Corporate planning at Rolls-Royce Motors Limited

In this article the authors describe the introduction to date of a formal planning process at a British manufacturing company which, according to its recent performance, had no pressing need to implement radical change. Is Rolls-Royce Motors' decision the symptom of a new trend in industry to overhaul planning techniques while the going is good? How was company morale used to justify a new planning style? Why did an evidently capable organization choose to engage consultancy assistance? While the company's intentions are not yet fully achieved, its experience may be of benefit to others contemplating a similar decision.     

The Role of Shocks in Employee Turnover*

This paper reports the findings from a recent study of nurse leavers at eight large hospitals in the National Health Service (NHS) of England and Wales. The study develops and extends an influential theory of employee turnover by describing how for some leavers a single, jarring event or shock triggers the decision to quit. By elaborating on the nature of shocks for this sample of 352 nurse leavers, the paper allows for improved understanding of nursing turnover and thus offers an example of relevant management research. The analysis of shock illustrates how conventional research methodologies can lead to a distorted picture of turnover. This has wider implications, both for any organization wishing to manage turnover effectively and for future research. The paper adds to the limited body of empirical analysis on actual leavers, thereby contributing to an ongoing methodological debate concerning the use of proxy variables. By highlighting flaws in the dominant methodology used to study turnover, the paper offers an example of management research that is also rigorous, and thus ‘pragmatic’.     

Dimension-wise sparse low-rank approximation of a matrix with application to variable selection in high-dimensional integrative analyzes of association

Many research proposals involve collecting multiple sources of information from a set of common samples, with the goal of performing an integrative analysis describing the associations between sources. We propose a method that characterizes the dominant modes of co-variation between the variables in two datasets while simultaneously performing variable selection. Our method relies on a sparse, low rank approximation of a matrix containing pairwise measures of association between the two sets of variables. We show that the proposed method shares a close connection with another group of methods for integrative data analysis – sparse canonical correlation analysis (CCA). Under some assumptions, the proposed method and sparse CCA aim to select the same subsets of variables. We show through simulation that the proposed method can achieve better variable selection accuracies than two state-of-the-art sparse CCA algorithms. Empirically, we demonstrate through the analysis of DNA methylation and gene expression data that the proposed method selects variables that have as high or higher canonical correlation than the variables selected by sparse CCA methods, which is a rather surprising finding given that objective function of the proposed method does not actually maximize the canonical correlation.     

A Joint Modeling Approach for Longitudinal Outcomes and Non-ignorable Dropout under Population Heterogeneity in Mental Health Studies

The paper proposes a joint mixture model to model non-ignorable drop-out in longitudinal cohort studies of mental health outcomes. The model combines a (non)-linear growth curve model for the time-dependent outcomes and a discrete-time survival model for the drop-out with random effects shared by the two sub-models. The mixture part of the model takes into account population heterogeneity by accounting for latent subgroups of the shared effects that may lead to different patterns for the growth and the drop-out tendency. A simulation study shows that the joint mixture model provides greater precision in estimating the average slope and covariance matrix of random effects. We illustrate its benefits with data from a longitudinal cohort study that characterizes depression symptoms over time yet is hindered by non-trivial participant drop-out.KEYWORDS: Latent growth curve, MNAR drop-out, survival analysis, finite mixture model, mental health     

Is the Precautionary Principle Really Incoherent?

The Precautionary Principle has been an increasingly important principle in international treaties since the 1980s. Through varying formulations, it states that when an activity can lead to a catastrophe for human health or the environment, measures should be taken to prevent it even if the cause‐and‐effect relationship is not fully established scientifically. The Precautionary Principle has been critically discussed from many sides. This article concentrates on a theoretical argument by Peterson (2006) according to which the Precautionary Principle is incoherent with other desiderata of rational decision making, and thus cannot be used as a decision rule that selects an action among several ones. I claim here that Peterson's argument fails to establish the incoherence of the Precautionary Principle, by attacking three of its premises. I argue (i) that Peterson's treatment of uncertainties lacks generality, (ii) that his Archimedian condition is problematic for incommensurability reasons, and (iii) that his explication of the Precautionary Principle is not adequate. This leads me to conjecture that the Precautionary Principle can be envisaged as a coherent decision rule, again.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Merit‐based Rewards,Job Satisfaction and Voluntary Turnover: Moderating Effects of Employee Demographic Characteristics

This paper draws on the reflection theory of compensation (Thierry, H. (1998). ‘Compensating work’. in P. J. D. Drenth, H. Thierry and C. J. de Wolff (eds), Handbook of Work and Organizational Psychology, 2nd edn, pp. 291–315, Psychology Press: Hove; Thierry, H. F. (2001). ‘Job evaluation systems and pay grade structures: do they match’, International Journal of Human Resource Management, 8, pp. 1313–1324) to examine the influence of individual merit‐based rewards on voluntary turnover via job satisfaction. It also tests the moderating effects of employees’ gender, age and education level between merit‐based rewards and job satisfaction. Data were collected from 636 employees in Japan at three points in time over a 12‐month period. The findings show that merit‐based rewards have a direct, positive effect on job satisfaction and an indirect effect on voluntary turnover. The effect of merit‐based rewards on job satisfaction was moderated by gender and education, providing evidence that merit‐based rewards are more important for male and highly educated employees. Practical and theoretical implications are discussed.     

Comparison of leadership styles in Confucian Asian countries

The purpose of this study was to examine the overall impact of four leadership styles (charismatic, directive, participative, and supportive) in four Confucian Asian countries, China, Japan, South Korea, and Singapore, by reviewing recent studies conducted in those countries. By reviewing 38 studies selected from 430 studies published between 2005 and 2016, we identify the impact of the four leadership styles in the four Asian countries. We start with the research question and purpose, and then propose criteria for selecting the relevant recent studies followed by a review of cultural heritage and its influence on leadership in the four Asian countries. We summarize and review the studies and, finally, discuss the theoretical and practical contributions of this study.