial statements, management discussion and analysis (MDA), and other corporate disclosures. As we know, shareholders and boards of directors are most concerned with the ‘Holy Trinity’ of earnings per share, dividends and market value changes. We believe that managers and stakeholders involved in performance evaluations have multiple interests that extend beyond traditional shareholder value measures. We note that the Balanced Scorecard (BSC) was developed as one tool to reflect and communicate these multiple measures. We test how managers use (or ignore) multiple performance measures and we posit that stakeholders will face many of the same constraints when using and processing multiple disclosures including Corporate Social Reports (CSR), environmental, or similar disclosures. While we do not directly test a wide variety of stakeholder disclosures, we examine eight (four for a single subject) shareholder values (financial measures) and four stakeholder values (nonfinancial measures). The eight measures included in our research instruments serve as proxies for the multiple concerns that might be of interest to many stakeholders. Note that stakeholders are likely to be extremely interested in nonfinancial performance measures, while many shareholders will likely concentrate on financial performance measures. Field research has reported managers tend to favor financial measures while discounting or ignoring nonfinancial measures when evaluating subordinates, making it difficult to align performance evaluations and incentives with corporate strategies (Ittner et al. Account Rev 78:725–758, 2003). In this study, we find the relative weights managers place on financial and nonfinancial performance measures are influenced by both (1) presentation order and (2) the relative importance of specific measures. When financial measures are presented first, the manager who performs better on financial measures is rated higher than the manager who performs better on nonfinancial measures. However, when nonfinancial measures are presented first, managers who excel on nonfinancial measures are rated higher. Reports that include financial measures that are relatively more (less) important also produce higher (lower) ratings for the manager who excels on financial measures. Thus, the relative weights that superiors place on financial and nonfinancial measures in evaluating corporate managers’ performance are substantially anchored both by the order in which measures are presented as well as by the importance of the specific performance measures employed. Other stakeholder disclosures are likely to be similarly anchored, perhaps biased, by primacy and a priori importance rankings.     

该反思你对人员管理的认识了

要保持竞争力,企业必须在人员管理方面采取大幅变革当婴儿潮一代临近传统上的退休年龄,具有前瞻思维的企业正加大对领导力发展与继任规划的投入。他们着眼于加强人才储备:让企业的青     

Determination of recovery effort for a probabilistic recovery system under various inventory control policies

In this study we investigate the desired level of recovery under various inventory control policies when the success of recovery is probabilistic. All the used and returned items go into a recovery process that is modelled as a single stage operation. The recovery effort is represented by the expected time spent for it. The effect of increasing recovery effort on the success probability together with unit cost of the operation is included by assuming general forms of dependencies. Alternative to recovered items, demand is satisfied by brand-new items. Four inventory control policies that differ in timing of and information used in purchasing decision are proposed. The objective is to find the recovery level together with inventory control parameter that minimize the long-run average total cost. A numerical study covering a wide range of system parameters is carried out. Finally computational results are presented with their managerial implications.     

Use of Markov Chain Monte Carlo Analysis with a Physiologically-Based Pharmacokinetic Model of Methylmercury to Estimate Exposures in U.S. Women of Childbearing Age

A Bayesian approach, implemented using Markov Chain Monte Carlo (MCMC) analysis, was applied with a physiologically‐based pharmacokinetic (PBPK) model of methylmercury (MeHg) to evaluate the variability of MeHg exposure in women of childbearing age in the U.S. population. The analysis made use of the newly available National Health and Nutrition Survey (NHANES) blood and hair mercury concentration data for women of age 16–49 years (sample size, 1,582). Bayesian analysis was performed to estimate the population variability in MeHg exposure (daily ingestion rate) implied by the variation in blood and hair concentrations of mercury in the NHANES database. The measured variability in the NHANES blood and hair data represents the result of a process that includes interindividual variation in exposure to MeHg and interindividual variation in the pharmacokinetics (distribution, clearance) of MeHg. The PBPK model includes a number of pharmacokinetic parameters (e.g., tissue volumes, partition coefficients, rate constants for metabolism and elimination) that can vary from individual to individual within the subpopulation of interest. Using MCMC analysis, it was possible to combine prior distributions of the PBPK model parameters with the NHANES blood and hair data, as well as with kinetic data from controlled human exposures to MeHg, to derive posterior distributions that refine the estimates of both the population exposure distribution and the pharmacokinetic parameters. In general, based on the populations surveyed by NHANES, the results of the MCMC analysis indicate that a small fraction, less than 1%, of the U.S. population of women of childbearing age may have mercury exposures greater than the EPA RfD for MeHg of 0.1 μg/kgg/day, and that there are few, if any, exposures greater than the ATSDR MRL of 0.3 μgg/kgg/day. The analysis also indicates that typical exposures may be greater than previously estimated from food consumption surveys, but that the variability in exposure within the population of U.S. women of childbearing age may be less than previously assumed.     

Residential Building Codes,Affordability, and Health Protection: A Risk-Tradeoff Approach

Residential building codes intended to promote health and safety may produce unintended countervailing risks by adding to the cost of construction. Higher construction costs increase the price of new homes and may increase health and safety risks through income and stock effects. The income effect arises because households that purchase a new home have less income remaining for spending on other goods that contribute to health and safety. The stock effect arises because suppression of new-home construction leads to slower replacement of less safe housing units. These countervailing risks are not presently considered in code debates. We demonstrate the feasibility of estimating the approximate magnitude of countervailing risks by combining the income effect with three relatively well understood and significant home-health risks. We estimate that a code change that increases the nationwide cost of constructing and maintaining homes by $150 (0.1% of the average cost to build a single-family home) would induce offsetting risks yielding between 2 and 60 premature fatalities or, including morbidity effects, between 20 and 800 lost quality-adjusted life years (both discounted at 3%) each year the code provision remains in effect. To provide a net health benefit, the code change would need to reduce risk by at least this amount. Future research should refine these estimates, incorporate quantitative uncertainty analysis, and apply a full risk-tradeoff approach to real-world case studies of proposed code changes.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.