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PRACA ORYGINALNA
Ocena wyników portów lotniczych w czasie pandemii COVID-19
1
Malazgirt Vocational School, Muş Alparslan University, Turkey
Data nadesłania: 28-06-2021
Data ostatniej rewizji: 11-10-2021
Data akceptacji: 25-10-2021
Data publikacji: 28-12-2021
Autor do korespondencji
GNPJE 2021;308(4):23-53
SŁOWA KLUCZOWE
KODY KLASYFIKACJI JEL
STRESZCZENIE
Globalizacja, handel międzynarodowy, turystyka oraz postęp gospodarczy
i technologiczny przyczyniły się do rozwoju branży lotniczej. By móc skutecznie rywalizować
w globalnie konkurencyjnym środowisku, porty lotnicze muszą efektywnie wykorzystywać
swoje zasoby i dokonywać oceny swoich wyników. W przypadku portów lotniczych
szeroko stosowaną metodą oceny wyników jest Data Envelopment Analysis (DEA).
Niniejsze badanie miało na celu określenie wyników i pozycji rankingowej wybranych
głównych międzynarodowych portów lotniczych w 2019 r. i I kwartale 2020 r. za pomocą
metody DEA, a także metod TOPSIS i EDAS. Analiza efektywności została przeprowadzona
z wykorzystaniem modeli CCR-DEA. Następnie dokonano oceny wyników alternatywnych
za pomocą metod TOPSIS i EDAS. Ranking lotnisk został natomiast opracowany
na podstawie uzyskanych wyników badań przeprowadzonych trzema metodami:
DEA, TOPSIS i EDAS. Badanie wykazało, że zastosowanie do oceny wydajności portów
lotniczych metody DEA wraz z metodami Multi-Criteria Decision-Making (MCDM) takimi
jak TOPSIS i EDAS, pozwala na uzyskanie pełnego i czytelnego rankingu jednostek decyzyjnych
(DMU).
REFERENCJE (141)
1.
Abate M. [2016], Economic effects of air transport market liberalization in Africa, Transportation Research Part A: Policy and Practice, 92: 326–337, https://doi.org/10.1016/j.tra.....
2.
Ablanedo-Rosas J., Gemoets G. [2010], Measuring the efficiency of Mexican airports, Journal of Air Transport Management, 16 (6): 343–345, https://doi.org/10.1016/j.jair....
3.
Adalı E. A., Tuş A. [2019], Hospital site selection with distance-based multi-criteria decisionmaking methods, International Journal of Healthcare Management: 1–11, https://doi.org/10.1080/204797....
4.
Aggarwal A., Choudhary C., Mehrotra D. [2018], Evaluation of smartphones in Indian market using EDAS, Procedia Computer Science, 132: 236–243, https://doi.org/10.1016/j.proc....
5.
Ahn Y.‑H., Min H. [2014], Evaluating the multi-period operating efficiency of international airports using data envelopment analysis and malmquist productivity index, Journal of Air Transport Management, 16 (6): 343–345, https://doi.org/10.1016/j.jair....
6.
Akbar Y. H., Kisilowski M. [2020], To bargain or not to bargain: Airlines, legitimacy and nonmarket strategy in a COVID-19 world, Journal of Air Transport Management, 88: 1–6, https://doi.org/10.1016/j.jair....
7.
Akçetin E., Kamacı H. [2020], Three-valued soft set and its multi-criteria group decision making via TOPSIS and ELECTRE, Scientia Iranica: 1–36, doi: 10.24200/sci.2020.54715.3881.
8.
Altın F. G. [2014], Evaluating pre and post financial crisis performances of companies in health sector with data envelopment analysis, Mehmet Akif Ersoy University Journal of Social Sciences Institute, 6 (11): 163–185, retrieved from https://dergipark.org.tr/tr/pu....
9.
Aldolou E., Perçin S. [2020], Financial performance evaluation of food and drink index using fuzzy MCDM approach, International Journal of Economics and Innovation, 6 (1): 1–19, https://doi.org/10.20979/ueyd.....
10.
Asker V., Battal U. [2017], Operational efficiency measurement at selected airports, International Journal of Management Economics and Business ICMEB17, Special Issue: 351–368, retrieved from https://dergipark.org.tr/tr/pu....
11.
