Knowledge that Transforms

In current debates about job automation, technology adoption is framed as a politics-neutral decision driven by the search for technical efficiency. Discussions about the nature of job design (i.e. the content and distribution of tasks within firms) and its associated automation risk are usually devoid of institutional context. However, job design may be affected by the way firms are governed. A critical feature of workplace governance is the extent to which decision making is shared by capital owners and workers via institutionalized forms of employee representation (ER). In this paper, we propose an evolutionary model to study the complementary fit and endogenous dynamics of job design and workplace governance. We show that two technological-political conventions are likely to emerge: in one of them workplace governance is based on ER and job designs have low automation risk; in the other, ER is absent and workers are involved in automation-prone production tasks. We explore the validity of the theory by using data from a large sample of European workers including detailed information on occupations, task environment, working conditions as well as presence of ER. Results are consistent with the theory: automation risk is negatively associated with the presence of ER. Our analysis can be useful to rationalize the historical experience of Nordic countries, where simultaneous experimentation with codetermination rights and job enrichment programs (supplemented by nationwide institutional reforms) seem to have had enduring consequences in the way these countries confront technological challenges. Policy debates about automation should avoid technological determinism and devote more attention to socio-institutional factors shaping the future of work.

When firms are heterogeneous, externalities within clusters can affect firms asymmetrically. These asymmetries at the firm level lead to a productivity effect at the cluster level that has been overlooked thus far. We develop a heterogeneous firm model where firms with different productivity levels decide how much to invest in market survival. With this model, we find a differentiation between high-productivity firms investing in market survival and low-productivity firms not investing in market survival. Cluster externalities alter the optimal market survival investment of firms, which in turn affects both cluster composition and cluster-level outcomes. By focusing on cluster productivity and assuming that cluster externalities take the form of knowledge spillovers, we find that the effect on the cluster depends on the particular type of knowledge spillovers. Using modelling outcomes and an extensive numerical simulation, we show that knowledge spillovers that reduce the cost of investment benefit investing, high-productivity firms and increase cluster productivity. By contrast, knowledge spillovers that imply that non-investing, low-productivity firms can free ride on the efforts of investing firms tend to reduce cluster productivity. We discuss ramifications for research on clusters and cluster policy, highlighting the importance of industry and knowledge spillover characteristics.

Scholars tend to assume that publicly funded R&D projects, which are competitively selected, outperform projects, which receive funding through a political selection process. In this paper, we empirically explore this assumption, examining the outcomes of 321 R&D projects that were funded by the U.S. Department of Energy's Hydrogen Program. Between 2003 and 2011, projects in this program could not only receive funding by means of a competitive selection process, but also by being earmarked by a U.S. member of Congress. We find that, whereas earmarked projects receive considerably lower peer review evaluation scores than non-earmarked projects, they do not consistently underperform in terms of the productivity, spillovers, and novelty of research- and science-based outcomes. Post-hoc analyses provide indications that this misalignment is driven by the existence of a bias of peer reviewers toward earmarked projects. Jointly, our findings challenge the dominant assumption that competitively selected projects always outperform politically selected ones in the setting of public R&D grants. In this way, we provide academics and policy makers with a richer perspective on the advantages and liabilities of earmarks.

Household sector innovation is significant in scale and scope. Thus far, it has been studied in isolation and with mixed evidence regarding the role of personal resources (consumers' income and discretionary time). We recognize that household sector innovation is embedded in the broader phenomenon of do-it-yourself (DIY) by consumers, as the literature reveals conceptual similarities, parallel motivations, and antecedents. The main distinction is that, whereas DIY goods may replicate existing products, household sector innovation is restricted to goods embodying a novel function. We explore if studying household sector innovation and DIY in an integrated framework helps to resolve previous inconsistent evidence on the role of personal resources. Based on a neoclassical model in which agents optimize their time allocation, we hypothesize that income and discretionary time positively relate to their DIY output, but—given that agents develop DIY goods—we hypothesize that income negatively relates to innovation. For discretionary time, we formulate a research question regarding its effect on innovation which we answer empirically. Our findings suggest that consumers with more personal resources derive more process benefits from DIY but that these benefits crowd out individuals' focus on the function of their objects, hence, the likelihood of developing innovations. Survey data from the United Arab Emirates (n = 2728) confirm our suppositions, showing that the relationship between personal resources and household sector innovation is more refined than suggested by previous studies.