Acculturation and Individualism as Predictors of Work‐Family Conflict in a Diverse Workforce

Ethnic and cultural diversity is an increasing reality in the US workplace. The current study highlights the importance of acknowledging the culturally heterogeneous nature of ethnic groups, and the need to focus on social identity characteristics such as cultural values when assessing group differences. We demonstrate that cultural values (i.e., individualism) contribute to employees' experiences of work‐family conflict beyond the effects of ethnicity. Specifically, we introduce a model informed by social identity theory that explains why acculturation is related to work‐family conflict. The model was tested with a sample of 309 employed Caucasian and Hispanic Americans. An empirical test of our model provides evidence that individualism mediates the relationship between language‐ and social‐based acculturation and work‐family conflict, even when controlling for ethnicity. Additionally, alternative models further reveal that the effects of acculturation and individualism contribute to work interfering with family. As an implication of the current study, we suggest that researchers and organizational managers should consider the cultural values of their diverse workforce when implementing policies that affect conflict between work and family. © 2013 Wiley Periodicals, Inc.     

Managing the Intangible Aspects of a Project: The Affect of Vision,Artifacts, and Leader Values on Project Spirit and Success in Technology‐Driven Projects

Successful projects are often characterized by a unique spirit. Phase one results, based on 193 employees partaking in 60 projects across organizations, support a model positing that leader building activities affect employees' emotions, attitudes, and behavioral norms that are focused on expected project outcomes, termed project spirit. Spirit affects employees' contextual performance behavior, which in turn affects success as proposed. Phase two cases, designed to ground these results in technology‐driven project contexts, highlight the value of managing the project's intangible aspects captured by spirit. Quantitative and qualitative findings imply that leaders can be coached to execute behaviors that generate a project's spirit, which boosts contextual performance behavior and increases project success.     

Managing Risks in Complex Projects

Dealing effectively with risks in complex projects is difficult and requires management interventions that go beyond simple analytical approaches. This is one finding of a major field study into risk management practices and business processes of 35 major product developments in 17 high‐technology companies. Almost one‐half of the contingencies that occur are not being detected before they impact project performance. Yet, the risk‐impact model presented in this article shows that risk does not affect all projects equally but depends on the effectiveness of collective managerial actions dealing with specific contingencies. The results of this study discuss why some organizations are more successful in detecting risks early in the project life cycle, and in decoupling risk factors from work processes before they impact project performance. The field data suggest that effective project risk management involves an intricately linked set of variables, related to work process, organizational environment, and people. Some of the best success scenarios point to the critical importance of recognizing and dealing with risks early in their development. This requires broad involvement and collaboration across all segments of the project team and its environment, and sophisticated methods for assessing feasibilities and usability early and frequently during the project life cycle. Specific managerial actions, organizational conditions, and work processes are suggested for fostering a project environment most conducive to effective cross‐functional communication and collaboration among all stakeholders, a condition important to early risk detection and effective risk management in complex project situations.     

Proportional Odds Models with High‐Dimensional Data Structure

The proportional odds model is the most widely used model when the response has ordered categories. In the case of high‐dimensional predictor structure, the common maximum likelihood approach typically fails when all predictors are included. A boosting technique pomBoost is proposed to fit the model by implicitly selecting the influential predictors. The approach distinguishes between metric and categorical predictors. In the case of categorical predictors, where each predictor relates to a set of parameters, the objective is to select simultaneously all the associated parameters. In addition, the approach distinguishes between nominal and ordinal predictors. In the case of ordinal predictors, the proposed technique uses the ordering of the ordinal predictors by penalizing the difference between the parameters of adjacent categories. The technique has also a provision to consider some mandatory predictors (if any) that must be part of the final sparse model. The performance of the proposed boosting algorithm is evaluated in a simulation study and applications with respect to mean squared error and prediction error. Hit rates and false alarm rates are used to judge the performance of pomBoost for selection of the relevant predictors.     

ARE ALL ECONOMIC FACTS GREATLY EXAGGERATED? THEORY COMPETITION AND SELECTIVITY

Abstract ..There is growing concern and mounting evidence of selectivity in empirical economics. Most empirical economic literatures have a truncated distribution of results. The aim of this paper is to explore the link between publication selectivity and theory contests. This link is confirmed through the analysis of 87 distinct empirical economics literatures, involving more than three and a half thousand separate empirical studies, using objective measures of both selectivity and contests. Our meta–meta‐analysis shows that publication selection is widespread, but not universal. It distorts scientific inference with potentially adverse effects on policy making, but competition and debate between rival theories reduces this selectivity and thereby improves economic inference.     

Controlling the Urban Fabric: The Complex Game of Distance and Proximity in European Upper‐Middle‐Class Residential Strategies

This article presents an open discussion of the processes of urban secession and gentrification in contemporary European cities, arguing that intergroup social dynamics in urban spaces are generally more complex than either extreme mutual avoidance or the colonization of neighbourhoods by the wealthiest groups. We analyse the residential strategies of urban upper‐middle class managers in various European metropolitan areas through in‐depth semi‐structured interviews to argue that these groups develop complex strategies of proximity and distance in relation to other social groups. The development of these ‘partial exit’ strategies takes place through specific combinations of practices that allow groups to select the dimensions they are willing to share with other social groups, and those in which they prefer a more segregated social environment for themselves and their families. The responses of our interviewees were consistently more nuanced and complex than suggested by a simplistic theory about their drive to withdraw from society, forcing us to develop more sophisticated conceptual frameworks to account for the growing prevalence of multi‐layered identities and spheres of reference and solidarity, specific combinations of elective segregation and local involvement, and more active patterns of mobility combined with local embeddedness.     

经销关系中双边道德风险的一种契约解决机制

对于需要进行专用性资产投资或通过契约安排形成专用性资产投资的经销关系中,往往会存在双边道德风险:一是生产商敲竹杠的道德风险;二是经销商隐蔽行为的道德风险。本文通过一个简单的不完全契约安排试图解决这种双边道德风险,以取得社会最优投资,促使交易的完整进行。     

The trilemma between accuracy,timeliness and smoothness in real-time signal extraction

The evaluation of economic data and the monitoring of the economy is often concerned with an assessment of the mid- and long-term dynamics of time series (trend and/or cycle). Frequently, one is interested in the most recent estimate of a target signal, a so-called real-time estimate. Unfortunately, real-time signal extraction is a difficult estimation problem that involves linear combinations of possibly infinitely many multi-step ahead forecasts of a series. Here, we address the performances of real-time designs by proposing a generic direct filter approach. We decompose the ordinary mean squared error into accuracy, timeliness and smoothness error components, and we propose a new tradeoff between these competing terms, the so-called ATS-trilemma. This formalism enables us to derive a general class of optimization criteria that allow the user to address specific research priorities, in terms of the accuracy, timeliness and smoothness properties of the corresponding concurrent filter. We illustrate the new methods through simulations, and present an application to Indian industrial production data.