G20 Ülkelerinin Açık Veri Ekosistem Performansı: MARCOS ve PSI Tabanlı Değerlendirme Modeli

Öz

Ülkelerin açık veri ekosistemleri kapsamında veri paylaşımları, şeffaf yönetimlerinin önemli bir göstergesi olmakla birlikte ekonomik ve sosyal değer oluşturma noktasında oldukça değerli bir eylem olarak kabul edilmektedir. Ayrıca açık veri paylaşımları, politikacılar ve araştırmacılar tarafından inovasyon ve girişimciliği destekleyen önemli bir unsur olarak nitelendirilmektedir. Başta Avrupa Birliği olmak üzere dünya genelinde birçok ülke açık devlet verisi kullanımını stratejik planlarına dahil etmiştir. Bu kapsamda, ülkelerin açık veri ekosistemleri odağında veri paylaşım performanslarını değerlendirmek oldukça önemlidir. Bu doğrultuda mevcut çalışmada, ekonomik olarak dünyanın en gelişmiş ülke topluluğu olarak kabul edilen G20 ülkelerini, açık veri ekosistemlerine ilişkin performansları bakımından değerlendirmek amaçlanmıştır. Ülkeler, 7 kritere göre değerlendirilmiştir. Kriter ağırlıkları PSI tekniği ile belirlenirken ülkeler MARCOS yöntemi kullanılarak değerlendirilmiştir. Sonuçlar, ağırlığı en yüksek olan kriterin “Veri ürünleri”, önem düzeyi en düşük olan kriterin ise “Veri altyapısı” olduğunu ortaya koymaktadır. Ayrıca sonuçlar, ABD’nin açık veri ekosistemleri bakımından en iyi performansa sahip ülke olduğunu ve performansı en kötü olan ülkenin ise Çin olduğunu ortaya koymaktadır.

Anahtar Kelimeler

• Açık veri ekosistemleri
• Veri paylaşımı
• PSI yöntemi
• MARCOS yöntemi
• Duyarlılık analizi.

ASSESSMENT OF G20 COUNTRIES' OPEN DATA ECOSYSTEM PERFORMANCE: A MARCOS AND PSI-BASED MODEL

Öz

The data sharing of countries within the scope of open data ecosystems is an important indicator of their transparent governance and is recognized as a highly valuable action in terms of creating economic and social value. Open data sharing is also recognized by policymakers and researchers as an important driver of innovation and entrepreneurship. Many countries around the world, including the European Union, have included the use of open government data in their strategic plans. In this context, it is very important to assess the data sharing performance of countries in the focus of open data ecosystems. Accordingly, the current study aims to assess the performance of G20 countries, which are considered to be the most economically developed countries in the world, in terms of their open data ecosystems. Countries were evaluated according to 7 criteria. Criteria weights are determined by the PSI technique, while countries are evaluated using the MARCOS method. The results show that the criterion with the highest weight is “Data products” and the criterion with the lowest importance is “Data infrastructure”. Also, the results reveal that the US is the country with the best performance in terms of open data ecosystems and China is the country with the worst performance.

Anahtar Kelimeler

• Open data ecosystems
• Data sharing
• PSI method
• MARCOS method
• Sensitivity analysis.

Kaynakça

1. Aaen, J., Nielsen, J. A., & Carugati, A. (2022). The dark side of data ecosystems: A longitudinal study of the DAMD project. European Journal of Information Systems, 31, 288–312.
2. Abdulla, A., Baryannis, G., & Badi, I. (2023). An integrated machine learning and MARCOS method for supplier evaluation and selection. Decision Analytics Journal, 9, 100342.
3. Agrawal, D., Zhang, C., Kettinger, W. J., & Adeli, A. M. (2022). Spy it before you try it: Intrinsic cues and open data app adoption. Communications of the Association for Information Systems, 50, 554–575.
4. Akbulut, O. Y. (2020). Gri Entropi temelli PSI ve ARAS ÇKKV yöntemleriyle Türk mevduat bankalarının performans analizi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(2), 171-187.
5. Akçakanat, Ö., & Aksoy, E. (2023). G-20 ülkelerinin yeşil merkez bankacılığı karnelerine göre değerlendirilmesi. Uluslararası Ekonomi İşletme ve Politika Dergisi, 7(1), 1-15.
6. Akyüz, G., & Aka, S. (2017). Çok kriterli karar verme teknikleriyle tedarikçi performansı değerlendirmede toplamsal bir yaklaşım. Yönetim ve Ekonomi Araştırmaları Dergisi, 15(2), 28-46.
7. Ali, J. (2022). A q-rung orthopair fuzzy MARCOS method using novel score function and its application to solid waste management. Applied Intelligence, 52(8), 8770-8792.
8. Altıntaş, F. F. (2021). Akdeniz ülkelerinin destinasyon rekabetçilik performanslarının analizi: MAIRCA ve MARCOS yöntemleri ile bir uygulama. Türk Turizm Araştırmaları Dergisi, 5(3), 1833-1856.

