Coordinating External Manufacturing of Product Modules*

Product modularization has changed gradually from mainly being a way to bring strategic flexibility into product design, to becoming a means to reach new suppliers in a globalized world. Use of external suppliers is facilitated by the “embedded coordination” brought by standardized module interfaces which reduce the interdependence between modules manufactured by different suppliers. However, the distance between design and manufacturing is increased by heavy reliance on suppliers, and requires coordination between design and manufacturing. Hence, this article aims to identify appropriate mechanisms to enable coordination of external manufacturing of product modules. The investigation is based on two case studies in one manufacturing company that has for long relied heavily on external suppliers. The case studies identify different means, coordination mechanisms, of handling the increased distance between design and manufacturing. In addition to organizational solutions, various intermediaries including especially the supply chain function act as bridges between design and manufacturing. The appropriate mechanism to use is decided by the character of the product and the degree of upgrading. We recommend openness to adaptation to situation dynamics rather than investment in optimizing the level of integration with a particular supplier.     

Nonparametric forecasting: a comparison of three kernel-based methods

In this paper the use of three kernel-based nonparametric forecasting methods - the conditional mean, the conditional median, and the conditional mode -is explored in detail. Several issues related to the estimation of these methods are discussed, including the choice of the bandwidth and the type of kernel function. The out-of-sample forecasting performance of the three nonparametric methods is investigated using 60 real time series. We find that there is no superior forecast method for series having approximately less than 100 observations. However, when a time series is long or when its conditional density is bimodal there is quite a difference between the forecasting performance of the three kernel-based forecasting methods.     

The Baby Boom and Its Causes: What We Know and What We Need to Know

This study analyzes the timing, magnitude, and volume of the mid‐twentieth century baby boom in European and non‐European Western countries. The baby boom is found to have been especially strong in the non‐European countries, fairly strong in some European countries, and quite weak in others. While the boom has often been linked with postwar economic growth and the recuperation of births postponed during the Depression era, we argue that this is only a limited part of the story. In most cases the recovery of the birth rate started well before the end of World War II, a fact not accounted for by existing theories. We investigate the roles played by the recovery of period as well as cohort fertility, the underlying marriage boom, and the recovery of marital fertility. We identify major puzzles for future research, including the reasons for strongly declining ages at marriage and the role played by contraceptive failure in the rise of high‐parity births.     

On the Choice of a Prior for Bayesian D-Optimal Designs for the Logistic Regression Model with a Single Predictor

The Bayesian design approach accounts for uncertainty of the parameter values on which optimal design depends, but Bayesian designs themselves depend on the choice of a prior distribution for the parameter values. This article investigates Bayesian D-optimal designs for two-parameter logistic models, using numerical search. We show three things: (1) a prior with large variance leads to a design that remains highly efficient under other priors, (2) uniform and normal priors lead to equally efficient designs, and (3) designs with four or five equidistant equally weighted design points are highly efficient relative to the Bayesian D-optimal designs.     

Degrouping mortality data for the elderly

Proposed in this paper is a technique for estimating, from coarsly grouped empirical death data, the age‐specific numbers of deaths for the elderly population. This question is primarily of interest in countries where the empirical data are available only in a grouped form, given usually in quinquennial age groups and in a large open‐ended interval for the ages 85 and over. The main reason that the official data are given in such a form in some countries of Southern Europe and in the Third World is the existence of heaping in the empirical data, i.e. misstatements in age recording, usually rounding to the nearest integer divisible with five. Our evaluation of the method on Swedish mortality data shows that the technique proposed can be efficiently applied to period mortality data.     

Drinking,Smoking, and Morality: Do ‘Drinkers and Smokers’ Constitute a Stigmatised Stereotype or a Real TB Risk Factor in the Time of HIV/AIDS?

This paper follows up an unexpected finding from a community survey that identified drinking and smoking as the most important tuberculosis (TB) risk factor, far ahead of ones commonly associated with TB such as poverty, overcrowded living conditions, and HIV-positive status. It reports perceptions of drinking and smoking from a three-phased study of the stigma associated with TB, consisting of a qualitative pilot study using focus-group discussions (2006), a larger-scale community survey (2007), and follow-up group discussions (2009). The community attitude survey was conducted with a sample of 1,020 adults living in a low-income township in the Eastern Cape Province, South Africa. The study found that the moral and the biomedical understanding of TB risk are intertwined. In the community survey, perceptions of drinking and smoking as TB risk were predicted by fear of contracting TB and being a self-reported born-again Christian. In the follow-up study, heavy drinking and smoking in shebeens (unlicensed township liquor outlets) was associated with a risky lifestyle that can spread both TB and HIV. The paper discusses the similarities and differences in the roles of church and shebeen in providing social support to township dwellers to cope with problems of daily life. It is tentatively concluded that the stereotypical shebeen ‘drinkers and smokers’, alternatively pitied and maligned by moral society, might serve as the scapegoat that deflects pollution from the ‘new’ TB linked to the AIDS epidemic.     

Fairness motivation in bargaining: a matter of principle

In this paper, we study the role of fairness motivation in bargaining. We show that bargaining between two strongly fairness motivated individuals who have different views about what represents a fair division may end in disagreement. Further, by applying the Nash bargaining solution, we study the influence of fairness motivation on the bargaining outcome when an agreement is reached. In particular, we show that the bargaining outcome is sensitive to the fairness motivation of the two individuals, unless they both consider an equal division fair. We argue that our results accommodate existing experimental and field data on bargaining.     

On Different Types of Uncertainties in the Context of the Precautionary Principle

Few policies for risk management have created more controversy than the precautionary principle. A main problem is the extreme number of different definitions and interpretations. Almost all definitions of the precautionary principle identify “scientific uncertainties” as the trigger or criterion for its invocation; however, the meaning of this concept is not clear. For applying the precautionary principle it is not sufficient that the threats or hazards are uncertain. A stronger requirement is needed. This article provides an in‐depth analysis of this issue. We question how the scientific uncertainties are linked to the interpretation of the probability concept, expected values, the results from probabilistic risk assessments, the common distinction between aleatory uncertainties and epistemic uncertainties, and the problem of establishing an accurate prediction model (cause‐effect relationship). A new classification structure is suggested to define what scientific uncertainties mean.     

Child care practice innovations: using a model of change to develop training strategies

Modernizing health and social services is a major part of the current government agenda in England. As a consequence of this agenda, social workers and their managers are faced with new initiatives designed to increase the effectiveness of social services. Managers and trainers frequently find themselves in a difficult position; they are expected to introduce innovations to a workforce who can feel overwhelmed by the degree and pace of change, and as a consequence some workers can be hostile or resistant to learning about, and working with, new initiatives. This paper describes ways in which a theoretical model of change can be used to analyse likely workforce responses to policy and practice innovations. Based on this analysis, consideration is given to the implications of these responses for training and staff development. The application of the model to the design and delivery of a training strategy is explored: the Framework for the Assessment of Children in Need and Their Families (Department of Health, Department for Education and Employment and The Home Office, 2000) is used as a case example. (This framework is new assessment guidance issued by the Department of Health for use in England.) The paper describes ways in which the model can assist educators promote effective learning and support practitioners and their managers through major change. Copyright © 2001 John Wiley & Sons, Ltd.