Avoiding the valley of death in educating strategists

Billions of dollars and hundreds of millions of hours are invested every year in executive education. However, much of this investment dies in a familiar “Valley of Death” (VoD) wherein what is learned in the classroom is not applied when the strategist returns back to work. Based on 30 in-depth interviews and live observation, we investigate the architecture of an executive education program designed to avoid the VoD. In the observed program, senior partners of a strategy consulting firm, and their key strategist clients, are brought together to co-learn strategy associated with scenario planning, and, at the same time, improve their ongoing business relations. We find that adopting a “paired learning structure” and utilizing “live case content” results in “group-level co-learning” (or the co-production of knowledge) that, participants report, avoids the VoD. This research contributes to the scholarship on learning architecture in executive education by establishing linkages to the literature on client-partner relationships, modelling the student, and service co-production in knowledge-intensive organizations, and, in the end, provides a blueprint that professional service firms and business schools, seeking to produce more value for their participants, can jointly emulate.     

Food Well-Being in Older Adults: Effects of a Universal Non-contributory Pension in Mexico

Social Indicators Research - One of the few universal programs in Latin America is the Food Pension for Adults Older than 68 (PAAM) of Mexico City, which aims to reduce food insecurity while...     

Comparison op some two sample tests for equality of variances

The F-test, F max-test and Bartlett's test are compared on the basis of power for the purpose of testing the equality of variances in two normal populations. The power of each test is expressed as a linear combination of F-probabilities. Bartlett's test is noted to be unbiased, UMPU, consistent against all alterna¬tives and the test which yields minimum length confidence intervals on the ratio of the variancesλ=σ₁ ² /σ² ₂ The two samples Bartlett critical values, although not recognized as such, are found in the works of other authors. Tables of the powers of each test are given for various values of λ, levels of significance a and the respective sample sizes, n₁ and n₂.     

Tests for bivariate mean residual life

In this paper we have developed tests for bivariate exponentiaIity against the ‘bivariate decreasing mean residual life (BDMRL)’ and ‘bivariate new better than used in expectation (BNBUE)’ classes of non-exponentia1 probability distributions. We have also obtained a large-sample approximation to make the test readily applicable.     

Teaching Literature to Highlight Social Policy Issues

Abstract

Graduate social work education can be enhanced through extensive and appropriate use of relevant literary works. This paper describes an elective course for second-year graduate social work students in which twentieth-century novels were used to highlight social policy issues. The paper deals with the relationships between art and social realities and the usefulness of literature for social policy analysis. A detailed account of this course and its evaluation is presented as well as its potential for replication.     

Bayes and empirical bayes estimation of the probability that z > x + y

Let X, Y and Z be independent random variables with common unknown distribution F. Using the Dirichlet process prior for F and squared erro loss function, the Bayes and empirical Bayes estimators of the parameters λ(F). the probability that Z > X + Y, are derived. The limiting Bayes estimator of λ(F) under some conditions on the parameter of the process is shown to be asymptotically normal. The aysmptotic optimality of the empirical Bayes estimator of λ(F) is established. When X, Y and Z have support on the positive real line, these results are derived for randomly right censored data. This problem relates to testing whether than used discussed by Hollander and Proshcan (1972) and Chen, Hollander and Langberg (1983).     

Investigating the impact of Hurricane Maria on an ongoing birth cohort in Puerto Rico

Population and Environment - Prior to Hurricane Maria, Puerto Rico already had 200+ hazardous waste sites, significant contamination of water resources, and among the highest rates of preterm birth...     

Evaluating Lightning-Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain

It is widely accepted that the relationship between lightning wildfire occurrence and its influencing factors vary depending on the spatial scale of analysis, making the development of models at the regional scale advisable. In this study, we analyze the effects of different biophysical variables and lightning characteristics on lightning-caused forest wildfires in Castilla y León region (Central Spain). The presence/absence of at least one lightning-caused fire in any 4 × 4-km grid cell was used as a dependent variable and vegetation type and structure, terrain, climate, and lightning characteristics were used as possible covariates. Five prediction methods were compared: a generalized linear model (GLM), a random forest model (RFM), a generalized additive model (GAM), a GAM that includes a spatial trend function (GAMs) and a spatial autoregressive model (AUREG). A GAMs with just one covariate, apart from longitude and latitude for each observation included as a combined effect, was considered the most appropriate model in terms of both predictive ability and simplicity. According to our results, the probability of a forest being affected by a lightning-caused fire is positively and nonlinearly associated with the percentage of coniferous woodlands in the landscape, suggesting that occurrence is more closely associated with vegetation type than with topography, climate, or lightning characteristics. The selected GAMs is intended to inform the Regional Government of Castilla y León (the fire and fuel agency in the region) regarding identification of areas at greatest risk so it can design long-term forest fuel and fire management strategies.     

Another generalization of the logarithmic series and the geometric distributions

A new generalization of the logarithmic series distribution is presented based on a generalized negative binomial distribution obtained from a generalized Poisson distribution compounded with the truncated gamma distribution. By length biasing this generalized log-series distribution, another generalized geometric distribution is uresented. For the generalized log-series distribution, maximum likelihood estimators are developed and an example is presented for illustration.