Ayağ Z. [2016], An integrated approach to concept evaluation in a new product development. Journal of Intelligent Manufacturing, 27: 991–1005. https://doi.org/10.1007/s10845....
12.
Aydogan E. K. [2011], Performance measurement model for Turkish aviation firms using the rough-AHP and TOPSIS methods under fuzzy environment, Expert Systems with Applications, 38 (4): 3992–3998. https://doi.org/10.1016/j.eswa....
13.
Azadfallah M. [2018], Multi-criteria decision making for ranking decision making units, International Journal of Productivity Management and Assessment Technologies (IJPMAT), 6 (1): 17–36. doi:10.4018/IJPMAT.2018010102.
14.
Babaee S., Bagherikahvarin M., Sarrazin R., Shen Y., Hermans E. [2015], Use of DEA and PROMETHEE II to Assess the Performance of Older Drivers. Transportation Research Procedia 10: 798–808. https://doi.org/10.1016/j.trpr....
15.
Babic R. S., Tatalovic M., Bajic J. [2017], Air transport competition challenges. International Journal of For Traffic and Transport Engineering 7 (2): 144–163. DOI: 10.7708/ijtte.2017.7(2).01.
16.
Banker R. D., Charnes A., Cooper W. W. [1984], Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30 (9): 1078–1092. https://doi.org/10.1287/mnsc.3....
17.
Barros P. C., Dieke P. U. C. [2007], Performance evaluation of Italian airports: A data envelopment analysis, Journal of Air Transport Management, 13 (4): 184–191. https://doi.org/10.1016/j.jair....
18.
Bartle J. R., Lutte R. K., Leuenberger D. Z. [2021], Sustainability and Air Freight Transportation: Lessons from the Global Pandemic, Sustainability, 13 (7): 1–13. https://doi.org/10.3390/su1307....
19.
Boussofiane A., Dyson R., Thanassoulis E. [1991], Applied data envelopment analysis, European Journal of Operational Research, 52 (1): 1–15. https://doi.org/10.1016/0377-2....
20.
Charles V., Kumar M. [2012], Data envelopment analysis and its application to management, Cambridge Scholar Publishing, Newcastle Upon Tyne, UK, 1–270.
21.
Charnes A., Cooper W. W., Rhodes E. [1978], Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (6): 429–444. https://doi.org/10.1016/0377-2....
22.
Chatterjee P., Banerjee A., Mondal S., Boral S., Chakraborty S. [2018], Development of a hybrid meta-model for material selection using design of experiments and EDAS method, Engineering Transactions, 66 (2): 187–207. http://et.ippt.pan.pl/index.ph....
23.
Chen C. T. [2000], Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114 (1): 1–9. https://doi.org/10.1016/S0165-....
24.
Chitnis A., Vaidya O. S. [2016], Efficiency ranking method using DEA and TOPSIS (ERM–DT): case of an Indian bank. Benchmarking: An International Journal, 23 (1): 166–182. https://doi.org/10.1108/bij-09....
25.
Choi K., Lee D., Olson D. L. [2015], Service quality and productivity in the U. S. airline industry: a service quality-adjusted DEA model, Service Business, 9: 137–160. DOI 10.1007/s11628-013–0221‑y.
26.
Chowdhury P., Paul S. K. [2020], Applications of MCDM methods in research on corporate sustainability A systematic literature review, Management of Environmental Quality: An International Journal, 31 (2): 385–405. DOI 10.1108/MEQ-12-2019–0284.
27.
Cooper W. W., Seiford L. M., Zhu J. [2011], Data envelopment analysis: History, models, and interpretations. In: Cooper W., Seiford L., Zhu J. (eds.) Handbook on data envelopment analysis, International Series in Operations Research & Management Science 164. Springer, Boston, MA. https://doi.org/10.1007/978-1-....
28.
Curi C., Gitto S., Mancuso P. [2011], New evidence on the efficiency of Italian airports: A bootstrapped DEA analysis. Socio-Economic Planning Sciences, 45 (2): 84–93. https://doi.org/10.1016/j.seps....
29.
Çelen A., Yalçın N. [2012], Performance assessment of Turkish electricity distribution utilities: An application of combined FAHP/TOPSIS/DEA methodology to incorporate quality of service, Utilities Policy, 23: 59–71. https://doi.org/10.1016/j.jup.....
30.