9. Altıntaş, F. F. (2022). Avrupa ülkelerinin enerji inovasyonu performanslarının analizi: Mabac ve Marcos yöntemleri ile bir uygulama. İşletme Akademisi Dergisi, 3(2), 188-216.
10. Altıntaş, F. F. (2023). Barış Performanslarının LOPCOW Tabanlı WISP Yöntemi İle Analizi: G7 Ülkeleri Örneği. Fenerbahçe Üniversitesi Sosyal Bilimler Dergisi, 3(2), 215-241.
11. Attri, R., & Grover, S. (2015). Application of preference selection index method for decision making over the design stage of production system life cycle. Journal of King Saud University-Engineering Sciences, 27(2), 207-216.
12. Ayçin, E., & Arsu, T. (2021). Sosyal gelişme endeksine göre ülkelerin değerlendirilmesi: MEREC ve MARCOS yöntemleri ile bir uygulama. İzmir Yönetim Dergisi, 2(2), 75-88.
13. Aydoğdu-Bağcı, S., & Türkoğlu, S. P. (2023). Kamu harcamalarının eğitim göstergelerindeki rolü: SD ve COCOSO yöntemleri ile üst-orta gelir grubu ülkelerinin analizi. Alanya Akademik Bakış, 7(3), 1267-1283.
14. Badi, I., Pamučar, D., Stević, Ž., & Muhammad, L. J. (2023). Wind farm site selection using BWM-AHP-MARCOS method: A case study of Libya. Scientific African, 19, e01511.
15. Batwara, A., Sharma, V., Makkar, M., & Giallanza, A. (2024). Impact of smart sustainable value stream mapping–Fuzzy PSI decision-making framework. Sustainable Futures, 7, 100201.
16. Bayrakci, E., & Aksoy, E. (2019). Bireysel emeklilik şirketlerinin ENTROPİ ağırlıklı ARAS ve COPRAS yöntemleri ile karşılaştırmalı performans değerlendirmesi. Business and Economics Research Journal, 10(2), 415-434.
17. Bilgin Sarı, E. (2019). Measuring The performances of the machines via Preference Selection Index (PSI) method and comparing them with values of Overall Equipment Efficiency (OEE). İzmir İktisat Dergisi, 34(4), 573-581.
18. Borujeni, M. P., & Gitinavard, H. (2017). Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method. Journal of Sustainable Mining, 16(4), 207-218.
19. Calzada, I., & Almirall, E. (2020). Data ecosystems for protecting European citizens’ digital rights. Transforming Government: People, Process and Policy, 14(2), 133-147.
20. Chauhan, R., Singh, T., Thakur, N. S., & Patnaik, A. (2016). Optimization of parameters in solar thermal collector provided with impinging air jets based upon preference selection index method. Renewable energy, 99, 118-126.
21. Corbett, J., Templier, M., Townsend, H., & Takeda, H. (2020). Integrating across sustainability, political, and administrative spheres: A longitudinal study of actors’ engagement in open data ecosystems in three Canadian cities. Communications of the Association for Information Systems, 47, 596–627.
22. Corrales-Garay, D., Ortiz-de-Urbina-Criado, M., & Mora-Valentín, E. M. (2019). Knowledge areas, themes and future research on open data: A co-word analysis. Government information quarterly, 36(1), 77-87.
23. Çanakçıoğlu, M., & Küçükönder, H. (2020). Entropi ve TOPSIS bütünleşik yaklaşimi ile BIST gida ve içecek endeksindeki şirketlerin finansal performanslarinin değerlendirilmesi. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 11(2), 200-217.
24. Çınaroğlu, E. (2021). CRITIC temelli MARCOS yöntemi ile yenilikçi ve girişimci üniversite analizi. Journal of Entrepreneurship and Innovation Management, 10(1), 111-133.
25. Dang, H. A. H., Pullinger, J., Serajuddin, U., & Stacy, B. (2023). Statistical performance indicators and index—a new tool to measure country statistical capacity. Scientific Data, 10(1), 146.
26. D’Hauwers, R., Walravens, N., & Ballon, P. (2022). Data ecosystem business models: Value and control in data ecosystems. Journal of Business Models, 10, 1–30.
27. Dehshiri, S. S. H., & Firoozabadi, B. (2022). A new application of measurement of alternatives and ranking according to compromise solution (MARCOS) in solar site location for electricity and hydrogen production: A case study in the southern climate of Iran. Energy, 261, 125376.
