Finding and Implementing Energy Efficiency Projects in Industrial Facilities

This study addresses the challenges of finding and implementing profitable energy efficiency (EE) projects, a critical foundation for sustainable operations. We focus on manufacturing enterprises, but many of our findings apply also to the back office of service operations. Our starting point is that, in nearly every industrial enterprise, there are many profitable EE projects that could be implemented but are not. An oft‐cited hindrance to implementation is the lack of an internal management framework in which to find, value, and execute these projects. Using a conceptual approach, we rely on proven sustainable operations tools to develop such a framework. We identify three major value drivers of EE projects: savings intensity, “green” image, and project complexity. We then describe a framework for understanding the context of EE projects in industry, with an underlying analytic foundation in optimal portfolio analysis. A case study of a large manufacturing site is used to illustrate emerging best practices—based on Kaizen management principles—for integrating EE project management with operations, engineering, and strategy.     

Time Series Modeling of Degradation Due to Outdoor Weathering

Environmental variables have an important effect on the reliability of many products such as coatings and polymeric composites. Long-term prediction of the performance or service life of such products must take into account the probabilistic/stochastic nature of the outdoor weather. In this article, we propose a time series modeling procedure to model the time series data of daily accumulated degradation. Daily accumulated degradation is the total amount of degradation accrued within one day and can be obtained by using a degradation rate model for the product and the weather data. The fitted model of the time series can then be used to estimate the future distribution of cumulative degradation over a period of time, and to compute reliability measures such as the probability of failure. The modeling technique and estimation method are illustrated using the degradation of a solar reflector material. We also provide a method to construct approximate confidence intervals for the probability of failure.     

Estimators based on ranks for arma models

In this paper we introduce a new family of robust estimators for ARMA models. These estimators are defined by replacing the residual sample autocovariances in the least squares equations by autocovariances based on ranks. The asymptotic normality of the proposed estimators is provided. The efficiency and robustness properties of these estimators are studied. An adequate choice of the score functions gives estimators which have high efficiency under normality and robustness in the presence of outliers. The score functions can also be chosen so that the resulting estimators are asymptotically as efficient as the maximum likelihood estimators for a given distribution.     

A Recursive Formula for the Probability of Occurrence of at Least m out of N Events

A recursive same-sign relation is derived that reduces the probability of occurrence of at least m out of N independent events to the probability of occurrence of at least m out of N ? 1 of these N events.     

Robust location estimation with missing data

In a missing data setting, we have a sample in which a vector of explanatory variables ${\bf x}_i$ is observed for every subject i, while scalar responses $y_i$ are missing by happenstance on some individuals. In this work we propose robust estimators of the distribution of the responses assuming missing at random (MAR) data, under a semiparametric regression model. Our approach allows the consistent estimation of any weakly continuous functional of the response's distribution. In particular, strongly consistent estimators of any continuous location functional, such as the median, L‐functionals and M‐functionals, are proposed. A robust fit for the regression model combined with the robust properties of the location functional gives rise to a robust recipe for estimating the location parameter. Robustness is quantified through the breakdown point of the proposed procedure. The asymptotic distribution of the location estimators is also derived. The proofs of the theorems are presented in Supplementary Material available online. The Canadian Journal of Statistics 41: 111–132; 2013 © 2012 Statistical Society of Canada     

Immigration,opportunity, and assimilation in a technology economy

Theory and Society - We examine access to institutions and opportunity for entrepreneurs in a rising tech economy. A significant proportion of entrepreneurs and CEOs of tech firms in the American...     

Erratum to: Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions

Social Indicators Research -     

A Portfolio Approach to Procurement Contracts

The purpose of this paper is to develop a general framework for supply contracts in which portfolios of contracts can be analyzed and optimized. We focus on a multi‐period environment with convex contract, spot market, and inventory holding costs. We specialize the model to the case of a portfolio consisting of option contracts. We characterize the optimal replenishment policy and show that it has a simple structure. Namely, the use of every different option contract and the spot market is dictated by a modified base‐stock policy. In addition, we derive conditions to determine when an option is relatively attractive compared to other options or the spot market. Finally, we present our computational study, where we report the sensitivity of the results to the parameters of the model. Our experiments indicate that portfolio contracts not only increase the manufacturer's expected profit, but can also reduce its financial risk.     

Path dependent societal transformation: Stratification in hybrid mixed economies

Theory and Society -