Dalfard V. M., Sohrabian A., Najafabadi A. M., Alvani J. [2012], Performance evaluation and prioritization of the leasing companies using super efficiency data envelopment analysis model, Acta Polytechnica Hungarica, 9 (3): 183–194.
31.
Das M. C., Sarkar B., Ray S. [2012], A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology, Socio-Economic Planning Sciences, 46 (3): 230–241. https://doi.org/10.1016/j.seps....
32.
Eichinger E. [2006], Operating conditions and performance of Brazilian airports. Proceeding of 5th Conference on Applied Infrastructure Research, 6–7 October, Berlin/Germany. https://www.infraday.tuberlin.....
33.
Emrouznejad A., Yang G. [2018], A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016, Socio-Economic Planning Sciences, 61: 4–8. https://doi.org/10.1016/j.seps....
34.
Ersoy Y. [2021], Performance evaluation in distance education by using data envelopment analysis (DEA) and TOPSIS Methods, Arabian Journal for Science and Engineering, 46: 1803–1817. https://doi.org/10.1007/s13369....
35.
Ersoy Y., Dogan N. Ö. [2020], An integrated model of fuzzy AHP/fuzzy DEA for measurement of supplier performance: A case study in textile sector, International Journal of Supply and Operations Management (IJSOM), 7 (1): 17–38. doi:10.22034/IJSOM.2020.1.2.
36.
Eshtaiwi M. I., Badi I. A., Abdulshaded A. M., Erkan T. E. [2017], Assessment of airport performance using the grey theory method, Grey Systems Theory and Application, 7 (3): 426–436. DOI 10.1108/GS-07-2017-0023.
37.
Esfahanipour A., Davari-Ardakani H. [2015], A hybrid multi criteria approach for performance evaluation: The case of a holding company, International Journal of Industrial Engineering & Production Research, 26 (4): 287–309. Doi:10.22068/ijiepr.26.4.287.
38.
Fan J.‑P., Li Y.‑J., Wu M.‑Q. [2019], Technology selection based on EDAS cross-efficiency evaluation method. IEEE Access, 7: 58974–58980. doi: 10.1109/ACCESS.2019.2915345.
39.
Farrell M. J. [1957], The measurement of productivity efficiency, Journal of the Royal Statistical Society, A 120 (3): 253–290. https://doi.org/10.2307/234310....
40.
Fernandes E., Pacheco R. R. [2018], Managerial performance of airports in Brazil before and after concessions, Transportation Research, Part A 118: 245–257. https://doi.org/10.1016/j.tra.....
41.
Fung M. K. Y., Wan K..KH., Hui Y. V., Law J. S [2008], Productivity changes in Chinese airports 1995–2004, Transportation Research, Part E, 44 (3): 521–542. https://doi.org/10.1016/j.tre.....
42.
Ghorabaee M. K., Zavadskas E. K., Olfat L., Turskis Z. [2015], Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS), INFORMATICA, 26 (3):435–451. https://doi.org/10.15388/Infor....
43.
Ghorabaee M. K., Amiri M., Zavadskas E. K., Turski Z., Antucheviciene J. [2017], A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria, Journal of Air Transport Management, 63: 45–60. https://doi.org/10.1016/j.jair....
44.
Gillen D., Lall A. [2001], Non-parametric measures of efficiency of US airports, International Journal of Transport Economics, 28 (3): 283–306. Retrieved from https://www.jstor.org/stable/4....
45.
Hwang C. L., Yoon K. [1981], Multiple attributes decision making methods and applications, Springer-Verlag, Berlin Heidelberg. 1–269. DOI: 10.1007/978-3-642-48318-9.
46.
Ibanez J. S., Garraton M. C., Meca A. S. [2020], A literature review of DEA efficiency methodology in defense sector, Academica Revista Latinoamericana de Administracion, 33 (3/4): 381–403. DOI 10.1108/ARLA-11-2019–0228.
47.
İnan T. T. [2018], The Effects of The Airline Business Models to The Airline Industry, Journal of Aviation, 2 (2): 119–124. https://doi.org/10.30518/jav.4....
48.
Jayant A., Sharma J. [2018], A Comprehensive literature review of MCDM techniques ELECTRE, PROMETHEE, VIKOR and TOPSIS Application in business competitive environment, International Journal of Current Research, 10 (2): 65461–65477. Retrieved from http://www.journalcra.com/site....
49.
