Bibliometric studies are not a recent trend of studies. Bibliometrics are in simple terms metrics of bibliography where the studies are focused on understanding the trend of researches on a particular field of study or diverse field of studies (Hicks, Wouters, Waltman, De Rijcke, & Rafols, 2015). Bibliometrics are statistical analyses of written publications, books, journals or thesis articles and are frequently used in the field of library and information science, including scientometrics (Arsenova, 2013; Leydesdorff, 2015).
Challenges of bibliometrics arise at every step of the study, selection of the specific software and type of analyses done. Thus, this article presented both the challenges and the solutions occurring in data analysis of bibliometrics.
This article, discusses and interprets the rest of the results from Malmquist DEA. Furthermore, the analysis of Malmquist index summaries for both output and input frontiers are interpreted.
Differences between Multi-stage and Cost- data envelopment analysis (DEA) was also discussed. However, the article will only interpret the results from cost efficiency analysis from the constant returns to scale (CRS) frontier.
In the previous article, discussed and interpreted the findings of cost efficiency using constant returns to scale (CRS) Cost Data Envelopment Analysis (DEA).
The cost efficiency analysis or cost data envelopment analysis or cost DEA is evaluated when information on prices and costs are available from the source of the data collected for input and output variables (Cooper, Seiford, & Zhu, 2011).
Malmquist productivity index evaluates the efficiency change over time as mentioned by Färe, Grosskopf, & Margaritis, (2011). However, Malmquist productivity index literature has been uneven with some authors assuming constant returns to scale and others allowing for variable returns to scale.
The Malmquist productivity index or more commonly malmquist Data Envelopment Analysis (DEA) was first incepted by the researcher Malmquist in 1953 as a quantity to be used in the analysis of consumption of inputs (Färe, Grosskopf, & Margaritis, 2011).