Value of Information in Closed Loop Supply Chains

We explore the value of information (VOI) in the context of a firm that faces uncertainty with respect to demand, product return, and product recovery (yield). The operational decision of interest in matching supply with demand is the quantity of new product to order. Our objective is to evaluate the VOI from reducing one or more types of uncertainties, where value is measured by the reduction in total expected holding and shortage costs. We start with a single period model with normally distributed demands and returns, and restrict the analysis to the value of full information (VOFI) on one or more types of uncertainty. We develop estimators that are predictive of the value and sensitivity of (combinations of) different information types. We find that there is no dominance in value amongst the different types of information, and that there is an additional pay‐off from investing in more than one type. We then extend our analysis to the multi‐period case, where returns in a period are correlated with demands in the previous period, and study the value of partial information (VOPI) as well as full information. We demonstrate that our results from the single period model (adapted for VOPI) carry‐over exactly. Furthermore, a comparison with uniformly distributed demand and return show that these results are robust with respect to distributional assumptions.     

Quality costing: a management review

This paper relates a review of the English language literature on quality costing and traces its historical development; it provides authoritative reading on the subject. The review also has a focus on collection and use of quality-costing methods, quantitative cost data and the role and views of accountants in the task of quality-cost collection and reporting. Amongst the main findings is the preoccupation with the prevention – appraisal – failure categorization of quality costs and lack of guidance on definitions. The considerable impact of the American quality profession on the development of quality costing is pointed out along with the increasingly positive stance of accountants.     

The Job Demand-Control (-Support) Model and psychological well-being: a review of 20 years of empirical research

The Job Demand-Control (JDC) model (Karasek, 1979) and the Job Demand-Control-Support (JDCS) model (Johnson, and Hall, 1988) have dominated research on occupational stress in the last 20 years. This detailed narrative review focuses on the JDC(S) model in relation to psychological well-being. It covers research from 63 samples, published in the period 1979-1997. In the review a distinction is drawn between two different hypotheses prevailing in research on the models. According to the strain hypothesis of the JDC model, employees working in a high-strain job (high demands-low control) experience the lowest well-being. The buffer hypothesis states that control can moderate the negative effects of high demands on well-being. Translating these hypotheses to the expanded JDCS model, the iso-strain hypothesis predicts the most negative outcomes among workers in an iso-strain job (high demands-low control-low social support/isolation), whereas the buffer hypothesis states that social support can moderate the negative impact of high strain on well-being. Although the literature gives considerable support for the strain and iso-strain hypotheses, support for the moderating influence of job control and social support is less consistent. The conceptualization of demands and control is a key factor in discriminating supportive from nonsupportive studies. Only aspects of job control that correspond to the specific demands of a given job moderate the impact of high demands on well-being. Furthermore, certain subpopulations appear to be more vulnerable to high (iso)strain, whereas others benefit more from high control. On the basis of the results of this review, suggestions for future research and theoretical development are formulated.     

Modeling heavy-tailed,skewed and peaked uncertainty phenomena with bounded support

A prevalence of heavy-tailed, peaked and skewed uncertainty phenomena have been cited in literature dealing with economic, physics, and engineering data. This fact has invigorated the search for continuous distributions of this nature. In this paper we shall generalize the two-sided framework presented in Kotz and van Dorp (Beyond beta: other continuous families of distributions with bounded support and applications. World Scientific Press, Singapore, 2004) for the construction of families of distributions with bounded support via a mixture technique utilizing two generating densities instead of one. The family of Elevated Two-Sided Power (ETSP) distributions is studied as an instance of this generalized framework. Through a moment ratio diagram comparison, we demonstrate that the ETSP family allows for a remarkable flexibility when modeling heavy-tailed and peaked, but skewed, uncertainty phenomena. We shall demonstrate its applicability via an illustrative example utilizing 2008 US income data.     