Kahraman C., Ghorabaee M. K., Zavadskas E. K., Onar S. C., Yazdani M., Oztaysi B. [2017], Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection, Journal of Environmental Engineering and Landscape Management, 25 (1): 1–12. https://doi.org/10.3846/164868....
50.
Karimi A., Barati M. [2018], Financial performance evaluation of companies listed on Tehran Stock Exchange, International Journal of Law and Management, 60 (3): 885–900. DOI 10.1108/IJLMA-12-2016–0145.
51.
Keskin B., Köksal C. D. [2019], A hybrid AHP/DEA-AR model for measuring and comparing the efficiency of airports, International Journal of Productivity and Performance Management, 68 (3): 525–541. DOI 10.1108/IJPPM-02-2018–0043.
52.
Kumar A., Anbanandam R. [2019], Location selection of multimodal freight terminal under STEEP sustainability, Research in Transportation Business & Management, 33: 1–16. https://doi.org/10.1016/j.rtbm....
53.
Kundakcı N. [2019], An integrated method using MACBETH and EDAS methods for evaluating steam boiler alternatives, Journal of Multi-Criteria Decision Analysis, 26 (1–2): 27–34. https://doi.org/10.1002/mcda.1....
54.
Lai P.‑L., Potter A., Beynon M., Beresford A. [2015], Evaluating the efficiency performance of airports using an integrated AHP/DEA-AR technique, Transport Policy, 42: 75–85. https://doi.org/10.1016/j.tran....
55.
Lee Y.‑C., Chung P.‑H., Shyu J. Z. [2017], Performance evaluation of medical device manufacturers using hybrid fuzzy MCDM, Journal of Scientific & Industrial Research, 76 (1): 28–31. Retrieved from http://nopr.niscair.res.in/han....
56.
Lee Z.‑Y., Chu M.‑T., Wang Y.‑T., Chen K.‑J. [2020], Industry performance appraisal using improved MCDM for next generation of Taiwan, Sustainability, 12 (13): 1–17. https://doi.org/10.3390/su1213....
57.
Liu J. S., Lu L. Y. Y., Lu W.‑M., Lin B. J. Y. [2013], A survey of DEA applications, Omega, 41 (5): 893–902. https://doi.org/10.1016/j.omeg....
58.
Lotfi F. H., Fallajnejad R., Navidi N. [2011], Ranking Efficient Units in DEA by Using TOPSIS Method, Applied Mathematical Sciences, 5 (1): 805–815. Retrieved from http://www.m-hikari.com/ams/am....
59.
Lozano S., Gutierrez E. [2011], Efficiency analysis and target setting of Spanish airports, Networks and Spatial Economics, 11 (1): 139–157. doi: 10.1007/s11067-008-9096-1.
60.
Mardani A., Jusoh A., Nor K. M. D., Kahalifah Z., Zakwan N., Valipour A. [2015], Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014, Economic Research-Ekonomska Istraživanja, 28 (1): 516–571. https://doi.org/10.1080/133167....
61.
Markovits-Somogyi R., Gecse G., Bokor Z. [2011], Basic efficiency measurement of Hungarian logistics centres using data envelopment analysis, Periodica Polytechnica Social and Management Sciences, 19 (2): 97–101. https://doi.org/10.3311/pp.so.....
62.
Merkert R., Mangia L. [2014], Efficiency of Italian and Norwegian airports: A matter of management or of the level of competition in remote regions?, Transportation Research, Part A: Policy and Practice, 62: 30–38. https://doi.org/10.1016/j.tra.....
63.
Mousavi-Nasab S. H., Sotoudeh-Anvari A. [2017], A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems, Materials and Design, 121: 237–253. https://doi.org/10.1016/j.matd....
64.
Paleckova I. [2019], Cost efficiency measurement using two-stage data envelopment analysis in the Czech and Slovak banking sectors, Acta Oeconomica, 69 (3): 445–466. https://doi.org/10.1556/032.20....
65.
Pedram M., Payan A. [2015], Efficiency evaluation of international airports in Iran using data envelopment analysis, Indian Journal of Science and Technology, 8 (S9): 67–74. DOI: 10.17485/ijst/2015/v8iS9/68554.
66.
Peker İ., Baki B. [2009], An application of efficiency measurement in Turkish airport with data envelopment analysis (Veri zarflama analizi ile Türkiye hava limanlarında bir etkinlik ölçümü uygulaması), Çukurova University Journal of Social Sciences Institute, 18 (2): 72–88. Retrieved from https://dergipark.org.tr/tr/pu....
67.
Pels E., Nijkamp P., Rietveld P. [2001], Relative efficiency of European airport operations, Transport Policy, 8: 183–192. https://doi.org/10.1016/S0967-... (01) 00012–9.
68.
Perçin S., Aldalou E. [2018], Financial performance evaluation of Turkish airline companies using integrated fuzzy AHP fuzzy TOPSIS model, International Journal of Economics and Innovation, 18. EYI Special Issue: 583–598. https://doi.org/10.18092/uliki....
69.
Prashanth K. D., Parthiban P., Dhanalakshmi R. [2020], Evaluation of the performance and ranking of suppliers of a heavy industry by TOPSIS method, Journal of Scientific & Industrial Research, 79 (2): 144–147. Retrieved from http://nopr.niscair.res.in/han....
70.
Roucello C., Seregina T., Urdanoz M. [2020], Measuring the development of airline networks: Comprehensive indicators, Transportation Research, Part A 133: 303–324. https://doi.org/10.1016/j.tra.....
71.
Rouyendegh B. D., Öztürk B. N., Cebeci K [2018], Performance management of supervisors in railway company: a case study, Management and Business Research Quarterly, 7: 10–20. https://doi.org/10.32038/mbrq.....
72.
Samancı S, Atalay KD, Isin FB [2021], Focusing on the big picture while observing the concerns of both managers and passengers in the post-covid era, Journal of Air Transport Management, 90: 1–10. https://doi.org/10.1016/j.jair....
73.
Sarkis J, Talluri S [2004] Performance based clustering for Benchmarking of US airports, Transportation Research Part A: Policy and Practice, 38 (5): 329–346. https://doi.org/10.1016/j.tra.....
74.
Seiford, L. M, Zhu, J [1999] Infeasibility of super-efficiency data envelopment analysis models, INFOR, 11 (1): 135–151.
75.
Serrano F, Kazda A. [2020], The future of airports post COVID-19, Journal of Air Transport Management, 89: 1–10. https://doi.org/10.1016/j.jair....
76.
Shih H. S., Shyur H.‑J., Lee E. S. [2007], An extension of TOPSIS for group decision making, Mathematical and Computer Modelling, 45 (7–8): 801–813. https://doi.org/10.1016/j.mcm.....
77.
Seçme N. Y., Bayrakdaroğlu A., Kahraman C. [2009], Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS, Expert Systems with Applications, 36 (9): 11699–11709. https://doi.org/10.1016/j.eswa....
78.
Seo E.‑J., Park J.‑W. [2018], A study on the effects of social media marketing activities on brand equity and customer response in the airline industry, Journal of Air Transport Management, 66: 36–41. https://doi.org/10.1016/j.jair....
79.
Shao M., Han Z., Sun J., Xiao C., Zhang S., Zhao Y. [2020], A review of multi-criteria decision making applications for renewable energy site selection, Renewable Energy, 157: 377–403. https://doi.org/10.1016/j.rene....
80.
Somogyi R. M. [2011], Ranking efficient and inefficient decision making units in data envelopment analysis, International Journal for Traffic and Transport Engineering, 1 (4): 245–256. Retrieved from http://ijtte.com/uploads/2011–....
81.
Sozen A., Mirzapour A., Çakir M. T. [2015], Selection of the best location for solar plants in Turkey, Journal of Energy in Southern Africa, 26 (4): 52–63. DOI: 10.17159/2413–3051/2016/v26i4a2093.
82.
Spasojevic B., Lohmann G., Scott N. [2018], Air transport and tourism – a systematic literature review (2000–2014), Current Issues in Tourism, 21(9): 975–997. https://doi.org/10.1080/136835....
83.
Stanujkic D., Zavadskas E. K., Ghorabaee M. K., Turskis Z. [2017], An extension of the EDAS method based on the use of interval grey numbers, Studies in Informatics and Control, 26 (1): 5–12. https://doi.org/10.24846/v26i1....
84.
Stichhauerova E., Pelloneova N. [2019], An efficiency assessment of selected German airports using the DEA model, Journal of Competitiveness, 11 (1): 135–151. https://doi.org/10.7441/joc.20....
85.
Suau-Sanchez P., Voltes-Dorta A., Cuguero-Escofet N. [2020], An early assessment of the impact of COVID-19 on air transport: Just another crisis or the end of aviation as we know it?, Journal of Transport Geography, 86: 1–8. https://doi.org/10.1016/j.jtra....
86.
Tehci A., Ersoy Y. [2020], Investigation of digital retail consumer complaints in the food industry during COVID-19: Market chain example of Turkey, The Journal of International Scientific Researches, 5 (Ek): 22–27. https://doi.org/10.23834/isrjo....
87.
Tolcha T. D., Brathen S., Holmgren J. [2020], Air transport demand and economic development in sub-Saharan Africa: Direction of causality, Journal of Transport Geography, 86: 1–14. https://doi.org/10.1016/j.jtra....
88.
Ulutaş A. [2019], The performance analysis of logistics companies with Entropy based EDAS method, International Journal of Economics and Administrative Studies, 23: 53–66. https://doi.org/10.18092/uliki....
89.
Yalcin N., Bayraktaroglu A., Kahraman C. [2012], Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries, Expert Systems with Applications, 39 (1): 350–364. https://doi.org/10.1016/j.eswa....
90.
Yalçın N., Uncu N. [2019], Applying EDAS as an applicable MCDM method for industrial robot selection, Sigma Journal of Engineering and Natural Sciences, 37 (3): 779–796. https://eds.yildiz.edu.tr/sigm....
91.
Yalçın N., Pehlivan N. P. [2019], Application of the Fuzzy CODAS Method Based on Fuzzy Envelopes for Hesitant Fuzzy Linguistic Term Sets: A Case Study on a Personnel Selection Problem, Symmetry, 11 (4): 1–27. https://doi.org/10.3390/sym110....
92.
Yoshida Y., Fujimoto H. [2004], Japanese-airport Benchmarking with the DEA and Endogenous-weight TFP methods: Testing the criticism of overinvestment in Japanese regional airports, Transportation Research, Part E (40): 533–546. https://doi.org/10.1016/j.tre.....
93.
Yoshimoto D., Alves C. J. P., Caetano M. [2018], Airport economic efficient frontier, Journal of Operations and Supply Chain Management, 11 (1): 26–36. http://dx.doi/10.12660/joscmv1....
94.
You P., Guo S., Zhao H., Zhao H. [2017], Operation performance evaluation of power grid enterprise using a hybrid BWM-TOPSIS method, Sustainability, 9 (12): 1–15. https://doi.org/10.3390/su9122....
95.
Zajac G. [2016], The role of air transport in the development of international tourism, Journal of International Trade, Logistics and Law, 2 (1): 1–8. http://jital.org/index.php/jit....
96.
Zhang H., Zhang Y., Zhang R. [2014], Dimension-specific efficiency measurement using data envelopment analysis, Mathematical Problems in Engineering, 1–9. https://doi.org/10.1155/2014/2....
97.
Zhou Y., Chen L. [2020], Twenty-year span of global coronavirus research trends: A bibliometric analysis, Environmental Research and Public Health, 17 (9): 1–12. https://doi.org/10.3390/ijerph....
98.
Wan T.‑C., Pham Y. T. H. [2019], Entrophy-TOPSIS method to evaluate Vietnam airlines’ domestic ground handling performance, International Journal of Mechanical and Production Engineering, 7 (11): 51–56. DOI:IJMPE-IRAJ-DOI-16582.
99.
Wang R.‑T., Ho C.‑T., Feng C.‑M., Yang Y.‑K. [2004], A comparative analysis of the operational performance of Taiwan’s major airports, Journal of Airport Management, 10 (5): 353–360. https://doi.org/10.1016/j.jair....
100.
Wilbert M. D., Serrano A. L. M., Flores M. R., Damasceno R., Franco V. R. [2017], Efficiency analysis of airports administered by infraero from 2003 to 2013, Applied Mathematical Sciences, 11 (25):1221–1238. https://doi.org/10.12988/ams.2....
101.
Xu B., Ouenniche J. [2012], A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices volatility forecasting models, Energy Economics, 34 (2): 576–583. https://doi.org/10.1016/j.enec....
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"Digitalizacja czasopisma Gospodarka Narodowa", sfinansowanego ze środków Ministerstwa Nauki i Szkolnictwa Wyższego przeznaczonych na działalność upowszechniającą naukę, w ramach umowy nr 555/P-DUN/2018.
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