Arenas of expectations for hydrogen technologies

Technological development is often described as an evolutionary process of variation, selection and retention. Different technologies are seen as variations, while the market and other institutions operate as a selection environment. It is less understood, however, how variation and selection relate in the case of emerging technologies. In this paper we introduce the concept of arenas of expectations to examine the relationship between variation and selection processes. Expectations are of particular interest in a pre-market phase of innovation, when performance, cost and other market criteria are less articulated and not stable. In arenas of expectations ‘enactors’ of particular technological variations voice and maintain expectations, while ‘selectors’ will compare and assess the competing claims. We analyse the expectations work of both parties in a case study on metal hydrides for the on-board storage of hydrogen for automotive applications. The paper concludes with a framework of ‘arenas of expectations’ as the linchpin between the processes of variation and selection of emerging technologies

Contradictory yet coherent? Inconsistency in performance feedback and R&D investment change

This paper is based upon doctoral research of the first author conducted while at the Center for Innovation Research, Tilburg University. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In this paper, we study to what extent inconsistent feedback signals about performance affect firm adaptive behavior in terms of changes made to research-and-development (R&D) investments. We argue that inconsistency in performance feedback—based on discrepancies between two distinct performance signals—affects the degree to which such investments will be changed. Our aim is to show that accounting for inconsistent performance feedback is necessary as predictions for the direction of change in R&D investments based on the individual performance feedback signals are contradictory. Furthermore, we contribute by proposing a holistic consideration mechanism as an alternative to the selective attention mechanism previously applied to inconsistent performance feedback. Our findings show that the impact of inconsistency depends on the exact configuration of the underlying performance feedback signal discrepancies. While consistently negative performance feedback signals would amplify their impact in stimulating increased R&D investments, inconsistent performance feedback signals created more nuanced effects. Having lower performance compared to an industry-based peer group—despite doing well compared to the previous year—made firms decrease their R&D investments. For the opposite case of inconsistent performance feedback, we did not find an effect on change in R&D investments. These findings support to a degree our contention that explaining the effects of inconsistent performance feedback requires a holistic consideration theoretical mechanism instead of one involving selective attention. In sum, these findings suggest future research should take into account the differences between distinct instances of inconsistent performance feedback

Social Performance Cues Induce Behavioral Flexibility in Humans

Behavioral flexibility allows individuals to react to environmental changes, but changing established behavior carries costs, with unknown benefits. Individuals may thus modify their behavioral flexibility according to the prevailing circumstances. Social information provided by the performance level of others provides one possible cue to assess the potential benefits of changing behavior, since out-performance in similar circumstances indicates that novel behaviors (innovations) are potentially useful. We demonstrate that social performance cues, in the form of previous players’ scores in a problem-solving computer game, influence behavioral flexibility. Participants viewed only performance indicators, not the innovative behavior of others. While performance cues (high, low, or no scores) had little effect on innovation discovery rates, participants that viewed high scores increased their utilization of innovations, allowing them to exploit the virtual environment more effectively than players viewing low or no scores. Perceived conspecific performance can thus shape human decisions to adopt novel traits, even when the traits employed cannot be copied. This simple mechanism, social performance feedback, could be a driver of both the facultative adoption of innovations and cumulative cultural evolution, processes critical to human success

Evaluation of intravoxel incoherent motion fitting methods in low-perfused tissue

Purpose To investigate the robustness of constrained and simultaneous intravoxel incoherent motion (IVIM) fitting methods and the estimated IVIM parameters (D, D* and f) for applications in brain and low‐perfused tissues. Materials and Methods Model data simulations relevant to brain and low‐perfused tumor tissues were computed to assess the accuracy, relative bias, and reproducibility (CV%) of the fitting methods in estimating the IVIM parameters. The simulations were performed at a series of signal‐to‐noise ratio (SNR) levels to assess the influence of noise on the fitting. Results The estimated IVIM parameters from model simulations were found significantly different (P < 0.05) using simultaneous and constrained fitting methods at low SNR. Higher accuracy and reproducibility were achieved with the constrained fitting method. Using this method, the mean error (%) for the estimated IVIM parameters at a clinically relevant SNR = 40 were D 0.35, D* 41.0 and f 4.55 for the tumor model and D 1.87, D* 2.48, and f 7.49 for the gray matter model. The most robust parameters were the IVIM‐D and IVIM‐f. The IVIM‐D* was increasingly overestimated at low perfusion. Conclusion A constrained IVIM fitting method provides more accurate and reproducible IVIM parameters in low‐perfused tissue compared with simultaneous fitting. Level of Evidence: