Aim/Purpose: The purpose of this paper is to understand doctoral and postdoctoral trainee preferences for different models of career development resources and how career-relevant social capital affects these preferences. Background: The supply and demand mismatch within the academic job market is augmented by a growing complaint that trainees are not prepared for a range of careers beyond the academic. So, trainees are often put in a position to seek out resources to navigate their career search processes, yet, the career development strategies that they pursue and the preferences that they have for different types of career development resources is not well understood. Drawing from existing higher education and social capital theory literatures, we examine how trainee preferences for career development resources are shaped by the career support received from their Principal Investigator (PI) and peers, as well as their own self-efficacy. Methodology: We focus on doctoral and postdoctoral trainees in the biomedical science and engineering disciplines at two sites (but involving three institutions) funded by the National Institutes of Health (NIH) Broadening Experiences in Scientific Training (BEST) Program, a program designed to help prepare trainees for a broad variety of bio-medically related careers within and outside of academic research. Using a survey of both BEST and non-BEST trainees (those not formally in a BEST program), we conducted descriptive and logistic regression analyses of survey data to assess the factors affecting trainee preferences for three different types of career development models: (1) an intensive cohort career development experience (BEST “cohort”), (2) ad-hoc resources (“cafeteria”), or (3) choosing not to seek any career development resources at all. Contribution: This study contributes to the doctoral trainee research base by (1) taking a quantitative approach to cohort based interventions for career development, concepts historically largely examined by qualitative methods, (2) distinguishing among the types and sources of support to better tease out the different types of relationships trainees may have, (3) identifying these issues for both the experiences of the doctoral student and the lesser-studied postdoctoral fellow, and (4) moving beyond a single institution study context by examining data from three different university programs, which allows us to control for institutional and demographic characteristics which importantly is recognized as a significant need in cohort model research. Findings: We find that social capital in the form of a supportive environment and peer support was critical for shaping career development preferences. Cohort programs were particularly attractive to trainees interested in careers outside of academic science and who had low career self-efficacy. Trainees who reported high levels of PI support were less likely to pursue other career development resources, while students reporting low levels of PI support were more likely to choose to participate in a career development focused BEST cohort community. Trainees who reported low levels of PI, department, and peer support were less likely to participate in formal career development events or resources offered by academic institutions. Recommendations for Practitioners: These findings can inform university and career development administrators about the social context in which trainees develop and how that matters for how they prefer and value different formats and intensities of career support. Our recommendations point to the importance of developing (if possible) different models for providing career development resources, so trainees can take advantage of the ones most suitable for them. We further recommend programs consider different marketing strategies for the types of career development programs they offer in order for trainees to understand their options and engage in the resources that make the most sense for them. Highlighting the benefits of cohort based programs will help attract those trainees who desire and need that type of support. This clarity in program goals not only helps to set and manage expectations for trainees to know what the outcomes can be, it also helps to inform programs in terms of what resources to use and measure in helping move trainees along in their own career progression. Recommendation for Researchers: We recommend empirically differentiating the different types of support trainees may receive, as our results emphasized that the source of support matters. We also recommend that this study be replicated across different disciplines to assess the extent to which these findings apply universally. Impact on Society: This research is especially important for its impact for the job market and graduate higher education. With the growth in graduate career development training available across U.S. campuses, by designing and targeting the appropriate interventions for career development in academic institutions we can better prepare trainees for their next steps after training as they enter into the job market. Future Research: Future research needs to further examine the black-boxes that are the doctoral student and postdoctoral experiences. This literature is growing, but we need a more concerted effort to understand how factors like support (in its various forms) work with other factors, like career development efficacy. Within this context, future research should look at first generation trainees, as well.

Purpose – The purpose of this paper is to develop a knowledge elicitation strategy to elicit and compile home energy retrofit knowledge that can be incorporated into the development of an intelligent decision support system to help increase the uptake of home energy retrofits. Major problems accounting for low adoption rates despite well-established benefits are: lack of information or information in unsuitable and usable format for decision making by homeowners. Despite the important role of expert knowledge in developing such systems, its elicitation has been fraught with challenges. Design/methodology/approach – Using extensive literature review and a Delphi-dominated data collection technique, the relevant knowledge of 19 industry experts, selected based on previously developed determinants of expert knowledge and suitable for decision making was elicited and compiled. Boolean logic was used to model and represent such knowledge for use as an intelligent decision support system. Findings – A combination of comprehensive knowledge elicitor training, Delphi technique, semi-structured interview, and job shadowing is a good elicitation strategy. It encourages experts to describe their knowledge in a natural way, relate to specific problems, and reduces bias. Relevant and consensus-based expert knowledge can be incorporated into the development of an intelligent decision support system. Research limitations/implications – The consensus-based and relevant expert knowledge can assist homeowners with decision making and industry practitioners and academia with corroboration and enhancement of existing knowledge. The strategy contributes to solving the knowledge elicitation challenge. Originality/value – No previous study regarding a knowledge elicitation strategy for developing an intelligent decision support system for the energy retrofit industry exists.

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Employees who focus on doing a few tasks well are less valuable to most organizations than employees who can adapt to the demands of constant change. Title and tenure have been replaced with performance and competencies. Competencies are the 40-60 behaviors that provide the most overall value to organizations, regardless of job descriptions. An effective system uses competencies for hiring, training, review and reward. Installing a competency-based system is not a simple undertaking, however. It requires culture change and a total commitment from management. If engaged properly, a competency-based system will cut expenses, reduce unwanted turnover, encourage healthy attrition, improve morale and increase the bottom line.

A handful of staff-led youth work mutuals are due to start this year, but how do you go about setting one up successfully?