Risk Management and Insurance-Related Journals: A Survey of Risk and Insurance Academics

ABSTRACT This research provides an assessment of the utility and quality of risk management and insurance (RMI)-related journals using professorial expert opinion. Although Social Science Citation Index (SSCI)-produced citation counts and article impact factors are widely available and commonly used methods of journal comparison, they are limited to very few generally premier journals in any field, including RMI, leaving stakeholders with substantial gaps when benchmarking journal factors. We bridge this gap by comparing RMI faculty opinion of quality to SSCI assessments for 13 journals with results indicating general consistency across these measures. The expert opinion approach is extended to assess quality across a sample of 30 RMI-related publications, along with assigning journal categories delineated based on reported academic utility, contributing to RMI boundary definitions. Posthoc analysis indicates only modest influences for some individual, institutional, and journal-related factors on professorial perceptions, evidence that expert opinions are reliable measures of RMI journal utility and quality. Additionally, only modest differences are found in journal quality assessments by academics relative to the teaching versus research institutional mission of their employers, as well as across perceived individual teaching versus research role expectations. Thus, the expert opinion approach to evaluating utility and quality, coupled with regression and subsample analysis, aids RMI academics and other stakeholders in journal assessment and boundary definition issues. These contributions to the advancement of journal assessment methodologies in general may also prove useful across academic disciplines. INTRODUCTION Two primary goals of business schools are (1) knowledge exploration attained through research activities primarily geared toward meeting the needs of other academics; and (2) knowledge exploitation attained through instruction that primarily serves the needs of students (Trieschmann et al., 2000). Trieschmann et al. (2000) liken "the priests of research purity" (2000: pp. 1130) to explorers and creators of deep knowledge, which appears most relevant to their academic peers, and "soldiers" as those who propagate such knowledge primarily to students through the instructional process. Those who seek ways to determine "research purity" in the form of journal quality assessment ratings have followed many paths in the RMI field alone, including assessments of research productivity (Colquitt, Dumm, and Gustavson, 1998); citation counts (Colquitt, 1997, 2003); library subscription rates at AACSB-accredited schools (Baur, Zivney, and Wells, 1996); surveys of colleges of business deans (McNamara and Kolbe, 1996); output concentration of RMI researchers (Chung and Puelz, 1992); page counts geared toward identifying leading contributors to RMI-related research (Cox and Gustavson, 1990,1991); and surveys of what American Risk & Insurance Association (ARIA) members read (Outreville and Malouin, 1985). Although each of these methods has provided various insights into RMI journal rating issues at particular points in time, most do not directly incorporate the opinion of the primary users of such research-academics themselves (Ferguson et al., 2000). The increasingly broad range of RMI-related topics, and persons engaged in RMI-related research (Colquitt, Dumm, Gustavson, 1998), adds a particularly relevant dimension in that journals may be identifiable based on differences in value or utilization across academic activities. Furthermore, overall quality and influence of research outlets are expected to change somewhat over time, hence the need to periodically update those RMI journal ratings. As such, the purpose of this article is to better understand the academic realm of RMI exploration through an analysis of both journal utility and quality ratings, an approach that adds an element of depth to more traditional journal rating designs. …