Training and organisational performance: A meta‐analysis of temporal,institutional and organisational context moderators

Drawing on systems theory, we conducted a moderated meta‐analysis of the training and organisational performance relationship using 119 primary studies. We examined the moderating effects of quality versus quantity of training, time, institutional and organisational context factors in the relationship between training and organisational performance. Our findings reveal that training is positively and directly related to organisational performance with no statistically significant difference between measures of training quality and quantity. We found that the relationship was stronger over time and that country performance orientation and country labour cost moderate the training and organisational performance relationship. We found no evidence for the moderating effects of the three organisational context moderators we examined (i.e. industry sector, organisational size and technology intensity). Finally, our results reveal that training type (i.e. general or firm‐specific) does not moderate the training and organisational performance relationship.     

Stories from the field: women’s networking as gender capital in entrepreneurial ecosystems

Small Business Economics - Women are under-represented in successful entrepreneurial ecosystems and the creation of women-only entrepreneurial networks has been a widespread policy response. We...     

The marketing of love: how attachment styles affect romantic consumption journeys

Journal of the Academy of Marketing Science - The experience of romantic love is closely interlocked with consumption journeys—yet how and why consumers engage in romantic consumption is not...     

On the Application of Markov Chain Monte Carlo Methods to Genetic Analyses on Complex Pedigrees

Markov chain Monte Carlo methods are frequently used in the analyses of genetic data on pedigrees for the estimation of probabilities and likelihoods which cannot be calculated by existing exact methods. In the case of discrete data, the underlying Markov chain may be reducible and care must be taken to ensure that reliable estimates are obtained. Potential reducibility thus has implications for the analysis of the mixed inheritance model, for example, where genetic variation is assumed to be due to one single locus of large effect and many loci each with a small effect. Similarly, reducibility arises in the detection of quantitative trait loci from incomplete discrete marker data. This paper aims to describe the estimation problem in terms of simple discrete genetic models and the single-site Gibbs sampler. Reducibility of the Gibbs sampler is discussed and some current methods for circumventing the problem outlined.     

Gender and ethnic differences in factors that influence food intake

Abstract The objective of this research was to ascertain the gender-and ethnic-related factors that influence what one eats. This survey was conducted using a validated, pilot-tested questionnaire in 11 states and the District of Columbia, which were participating in the W-182 Western Regional Research project. The results indicated that the factors that influence what one eats differ by gender and ethnicity. Men were very much influenced by likes and dislikes, and by their spouse or significant other. Women were influenced by likes and dislikes, and health. Food likes/dislikes and concerns about health and weight were among the leading four factors for all ethnic groups. Food likes/dislikes were the top factor influencing what is eaten by 51% or more of Asians, Pacific Islanders, Caucasians and Hispanics. Concern about health was the top factor for 62% and 58%, respectively, of African Americans and Native Americans.