Measuring Sharedness of Team-Related Knowledge: Design and Validation of a Shared Mental Model Instrument

Many researchers have explored how people share and construct similar mental models in teams. They have claimed that successful team performance depends on a shared mental model of team members about task, team, equipment and situation. Most of the literature has illustrated simplified relationships between a team's mental model and their performance without a valid instrument addressing the confined and relevant constructs of a shared mental model. This paper describes the instrument development steps and the conceptual framework for factors associated with shared mental models. After development and refinement, the instrument was finalized for use to measure team-related knowledge. The final instrument consists of 42 items that are linked to the five emergent factors of shared mental models including general task and team knowledge, general task and communication skills, attitude toward teammates and task, team dynamics and interactions, and team resources and working environment.     

Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation

Box–Cox together with our newly proposed transformation were implemented in three different real world empirical problems to alleviate noisy and the volatility effect of them. Consequently, a new domain was constructed. Subsequently, universe of discourse for transformed data was established and an approach for calculating effective length of the intervals was then proposed. Considering the steps above, the initial forecasts were performed using frequently used fuzzy time series (FTS) methods on transformed data. Final forecasts were retrieved from initial forecasted values by proper inverse operation. Comparisons of the results demonstrate that the proposed method produced more accurate forecasts compared with existing FTS on original data.     

The Eating Disorders NOS Diagnostic Profile Among College Women

Abstract

The authors examined a proposed profile of eating-related behaviors, associated features, developmental issues, and help-seeking behavior among college women, using an eating disorder response program. The most common symptom scenario was a pattern of regular binge eating, together with daily exercise and occasional purging. The most common associated features were distressing or dysfunctional overconcern about body image and self-esteem, usually with day-to-day stress and intermittent depression. The women who fit this pattern also presented developmental issues of perfectionism, conflictual relationships with parents, and struggles for independence; and they tended to be ambivalent about seeking services. Implications for practice, including the need to develop a framework for eating disorder responses on campus that includes preventive programs and developmental interventions to target emerging and moderate concerns are discussed; limitations and the preliminary nature of the findings are explicated.     

The burdens of social capital: How socially-involved people dealt with stress after Hurricane Katrina

Research shows that those with greater social capital enjoy better physical and mental health. The current study illuminates a paradox of social capital which may afflict those involved in traumatic events. Several years of survey data reveal a dynamic picture of the link between social capital and stress following Hurricane Katrina. Results reveal that initially after Katrina, those who were more socially embedded carried the greatest load with respect to helping the displaced population, thus experiencing more stress. But over time, the most socially-involved then snapped back from their stressful experiences more rapidly than isolates. This confirms that over the course of stressful events, social involvement first exposes people to more stress, but as time passes, provides them a significant buffer against negative psychosocial experiences.     

Comment on “Constrained Optimization Approaches to Estimation of Structural Models”

We revisit the comparison of mathematical programming with equilibrium constraints (MPEC) and nested fixed point (NFXP) algorithms for estimating structural dynamic models by Su and Judd (2012). Their implementation of the nested fixed point algorithm used successive approximations to solve the inner fixed point problem (NFXP‐SA). We redo their comparison using the more efficient version of NFXP proposed by Rust (1987), which combines successive approximations and Newton–Kantorovich iterations to solve the fixed point problem (NFXP‐NK). We show that MPEC and NFXP are similar in speed and numerical performance when the more efficient NFXP‐NK variant is used.     

Inference on Causal Effects in a Generalized Regression Kink Design

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. We characterize a broad class of models in which a sharp “Regression Kink Design” (RKD or RK Design) identifies a readily interpretable treatment‐on‐the‐treated parameter (Florens, Heckman, Meghir, and Vytlacil (2008)). We also introduce a “fuzzy regression kink design” generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. Using a kink in the unemployment benefit formula, we apply a fuzzy RKD to empirically estimate the effect of benefit rates on unemployment durations in Austria.     

Frailty modelling approaches for semi-competing risks data

Lifetime Data Analysis - In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an...     

Unveiling the Canvas Ceiling: A Multidisciplinary Literature Review of Refugee Employment and Workforce Integration

Increasing levels of displacement and the need to integrate refugees in the workforce pose new challenges to organizations and societies. Extant research on refugee employment and workforce integration currently resides across various disconnected disciplines, posing a significant challenge for management scholars to contribute to timely and relevant solutions. In this paper, we endeavour to address this challenge by reviewing and synthesizing multidisciplinary literature on refugee employment and workforce integration. Using a relational framework, we organize our findings around three levels of analysis – institutional, organizational and individual – to outline the complexity of factors affecting refugees’ employment outcomes. Based on our analysis, we introduce and elaborate on the phenomenon of the canvas ceiling ? a systemic, multilevel barrier to refugee workforce integration and professional advancement. The primary contributions of this paper are twofold. First, we map and integrate the multidisciplinary findings on the challenges of refugee workforce integration. Second, we provide management scholarship with a future research agenda to address the knowledge gap identified in this review and advance practical developments in this domain.     

Collective versus Individual Effects in Survival Analysis of Multiple Failures

In survival analysis, we sometimes encounter data with multiple censored outcomes. Under certain scenarios, partial or even all covariates have ‘similar’ relative risks on the multiple outcomes in the Cox regression analysis. The similarity in covariate effects can be quantified using the proportionality of regression coefficients. Identifying the proportionality structure, or equivalently whether covariates have individual or collective effects, may have important scientific implications. In addition, it can lead to a smaller set of unknown parameters, which in turn results in more accurate estimation. In this article, we develop a novel approach for identifying the proportionality structure. Simulation shows the satisfactory performance of the proposed approach and its advantage over estimation under no assumed structure. We analyse three datasets to demonstrate the practical application of the proposed approach.     

Dealing with the Initial Observation in the LM Unit Root Test

This article proposes a linearly weighted unit root test with a new weighting scheme which reflects the trade-off in power between the ADF and LM tests regarding the initial value of a time series. Simulation results indicate that the proposed test has better power performance and works better than other available tests in the literature for a range of initial conditions.