Currents and sub-currents in innovation flows: Explaining innovativeness using new-product announcements

The creation of new knowledge is a haphazard process: not every sector in an economy is equally involved. The effect of industry structure on innovativeness has been a focus of attention for a long time by both academics and policymakers. In a much quoted article, using unique data - new-product announcements - Acs and Audretsch [Acs, Z.J., Audretsch, D.B., 1988. Innovation in large and small firms: an empirical analysis. American Economic Review 78(4), 678-690] identified several characteristics of industry structure and their effects on innovativeness. By analyzing a new and more consciously compiled database, we re-examine their original claims. Our results largely support their findings: industry concentration and degree of unionization for instance hamper innovation; skilled labor promotes it. Our findings diverge in one significant respect from theirs: we suggest that the large firms do not contribute more to an industry’s innovativeness than small firms. At the industry level, we find strong support for the Schumpeter Mark I perspective of creative destruction by small firms rather than creative accumulation by large firms. In addition, we show that less dedicated innovators prove more susceptible to firm-external industry factors than more committed innovators. An unfavorable competitive environment decreases the likelihood that less successful innovators will announce new products.     

Selection as contract to teach at the student's level. Experiences from a South African mathematics and science foundation year

The selection of students is a critical issuecurrently facing South African higher educationinstitutions. The identification and selection ofdisadvantaged students with the potential to succeedin mathematics- and science-based study is aparticularly pressing problem. The new South Africanhigher education law requires that selection is donein a fair and transparent manner. Selection has to befollowed by adequate support for selected students tosucceed in their study programmes. Issues of accessare closely coupled to issues of retention andsuccess. The research results discussed in this paperillustrate how these issues can be successfullyaddressed and how selection fairness and effectivenessmay be optimised under the constraints of selectionefficiency. An optimal solution can be found bydeveloping test specifications and selection cut-offvalues based on the teaching programme for which theselection is done. The resulting close fit betweenselection testing and teaching after selection leadsto a reasonable expectation of success for selectedstudents in the study programme. Under suchconditions, selection can be seen as a contract toteach at the student's level.     

Phase analysis in maximal sprinting: an investigation of step-to-step technical changes between the initial acceleration,transition and maximal velocity phases

Abstract

The aim of this study was to investigate spatiotemporal and kinematic changes between the initial acceleration, transition and maximum velocity phases of a sprint. Sagittal plane kinematics from five experienced sprinters performing 50-m maximal sprints were collected using six HD-video cameras. Following manual digitising, spatiotemporal and kinematic variables at touchdown and toe-off were calculated. The start and end of the transition phase were identified using the step-to-step changes in centre of mass height and segment angles. Mean step-to-step changes of spatiotemporal and kinematic variables during each phase were calculated. Firstly, the study showed that if sufficient trials are available, step-to-step changes in shank and trunk angles might provide an appropriate measure to detect sprint phases in applied settings. However, given that changes in centre of mass height represent a more holistic measure, this was used to sub-divide the sprints into separate phases. Secondly, during the initial acceleration phase large step-to-step changes in touchdown kinematics were observed compared to the transition phase. At toe-off, step-to-step kinematic changes were consistent across the initial acceleration and transition phases before plateauing during the maximal velocity phase. These results provide coaches and practitioners with valuable insights into key differences between phases in maximal sprinting.     

Improving Item-Exposure Control in Adaptive Testing

One of the methods of controlling test security in adaptive testing is imposing random item-ineligibility constraints on the selection of the items with probabilities automatically updated to maintain a predetermined upper bound on the exposure rates. Three major improvements of the method are presented. First, a few modifications to improve the initialization of the method and accelerate the impact of its feedback mechanism on the observed item-exposure rates are introduced. Second, the case of conditional item-exposure control given the uncertainty of examinee's ability parameter is addressed. Third, although rare for a well-designed item pool, when applied in combination with the shadow-test approach to adaptive testing the method may meet occasional infeasibility of the shadow-test model. A big M method is proposed that resolves the issue. The practical advantages of the improvements are illustrated using simulated adaptive testing from a real-world item pool under a variety of conditions.     

Does Facebook Use Predict College Students’ Social Capital? A Replication of Ellison,Steinfield, and Lampe’s (2007) Study Using the Original and More Recent Measures of Facebook Use and Social Capital

In 2007 Ellison, Steinfield, and Lampe published an article on the positive association between Facebook use and social capital that started a decade of research on the social outcomes of social network site use. Although cited almost 9,000 times, it received critique on the conceptualization and operationalization of Facebook use and social capital. In this study we replicate Ellison et al.’s study with original and alternative measures of social capital and Facebook use, thereby shedding light on the robustness, stability, and ecological validity of the original findings. We found that Facebook intensity positively predicts the original social capital measures, lending support to the validity of the original findings. Its relationship with structural measures, however, was weak for bridging and absent for bonding social capital.