Page 38 - Azerbaijan State University of Economics

7. Fuad Selamzade: Measurement of the Efficiency of Azerbaijan Region Hotel
8. Organization: Window Analysis and Malmquist Index

If the change index in Malmquist TFP is greater than 1, it indicates that TFP
increases or improves from period s to period t and d and if this value is less than 1,
it indicates that decreases.

VARIABLES
Data used in the study Data were obtained from the official website of the State
Statistics Committee of the Republic of Azerbaijan. Within the scope of study, 10
regions of the Republic of Azerbaijan were included by using data of 2006-2018. In
the efficiency analysis performed, Staff (average annual number of employees),
Room (total number of rooms), Capacity (total capacity) and Expenditure (total
annual expenditure, thousand manats) were used as input variables and Guest
(number of people placed), Overnight (overnight stay of guests) and income (total
annual income, one thousand Manats) were used as output variables. According to
the statistical data obtained, the highest amount in input and output variables was in
Baku and the least amount was in the region of Upper Karabakh. Because the other
parts of the Upper Karabakh region are occupied by Armenia except for Tartar, only
the data of Tartar city in 2006-2017 and Fuzuli city in 2018 are presented on the
website of the Statistical Committee. Therefore, the Nagorno-Karabakh Region was
not included in the scope of the study.

FINDINGS
Window analysis is a time dependent DEA technique and it was used in this study to
measure how efficiency values of regions of Azerbaijan Republic changed during
years of 2006 and 2018. Since it is more important to maximize the existing inputs
and outputs in the tourism sector, especially in hotel organizations, as in all production
and service sectors, efficiency measurements have been performed by using output-
oriented, constant-scale and variable-scale window analyses. The mean efficiency of
the window analysis was measured by quadruple windows. In the first window, the
efficiency average of the regions for the years 2006-2007-2008-2009 is represented. In
the second window analysis, the efficiency scores of 2006 are reduced and the
efficiency scores of 2010 are added. With this method, the last window reflects the
mean efficiency scores of the years 2015-2016-2017-2018. If the result of Window
Analysis is taken as 1, it means that the region is efficient in four years.

Results of efficiency scores obtained by output-oriented, constant-scale window analysis
are presented in Table 1. According to the results of the analysis, Baku, Lenkeran and
Aran in the first window, Baku in the second and sixth windows, Baku and Nakhchivan
Autonomous Republic in the seventh window, and Nakhchivan Autonomous Republic in
the eight, nine and tenth windows were fully efficient. It was found in the third, fourth and
fifth windows that there was no region with full efficiency score.
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