Informal workplace learning (IWL) is an important part of workrelated continuing education, especially in the case of bluecollar workers. The current article presents a new measure of IWL, which we developed based on the already existing Dynamic Model of Informal Learning by Tannenbaum et al. (2010). We extended the model to eight components by theoretical considerations, introducing a second-order structure. Each component is represented on the IWL scale with three items, the subscales have sound internal consistencies (α range between .76 and .92). The article also presents a short version of the scale comprising eight items (α = .79). Study 1 describes the process of item selection, while Study 2 deals with different theoretically conceivable models comparing their model fits. The predicted model with eight factors in a second-order structure achieves the best model fit. In addition, convergent, discriminant, and criterion validity are demonstrated. Mediumsized relationships of IWL components to conscientiousness and learning outcomes confirm the nomological network we developed previously in our study. The discussion provides limitations and possible scientific and practical applications of the IWL scale, for example, the transfer of the measure to other contexts and target groups. K E Y W O R D S blue-collar workers, informal workplace learning, scale development

We investigated informal workplace learning (IWL) within an under-researched target group: blue-collar workers. IWL is particularly important for these workers because of learning barriers to participation in formal training. Based on meta-analytical conceptualizations and findings, we developed a conceptual framework of antecedents, processes, and learning outcomes of IWL among blue-collar workers (APO framework), following an input-process-output perspective. The results of our structural equation model analysis with N = 702 blue-collar workers from small and medium-sized businesses provided support for seven of eight hypotheses: Personal antecedents, namely curiosity, learning goal orientation, and self-directed learning orientation were positively related to IWL; organizational antecedents, namely social support—containing supervisor support, coworker support, and error-related learning climate—and, surprisingly, time pressure were positively related to IWL; IWL was positively related to three learning outcomes, namely job involvement, newly acquired competency, and organizational citizenship behavior. The findings establish a basis for future longitudinal studies and theory building in workplace learning research, and they provide managers in organizations with guidance to promote IWL.

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The challenges resulting from increasing digitalization and globalization require flexible continuing education for white-collar workers. Especially informal learning becomes increasingly important in the modern workplace. Practitioners want to promote informal learning among employees, researchers want to unveil conducive contextual conditions for informal learning, but they lack an appropriate, validated measure. Based on the octagon model of informal workplace learning (Decius et al., Human Resource Development Quarterly, 2019, 30, 495-535) and an existing 24-item scale for blue-collar workers, we present a short version of eight items for use among white-collar workers.Using three independent samples of 695, 500, and 3134German employees, we show that the second-order factor structure-following the multidimensional octagon modelhas a better fit compared with a model in which all items load on a single factor. The short scale is strongly correlated with the original full scale. The scale's reliability is satisfying (α = 0.76/0.77/0.85; ω = 0.78/0.78/0.86), considering the heterogeneous conceptual nature of informal learning.Regarding criterion validity, we found theoretically expected correlations with job demands, job autonomy, knowledge/skill acquisition, age, and self-directed learning

One of the main challenges in technology transfer is to actively involve small and medium-sized enterprises (SMEs)—which are most in need of and benefit the most from collaborative Research and Development (R&D) programs. This study presents a large-scale collaboration program which focuses on project-based technology transfer in SMEs with little to no prior experience in collaborative research projects. The core of this collaboration program is the temporary secondment of scientists from a Research and Technology Organization (RTO) into an SME to jointly work on a practical project objective—which is directly tailored to the demands of the SME. To evaluate the effectiveness of this approach in overcoming barriers related to finding the right collaboration partner, limited resources, and limited absorptive capabilities, we adopt the R&D Lifecycle Model as a theoretical framework. Our findings, using self-reported and objective data from 106 different projects in a structural equation model, highlight that most SMEs in the considered cluster environment not only successfully mastered a challenging topic in the context of industry 4.0 that immediately benefits the organization, but also engaged in new R&D projects to strengthen their scientific and technical human capital in the long term. Moreover, consistent with previous literature, we found that trust is the main driver within the R&D Lifecycle Model both in building capabilities and economic growth. Based on these insights, we consider a long and close secondment of scientists to SMEs as key for collaboration projects and discuss implications for research and future technology transfer approaches.