28. Demir, A. T., & Moslem, S. (2024). Evaluating the effect of the COVID-19 pandemic on medical waste disposal using preference selection index with CRADIS in a fuzzy environment. Heliyon, 10(5).
29. Demir, G. (2022). Hayat dışı sigorta sektöründe kurumsal performansın PSI-SD tabanlı MABAC metodu ile ölçülmesi: Anadolu Sigorta örneği. Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(1), 112-136.
30. Deveci, M., Özcan, E., John, R., Pamucar, D., & Karaman, H. (2021). Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS. Applied Soft Computing, 109, 107532.
31. Du, P., Chen, Z., Wang, Y., & Zhang, Z. (2022). A hybrid group-making decision framework for regional distribution network outage loss assessment based on fuzzy best-worst and MARCOS methods. Sustainable Energy, Grids and Networks, 31, 100734.
32. Dünya Bankası, (2022). İstatistiksel Performans Göstergeleri. https://databank.worldbank.org/source/statistical-performance-indicators-(spi) (25.07.2024).
33. Ecemiş, O., & Coşkun, A. (2022). Türkiye’de bilişim teknolojileri kullanımının ÇKKV yöntemleriyle incelenmesi 2014-2021 dönemi. Avrupa Bilim ve Teknoloji Dergisi, (37), 81-89.
34. Eren, H., & Aksoy, E. (2021). Ülkelerin Lojistik Performanslarına Göre Uluslararası Demiryolları İstatistikleri Açısından Kümelenmesi. Ekonomi Bilimleri Dergisi, 13(2), 111-137.
35. Fang, J., & Zhao, L. (2024). Synergistic evolution mechanisms for improving open government data ecosystems using the Haken model. Library & Information Science Research, 46, 101284.
36. Fang, J., Zhao, L., & Li, S. (2024). Exploring open government data ecosystems across data, information, and business. Government Information Quarterly, 41(2), 101934.
37. Gençtürk, M., Senal, S., & Aksoy, E. (2021). COVID-19 pandemisinin katılım bankaları üzerine etkilerinin bütünleşik CRITIC-MARCOS yöntemi ile incelenmesi. Muhasebe ve Finansman Dergisi, (92), 139-160.
38. Di Gennaro, L. (2024). Is there a quantitative relationship between democracy and official statistics?. Statistical Journal of the IAOS, 40(3), 511-519.
39. Ghazinoory, S., Nasri, S., Dastranj, R., & Sarkissian, A. (2021). Bio to bits”: The Millennium Ecosystem Assessment (MA) as a metaphor for Big Data ecosystem assessment. Information Technology & People, 35, 835–858.
40. Given, L. M., Polkinghorne, S., & Cattlin, J. (2023). Structural elements and spheres of expertise: Creating a healthy ecosystem for cultural data initiatives. Journal of the Association for Information Science and Technology, 1-17.
41. Görçün, Ö. F., & Doğan, G. (2023). Mobile crane selection in project logistics operations using Best and Worst Method (BWM) and fuzzy Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS). Automation in Construction, 147, 104729.
42. Gupta, A., Panagiotopoulos, P., & Bowen, F. (2020). An orchestration approach to smart city data ecosystems. Technological Forecasting and Social Change, 153, 119929.
43. Hambleton, I. R., & Jeyaseelan, S. (2024). The silent barrier: exploring data availability in Small Island Developing States. Revista Panamericana de Salud Pública, 48, e80.
44. Huang, R., Lai, T., & Zhou, L. (2017). Proposing a framework of barriers to opening government data in China: A critical literature review. Library Hi Tech, 35(3), 421-438.
45. Jaime, A., Osorio-Sanabria, M. A., Alcantara-Concepcion, T., & Barreto, P. L. (2021). Mapping the open access ecosystem. The Journal of Academic Librarianship, 47(5), 102436.
46. Kabakcı, C. Ç., & Bilgin Sarı, E. (2019). Türk bankacılık sektöründe finansal performansın tercih seçim endeksi (PSI) yöntemiyle analizi. Ekonomi Politika ve Finans Araştırmaları Dergisi, 4(3), 370-383.
47. Kamariotou, M., & Kitsios, F. (2022). Bringing digital innovation strategies and entrepreneurship: The business model canvas in open data ecosystem and startups. Future Internet, 14, 127.
48. Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government information quarterly, 30(4), 508-513.
49. Keleş, M. K., & Alaca, D. (2023). Dijital Pazarlama Teknolojilerinin PIV ve CODAS Yöntemleri ile Analizi. Mehmet Akif Ersoy Üniversitesi Uygulamalı Bilimler Dergisi, 7(1), 84-101.
50. Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry, 13(4), 525.
51. Kitsios, F., & Kamariotou, M. (2023). Digital innovation and entrepreneurship transformation through open data hackathons: Design strategies for successful start-up settings. International Journal of Information Management, 69, 102472.
52. Kitsios, F., Papachristos, N., & Kamariotou, M. (2017). Business models for open data ecosystem: Challenges and motivations for entrepreneurship and innovation. in: 2017 IEEE 19th Conference on Business Informatics (CBI) (pp. 398–407).
53. Koca, G., & Bingöl, M. S. (2022). Hayat-dışı sigorta şirketlerinin performanslarının CRITIC tabanlı MARCOS yöntemi ile değerlendirilmesi. Bilecik Şeyh Edebali Üniversitesi Sosyal Bilimler Dergisi, 7(1), 70-83.
54. Lnenicka, M., & Komarkova, J. (2019). Big and open linked data analytics ecosystem: Theoretical background and essential elements. Government Information Quarterly, 36(1), 129-144.
55. Lnenicka, M., Nikiforova, A., Clarinval, A., Luterek, M., Rudmark, D., Neumaier, S., Kevi´c, K., & Rodríguez Bolívar, M. P. (2024a). Sustainable open data ecosystems in smart cities: A platform theory-based analysis of 19 European cities. Cities, 148.
56. Lnenicka, M., Nikiforova, A., Luterek, M., Milic, P., Rudmark, D., Neumaier, S., ... & Bolívar, M. P. R. (2024b). Identifying patterns and recommendations of and for sustainable open data initiatives: a benchmarking-driven analysis of open government data initiatives among European countries. Government Information Quarterly, 41(1), 101898.
57. Lnenicka, M., Nikiforova, A., Luterek, M., Milic, P., Rudmark, D., Neumaier, S., ... & Bolívar, M. P. R. (2024). Understanding the development of public data ecosystems: From a conceptual model to a six-generation model of the evolution of public data ecosystems. Telematics and informatics, 102190.
58. Lokshin, M. (2022). The highways and side roads of statistical capacity building. Statistical Journal of the IAOS, 38(3), 753-768.
59. Madić, M., Antucheviciene, J., Radovanović, M., & Petković, D. (2017). Determination of laser cutting process conditions using the preference selection index method. Optics & Laser Technology, 89, 214-220.
60. Maniya, K. & Bhatt, M. G. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials & Design, 31(4), 1785-1789.
61. McLeod, M. (2023). Managing Caribbean tourism data ecosystems. Current Issues in Tourism, 1-17.
62. Meral, İ. G. (2023). BRICS-T Ülkelerinin İnovasyon Performanslarının MEREC-MARCOS Yöntemi ile Değerlendirilmesi. Kastamonu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(2), 550-571.
63. Mergel, I., Kleibrink, A., & Sörvik, J. (2018). Open data outcomes: US cities between product and process innovation. Government Information Quarterly, 35(4), 622-632.
64. Oliveira, M. I., Barros Lima, G. de F., & Farias L´oscio, B. (2019). Investigations into data ecosystems: a systematic mapping study. Knowledge and Information Systems, 61, 589–630.
65. Open Data Watch, (2022). Açık Veri Envanteri (ODIN). https://odin.opendatawatch.com/ (25.07.2024).
66. Özdağoğlu, A., Keleş, M. K., & Işıldak, B. (2021). Dünyanın En İşlek Havalimanlarının Pıprecıa-E, Smart Ve Marcos Yöntemleri İle Değerlendirilmesi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (58), 333-352.
67. Özel-Sönmez, G., & Toktaş, P. (2024). Supplier selection using the integrated MEREC–CoCoSo methods in a medical device company. Journal of Scientific Reports-A, (56), 116-133.
68. Pala, O. (2021). IDOCRIW ve MARCOS temelli BİST ulaştırma işletmelerinin finansal performans analizi. Kafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(23), 263-294.
69. Pamucar, D., Ulutaş, A., Topal, A., Karamaşa, Ç., & Ecer, F. (2024). Fermatean fuzzy framework based on preference selection index and combined compromise solution methods for green supplier selection in textile industry. International Journal of Systems Science: Operations & Logistics, 11(1), 2319786.
