External knowledge search,absorptive capacity and radical innovation in high-technology firms

Open innovation and absorptive capacity are two concepts based on the idea that companies can leverage the knowledge generated externally to improve their innovation performance. The aim of this paper is to analyse the joint effect of open innovation and absorptive capacity on a firm's radical innovation. Open innovation is expressed in terms of external search breadth and depth strategies and absorptive capacity is described by distinguishing between potential and realized absorptive capacity. In order to test our hypotheses, we carried out empirical research in firms operating in high-technology industries. The results indicate that internal routines and processes for absorbing external knowledge help explain radical innovation as they show a significant effect of potential and realized absorptive capacity. Also, there is a moderating effect of absorptive capacity on open innovation. Specifically, potential absorptive capacity exerts a positive effect on the relationship between external search breadth and depth and radical innovation. Realized absorptive capacity moderates the influence of external search breadth. These findings confirm the complementary nature of absorptive capacity and open innovation search strategies on radical innovation.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression

This article proposes several estimators for estimating the ridge parameter k based on Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value, and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criteria are very informative because, if several estimators have an equal estimated MSE, then those with low average value and standard deviation of k should be preferred. Based on the simulated results, we may recommend some biasing parameters that may be useful for the practitioners in the field of health, social, and physical sciences.     

Australia and the Global South: Knowledge and the Ambiguities of Place and Identity

Australia was settled as a colony of Britain from the 17th century, and its early history of violent occupation has gradually given way to a relatively peaceful, wealthy, multicultural society. As a post-colonial country, its people share characteristics with those of Britain, but, as a multicultural society, national identity is increasingly influenced by the cultures of many countries, from both the global North and South. In this paper, the question of Australia's placement as a country of the global North or South is explored. Considerations of geography, the economy, political regimes and national identity are the backdrop to an investigation of Australian scholarship and the attitudes of scholars to the inclusion of Australia as a country of the global South.     

Ethical Numbers: Ethics Training in U.S. Graduate Statistics Programs, 2013–2014

As important members of research teams, statisticians bear an ethical responsibility to analyze, interpret, and report data honestly and objectively. One way of reinforcing ethical responsibilities is through required courses covering a variety of ethics-related topics at the graduate level. We assessed ethics requirements for graduate-level statistics training programs in the United States for the 2013–2014 academic year using the websites of 88 universities, examining 103 biostatistics programs, and 136 statistics degree programs. We categorized programs’ ethics training requirements as required or not required. Thirty-one (35.1%) universities required an ethics course for at least some degree students. Sixty-two (25.5%) degree programs required an ethics course for at least some students. The majority (77.4%) of required courses were worth 0 or 1 credit. Of the 177 programs without an ethics requirement, 19 (10.7%) listed an ethics elective. Although a single ethics course is insufficient for instilling an ethical approach to science, degree programs that model expectations through coursework point to the value of ethics in science. More training programs should prepare statisticians to consider the ethical dimensions of their work through required coursework. Supplementary materials for this article are available online.     

Developing a Broadly Applicable Measure of Risk Perception

Decades of research identify risk perception as a largely intuitive and affective construct, in contrast to the more deliberative assessments of probability and consequences that form the foundation of risk assessment. However, a review of the literature reveals that many of the risk perception measures employed in survey research with human subjects are either generic in nature, not capturing any particular affective, probabilistic, or consequential dimension of risk; or focused solely on judgments of probability. The goal of this research was to assess a multidimensional measure of risk perception across multiple hazards to identify a measure that will be broadly useful for assessing perceived risk moving forward. Our results support the idea of risk perception being multidimensional, but largely a function of individual affective reactions to the hazard. We also find that our measure of risk perception holds across multiple types of hazards, ranging from those that are behavioral in nature (e.g., health and safety behaviors), to those that are technological (e.g., pollution), or natural (e.g., extreme weather). We suggest that a general, unidimensional measure of risk may accurately capture one's perception of the severity of the consequences, and the discrete emotions that are felt in response to those potential consequences. However, such a measure is not likely to capture the perceived probability of experiencing the outcomes, nor will it be as useful at understanding one's motivation to take mitigation action.     

Efficacy,Action, and Support for Reducing Climate Change Risks

A growing body of research demonstrates that believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts. Despite this potentially critical role of efficacy beliefs, measures and their use vary wildly in climate change risk perception and communication research, making it hard to compare and learn from efficacy studies. To address this problem and advance our understanding of efficacy beliefs, this article makes three contributions. First, we present a theoretically motivated approach to measuring climate change mitigation efficacy, in light of diverse proposed, perceived, and previously researched strategies. Second, we test this in two national survey samples (Amazon's Mechanical Turk N = 405, GfK Knowledge Panel N = 1,820), demonstrating largely coherent beliefs by level of action and discrimination between types of efficacy. Four additive efficacy scales emerge: personal self‐efficacy, personal response efficacy, government and collective self‐efficacy, and government and collective response efficacy. Third, we employ the resulting efficacy scales in mediation models to test how well efficacy beliefs predict climate change policy support, controlling for specific knowledge, risk perceptions, and ideology, and allowing for mediation by concern. Concern fully mediates the relatively strong effects of perceived risk on policy support, but only partly mediates efficacy beliefs. Stronger government and collective response efficacy beliefs and personal self‐efficacy beliefs are both directly and indirectly associated with greater support for reducing the risks of climate change, even after controlling for ideology and causal beliefs about climate change.     

Inequality Assessment by Probabilistic Development Indices

Social Indicators Research - This paper analyses the Human Development Index (HDI) time series from 2010 to 2017. An alternative index is studied, which combines the same components of the HDI by...