The Effect of Socialization Mechanisms and Performance Measurement on Supplier Integration in New Product Development

This article examines the effect of socialization mechanisms and supplier performance measurement on the level of supplier integration in new product development and subsequent firm performance outcomes. Prior research has found socialization mechanisms and performance measures to be effective in managing supplier relationships, though research examining their impact within a product development context has been limited. Socialization mechanisms, such as supplier conferences and on‐site visits, help establish communication and information‐sharing routines necessary to achieve supplier integration in the product development process. Using performance measures to evaluate a supplier helps focus managerial attention on areas such as innovation and communication that are important to integration success. A structural equation model, using a sample of 142 manufacturing firms based in the United Kingdom, indicates that the level of supplier integration in new product development is positively influenced by socialization mechanisms and innovation‐focused measures of supplier performance, but not significantly associated with the use of communication measures. In turn, increased levels of supplier integration led to improvements in both collaboration outcomes and business performance. Socialization mechanisms were also found to have a direct effect on collaboration outcomes achieved by the firm. Managerial implications and future research directions are discussed.     

The association between job skill discretion, decision authority and burnout

This paper reports on the relationship between dimensions of control (skill discretion and decision authority) and burnout (emotional exhaustion, depersonalization, and reduced personal accomplishment) among 164 human service workers. It examines the differential influence of job demands, control (skill discretion and decision authority) and social support (supervisor, co-workers, others) on each burnout dimension. Then it examines the moderating effects of higher skill discretion, higher decision authority, and higher social support on burnout. Low skill discretion was found to be associated with high emotional exhaustion and depersonalization and low personal accomplishment. The effects of decision authority were not statistically significant. High job demands were associated with high emotional exhaustion only. Social support (supervisor, co-worker, and others) was not associated with burnout when demographic variables and job characteristics were controlled for. Neither dimension of control moderated the impact of high job demands on burnout. Social support did not moderate the impact of high demands, low skill discretion, or low decision authority on any burnout dimension. The full model explained 44% of the variance in emotional exhaustion, 25% in depersonalization, and 42% in personal accomplishment. Despite its limitations, the study suggests that the Job Demand-Control model may provide a useful theoretical foundation for the study of burnout, but that the control dimensions need to be evaluated independently since they appear to be differentially related to the burnout dimensions.     

Accountability and the Camera Perspective Bias in Videotaped Confessions

Prior research indicates that altering the perspective from which a videotaped confession is recorded influences assessments of the confession's voluntariness. The present study examined whether increasing decision makers' sense of accountability attenuates this biasing effect of camera perspective. Participants in a high-accountability (but not a low-accountability) condition were told that they would have to justify their judgments concerning the voluntary status of a video-taped confession to a trial judge. Although supplementary measures indicated that high-accountability participants processed information contained in the video-taped confession more carefully and thoroughly, the camera perspective bias persisted. This result adds to a growing body of work indicating that the criminal justice system needs to be seriously concerned with how it acquires and utilizes videotaped confession evidence.     

The fourth age and the concept of a ‘social imaginary’: A theoretical excursus

This paper explores the idea of the ‘fourth age’ as a form of social imaginary. During the latter half of the twentieth century and beyond, the cultural framing of old age and its modern institutionalisation within society began to lose some of its former chronological coherence. The ‘pre-modern’ distinction made between the status of ‘the elder’ and the state of ‘senility’ has re-emerged in the ‘late modern’ distinction between the ‘third’ and the ‘fourth’ age. The centuries-old distaste for and fear of old age as ‘senility’ has been compounded by the growing medicalization of later life, the emergence and expansion of competing narratives associated with the third age, and the progressive ‘densification’ of the disabilities within the older institutionalised population. The result can be seen as the emergence of a ‘late modern’ social imaginary deemed as the fourth age. This paper outlines the theoretical evolution of the concept of a social imaginary and demonstrates its relevance to aging studies and its applicability to the fourth age.     

Computational methods for complex stochastic systems: a review of some alternatives to MCMC

We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situations they can be difficult to implement; and suffer from problems such as poor mixing, and the difficulty of diagnosing convergence. Here we review three alternatives to MCMC methods: importance sampling, the forward-backward algorithm, and sequential Monte Carlo (SMC). We discuss how to design good proposal densities for importance sampling, show some of the range of models for which the forward-backward algorithm can be applied, and show how resampling ideas from SMC can be used to improve the efficiency of the other two methods. We demonstrate these methods on a range of examples, including estimating the transition density of a diffusion and of a discrete-state continuous-time Markov chain; inferring structure in population genetics; and segmenting genetic divergence data.     

Profile upper Confidence Limits from Discrete Data

When the data are discrete, standard approximate confidence limits often have coverage well below nominal for some parameter values. While ad hoc adjustments may largely solve this problem for particular cases, Kabaila & Lloyd (1997) gave a more systematic method of adjustment which leads to tight upper limits, which have coverage which is never below nominal and are as small as possible within a particular class. However, their computation for all but the simplest models is infeasible. This paper suggests modifying tight upper limits by an initial replacement of the unknown nuisance parameter vector by its profile maximum likelihood estimator. While the resulting limits no longer possess the optimal properties of tight limits exactly, the paper presents both numerical and theoretical evidence that the resulting coverage function is close to optimal. Moreover these profile upper limits are much (possibly many orders of magnitude) easier to compute than tight upper limits.