Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.     

Observed and parent‐reported conscience in childhood: Relations with bullying involvement in early primary school

This exploratory study aimed to examine which components of early childhood conscience predicted bullying involvement around school entry. In the population‐based Generation R Study, teacher reports of bullying involvement and parent reports of conscience were available for 3,244 children (M age = 6.7 years). Higher levels of overall conscience predicted lower bullying perpetration scores, independently of intelligence quotient, temperamental traits and sociodemographic characteristics. Particularly, the subscales guilt, confession, and internalized conduct, and to a lesser extent empathy, predicted bullying perpetration. Conscience was not related to victimization. Similar results were found using observations during so‐called ‘cheating games’ (subsample N = 450 children). Findings suggest that improving children's understanding of moral standards and norms may be a potential target for bullying intervention programs in early primary school.     

The Development of Multiple Self‐Concept Dimensions During Adolescence

The purpose of this research was to analyze the development of self‐concept during adolescence. Participants included 484 teenagers (226 boys and 258 girls) from middle‐class families in the Basque Country region of Spain (M_age = 14.99, SD = 1.81 in Time 1 and M_age = 15.64, SD = 1.80 in Time 2). Longitudinal analysis found differences in the general school dimension. Six dimensions (math, verbal, general school, physical abilities, parent relationships and same‐sex relationships) reported a linear trend with a decreasing monotonic pattern; self‐esteem fit a cubic trend and physical appearance a quadratic trend line. Males showed higher means in self‐esteem, math, physical abilities, physical appearance, emotional stability and parent relationships; and females had higher values in verbal and general school.     

A NOTE ON THE USE OF SELECTED NONFINANCIAL RATIO VARIABLES TO PREDICT SMALL-BUSINESS LOAN PERFORMANCE*

Small business loan applications have not been evaluated successfully by traditional methods. This paper explores the possibility of using three types of nonfinancial ratio variables (owner, firm, and loan characteristics) to predict whether a small business will pay off or default its loan. The owner and loan variables were better predictors of loan success than the firm variables.     

Revisiting das gupta: Refinement and extension of standardization and decomposition

Standardization and decomposition are established and widely used demographic techniques for comparing rates and means between groups with differences in composition. The difference in rates and means has heretofore been resolved in terms of the contribution of variables to compositional effects for each variable and an overall rate effect. This study demonstrates that the resolution of differences is attainable at the categorical level for both compositional effects and rate effects. Refinements to Das Gupta’s equations yield a complete decomposition because of the additivity of categorical compositional and rate effects. Other refinements allow the decomposition of polytomous variables. Extensions to the method provide for the decomposition of the standard deviation and the multivariate index of dissimilarity.     

对中国行政法的反思:一个香港的视角

中国的现代行政法与中国古代法律传统没有多大的延续性。相比较而言,英国行政法有着其引以为荣的绵延数世纪的历史,其重心在于对行政行为的司法审查。中国行政法的结构与英国行政法的结构截然不同。在中国的行政诉讼制度中,就司法审查的范围而言:首先,抽象行政行为不受司法审查;其次,内部行政行为不受司法审查;再者,《行政诉讼法》只授权对某些类型的具体行政行为案件进行司法审查。就行政行为的审查理由或标准而言,中国法律的有关规定要比英国或香港的较为有限。但就一方面而言,中国法律提供的审查空间和力度似乎比英国或香港更为宽泛,这便是对行政行为的事实依据的审查。     

Identifying social innovations in European local rural development initiatives

Social innovation is attracting increasing attention in research and policy, heightened by continuing austerity across Europe. Therefore, this paper examines earlier research into community-led local development (CLLD) initiatives in rural areas of Europe to develop our understanding of the meaning and scope of rural social innovation. We draw on a Schumpeterian view where innovations emerge from new combinations of resources that bring about positive changes and create value in society. A Schumpeterian social innovation framework is derived as the basis for re-analysing data from previous evaluations of LEADER policy in five different national contexts. This elicits a clearer understanding of social innovation in a rural development context, identifying different processes and outcomes that create social value. As the CLLD agenda and the demand for innovation in Europe gather pace, our aspirations are to inform future research and other initiatives on how to integrate social innovation into the design and evaluation of new rural development policies and programmes.     

A Literature Review of Organizational Behavior Management Interventions in Human Service Settings from 1990 to 2016

We reviewed the Journal of Applied Behavior Analysis (JABA), Journal of Organizational Behavior Management (JOBM), and Behavior Analysis in Practice (BAP) from 1990 to 2016, to identify articles that evaluated organizational behavior management interventions in a human service setting. Of those articles, 75 articles met the inclusion criteria for the review, 44 from JABA (1990 to 2016), 22 from JOBM (1990 to 2016), and 7 from BAP (2008 to 2016). We categorized each selected article by setting, employee population, client population, assessment, dependent variable, independent variable, and outcome measures. Results from the review are discussed for all three journals. Recommendations are made to broaden the scope of population and dependent variable targets, include more assessments, and include outcome data when applicable.     

An empirical assessment of the operational performance through internal benchmarking: a case of a global logistics firm

This article solves an operational performance measurement problem of a global logistics firm through an internal benchmarking tool. The intended impact is to enable logistics firms to form a deeper understanding of their own internal processes and metrics. The methodology of this in-depth action research involves a sequential approach with a series of interviews, questionnaire-based surveys, operations data collated through observations and process mapping yielding real-world data. A series of statistical tests are conducted to analyse the collated data. Strategic priorities of the firm are integrated with the firm’s operational performance to ascertain the effective performance by considering both the tangible and intangible measures. The outcomes inform both practitioners and academics how the firm could improve its freight forwarding business’s profitability by ensuring that its operations meet the prioritised criteria. The ‘best practice’ derived from internal benchmarking forms an intermediate step towards external benchmarking. The outcomes facilitate investigating the current business strategy, the standard operating procedures and the scope of improving those.     

Confidence interval estimation of the difference between paired AUCs based on combined biomarkers

In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice.