• Journal of the Korean Society for information Management
• /
• v.34 no.2
• /
• pp.7-26
• /
• 2017

There has been growing interest in the methods for measuring the credits of individual authors in multi-authored research papers in response to the increase of research collaboration. Having a good understanding for academic norms of individual discipline is essential to measure author credit effectively. However, many Korean universities do not consider different norms for determining the order of authors across disciplines. Rather, they tend to use a standardized method to assess the credits of authors in multi-authored papers. Therefore, this study presented some problems of applying a standardized method to measure author credits in multi-authored papers in economics. The findings of this study confirmed the frequent use of alphabetical author order in economics papers; however, many university guidelines for research evaluation do not take account the alphabetical authorship in measuring the credits of authors. The authors suggest the needs for (1) establishment of a clear definition for primary authors, (2) flexibility in assessment methods for author credit, and (3) empirical research on author credit.

• Journal of the Korean Society for information Management
• /
• v.31 no.2
• /
• pp.57-77
• /
• 2014

As co-authorship has been prevalent within science communities, counting the credit of co-authors appropriately is an important consideration, particularly in the context of identifying the knowledge structure of fields with author-based analysis. The purpose of this study is to compare the characteristics of co-author credit counting methods by utilizing correlations, multidimensional scaling, and pathfinder networks. To achieve this purpose, this study analyzed a dataset of 2,014 journal articles and 3,892 cited authors from the Journal of the Architectural Institute of Korea: Planning & Design from 2003 to 2008 in the field of Architecture in Korea. In this study, six different methods of crediting co-authors are selected for comparative analyses. These methods are first-author counting (m1), straight full counting (m2), and fractional counting (m3), proportional counting with a total score of 1 (m4), proportional counting with a total score between 1 and 2 (m5), and first-author-weighted fractional counting (m6). As shown in the data analysis, m1 and m2 are found as extreme opposites, since m1 counts only first authors and m2 assigns all co-authors equally with a credit score of 1. With correlation and multidimensional scaling analyses, among five counting methods (from m2 to m6), a group of counting methods including m3, m4, and m5 are found to be relatively similar. When the knowledge structure is visualized with pathfinder network, the knowledge structure networks from different counting methods are differently presented due to the connections of individual links. In addition, the internal validity shows that first-author-weighted fractional counting (m6) might be considered a better method to author clustering. Findings demonstrate that different co-author counting methods influence the network results of knowledge structure and a better counting method is revealed for author clustering.

• Journal of Korean Library and Information Science Society
• /
• v.46 no.4
• /
• pp.191-205
• /
• 2015

As the first step in developing the optimal co-authorship allocation method, this study investigated the co-authorship allocation standards of Korean Universities on journal publications. The study compared the standards of 27 Korean universities with Library and Information Science (LIS) departments, and analyzed author rankings generated by applying inflated, fractional, harmonic, and university standard method of co-authorship allocation to 189 Korean LIS faculty publications from 2001 to 2014. The university standards most similar to the standard co-authorship allocation method in bibliometrics(i.e. Vinkler) were those whose co-author credits summed up to 1. However, the university standards differed from Vinkler's in allocating author credits based on primary and secondary author classification instead of allocation based on author ranks. The statistical analysis of author rankings showed that the harmonic method was most similar to the university standards. However, the correlation between the university standards whose co-author credits summed up to greater than 1 and harmonic method was lower. The study results also suggested that middle-level authors are most sensitive to co-authorship allocation methods. However, even the most generous university standards of co-authorship allocation still penalizes collaborative research by reducing each co-authors credit below those of single authors. Follow-up studies will be needed to investigate the optimal method of co-authorship credit allocation.

• Journal of Korean Library and Information Science Society
• /
• v.48 no.2
• /
• pp.295-322
• /
• 2017

As a first step in developing a more effective and robust approach to faculty research performance assessment, this study analyzed the existing faculty research assessment methods by comparing Korean universities' research evaluation standards, National Research Foundation of Korea's (KRF) standard for assessing research proposals, and various bibliometric measures. The study data included research evaluation standards of KRF along with 27 Korean universities with Library and Information Science (LIS) department, and the publication data of 183 LIS faculties in Korean universities from 2001 to 2015, which consisted of 3,863 papers 16,978 citations. After the comparative analysis of research evaluation standards, the study examined the rankings of institutions and faculty produced by applying the collected standards and bibliometric metrics to the publication data. The study showed that Korean university standards for research evaluation, which aim to consider both productivity and impact of faculty research, differ from similar bibliometric measures such as h-index, and the difference could significantly impact the assessment of faculty research performance.

• Journal of Environmental Policy
• /
• v.13 no.1
• /
• pp.69-93
• /
• 2014

The aim of this research was to develop a climate change vulnerability index at the district level (Si, Gun, Gu) with respect to the health care sector in Korea. The climate change vulnerability index was esimated based on the four major causes of climate-related illnesses : vector, flood, heat waves, and air pollution/allergies. The vulnerability assessment framework consists of six layers, all of which are based on the IPCC vulnerability concepts (exposure, sensitivity, and adaptive capacity) and the pathway of direct and indirect impacts of climate change modulators on health. We collected proxy variables based on the conceptual framework of climate change vulnerability. Data were standardized using the min-max normalization method. We applied the analytic hierarchy process (AHP) weight and aggregated the variables using the non-compensatory multi-criteria approach. To verify the index, sensitivity analysis was conducted by using another aggregation method (geometric transformation method, which was applied to the index of multiple deprivation in the UK) and weight, calculated by the Budget Allocation method. The results showed that it would be possible to identify the vulnerable areas by applying the developed climate change vulnerability assessment index. The climate change vulnerability index could then be used as a valuable tool in setting climate change adaptation policies in the health care sector.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.16 no.3
• /
• pp.147-154
• /
• 2011

Decision making in Environmental Impact Assessment (EIA) and Consultation on the Coastal Area Utilization (CCAU) is footing on the survey reports, thus requires concrete and accurate information on the natural habitats. In spite of the importance of reporting the ecological quality and status of habitats, the accumulated knowledge and recent techniques in ecology such as the use of investigated cases and indicators/indices have not been utilized in evaluation processes. Even the EIA report does not contain sufficient information required in a decision making process for conservation and development. In addition, for CCAU, sampling efforts were so limited that only two or a few stations were set in most study cases. This hampers transferring key ecological information to both specialist review and decision making processes. Hence, setting the effective number of sampling stations can be said as a prior step for better assessment. We introduced a few statistical techniques to determine the number of sampling stations in macrobenthos surveys. However, the application of the techniques requires a preliminary study that cannot be performed under the current assessment frame. An analysis of the spatial configuration of sampling stations from 19 previous studies was carried out as an alternative approach, based on the assumption that those configurations reported in scientific journal contribute to successful understanding of the ecological phenomena. The distance between stations and number of sampling stations in a $4{\times}4$ km unit area were calculated, and the medians of each parameter were 2.3 km, and 3, respectively. For each study, approximated survey area (ASA, $km^2$) was obtained by using the number of sampling stations in a unit area (NSSU) and total number of sampling stations (TNSS). To predict either appropriate ASA or NSSU/TNSS, we found and suggested statistically significant functional relationship among ASA, survey purpose and NSSU. This empirical approach will contribute to increasing sampling effort in a field survey and communicating with reasonable data and information in EIA and CCAU.