Perception of own death risk

Individuals’ perception of their own road-traffic and overall mortality risks are examined in this paper. Perceived risk is compared with the objective risk of the respondents’ peers, i.e. their own gender and age group, and the results suggest that individuals’ risk perception of their own risk is biased. For road-traffic risk we obtain similar results to what have been found previously in the literature, overassessment and underassessment among low- and high-risk groups, respectively. For overall risk we find that all risk groups underestimate their risk. The results also indicate that men's risk bias is larger than women’s.

Organizational wisdom practices and firm product innovation

Review of Managerial Science - The manner in which organizational wisdom-related variables or practices (e.g., reasoning, intuition, virtue, prudence, and aesthetics) are related to firm product...     

WebStress: a web interface to explore a multidatabase bibliographic corpus on occupational stress

A bibliographic study on a multidisciplinary subject, such as occupational stress, requires a multidatabase query facility. Given this, we searched eight databases belonging to different fields (medicine, psychology, etc.) and from different countries. Thus, more than 26000 references on occupational stress were gathered. A bibliographic corpus of this sort is unusable because of the heterogeneous format of the records and the number of duplicate entries. Considering the limitations of commercial programs, we have developed a system, called WebStress, for reformatting the data and removing duplicates. The huge number of references and the research needs of updating and searching have necessitated the addition of several other functions to WebStress. Therefore WebStress comprises a web interface that makes it possible to search the corpus with advanced features (using clustering, a specialized thesaurus on stress and Boolean queries). In addition to the usual bibliographic queries on a specific database such as Medline, WebStress provides bibliometric analysis of the corpus, which might contribute to a detailed analysis on occupational stress in order to highlight the networks of researchers and to find the main topics studied in this area. WebStress is not yet available to researchers in general. It is being further developed, and also permission needs to be obtained from the eight commercial bibliographic databases that it consults.     

Increasing women's contribution on board decision making: The importance of chairperson leadership efficacy and board openness

In the last decade, the number of women on corporate boards has increased slightly, but the prevailing minority status of women directors implies that they will continue to face social barriers. While prior research has largely focused on explaining social barriers (e.g., being categorized as an out-group member) to increase diversity and its negative consequences, how boards can avoid these obstacles remains unclear. Stemming from recategorization theory, we examine whether and to what extent board chairperson leadership efficacy and board openness (as mechanisms to avoid out-group bias) enhance the influence of women when they are in the minority in board decision-making. In a sample of 146 Norwegian firms, we found a positive relationship between women minorities and women directors’ contribution to board decision-making. Moreover, we found that this positive impact increases when the board chairperson exercises leadership and the board operates in an atmosphere of openness.     

Estimation of symmetric disagreement using a uniform association model for ordinal agreement data

The Cohen kappa is probably the most widely used measure of agreement. Measuring the degree of agreement or disagreement in square contingency tables by two raters is mostly of interest. Modeling the agreement provides more information on the pattern of the agreement rather than summarizing the agreement by kappa coefficient. Additionally, the disagreement models in the literature they mentioned are proposed for the nominal scales. Disagreement and uniform association models are aggregated as a new model for the ordinal scale agreement data, thus in this paper, symmetric disagreement plus uniform association model that aims separating the association from the disagreement is proposed. Proposed model is applied to real uterine cancer data.     

Computing the Exact Fisher Information Matrix of Periodic State-Space Models

The purpose of this article is to develop algorithms for computing the exact Fisher information matrix of periodic time-varying state-space models. We first present a relatively simple recursive algorithm which computes the elements of the exact information matrix without involving numerical differentiation, since all required derivatives are analytically evaluated. The proposed algorithm extends the procedure due to Cavanaugh and Shumway (1996 Cavanaugh , J. E. , Shumway , R. H. ( 1996 ). On computing the expected Fisher information matrix for state-space model parameters . Statist. Probab. Lett. 26 : 347 – 355 .[Crossref], [Web of Science ®] , [Google Scholar]) to the periodic state-space framework. Exploiting the approach used in Klein et al. (2000 Klein , A. , Mélard , G. , Zahaf , T. ( 2000 ). Construction of the exact Fisher information matrix of Gaussian time series models by means of matrix differential rules . Linear Alg. Applic. 321 : 209 – 232 .[Crossref], [Web of Science ®] , [Google Scholar]), a second algorithm is proposed in order to obtain the exact information matrix as a whole instead of element by element. The algorithms are first developed in a general framework and then specialized to the case of a periodic Gaussian vector autoregressive moving-average (PVARMA) model.     

Leverages and Influential Observations in a Regression Model with Autocorrelated Errors

This article deals with the general form of the hat matrix and the DFBETA measure to detect the influential observations and the leverages in the linear regression model with more than one regressor when the errors are from AR(1) and AR(2) processes. Previous studies dealing with the influential observations and the leverages in the constant mean model and regression through the origin model are obtained as special cases. To demonstrate the utility of the hat matrix and the DFBETA measure, two numerical examples based on the ice cream consumption data with AR(1) errors and the Fox-Hartnagel data with AR(2) errors are analyzed. The results show that the parameter of the autoregressive process affects the influential and leverage points.     

More Large Accidents Through Complexity

Many would tend to characterize modern society as steeped in complexity. This complexity is seen by a number of professional people to imply risk-taking--or risk-making--on a high level. "A single mistake may give consequences of quite different proportions from earlier times," as one critic puts it. This hypothesis of increasing risks on a high level--of worst things getting worse--has been tested on fires in Sweden. Fire has always been a powerfully upsetting agent to the social fabric. Today industrial fires dominate the picture economically. The cost of industrial fires is about three times the cost of residential fires in Sweden. It is of interest to note that the damage cost of the worst fires (as measured in insurance payments) does not form an increasing part of overall fire damage costs, as one would expect from the above hypothesis. Whether the hypothesis holds with regard to indirect costs due to production stand-still is more uncertain. We can conclude that the potential of complexity to create large abnormal occurrences may have been somewhat prematurely announced--at least with regard to fires in Sweden.     

The Access/Impact Problem and the Green and Gold Roads to Open Access: An Update

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles open access (OA, i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). About 10% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers’ employers and funders, as they are now increasingly beginning to do.