Decision settings analysis – a tool for analysis and design of human activity systems

The paper describes a methodology to be used for analysis and design of human activity systems. The methodology is based on an analysis of the decision settings whereas most other decision analysis methodologies are analysing the process. The decision concept is analysed and discussed. A distinction between programmed and programmable as well as non-programmed and non-programmable decisions is proposed. A classification of different information types for decision making is presented. A methodology based on a systemic and systematic analysis of the information requirements of an organization is proposed. This methodology also indicates organizational discrepancies and information imbalances. The methodology focuses the settings of the decisions on all levels of organizations. The methodology can be regarded as a dynamic, learning system. The author proposes further research on the individuals decision making abilities.     

Seasonal forcing on the dynamics ofClethrionomys rufocanus: Modeling geographic gradients in population dynamics

We interpret gradients in population dynamics of the gray-sided vole from the southwestern part of the island of Hokkaido to its northeastern part within the framework of a phenomenological model involving the relative length of summer and winter. In Hokkaido, as in other northern regions, both spring and fall is considered as short transition periods between the two main seasons — summer (the primary breeding season) and winter (the non-reproductive or secondary breeding season). We show that the geographic transition in dynamics may be understood as the combined consequence of different patterns of density-dependence during summer and winter, and geographically varying season lengths. Differences are shown to exist between summer and winter with respect to strength of density-dependence. Direct density-dependence, in particular, is stronger during winter than during summer. A model is presented to show how relative lengths of seasons can induce both stable and periodically fluctuating population dynamics. The results are compared and contrasted with what is otherwise known about the gradient in rodent dynamics in Fennoscandia.     

Shrinkage Structure of Partial Least Squares

Partial least squares regression (PLS) is one method to estimate parameters in a linear model when predictor variables are nearly collinear. One way to characterize PLS is in terms of the scaling (shrinkage or expansion) along each eigenvector of the predictor correlation matrix. This characterization is useful in providing a link between PLS and other shrinkage estimators, such as principal components regression (PCR) and ridge regression (RR), thus facilitating a direct comparison of PLS with these methods. This paper gives a detailed analysis of the shrinkage structure of PLS, and several new results are presented regarding the nature and extent of shrinkage.     

Does education influence wildlife friendly landscaping preferences?

In sprawling metropolitan areas, residential landscaping is a major concern with respect to biodiversity conservation, and it could play a critical role in conserving wildlife habitat. In the United States, residential landscaping typically consists of maintained lawns with specimen plantings of non-native trees and shrubs; such designs provide poor habitat for urban wildlife species. We conducted a case study of Raleigh, North Carolina residents to determine how providing information about the benefits of native plant landscaping to bird species influenced urban residents’ landscaping preferences. We used Wilcoxon Signed Rank tests to determine if respondent preferences for 0, 50, 75 and 100 % native plant landscaping coverages changed after residents were informed about the benefits that native plants provide for birds. Initially, the 50 % native landscaping coverage was most preferred by residents; however, preferences for all four native plant landscaping coverage designs were significantly different after the informational treatment. Neutrality changed to opposition for the 0 % native plant coverage, while opposition changed to support and neutrality for the 75 and 100 % native plant coverage designs, respectively. After the informational treatment, the 50 and 75 % native plant landscaping coverage had the highest mean preference levels, although the 100 % design was ranked first more than any other design. Our findings suggest that residential support for native plant landscaping is higher than is reflected by typical residential landscaping practices, and that dissemination of information regarding the benefits of native plant landscaping to birds could alter public preferences for native plant landscaping.     

Personality factors predicting changes in shift work tolerance: A longitudinal study among nurses working rotating shifts

Abstract

The aim of the present study was to investigate the relationship between personality factors (hardiness, morningness, flexibility, and languidity) and longitudinal changes on different measures of shift work tolerance (fatigue, sleepiness, anxiety and depression) over one year among nurses working rotating shifts. A total of 642 female Norwegian nurses working in a rotating three-shift schedule participated in the study. The cohort was established by age-stratified selection among members of the Norwegian Nurses Association in 2008. Questionnaires were administered in 2008/2009 (T1) and in 2009/2010 (T2). The results showed that hardiness was negatively related to fatigue, anxiety and depression at T2 when controlling for the scores on these constructs at T1. Morningness was not related to any indicators of shift work tolerance at T2 when controlling for shift work tolerance at T1. Flexibility was negatively related to anxiety at T2 when controlling for anxiety at T1. Languidity was positively related to sleepiness and fatigue at T2 when controlling for sleepiness and fatigue at T1. The findings indicate that personality factors, especially hardiness, can predict changes related to shift work tolerance over a period of one year.     

Long-term dynamics of household size and their environmental implications

Little is known about the environmental implications of long-term historical trends in household size. This paper presents the first historical assessment of global shifts in average household size based on a variety of datasets covering the period 1600–2000. Findings reveal that developed nations reached a threshold in 1893 when average household size began to drop rapidly from approximately 5.0 to 2.5. A similar threshold was reached in developing nations in 1987. With the notable exceptions of Ireland, and England and Wales in the early 1800s, and India and the Seychelles in the late 1900s, the number of households grew faster than population size in every country and every time period. These findings suggest accommodating housing may continue to pose one of the greatest environmental challenges of the twenty-first century because the impacts of increased housing present a threat to sustainability even when population growth slows. Future research addressing environmental impacts of declining household size could use an adapted IPAT model, I = PHoG: where environmental impact (I) = population × personal goods (P) + households × household goods (HoG).     

The impact of US tariffs against China on US imports: Evidence for trade diversion?

We provide evidence on the existence of short-run trade diversion effects towards third countries as a consequence of tariff shocks. We exploit sudden policy changes in the context of the trade dispute between the United States and China in 2018. Based on a data set covering monthly product-level information on US imports from 30 countries for the period 2016 until May 2019, we employ a difference-in-differences estimation framework. Doing so, we can show a strong negative direct effect of US tariffs on US imports from China, but do not find evidence for significant short-run trade diversion effects towards third countries.