Better know an HRD scholar: a conversation with John Bing

This paper contains a conversation with John Bing, and is part of a series that focuses on different human resource development (HRD) scholars – the aim being to better understand the people behind the names we see in print and at HRD scholarly conferences. John is Chairman of the Board at ITAP International, is a well-known scholar-practitioner, was a recipient of the ASTD International Practitioner of the Year Award, and received the AHRD Service Award in 2010. The conversation explores John's background, how he got into HRD, his time in the Peace Corps, his work with Geert Hofstede, and his wide range of experience in cross-cultural HRD. The conversation also considers how world experiences improve research and practice, the benefits and challenges of applying research in practice, and the importance of practitioners having a sound education in research and statistics.     

Estimating the number of clusters in a data set via the gap statistic

We propose a method (the 'gap statistic') for estimating the number of clusters (groups) in a set of data. The technique uses the output of any clustering algorithm (e.g. K -means or hierarchical), comparing the change in within-cluster dispersion with that expected under an appropriate reference null distribution. Some theory is developed for the proposal and a simulation study shows that the gap statistic usually outperforms other methods that have been proposed in the literature.     

AT THE MOVIES: THE ECONOMICS OF EXHIBITION CONTRACTS

We describe a real-world profit sharing contract—the movie exhibition contract—and consider alternative explanations for its use. Two explanations based on difficulties with forecasting fit the facts better than asymmetric information models. The first emphasizes two-sided risk aversion; the second emphasizes measurement costs. Transaction costs and long-term relationships also affect contractual practices. We use an original data set of all exhibition contracts involving 13 theaters owned by a prominent St. Louis exhibitor over a two-year period to inform our theories and test hypotheses. The findings question traditional contract theory and may be relevant for other contracting environments.(JEL L14 , L82 , D45 , D80 )     

利用双电极装置提高等电聚焦通量

在最大电压12 000 V下操作,蛋白质在固定pH梯度(IPGs)上的等电聚集(IEF)可以在3 h内完成。采用改装的电极装置,将两电极对通过线路并联,可使IEF的通量加倍。、与常规的单电极对相比,成对的IPGs的电压梯度几乎一致,并在大致两倍的电流下运行,IEF可在大致相同的时间内完成。     

Search for relevant subsets of binary predictors in high dimensional regression for discovering the lead molecule

One of the main problems that the drug discovery research field confronts is to identify small molecules, modulators of protein function, which are likely to be therapeutically useful. Common practices rely on the screening of vast libraries of small molecules (often 1–2 million molecules) in order to identify a molecule, known as a lead molecule, which specifically inhibits or activates the protein function. To search for the lead molecule, we investigate the molecular structure, which generally consists of an extremely large number of fragments. Presence or absence of particular fragments, or groups of fragments, can strongly affect molecular properties. We study the relationship between molecular properties and its fragment composition by building a regression model, in which predictors, represented by binary variables indicating the presence or absence of fragments, are grouped in subsets and a bi-level penalization term is introduced for the high dimensionality of the problem. We evaluate the performance of this model in two simulation studies, comparing different penalization terms and different clustering techniques to derive the best predictor subsets structure. Both studies are characterized by small sets of data relative to the number of predictors under consideration. From the results of these simulation studies, we show that our approach can generate models able to identify key features and provide accurate predictions. The good performance of these models is then exhibited with real data about the MMP–12 enzyme.     

Organizational Resilience: A Valuable Construct for Management Research?

Recently, the concept of resilience has gained new momentum in organization studies. It is held to be a very promising concept to explain how organizations can survive and thrive amidst adversity or turbulence. However, findings from an earlier review about resilience in the organizational and business context show that, although empirical research on the concept has increased, there is still a need for more clarity in terms of its measurement. The aim of this paper is to present a systematic review of the organizational resilience construct that covers both conceptual and operational issues. We discuss why researchers criticize resilience for being fuzzy and move on to identify and analyse existing literature under the lens of construct development and taxonomies. With this study, we aim to point out conceptual problems for future researchers to address conceptual clarity and to develop a clearer, more parsimonious concept. We conclude with a suggestion about future measurement.     

Race,Religion, and Opposition to Same‐Sex Marriage*

Objective. We examine racial differences in support for same‐sex marriage, and test whether the emerging black‐white gap is a function of religiosity. We explore how religious factors play a crucial role in racial differences, and how secular factors have varying effects on attitudes for whites and African Americans. Methods. Using data from the General Social Surveys, we estimate ordinal logistic regression models and stacked structural equation models. Results. We show that the racial divide is a function of African Americans' ties to sectarian Protestant religious denominations and high rates of church attendance. We also show racial differences in the influence of education and political values on opposition to same sex marriage. Conclusions. Religious factors are a source of racial differences in support for same‐sex marriage, and secular influences play less of a role in structuring African Americans' beliefs about same‐sex marriage.     

A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: application to robust clustering

We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing multidimensional instead of univariate scale variables for the mixture of scaled Gaussian family of distributions. In contrast to most existing approaches, the derived distributions can account for a variety of shapes and have a simple tractable form with a closed-form probability density function whatever the dimension. We examine a number of properties of these distributions and illustrate them in the particular case of Pearson type VII and t tails. For these latter cases, we provide maximum likelihood estimation of the parameters and illustrate their modelling flexibility on simulated and real data clustering examples.