70. Pathak, V. K., Singh, R., & Gangwar, S. (2019). Optimization of three-dimensional scanning process conditions using preference selection index and metaheuristic method. Measurement, 146, 653-667.
71. Runeson, P., Olsson, T., & Linåker, J. (2021). Open Data Ecosystems — An empirical investigation into an emerging industry collaboration concept. Journal of Systems and Software, 182, 111088.
72. Samant, M. R., Krisna, S. K., Khishorre, K. R., & Sreeharan, B. N. (2022). A Systematic way of using Preference Selection Index Methodology for Selecting Suspension Coil Spring Material. Materials Today: Proceedings, 68, 2249-2257.
73. Scheider, S., Lauf, F., Moller, F., & Otto, B. (2023). A reference system architecture with data sovereignty for human-centric data ecosystems. Business & Information Systems Engineering.
74. Sendi, P. P., & Clemen, R. T. (1999). Sensitivity analysis on a chance node with more than two branches. Medical decision making, 19(4), 499-502.
75. Shen, C., Riaz, Z., Palle, M. S., Jin, Q., & Peña-Mora, F. (2015). Open data landscape: a global perspective and a focus on China. In open and big data management and innovation: 14th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2015, Delft, The Netherlands, October 13-15, 2015, Proceedings 14 (pp. 247-260).
76. Stević, Ž., & Brković, N. (2020). A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company. Logistics, 4(1), 4.
77. Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & industrial engineering, 140, 106231.
78. Tan, E. (2023). Designing an AI compatible open government data ecosystem for public governance. Information Polity, 28(4), 541-557.
79. Toorajipour, R., Oghazi, P., & Palmié, M. (2024). Data ecosystem business models: Value propositions and value capture with Artificial Intelligence of Things. International Journal of Information Management, 78, 102804.
80. Trung, D. D. (2022). Development of data normalization methods for multi-criteria decision making: applying for MARCOS method. Manufacturing review, 9, 22.
81. Tuş, A., & Adalı, E. A. (2018). CODAS ve PSI yöntemleri ile personel değerlendirmesi. Alphanumeric Journal, 6(2), 243-256.
82. Wainwright, T., Huber, F., Stöckmann, C., & Kraus, S. (2023). Open data platforms for transformational entrepreneurship: Inclusion and exclusion mechanisms. International Journal of Information Management, 72, 102664.
83. Wang, W., Chen, Y., Wang, Y., Deveci, M., Cheng, S., & Brito-Parada, P. R. (2024). A decision support framework for humanitarian supply chain management–Analysing enablers of AI-HI integration using a complex spherical fuzzy DEMATEL-MARCOS method. Technological Forecasting and Social Change, 206, 123556.
84. Wang, Y., Wang, W., Wang, Z., Deveci, M., Roy, S. K., & Kadry, S. (2024). Selection of sustainable food suppliers using the Pythagorean fuzzy CRITIC-MARCOS method. Information Sciences, 664, 120326.
85. Wilson, B., & Cong, C. (2021). Beyond the supply side: Use and impact of municipal open data in the US. Telematics and Informatics, 58, 101526.
86. Yoon, A., & Copeland, A. (2020). Toward community-inclusive data ecosystems: Challenges and opportunities of open data for community-based organizations. Journal of the Association for Information Science and Technology, 71, 1439–1454.
87. Young, M. M. (2020). Implementation of digital‐era governance: the case of open data in US cities. Public Administration Review, 80(2), 305-315.
88. Yue, L. X., & Liu, W. Y. (2016). A comparative study on the current situation of domestic and foreign g overnment data open. Library and Information Service, 60(14), 94-101.
89. Zhan, M., & Li, Y. L. (2024). Evaluation and selection of sustainable hydrogen production technologies with unknown expert weights based on extended MARCOS under hybrid information. International Journal of Hydrogen Energy, 77, 1043-1055.
90. Zheng, L. & Gao, F. (2015). Research on open government data platform in China: framework, status and suggestions. E-Government, 12(7), 8-16.