Demystifying academics to enhance university-business collaborations in environmental science.

In countries globally (e.g. UK, Australia) there is intense political interest in fostering effective universitybusiness collaborations, but there has been scant attention devoted to exactly how individual scientists' workload (i.e. specified tasks) and incentive structures (i.e. assessment criteria) may act as a key barrier to this. To investigate this an original, empirical dataset is derived from UK job specifications and promotion criteria, which distil universities' varied drivers into requirements upon academics. This reveals the nature of the severe challenge posed by a heavily timeconstrained culture; specifically, a tension exists between opportunities presented by working with industry and non-optional duties (e.g. administration, teaching). Thus, to justify the time to work with industry, such work must inspire curiosity and facilitate future novel science in order to mitigate its conflict with the overriding imperative for academics to publish. It must also provide evidence of real-world changes (i.e. impact), and ideally other reportable outcomes (e.g. official status as a business' advisor), to feed back into the scientist's performance appraisals. Indicatively, amid 20-50 key duties, scientists may be able to free up to 0.5 days/week for work with industry. Thus specific, pragmatic actions, including short-term and time-efficient steps, are proposed in a 'user guide' to help initiate and nurture a long-term collaboration between an early- to mid-career environmental scientist and a practitioner in the insurance industry. These actions are mapped back to a tailored typology of impact and newly-created representative set of appraisal criteria to explain how they may be effective, mutually beneficial, and overcome barriers. Throughout, the focus is on environmental science, with illustrative detail provided through the example of natural hazard risk modelling in the insurance industry. However, a new conceptual model is developed, joining perspectives from literatures on academics' motivations and performance assessment, which we tentatively posit is widely applicable. Sector-specific details (e.g. list of relevant impacts, 'user guide') may serve as templates globally and across sectors.