Peer and Friend Influences on Children's Eating

Peers and friends are perceived as important role models for the formation of children's attitudes and behaviours. A wealth of research has aimed to establish the contribution of peers and friends to children's developing eating behaviours, and their attitudes towards eating. This review describes and evaluates such research. Experimental research examining peer modelling of food consumption and liking is reviewed, and several individual child factors that are suggested to make children more or less receptive to peer and friend influences are discussed. The influence of children's perceptions of their peers’ and friends’ eating behaviours upon their own eating practices is also explored. The benefits of future longitudinal research to improve understanding of peer and friend influences on children's eating are emphasized.     

Modelling of connected processes

The problem of comparing, contrasting and combining information from different sets of data is an enduring one in many practical applications of statistics. A specific problem of combining information from different sources arose in integrating information from three different sets of data generated by three different sampling campaigns at the input stage as well as at the output stage of a grey-water treatment process. For each stage, a common process trend function needs to be estimated to describe the input and output material process behaviours. Once the common input and output process models are established, it is required to estimate the efficiency of the grey-water treatment method. A synthesized tool for modelling different sets of process data is created by assembling and organizing a number of existing techniques: (i) a mixed model of fixed and random effects, extended to allow for a nonlinear fixed effect, (ii) variogram modelling, a geostatistical technique, (iii) a weighted least squares regression embedded in an iterative maximum-likelihood technique to handle linear/nonlinear fixed and random effects and (iv) a formulation of a transfer-function model for the input and output processes together with a corresponding nonlinear maximum-likelihood method for estimation of a transfer function. The synthesized tool is demonstrated, in a new case study, to contrast and combine information from connected process models and to determine the change in one quality characteristic, namely pH, of the input and output materials of a grey-water filtering process.     

Did small and medium enterprises maintain better jobs during the early years of the recession? Job quality multidimensional evidence from Spain

While the literature has indeed confirmed a general tendency linking small and medium enterprises (SMEs) to a dynamic of greater job creation, there is little available evidence on what has happened to job quality since the financial crisis. Through a representative sample of 5311 employees in 2008 (first year of job destruction) and 4925 employees in 2010 (last year for which data were available), and using a two-stage structural equation model, this article empirically analyses the multidimensional determinants of job quality, by enterprise-size class, in Spain. The research has revealed three main results. First, job quality in Spain improved in all enterprises, regardless of their size, during the early years of the recession. Second, the greatest improvements were found in SMEs. Although job quality was already better in SMEs than in large enterprises in 2008, the differences between them subsequently widened. Third, this accelerated divergence was explained by the following dimensions: working conditions, work intensity, health and safety at work, and work–life balance. These dimensions were much more positive in SMEs. Employment-related public policy should therefore focus more specifically on SMEs. There are two reasons for this. First, despite the recession, SMEs have shown themselves to be key factors in the explanation of job quality. Second, by making changes to their value generation model, they could continue to drive the creation of better quality jobs.     

The limitations of using school league tables to inform school choice

Summary. In England, so-called 'league tables' based on examination results and test scores are published annually, ostensibly to inform parental choice of secondary schools. A crucial limitation of these tables is that the most recent published information is based on the current performance of a cohort of pupils who entered secondary schools several years earlier, whereas for choosing a school it is the future performance of the current cohort that is of interest. We show that there is substantial uncertainty in predicting such future performance and that incorporating this uncertainty leads to a situation where only a handful of schools' future performances can be separated from both the overall mean and from one another with an acceptable degree of precision. This suggests that school league tables, including value-added tables, have very little to offer as guides to school choice.     

The Food Crisis and its Impacts on Poverty in Senegal and Mali: Crossed Destinies

This article uses two CGE macro‐micro models to analyse the distributional impact of the food crisis and policy responses in two neighbouring African countries, both of which are strongly dependent on agriculture. The approach captures structural differences at both the macro and micro level for household income and expenditure structures, and the results reveal differences for poverty impact at the national and sub‐group levels, as well as for inequality and pro‐poor analysis. The importance of country‐specific analysis and the risk of extrapolating conclusions from one country to another are also highlighted.     

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distributions that can address data dispersion along with excess zeros. This work develops a zero-inflated sum-of-Conway-Maxwell-Poissons (ZISCMP) regression as a flexible analysis tool to model count data that express significant data dispersion and contain excess zeros. This class of models contains several special case zero-inflated regressions, including zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), zero-inflated binomial (ZIB), and the zero-inflated Conway-Maxwell-Poisson (ZICMP). Through simulated and real data examples, we demonstrate class flexibility and usefulness. We further utilize it to analyze shark species data from Australia's Great Barrier Reef to assess the environmental impact of human action on the number of various species of sharks.     

A dynamic business modelling approach to design and experiment new business venture strategies

Business Modelling has evolved as a key activity to reflect new business venture strategy by framing the way a firm will operate and how it will function in achieving its goals (e.g., profitability, growth, innovation, social impact). However, scholars and practitioners have criticized the adoption of a too static perspective in the design and use of conventional Business Model representations. Such a static perspective prevents nascent entrepreneurs experimenting with their Business Models and, as a result, identifying the most effective strategies, especially in terms of business sustainability and profitability. In this paper, we argue that combining conventional Business Model schemas with System Dynamics modelling results in a strategy design tool that may overcome several limitations related to a static view of Business Model representation. Mapping the different key elements underlying value creation processes into a system of causal interdependencies – through the use of simulation – allows strategy analysts and entrepreneurs to experiment and learn how the business reacts to strategic and organizational changes in terms of performance, innovation and value creation. As such, Dynamic Business Models provide useful insights to strategy formulation and business venturing by capturing how critical Business Model elements interact to produce enduring competitive advantages over time.     

Room for manoeuvre: User participation in water resources management in Burkina Faso

Participation in natural resources management is widely promoted in sub‐Saharan Africa, but faces mounting criticism from social science scholars who rarely engage with it in practice. We use the notion of room for manoeuvre to reflect on a multi‐level participatory approach designed to support the Burkinabè Integrated Water Resources Management policy and propose ways of engaging constructively with local users and policy‐makers. Within an “invited space” of participation, water users’ room for manoeuvre was enhanced through the acquisition of new knowledge on the legal Integrated Water Resources Management (IWRM) framework. This allowed them to interact with decision‐makers and to extend their networks. Power imbalances were discussed, but this did not lead to modifying existing power structures that hinge on broader societal dynamics.     

Understanding the theory behind the Last Planner System using the Language-Action Perspective: two case studies

Since the Last Planner System® (LPS) was devised in the early 90s, a number of studies have pointed out the need to understand the underlying theory in which it is based on. The Language-Action Perspective (LAP) has been suggested as a suitable approach to understand the management of commitments in the LPS. This paper aims to assess the contribution of LAP to understand construction planning and control systems based on LPS. Two case studies were carried out in different construction companies, both highly experienced on the use of LPS. The results reveal the role of LAP for creating explicit representations of commitment flows that can be used to explain the sources of complexity and failures in planning systems, as well as for describing the profile of planning and control meetings.     

Estimation and inference of the joint conditional distribution for multivariate longitudinal data using nonparametric copulas

In this paper we study estimating the joint conditional distributions of multivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models, we consider a class of time-varying transformation models and combine the two marginal models using nonparametric empirical copulas. Our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Empirical copulas combined with time-varying transformation models may allow quite flexible modelling for the joint conditional distributions for multivariate longitudinal data. We derive the asymptotic properties for the copula-based estimators of the joint conditional distribution functions. For illustration we apply our estimation method to an epidemiological study of childhood growth and blood pressure.