Hospital-sponsored networks. The rush to consolidate and the future of medical practice

As the medical delivery system undergoes fundamental change, there is a growing pressure on hospitals to form networks with physicians. The prime motivation for these entities is to preserve market share and fill beds. There is likewise intense pressure on physicians to join them, even if these networks do not serve their best interests, or the goal of fostering physician-centered practice. A transformation is under way, however, that may well place doctors again in the central role of guiding the new modes of medical practice in the United States.     

Estimating the prevalence of sensitive behaviour and cheating with a dual design for direct questioning and randomized response

Randomized response is a misclassification design to estimate the prevalence of sensitive behaviour. Respondents who do not follow the instructions of the design are considered to be cheating. A mixture model is proposed to estimate the prevalence of sensitive behaviour and cheating in the case of a dual sampling scheme with direct questioning and randomized response. The mixing weight is the probability of cheating, where cheating is modelled separately for direct questioning and randomized response. For Bayesian inference, Markov chain Monte Carlo sampling is applied to sample parameter values from the posterior. The model makes it possible to analyse dual sample scheme data in a unified way and to assess cheating for direct questions as well as for randomized response questions. The research is illustrated with randomized response data concerning violations of regulations for social benefit.     

Multivariate non-linear time series modelling of exposure and risk in road safety research

Summary.  A multivariate non-linear time series model for road safety data is presented. The model is applied in a case-study into the development of a yearly time series of numbers of fatal accidents (inside and outside urban areas) and numbers of kilometres driven by motor vehicles in the Netherlands between 1961 and 2000. The model accounts for missing entries in the disaggregated numbers of kilometres driven although the aggregated numbers are observed throughout. We consider a multivariate non-linear time series model for the analysis of these data. The model consists of dynamic unobserved factors for exposure and risk that are related in a non-linear way to the number of fatal accidents. The multivariate dimension of the model is due to its inclusion of multiple time series for inside and outside urban areas. Approximate maximum likelihood methods based on the extended Kalman filter are utilized for the estimation of unknown parameters. The latent factors are estimated by extended smoothing methods. It is concluded that the salient features of the observed time series are captured by the model in a satisfactory way.     

Context Matters: Explaining How and Why Mobilizing Context Influences Motivational Dynamics

The emphasis in the social-psychological collective action literature is on why individuals take part in collective action; however, it does not elaborate on how different mobilizing contexts may appeal to distinct motivational dynamics to participate. The present study connects the microlevel of motivational dynamics of individual protesters with the mesolevel of social movement characteristics. To do so a field study was conducted. Protesters were surveyed in the act of protesting in two different demonstrations in two different town squares simultaneously organized by two social movements at exactly the same time against the same budget cuts proposed by the same government. But with one fundamental difference, the movements emphasized different aspects of the policies proposed by the government. This most similar systems design created a unique natural experiment, which enabled the authors to examine whether the motivational dynamics of individual protesters are moderated by the social movement context. Previous research suggested an instrumental path to collective action, and the authors added an ideology path. The authors expected and found that power-oriented collective action appeals to instrumental motives and efficacy and that value-oriented collective action appeals to ideological motives, and, finally, that efficacy mediates on instrumental motives and motivational strength, but only so in power-oriented action.     

Metaphors of Protest: A Classification of Motivations for Collective Action

This article proposes a classification of motivations for collective action based in three of Tetlock's (2002) metaphors of social functionalism (i.e., people as intuitive economists, politicians, and theologians). We use these metaphors to map individual- and group-based motivations for collective action from the literature onto the distinction between individuals who are strongly or weakly identified with their social group. We conclude that low identifiers can be best understood as intuitive economists (supported by both early and recent work on collective action), whereas high identifiers can be best thought of as intuitive politicians or theologians (as recent work on social identity has started to explore). Interestingly, our classification reveals a remarkable lack of attention for the intuitive theologian's motivation for collective action. We therefore develop new hypotheses for future research, and derive recommendations for policy and practice from our analysis.