While problems of self‐report measures of work stress have long been recognized, those of more ‘objective’ measures are often underestimated. Combining both in structural equation models yields more valid estimates, yet correlations with indicators of well‐being or strain rarely exceed .30. To decide whether this is due to insufficient validity of instruments or to the multi‐causal aetiology of well‐being, the concept of ‘shared job strain’ is introduced. This is a latent variable, with individual symptoms of strain of two workers holding the same job as indicators. Thus, it represents the strain that these two workers have in common, while truly individual variance is removed. It should, therefore, show much higher correlations with job stressors than do individual symptoms of strain. To estimate stressors, self‐reports of the two workers and of two independent observers are used as indicators. Four stressors explained two‐thirds of the variance in ‘shared job strain’. It is concluded (a) that estimating latent job stressors on the basis of self‐report and observer indicators yields highly valid measurement and (b) that the substantive argument is supported. There probably is an upper limit of 15 to 20 per cent variance in total strain symptoms that can be explained by job stressors.

Local clusters and the co-location of firms are repeatedly related to a high level of innovativeness in the literature. The underlying argument is that firms that are co-located with other firms of the same industry undertake more innovation than “lonely” firms because of spillovers, local labour markets and cooperations. These arguments are tested here for four industries in Germany. To this end, four different hypotheses about the impact of co-location on the innovativeness of firms are formulated and empirically compared. The results show that the innovativeness of firms indeed depends on the existence of other firms in the same region. However, the relationship between co-location and innovation output depends on the industry studied.Innovations, spillovers, patents, economies of location,

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This paper explores whether coach training or coaching experience leads to better coaching quality and quality control. In two large studies, both coaches (N1 = 2267) and personnel managers who book coaches for their company (N2 = 754) answered questions about coaching quality and quality control. The results show that more coach training leads to not only a better self-perceived coaching quality (Study 1) but also a better other-perceived coaching-quality (Study 2); moreover, more coach training positively affects quality control. It is remarkable that coaching experience showed no significant relation regarding other-perceived coaching quality and quality control. Study 2 further revealed that references lead to more recommendations but not to a better coaching quality or quality control. Thus, coach training is an essential factor when selecting organizational coaches. Further re-Declarations and Data Availability Statemen The data that supports the findings of these studies are available upon request.