The Impact of Lean Management Practices and Sustainably‐Oriented Innovation on Sustainability Performance of Small and Medium‐Sized Enterprises: Empirical Evidence from the UK

While lean management practices (LMP) help small and medium‐sized enterprises (SMEs) to be efficient, sustainability‐oriented innovation (SOI) facilitates adopting environmental and social practices. Although prior research looks into the effect of LMP on the economic performance (EP) of SMEs, less is known about the effect of LMP on sustainability (economic, environmental and social) performance. Studies on the effect of SOI on sustainability and economic performance are also scant. Additionally, examining the mediating effect of corporate social responsibility (CSR) practices (environmental and social practices) on both LMP and SOI achieving sustainability performance (SP) is rare. This research bridges these knowledge gaps by answering the question of how LMP, SOI, CSR practices, sustainability and economic performance are correlated. Through hypothesis testing using structural equation modelling, this study reveals the impact of LMP, SOI, CSR (environmental and social) practices on sustainability and economic performance. The study uses data from 119 SMEs within manufacturing industries in the Midlands, UK. The analysis reveals that LMP and SOI facilitate achieving both sustainability and economic performance, and SOI mediates LMP to achieve sustainability performance. Additionally, although CSR practices mediate LMP to achieve sustainability performance, they only borderline mediate SOI to achieve sustainability performance.     

Calibration estimation in dual-frame surveys

Survey statisticians make use of auxiliary information to improve estimates. One important example is calibration estimation, which constructs new weights that match benchmark constraints on auxiliary variables while remaining “close” to the design weights. Multiple-frame surveys are increasingly used by statistical agencies and private organizations to reduce sampling costs and/or avoid frame undercoverage errors. Several ways of combining estimates derived from such frames have been proposed elsewhere; in this paper, we extend the calibration paradigm, previously used for single-frame surveys, to calculate the total value of a variable of interest in a dual-frame survey. Calibration is a general tool that allows to include auxiliary information from two frames. It also incorporates, as a special case, certain dual-frame estimators that have been proposed previously. The theoretical properties of our class of estimators are derived and discussed, and simulation studies conducted to compare the efficiency of the procedure, using different sets of auxiliary variables. Finally, the proposed methodology is applied to real data obtained from the Barometer of Culture of Andalusia survey.     

经济增长与"克强指数"的动态关系研究 ——基于重庆市1985—2014年数据

"克强指数"是英国著名政经杂志《经济学人》在 2010 年推出的用于评估中国 GDP 增长量的指标,由工业用电量、铁路货运量、中长期贷款按一定权重计算得到.根据重庆市经济发展特色,选取重庆市 1985—2014 年的相关经济发展指标,探讨重庆市经济增长与"克强指数"之间的动态关系,为客观公正评价重庆市经济发展情况提供思路.     

Testing Overdispersion in CUBE Models

A practical problem with large-scale survey data is the possible presence of overdispersion. It occurs when the data display more variability than is predicted by the variance–mean relationship. This article describes a probability distribution generated by a mixture of discrete random variables to capture uncertainty, feeling, and overdispersion. Specifically, several tests for detecting overdispersion will be implemented on the basis of the asymptotic theory for maximum likelihood estimators. We discuss the results of a simulation experiment concerning log-likelihood ratio, Wald, Score, and Profile tests. Finally, some real datasets are analyzed to illustrate the previous results.     

Influence diagnostics for the Weibull-Negative-Binomial regression model with cure rate under latent failure causes

In this paper, we propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest follows the Negative Binomial distribution and the time to event follows a Weibull distribution. Indeed, we introduce the Weibull-Negative-Binomial (WNB) distribution, which can be used in order to model survival data when the hazard rate function is increasing, decreasing and some non-monotonous shaped. Another advantage of the proposed model is that it has some distributions commonly used in lifetime analysis as particular cases. Moreover, the proposed model includes as special cases some of the well-know cure rate models discussed in the literature. We consider a frequentist analysis for parameter estimation of a WNB model with cure rate. Then, we derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. Finally, the methodology is illustrated on a medical data.     

Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics

We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Assessing the relevance of higher education courses

The establishment of the European Higher Education Area has involved specifying lists of professional competencies that programs are expected to develop, and with this the need for procedures to measure how every course within a higher education program is aligned with the program's competencies. We propose an instrument for characterizing this alignment, a process that we call assessing the relevance of a course. Using information from the course syllabus (objectives, contents and assessment scheme), our instrument produces indicators for characterizing the syllabus in terms of a competence list and for assessing its coherence. Because assessment involves quality, the results obtained can also be used to revise and improve the course syllabus. We illustrate this process with an example of a methods course from a mathematics teacher education program at a Spanish university.     

Semi-structured interview protocol for constructing logic models

This paper details a semi-structured interview protocol that evaluators can use to develop a logic model of a program's services and outcomes. The protocol presents a series of questions, which evaluators can ask of specific program informants, that are designed to: (1) identify key informants basic background and contextual information, (2) generate logic model elements, (3) model program inputs, activities, outputs, and outcomes, (4) build a rational theory, (5) develop a program theory, (6) prioritize logic model elements, and (7) build a graphical or tabular logic model. The paper will also provide an example of how this approach was used to develop a logic model for a youth mentoring program. It is our hope and belief that with this interview protocol, novice evaluators will be able to generate comprehensive logic models like seasoned professional evaluators.     

Barrios and burbs: residential context and health-risk behaviors among Angeleno adolescents

The increasing size of the Latino immigrant population in the United States underscores the need for a more complete understanding of the role that social context plays in influencing the health of immigrants and their children. This analysis explores the possibility that residential location influences the health-risk behaviors of Latino youth in Los Angeles County, California. The data come from the Los Angeles Family and Neighborhood Survey. We apply multivariate, multilevel Rasch models to two scales of adolescent health-risk behaviors (substance use and delinquency). The findings suggest that residence in Census tracts characterized by above-county-average levels of Latinos and above-county-average levels of poverty is associated with increased odds of health-risk behaviors for Latino adolescents, particularly for those born in the United States. The findings lend support to the contention, put forth in the segmented assimilation literature, that disadvantaged urban contexts increase the risk that U.S.-born children of immigrants will experience downward assimilation.