Knowledge management for sustainability in operations

Abstract

The purpose of this paper is to examine the effect of Knowledge Management (KM) as a platform to enable sustainability in firms’ operations and to provide recommendations for managers to integrate sustainable operations into their business strategies. The urgency to create and implement sustainable operations is also argued. The conceptual framework is based on the hypothesis that KM contributes to the achievement of more suitable operations. To test this hypothesis, a model of structural equations was developed with data collected from 345 SMEs. Empirical evidence supported the hypothesis, indicating that KM represents an important alternative to implementing sustainability. The results suggest that managers need to implent KM, as they will enable a better understanding and awareness regarding the global dangerous impacts from unsustainable operations mainly focused on sales and cost reduction. For this reason, this research provides evidence that KM offers an alternative impulse on the quest for more sustainable operations.     

Deconstructing Gender Differences in Experienced Well-Being Among Older Adults in the Developing World: The Roles of Time Use and Activity-Specific Affective Experiences

Social Indicators Research - Due to declining fertility rates and increasing longevity, the world is growing older. Improving the quality of life of older adults, and not merely preventing deaths,...     

Efficiency of a Linear Combination of the Median and the Sample Mean: The Double Truncated Normal Distribution

Abstract.  We characterize all symmetric location models for which a linear combination of the median and the sample mean is an asymptotically efficient estimator of the location parameter. The resulting model can be understood as a symmetrized or double truncated normal distribution. A simple algorithm to estimate the parameters is given and an application is presented.     

Empirical likelihood for nonlinear models with missing responses

In this paper, a nonlinear model with response variables missing at random is studied. In order to improve the coverage accuracy for model parameters, the empirical likelihood (EL) ratio method is considered. On the complete data, the EL statistic for the parameters and its approximation have a χ² asymptotic distribution. When the responses are reconstituted using a semi-parametric method, the empirical log-likelihood on the response variables associated with the imputed data is also asymptotically χ². The Wilks theorem for EL on the parameters, based on reconstituted data, is also satisfied. These results can be used to construct the confidence region for the model parameters and the response variables. It is shown via Monte Carlo simulations that the EL methods outperform the normal approximation-based method in terms of coverage probability for the unknown parameter, including on the reconstituted data. The advantages of the proposed method are exemplified on real data.     

Maximum likelihood estimator in a multi-phase random regression model

We consider a random regression model with several-fold change-points. The results for one change-point are generalized. The maximum likelihood estimator of the parameters is shown to be consistent, and the asymptotic distribution for the estimators of the coefficients is shown to be Gaussian. The estimators of the change-points converge, with n ^?1 rate, to the vector whose components are the left end points of the maximizing interval with respect to each change-point. The likelihood process is asymptotically equivalent to the sum of independent compound Poisson processes.     

Incorporation of Migrant Students Returning From the United States to High Schools in Mexico

The purpose of this research was to identify the difficulties faced by the Mexican migrant students when incorporated into the Mexican education system after having studied in the United States of America. Thirty migrant middle school students, two principals, two social workers and one teacher participated in the study. The study (conducted in two phases) collected information regarding: school admission, adjustment to the school organization, adaptation to learning situations and the perception of school belonging. The main problems found during the admission and enrolment procedures in Mexican schools are: language use, diagnostic assessment, didactic processes that take place in the classroom, complementary support activities, grade repetition, very little family involvement and the separation of the students from their migrant parents.     

Model selection by LASSO methods in a change-point model

The paper considers a linear regression model with multiple change-points occurring at unknown times. The LASSO technique is very interesting since it allows simultaneously the parametric estimation, including the change-points estimation, and the automatic variable selection. The asymptotic properties of the LASSO-type (which has as particular case the LASSO estimator) and of the adaptive LASSO estimators are studied. For this last estimator the Oracle properties are proved. In both cases, a model selection criterion is proposed. Numerical examples are provided showing the performances of the adaptive LASSO estimator compared to the least squares estimator.     

Business Coach – nicht nur fürs Business

In many organizations business coaching is one of the favorite personnel development tools. The focus is clearly on economical targets. In these days, however, this is not enough to accompany managers successfully. The results of a qualitative empirical study show that not only business related topics but also relevant personal topics of a manager should be integrated into a coaching process to ensure lasting work improvements as well as any necessary individual development.