J. López-Gijón

H-Classics: characterizing the concept of citation classics through H-index

Citation classics identify those highly cited papers which are an important reference point in a research field. To identify a paper as a citation classic we have to fix a citation threshold value. Usually, this threshold value should not be the same for all research fields because each field presents its respective citation pattern. Studies of citation classics in the literature define particular criteria and methods to set citation thresholds, which are often set arbitrarily and designed ad-hoc, and do not allow the scientific community to validate and compare their results. In this paper we introduce the concept of H-Classics to overcome this problem and provide scientific community a standardization of key constructs. We present a new and systematic method to identify citation classics. This identification method of highly cited papers is based on the H-index and thank to the properties of H-index it is sensitive to the own characteristics of any research discipline and also its evolution. Therefore, the concept of H-Classics allows to systematize search procedure of citation classics for any field of research.

A Fuzzy Linguistic Extended LibQUAL+ Model to Assess Service Quality in Academic Libraries

LibQUAL+ model is the best-known method for the quality evaluation of library services, but it has two major drawbacks. First, to measure the quality, it is devised on a cardinal scale: the service levels range from 1 to 9. However, the standard representation of the concepts used by humans for communication is the natural language and, hence, users should express their judgments by using words instead of numbers. Second, it considers that all users’ opinions are equally important. Nevertheless, users do not play an equal role in assessing the service quality, i.e., the opinion given by some users should be more relevant than the opinion provided by others. To solve these drawbacks, we present an extended LibQUAL+ model representing the users’ perceptions by using a fuzzy linguistic modeling and taking into account that users’ opinions on the library services are not equally important.

Aggregation operators in group decision making: Identifying citation classics via H-classics.

Abstract To analyze the past, present and future of a particular research field, classic papers are usually studied because they identify the highly cited papers being a relevant reference point in that specific research area. As a result of the possible mapping between high quality research and high citation counts, highly cited papers are very interesting. The objective of this study is to use the H-classics method, which is based on the popular h-index, to identify and analyze the highly cited documents published about aggregation operators in the research area of group decision making. According to the H-classics method, this research area is represented by 87 citation classics, which have been published from 1988 to 2014. Authors, affiliations (universities/institutions and countries), journals, books and conferences, and the topics covered by these 87 highly cited papers are studied.