Coping resources,coping strategies and adjustment to organizational change: Direct or buffering effects?

Abstract

This study examined the effects of personal and social resources, coping strategies and appraised stress on employees' levels of anxiety and depression. In relation to the effects of resources and coping strategies, two different models were tested. The main effects model proposes that, irrespective of the level of stress, coping resources and coping strategies have direct effects on well-being. In contrast, the buffering model predicts that the buffering effects of coping resources ad strategies are only evident at high levels of stress. One hundred lawyers completed a structured self-administered questionnaire that measured their personal and social resources, use of problem-focused and emotion-focused coping strategies, and appraisals of the stressfulness of the situation. Results revealed generally strong support for the main effects model in the prediction of employee levels of anxiety and depression. Lower levels of anxiety were linked to judgements of lower levels of organizational change, greater self-confidence, greater internality of control beliefs and less use of emotion-focused coping strategies. Lower levels of depression in employees were also linked to judgements of lower levels of organizational change, greater use of resources and less appraised stress. There was only limited support for the buffering effects model. Due to the small size of the sample, the findings need to be explored further in other contexts.     

The role of stress and social support in Sick Building Syndrome

Sick Building Syndrome (SBS) involves seemingly healthy individuals experiencing long-lasting symptoms of physical distress in their work settings and is estimated to exist in 20 to 30% of all work settings in the USA. We examined differences in stress, social support and both physical and psychological symptoms reported by hospital personnel working in known SBS sites in Halifax, Nova Scotia (n = 297) with control employees working in relatively SBS-free settings (n = 228). We found that employees reporting that their health had been affected by the building in which they worked and those complaining of poor air quality were more likely to be found in SBS locations. In addition, those people with higher levels of organizational support and marginally higher levels of union support were also more likely to be found in SBS locations. Further analyses revealed that employees with higher role overload and greater family support, but lower levels of organizational support were more likely to report that their own health had been adversely affected by their place of work. Perceptions of poor air quality were predicted by higher levels of role conflict, role overload, and organizational stress and lower levels of organizational support. These results suggest that SBS may not be solely dependent on environmental factors.     

Supplier–Buyer Negotiation Games: Equilibrium Conditions and Supply Chain Efficiency

In a decentralized supply chain, supplier–buyer negotiations have a dynamic aspect that requires both players to consider the impact of their decisions on future decisions made by their counterpart. The interaction generally couples strongly the price decision of the supplier and the quantity decision of the buyer. We propose a basic model for a repeated supplier–buyer interaction, during several rounds. In each round, the supplier first quotes a price, and the buyer places an order at that price. We find conditions for existence and uniqueness of a well‐behaved subgame‐perfect equilibrium in the dynamic game. When costs are stationary and there are no holding costs, we identify some demand distributions for which these conditions are met, examine the efficiency of the equilibrium, and show that, as the number of rounds increases, the profits of the supply chain increase towards the supply chain optimum. In contrast, when costs vary over time or holding costs are present, the benefit from multi‐period interactions is reduced and after a finite number of time periods, supply chain profits stay constant even when the number of rounds increases.     

Likelihood Estimation and Inference in a Class of Nonregular Econometric Models

We study inference in structural models with a jump in the conditional density, where location and size of the jump are described by regression curves. Two prominent examples are auction models, where the bid density jumps from zero to a positive value at the lowest cost, and equilibrium job‐search models, where the wage density jumps from one positive level to another at the reservation wage. General inference in such models remained a long‐standing, unresolved problem, primarily due to nonregularities and computational difficulties caused by discontinuous likelihood functions. This paper develops likelihood‐based estimation and inference methods for these models, focusing on optimal (Bayes) and maximum likelihood procedures. We derive convergence rates and distribution theory, and develop Bayes and Wald inference. We show that Bayes estimators and confidence intervals are attractive both theoretically and computationally, and that Bayes confidence intervals, based on posterior quantiles, provide a valid large sample inference method.     

2-Distance vertex-distinguishing index of subcubic graphs

This paper addresses the performance of scheduling algorithms for a two-stage no-wait hybrid flowshop environment with inter-stage flexibility, where there exist several parallel machines at each stage. Each job, composed of two operations, must be processed from start to completion without any interruption either on or between the two stages. For each job, the total processing time of its two operations is fixed, and the stage-1 operation is divided into two sub-parts: an obligatory part and an optional part (which is to be determined by a solution), with a constraint that no optional part of a job can be processed in parallel with an idleness of any stage-2 machine. The objective is to minimize the makespan. We prove that even for the special case with only one machine at each stage, this problem is strongly NP-hard. For the case with one machine at stage 1 and m machines at stage 2, we propose two polynomial time approximation algorithms with worst case ratio of \(3-\frac{2}{m+1}\) and \(2-\frac{1}{m+1}\), respectively. For the case with m machines at stage 1 and one machine at stage 2, we propose a polynomial time approximation algorithm with worst case ratio of 2. We also prove that all the worst case ratios are tight.     

Quantile Regression under Misspecification,with an Application to the U.S. Wage Structure

Quantile regression (QR) fits a linear model for conditional quantiles just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean‐squared error linear approximation to the conditional expectation function even when the linear model is misspecified. Empirical research using quantile regression with discrete covariates suggests that QR may have a similar property, but the exact nature of the linear approximation has remained elusive. In this paper, we show that QR minimizes a weighted mean‐squared error loss function for specification error. The weighting function is an average density of the dependent variable near the true conditional quantile. The weighted least squares interpretation of QR is used to derive an omitted variables bias formula and a partial quantile regression concept, similar to the relationship between partial regression and OLS. We also present asymptotic theory for the QR process under misspecification of the conditional quantile function. The approximation properties of QR are illustrated using wage data from the U.S. census. These results point to major changes in inequality from 1990 to 2000.     

A note on the correlation structure of transformed Gaussian random fields

Transformed Gaussian random fields can be used to model continuous time series and spatial data when the Gaussian assumption is not appropriate. The main features of these random fields are specified in a transformed scale, while for modelling and parameter interpretation it is useful to establish connections between these features and those of the random field in the original scale. This paper provides evidence that for many ‘normalizing’ transformations the correlation function of a transformed Gaussian random field is not very dependent on the transformation that is used. Hence many commonly used transformations of correlated data have little effect on the original correlation structure. The property is shown to hold for some kinds of transformed Gaussian random fields, and a statistical explanation based on the concept of parameter orthogonality is provided. The property is also illustrated using two spatial datasets and several ‘normalizing’ transformations. Some consequences of this property for modelling and inference are also discussed.     

Similarities and Differences between Leadership and Management: High‐Performance Competencies in the British Royal Navy

This paper describes the research, analysis and development of a model clarifying the similarities and differences in competencies and personality factors 1 associated with effective Leadership and Management in the Royal Navy. A questionnaire study was conducted on a sample of 261 Officers and Ratings (Sailors). Their performance was rated through the organization's rigorous appraisal process, whilst competency and personality data were gathered through the Occupational Personality Questionnaire and the Leadership Dimensions Questionnaire. The results identify the common and unique relevance of specific competencies and personality factors and so provide an illuminating insight into the differences between the constructs of leadership and management. The critical factors related to effective leadership and management performance are also identified.