Intervention Research as Management Research in Practice: Learning from a Case in the Fashion Design Industry

Research in the field of management and organizational sciences has yielded a deeper understanding of many emerging business issues. However, the relevance of the contributions has been increasingly criticized, in both the academic and public spheres. We propose the intervention research approach – originally developed by the research group at Ecole des Mines de Paris – as a design science approach able to address both the relevance gap issue and the growing complexity of management practice. It is argued that increasing our understanding of management requires research that is more insightful, influential and immediately applicable. This in turn requires closer collaboration between management and researchers during the inquiry process, which is not always easy to achieve. An illustrative case study of an intervention research project focusing on creativity, conducted in Italy in collaboration with a fashion company, demonstrates how intervention research can be rigorous and relevant to practitioners, and how it can advance theoretical knowledge in management science.     

Biopharmaceutical and chemical firms’ R&D disclosure,and cost of equity: The impact of the regulatory regime

Based on the proprietary costs theory, this paper aims to survey whether the regulatory regime (mandatory versus voluntary) of research and development (R&D) narrative disclosures impacts, by the means of a reduced information asymmetry, on the cost of equity capital. In order to construct a disclosure index to investigate the extent and the comprehensiveness of R&D information, the methodology adopted was the content analysis of 77 biopharmaceutical and chemical listed companies’ management reports from eight Western European countries across the period 2005–2009. Hence, we obtained an (unbalanced) panel data of 309 observations. The cost of capital has subsequently been regressed on the disclosure index. Results confirm a larger amount of R&D disclosures whereas information is more regulated, but they do not confirm an inverse relation with the cost of capital.     

American family: looking good

The American family is becoming stronger because marriage and parenthood are becoming options, not mandates. Previously nearly 95% of Americans were married, a higher percentage than any other country except India. Often people become parents for the wrong reasons, such as parents of the couple wanted grandchildren or the feeling that one must have a baby to have meaning in life. Later marriage is seen as eventually lowering the divorce rate because adults will be mature. Increased use of contraception, and abortion as a last resort, is reducing the number of unplanned, unwanted children who may be abused. Reminders of the motherhood mandate are traditional houses in the suburbs far from jobs. Traditionally commuting times for women have been less than for men, presumably to allow them to spend more time with the children. It is also suggested that schools give realistic courses on parenting and emphasize that having children is not for everyone.     

Some measures of kurtosis and their inference on large datasets

AStA Advances in Statistical Analysis - This paper deals with the estimation of kurtosis on large datasets. It aims at overcoming two frequent limitations in applications: first, Pearson's...     

Bayesian inference for contingency tables with given marginals

Summary In this paper we introduce a class of prior distributions for contingency tables with given marginals. We are interested in the structrre of concordance/discordance of such tables. There is actually a minor limitation in that the marginals are required to assume only rational values. We do argue, though, that this is not a serious drawback for all applicatory purposes. The posterior and predictive distributions given anM-sample are computed. Examples of Bayesian estimates of some classical indices of concordance are also given. Moreover, we show how to use simulation in order to overcome some difficulties which arise in the computation of the posterior distribution.     

Bayesian analysis of dynamic magnetic resonance breast images

Summary.  We describe an integrated methodology for analysing dynamic magnetic resonance images of the breast. The problems that motivate this methodology arise from a collaborative study with a tumour institute. The methods are developed within the Bayesian framework and comprise image restoration and classification steps. Two different approaches are proposed for the restoration. Bayesian inference is performed by means of Markov chain Monte Carlo algorithms. We make use of a Metropolis algorithm with a specially chosen proposal distribution that performs better than more commonly used proposals. The classification step is based on a few attribute images yielded by the restoration step that describe the essential features of the contrast agent variation over time. Procedures for hyperparameter estimation are provided, so making our method automatic. The results show the potential of the methodology to extract useful information from acquired dynamic magnetic resonance imaging data about tumour morphology and internal pathophysiological features.     

A statistical framework for expression-based molecular classification in cancer

Summary. Genome-wide measurement of gene expression is a promising approach to the identification of subclasses of cancer that are currently not differentiable, but potentially biologically heterogeneous. This type of molecular classification gives hope for highly individualized and more effective prognosis and treatment of cancer. Statistically, the analysis of gene expression data from unclassified tumours is a complex hypothesis-generating activity, involving data exploration, modelling and expert elicitation. We propose a modelling framework that can be used to inform and organize the development of exploratory tools for classification. Our framework uses latent categories to provide both a statistical definition of differential expression and a precise, experiment-independent, definition of a molecular profile. It also generates natural similarity measures for traditional clustering and gives probabilistic statements about the assignment of tumours to molecular profiles.     

Demographic and Predeparture Factors Associated with Drinking and Alcohol-Related Consequences for College Students Completing Study Abroad Experiences

Abstract

Objective: Study abroad students are at risk for increased and problematic drinking behavior. As few efforts have been made to examine this at-risk population, the authors predicted drinking and alcohol-related consequences abroad from predeparture and site-specific factors. Participants: The sample consisted of 339 students completing study abroad programs. Methods: Participants filled out online measures at predeparture, abroad, and at postreturn. Results: The authors found that drinking and consequences abroad were predicted by a number of factors, including demographics (eg, younger age, male sex, Greek affiliation, white ethnicity), student factors (eg, low GPA, major area of study), study abroad site factors (eg, apartment living abroad, study in Europe), predeparture levels of drinking and consequences, sensation seeking, and goals related to social gathering. Conclusions: Findings can be used to inform campus policies for admission to study abroad programs as well as assist in the development of interventions targeted toward preventing risk for students during abroad experiences.