工商管理专业实践教学特点、限制因素及对策

开放教育工商管理专业实践教学具有三方面的特点但同时面临资金、硬件、师资等条件限制。解决开放教育工商管理专业实践教学问题是一个系统工程,必须综合分析,系统谋划,紧紧围绕应用型人才培养目标进行。     

Spanish validation of the Servant Leadership Short Scale for young adults and adolescents / Validación de la Escala de Liderazgo de Servicio Versión Abreviada en español para jóvenes adultos y adolescentes

The aim of the current study was to validate a shortened Spanish version of the Servant Leadership Profile (SLP). In Study 1, a number of experts evaluated and reduced the original scale to 14 items and named the revised version the Servant Leadership Short Scale (SLSS). An exploratory factor analysis conducted with a sample of 1,001 students revealed two possible structure solutions, a one-factor solution and a two-correlated factor solution. Study 2 used a different sample of 456 students to examine the explored structures using confirmatory factor analysis. A one-factor solution was proposed (χ²/df = 3.4, CFI = .91, TLI = .90, RMSEA = .07, SRMR = .06). Finally, in Study 3, servant leadership was used as a predictor of self-efficacy (b = .685, p < .001) and demonstrated good predictive validity. This model explained 41.55% of the variance on self-efficacy. Reliability analyses of the three studies showed that this 14-item Spanish version had high internal consistency. Together, the results of the three studies support the application of the SLSS in future research.     

The characterization of Monte Carlo errors for the quantification of the value of forensic evidence

Recent developments in forensic science have lead to a proliferation of methods for quantifying the probative value of evidence by constructing a Bayes Factor that allows a decision-maker to select between the prosecution and defense models. Unfortunately, the analytical form of a Bayes Factor is often computationally intractable. A typical approach in statistics uses Monte Carlo integration to numerically approximate the marginal likelihoods composing the Bayes Factor. This article focuses on developing a generally applicable method for characterizing the numerical error associated with Monte Carlo integration techniques used in constructing the Bayes Factor. The derivation of an asymptotic Monte Carlo standard error (MCSE) for the Bayes Factor will be presented and its applicability to quantifying the value of evidence will be explored using a simulation-based example involving a benchmark data set. The simulation will also explore the effect of prior choice on the Bayes Factor approximations and corresponding MCSEs.     

产业结构升级视阈下安徽省经济发展方式转变的实证分析

产业结构升级是转变安徽经济发展方式、实现经济可持续发展的内在要求，实现经济由数量型扩张向质量型发展的动力需求.文章在阐述产业结构升级对促进安徽省经济发展方式转变的理论基础上，首先对三大产业的增长与经济增长关系做初步分析，然后选取测度产业结构升级的经济发展指标，用综合评价法构建一套科学的产业结构升级与经济发展的关系框架，最后以产业结构升级为视角对安徽省如何转变经济发展方式提出建议.     

On the bias of factor score determinacy coefficients based on different estimation methods of the exploratory factor model

The factor score determinacy coefficient represents the common variance of the factor score predictor with the corresponding factor. The aim of the present simulation study was to compare the bias of determinacy coefficients based on different estimation methods of the exploratory factor model. Overall, determinacy coefficients computed from parameters based on maximum likelihood estimation, unweighted least squares estimation, and principal axis factoring were more precise than determinacy coefficients based on generalized least squares estimation and alpha factoring.     

Validity and reliability of the Italian Gambling Functional Assessment–Revised

Problem gambling is a growing phenomenon in Italy, and there is increasing interest in studying the reasons for gambling in the Italian community. The Gambling Functional Assessment–Revised (GFA-R) was developed to assess two contingencies maintaining gambling behaviour: positive reinforcement and escape. The study hypothesized that the GFA-R could be translated and adopted in the Italian context. The main purpose of this study was to test the factor structure of the Italian version of the GFA-R by means of confirmatory factor analysis, its internal consistency and validity, in a sample of 667 Italian-speaking adults, recruited at universities, banks, of?ces, industries, markets, public parks and shops in five regions: Piemonte, Veneto, Lazio, Calabria and Puglia. The study found that the scale was internally consistent, and results showed that the original two-factor model fitted the data well. It also found moderate correlations between the GFA-R-I and both SOGS scores and GRCS scores. These results will allow Italian psychologists, educators and policymakers to identify specific contingencies maintaining gambling behaviour (positive reinforcement vs. escape) in the Italian community, detecting people more at risk of developing disordered gambling, with significant improvements in terms of prevention and clinical intervention.     

Error variance bias in neighbour balance and evenness of distribution designs

Neighbour balance and evenness of distribution designs help to address user concerns in the two‐dimensional layout of agricultural field trials. This is done by minimising the occurrence of pairwise treatment plot neighbours and ensuring that the replications of treatments are spread out across rows and columns of a trial. Such considerations result in a restriction on the normal randomisation process for a row‐column design which can lead to error variance bias. In this paper, uniformity trial data is used to assess the degree of this bias for both resolvable and non‐resolvable designs. Comparisons are made with a similar investigation using Linear Variance spatial designs.     

Bayesian analysis for confirmatory factor model with finite-dimensional Dirichlet prior mixing

Confirmatory factor analysis (CFA) model is a useful multivariate statistical tool for interpreting relationships between latent variables and manifest variables. Often statistical results based on a single CFA are seriously distorted when data set takes on heterogeneity. To address the heterogeneity resulting from the multivariate responses, we propose a Bayesian semiparametric modeling for CFA. The approach relies on using a prior over the space of mixing distributions with finite components. Blocked Gibbs sampler is implemented to cope with the posterior analysis. Results obtained from a simulation study and a real data set are presented to illustrate the methodology.     

Paternal Risk Factors for Child Maltreatment and Father's Participation in a Primary Prevention Program in Germany

ABSTRACT

Across the globe, the research into the influence of paternal risk and protective factors on the family, as well as on the involvement of fathers in family-related interventions, is lacking. This study utilized 506 families and examined the characteristics of fathers in psychosocially stressed families and associations between paternal risk factors (PRFs: mental health disorder, physical health disorder, young paternity, unemployment, absence of father) and family risk factors (FRFs: problematic financial situation, problematic housing situation, social isolation) for child maltreatment. The identification of PRFs and FRFs was carried out using information from consultations with social education workers and from a risk inventory completed by the mothers. The data analysis revealed an increased incidence of economic problems found in families with fathers having mental health issues, fathers under the age of 22, and unemployed fathers or single mothers. Other factors such as social isolation occurred more often in families with a single mother. The present study underlines the importance of a father's involvement for young families. Future research and program recommendations should always systematically include the father's role in family-related interventions.     

品牌形象认知与品牌选择关系的实证研究

消费者的品牌形象认知对其品牌选择行为有重要影响。在消费者的品牌形象认知指标中,从对其品牌选择影响性质的差异来看,存在＂维护因子＂与＂增长因子＂两类指标。＂维护因子＂是品牌选择行为,也是品牌价值产生的必要条件;＂增长因子＂是品牌价值产生的充分条件,但必须在＂维护因子＂的基础上起作用。通过对不同品牌形象认知指标与消费者品牌选择行为之间的关系分析,有助于品牌管理者合理分配资源,提高品牌管理效率。