The Development of A County Level Index Of Well-Being

In an effort to assess the level of community need and inform responsive resource allocation, Larimer County, Colorado developed a county-level index of well-being. This paper describes the development of that index including the selection of indicators and the methodology for scoring and presenting those indicators. We also present how the local community used the information and describe problems we found while aggregating indicators. Next, we show the results of evaluating our index using Hagerty et al.’s (2001, Social Indicators Research 55, pp. 1–96) 14 criteria for determining validity and usefulness of quality of life indices. The Larimer County index performed above both the “satisfactory” rating and the mean of the 22 indices evaluated using Hagerty et al.’s. We conclude that the Larimer County index is based on a solid approach that will be helpful to local policy makers.     

The Determinants of Low Fertility in India

Using a conceptual framework focusing on factors that enhance or reduce fertility relative to desired family size (see Bongaarts 2001), we study fertility variation across time (1992–2006) and space (states) in India. Our empirical analyses use data from three waves of the Indian National Family Health Surveys. We find that this framework can account for a substantial portion of the variation in the total fertility rate (TFR) over time and across states. Our estimates focus attention on the critical components of contemporary Indian fertility, especially desired family size, unwanted fertility, son preference, and fertility postponement.     

Solutions for a class of invex programming problems

A nonconvex constrained optimization problem is considered in which the constraints are of the form of generalized polynomials. An invexity kernel is established for this class of problem, and a consequent theorem gives sufficient conditions for the solutions of such problems.     

Analyzing survival data in conjunction with time-dependent surrogate endpoints in clinical trials

Current survival techniques do not provide a good method for handling clinical trials with a large percent of censored observations. This research proposes using time-dependent surrogates of survival as outcome variables, in conjunction with observed survival time, to improve the precision in comparing the relative effects of two treatments on the distribution of survival time. This is in contrast to the standard method used today which uses the marginal density of survival time, T. only, or the marginal density of a surrogate, X, only, therefore, ignoring some available information. The surrogate measure, X, may be a fixed value or a time-dependent variable, X(t). X is a summary measure of some of the covariates measured throughout the trial that provide additional information on a subject's survival time. It is possible to model these time-dependent covariate values and relate the parameters in the model to the parameters in the distribution of T given X. The result is that three new models are available for the analysis of clinical trials. All three models use the joint density of survival time and a surrogate measure. Given one of three different assumed mechanisms of the potential treatment effect, each of the three methods improves the precision of the treatment estimate.     

Measurement of Abnormal Returns From Small Firms

Correction for heteroscedasticity in returns from portfolios long in small firms and short in large firms listed on the New York Stock Exchange reduces the estimate of market risk and increases the estimated abnormal return. Greatly improved diagnostic test statistics are obtained, strengthening the evidence for the existence of positive average abnormal returns from small firms. Periodicity of order 6 and 12 months is identified. The estimation procedure operates by exploiting the autoregressive pattern of heteroscedasticity in the return data.     

The Roles of Worker Expertise,Information Sharing Quality,and Psychological Safety in Manufacturing Process Innovation: An Intellectual Capital Perspective

This paper examines the roles of three elements of intellectual capital in implementing process innovations. Building upon prior literature, we develop a model describing how worker expertise, information sharing quality, and psychological safety work together as elements of the human, structural, and social dimensions of intellectual capital to influence the technical success of manufacturing process innovation (MPI) projects. Results of an analysis of data describing 179 MPI projects in US firms strongly support a multidimensional, process‐oriented view of intellectual capital's effects on MPI project technical performance. We also find that the incrementalness of an MPI project plays a moderating role over the relationship between worker expertise and MPI performance. Our study provides insights on how intellectual capital can be more effectively accumulated in a project environment.     

Is 60 the New 50? Examining Changes in Biological Age Over the Past Two Decades

Increasing life expectancy has been interpreted as improving health of a population. However, mortality is not always a reliable proxy for the pace of aging and could instead reflect achievement in keeping ailing people alive. Using data from NHANES III (1988–1994) and NHANES IV (2007–2010), we examined how biological age, relative to chronological age, changed in the United States between 1988 and 2010, while estimating the contribution of changes in modifiable health behaviors. Results suggest that biological age is lower for more recent periods; however, the degree of improvement varied across age and sex groups. Overall, older adults experienced the greatest improvement or decreases in biological age. Males, especially those in the youngest and oldest groups, experienced greater declines in biological age than females. These differences were partially explained by age- and sex-specific changes in behaviors, such as smoking, obesity, and medication use. Slowing the pace of aging, along with increasing life expectancy, has important social and economic implications; thus, identifying modifiable risk factors that contribute to cohort differences in health and aging is essential.     

When Heterosexuality is Questioned: Stifling Suspicion Through Public Displays of Heterosexual Identity

This study examined public heterosexual identity management practices of heterosexual-identified young adults in the United States. Analysis of 415 participants’ written narratives indicated that 41% (n = 169) described consciously engaging in public displays of their heterosexual status in relation to suspicion about their sexual orientation. This article describes our findings regarding five aspects of these narratives of suspicion: types of suspicion, causes of suspicion, reasons for concern about suspicion, the types of public displays of heterosexual status employed to quell suspicion, and intended audiences for these displays. Overall, the results indicated that heterosexual identity suspicion is multifaceted, this suspicion serves as a catalyst for public displays of heterosexual status, and the climate of suspicion described by our participants reflects and reinforces contemporary heterosexism.     

Complexity Factors and Intuition-based Methods for Facility Network Design

Logistics managers frequently utilize decision support systems (DSS) to make facility network design decisions. Many DSS do not provide optimization capabilities, but instead rely on scenario evaluation as a means for developing solutions. We experimentally assessed the performances of decision makers, including experienced managers, who used four variants of a scenario evaluation-based DSS to solve realistically sized network design problems of varying complexities. Complexity factors included DSS attributes, problem size, network types, and demand dispersion patterns. Decision makers' performances were assessed relative to optimal solutions. Overall, the decision makers generated relatively high-quality solutions using the DSS variants. The type of design problem solved did not significantly impact problem-solving performance. However, performance degraded and variability in solution quality escalated as problem size was increased. The availability of incremental solution cost improvement cues in the DSS significantly improved solution quality and reduced performance variability. Iconic graphic enhancements to the DSS did not consistently affect performance. However, significant interactions existed among the effects of DSS graphics capabilities, DSS information cues, and problem attributes.     

The Influences of User Characteristics on Performance in a Logistics DSS Application

Decision Support Systems (DSS) are widely used in logistics decision applications, and a large number and variety of systems are commercially available. We investigate the contributions of user characteristics including experiences, data preferences, intuition, and effort to decision performance in a logistics DSS context. The study includes a laboratory experiment in which decision makers with varied experiences used a DSS to make facility network design decisions for problems of varying complexity. Two variants of the DSS are utilized in order to examine the interactions of a DSS decision aid with user characteristics. We find that intuition and effort are associated with decision-making performance. High analytic ability is not related to intuition, however. Education and previous experience are associated with performance. Yet these characteristics are also unrelated to intuition. Decision makers who highly value disaggregated data provided by the DSS tend to perform poorly. Also, the results suggest that the effects of users' experiences and preferences on performance are influenced by an analytical decision aid.