Reference Publication Year Spectroscopy (RPYS) with publications in the area of academic efficiency studies: what are the historical roots of this research topic? is a research paper published in Applied Economics (2017). On theSindex it has a DataRank of 0.489. It has been cited 25 times.
In this study, we explore the historical roots of the relatively new topic in scientometrics of academic efficiency assessments. We are interested in the contributions of researchers from the past which have been revealed as important for the topic in the long run. The technique of Reference Publication Year Spectroscopy (RPYS) has been recently introduced which is based on the analysis of the frequency with which references are cited in the publications of a specific research field (here: academic efficiency assessments). The study is based on papers conducted for a systematic review of empirical articles on technical efficiency in academic research production: 60 papers (published between 1992 and 2012) and 1314 cited references. Results indicated that 5 peaks are clearly identifiable until 2000. They correspond, respectively, to the years 1957 (The founding article of Farrell), 1978 (Proposition of a new promising approach: the Data Envelopment Analysis (DEA) by Charnes et al.), 1988 (Research-teaching multi-output model and integration of quality indicators), 1990 (DEA in the service of Research Assessment Exercise) and 1997 (Introduction of weight restrictions in DEA). The peaks are described with the underlying publications and recent developments (since 2000) in the area of academic efficiency studies are outlined.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.489
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.