Understanding Drivers of Risk‐Adjusted Performance for Service Firms with International Operations*

This article investigates whether international operations of service firms increase performance while reducing risk. The article draws on a longitudinal dataset of 584 internationally operating service firms from the United States. Analysis indicates that international diversification is negatively related to risk‐adjusted performance. However, it is established that international diversification interacts with internationalization and positively influences risk‐adjusted performance. This finding offers significant promise for firms, as it indicates that international operations (if managed well), through exposure to varied foreign markets coupled with adequate global scope, can lead to firms’ increased risk‐adjusted performance. The results provide a mechanism for decision‐makers to better understand international operations of service firms and present a strategy for achieving success in international markets by effectively managing two important levers: internationalization and international market diversification.     

The magic matrix as a smart machine evaluator: Machine performance measurement,level of competitiveness

Today's competitive environment compels companies to be the best at the work they do. Machining efficiency establishes the plant level of performance and thus the ability to compete in the market. However, as product mix changes, and new machines possessing more and better capabilities are introduced, machining efficiency varies over time. Therefore, continuous evaluation of machine fitness for product mix has to be made. This is a huge task and is seldom done due to a lack of efficient tools to perform such an evaluation. This paper presents a computerized method that may be used to perform the evaluation task and establish the company level of competitiveness in an honest, and just way, free from improper influence. Conclusions drawn, and actions and decisions made as a result of the evaluation, are the prerogative of management. The evaluation method employs a matrix concept, which is fully described in this paper.     

A monte carlo study on two methods of calculating the mle's covariance matrix in a seemingly unrelated nonlinear regression. *

Econometric techniques to estimate output supply systems, factor demand systems and consumer demand systems have often required estimating a nonlinear system of equations that have an additive error structure when written in reduced form. To calculate the ML estimate's covariance matrix of this nonlinear system one can either invert the Hessian of the concentrated log likelihood function, or invert the matrix calculated by pre-multiplying and post multiplying the inverted MLE of the disturbance covariance matrix by the Jacobian of the reduced form model. Malinvaud has shown that the latter of these methods is the actual limiting distribution's covariance matrix, while Barnett has shown that the former is only an approximation.

In this paper, we use a Monte Carlo simulation study to determine how these two covariance matrices differ with respect to the nonlinearity of the model, the number of observations in the dataet, and the residual process. We find that the covariance matrix calculated from the Hessian of the concentrated likelihood function produces Wald statistics that are distributed above those calculated with the other covariance matrix. This difference becomes insignificant as the sample size increases to one-hundred or more observations, suggesting that the asymptotics of the two covariance matrices are quickly reached.     

Perceived inequity, communal orientation and burnout: The role of helping models

A large amount of empirical evidence has shown that professional helpers who perceive inequity in their relationships with their clients experience burnout. However, in such a situation, communal orientation (a desire to give benefits in response to the perceived needs of others), has been found to buffer burnout. In the present study, this buffering effect was investigated from the perspective of helping models. French nurses ( n =60) and social workers ( n =68) completed a questionnaire designed to evaluate perceived inequity, communal orientation and burnout. The results showed that, as expected, the buffering effect of communal orientation greatly depends on the helping model. Among professionals who endorsed a medical model of helping (wherein recipients are expected to be relatively passive to get better), those high on communal orientation experienced a low level of burnout when they perceived inequity. However, among professionals with a compensatory helping model (wherein recipients are expected to be active to get better), not only had perceived imbalance no buffering effect but also it reduced personal accomplishment. It was speculated that with a medical model, a perceived imbalance in the relationships does not hinder the desire to respond to the perceived needs of others. However, within a compensatory model, a perceived imbalance probably impedes the self efficacy of professionals high in communal orientation, that is who desire to respond to the perceived needs of others.     

Introduction

No abstract available for this article.     

A bayesian analysis of autoregressive models with random normal coefficients

In this paper we consider a Bayesian analysis for an autoregressive model with random normal coefficients (RCA). For the proposed procedure we use conjugate priors for some parameters and improper vague priors for others. The inference for the parameters is made via Gibbs sampler and the convergence is assessed with multiple chains and Gelman and Rubin criterium. Forecasts are based on the predictive density of future observations. Some remarks are also made regarding order determination and stationarity. Applications to simulated and real series are given.     

Solving the Classification Problem in Discriminant Analysis Via Linear and Nonlinear Programming Methods*

This paper demonstrates the feasibility of applying nonlinear programming methods to solve the classification problem in discriminant analysis. The application represents a useful extension of previously proposed linear programming-based solutions for discriminant analysis. The analysis of data obtained by conducting a Monte Carlo simulation experiment shows that these new procedures are promising. Future research that should promote application of the proposed methods for solving classification problems in a business decision-making environment is discussed.     

The Role of Existing Knowledge in New Product Innovativeness and Performance

The purpose of this study is to provide a more thorough assessment of the link between existing knowledge and organizational performance than currently exists in the literature. We identify factors and processes influential in the management of existing knowledge within the areas of learning culture, knowledge building, and organizational performance. Through structural equation modeling, a more thorough examination is given of the role existing knowledge plays in new product performance and innovativeness. In completing this task, we provide insight into the subprocesses of knowledge building by evaluating the influence of shared interpretation and two aspects of information acquisition—efficiency and degree of innovativeness of newly acquired information—on new product development (NPD) outcomes. Included in the examination of these processes are organizational culture and structure characteristics believed to influence knowledge management success.     

普遍主义福利思想和福利模式的相互作用及演变——解析西方福利国家困境

普遍主义是西方福利国家的思想原则。二战以后,根据这个原则西方国家创建了以北欧为代表的覆盖全体公民、综合各种福利项目的福利模式;同时西欧国家开创了如公民权、社会公正、社会进步的理念,其理念是普遍主义福利国家的形成的政治思想基础。几十年后,许多新福利思想已经创造了福利国家的新时代。这些理论是否拓展和促进了福利国家及其原则?事实是,在西方,普遍主义已经被逐渐丢掉其核心价值,代之以更实用的、折中的、妥协的福利理论,这些已经远离普遍主义的宗旨;即使依据这些新的理论,西方国家也难以走出困境的怪圈。     

Testing the Interaction Effects of Task Complexity in Computer Training Using the Social Cognitive Model

Using a Modified Social Cognitive Theory framework, this study examines the behavior modeling and lecture‐based training approaches to computer training. It extends the existing Social Cognitive Model for computer training by adding the task complexity construct to training method, prior performance, computer self‐efficacy, outcome expectations, and performance. A sample of 249 students from a large state university served as participants in a laboratory experiment that was conducted to determine the task complexity*training method and task complexity* self‐efficacy interaction effects on performance. Structural equation modeling with interaction effects was used to analyze the data. The results show that behavior modeling outperforms lecture‐based training in a measure of final performance when task complexity is high. Further, it is found that computer self‐efficacy has a greater positive effect on performance when task complexity is high than when task complexity is low. Prior performance is also found to be an important variable in the model.