Prague Economic Papers 2023, 32(2):129-158 | DOI: 10.18267/j.pep.824

Efficiency of Digital Economy in the Context of Sustainable Development: DEA-Tobit Approach

Viktorija Skvarciany ORCID...a, Indrė Lapinskaitė ORCID...a, Viktorija Stasytytė ORCID...a
a Vilnius Gediminas Technical University, Vilnius, Lithuania

The paper aims at measuring the efficiency of the digital economy in EU countries. For that purpose, data envelopment analysis (DEA) is used. Sub-dimensions of the Digital Economy and Society Index (DESI) are used as inputs and the Sustainable Development Goals Index (SDGI) as an output. The results revealed that Bulgaria, Italy and Romania are the most efficient digital economies in terms of human capital; Belgium, Bulgaria, Cyprus, Croatia, Estonia, Finland, Greece, Lithuania, Poland and Portugal in terms of connectivity; Bulgaria, Hungary and Romania in terms of integration of digital technology; and Romania in terms of digital public services. The result of tobit regression analysis showed that not all the indicators of the DESI dimensions positively influence the efficiency of the digital economy.

Keywords: digital economy, sustainable development, data envelopment analysis
JEL classification: F43, O47

Received: August 15, 2022; Revised: February 1, 2023; Accepted: February 7, 2023; Published: April 26, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Skvarciany, V., Lapinskait&#, I., & Stasytyt&#, V. (2023). Efficiency of Digital Economy in the Context of Sustainable Development: DEA-Tobit Approach. Prague Economic Papers, 32(2), 129-158. doi: 10.18267/j.pep.824
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Ait Sidhoum, A., Serra, T., Latruffe, L. (2019). Measuring sustainability efficiency at farm level: a data envelopment analysis approach. European Review of Agricultural Economics, 47(1), 200-225. https://doi.org/10.1093/erae/jbz015 Go to original source...
    2. Alouffi, B., Hasnain, M., Alharbi, A., Alosaimi, W., Alyami, H., Ayaz, M. (2021). A Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies. IEEE Access, 9, 57792-57807. https://doi.org/10.1109/ACCESS.2021.3073203 Go to original source...
    3. Amalnick, M. S., Zadeh, S. A. (2017). Concurrent Evaluation of Customer Relationship Management and Organizational Excellence: An Empirical Study. Performance Improvement Quarterly, 30(1), 55-88. https://doi.org/10.1002/piq.21240 Go to original source...
    4. Bánhidi, Z., Dobos, I., Nemeslaki, A. (2020). What the overall Digital Economy and Society Index reveals: A statistical analysis of the DESI EU28 dimensions. Regional Statistics, 10(2), 46-62. https://doi.org/10.15196/RS100209 Go to original source...
    5. Baºol, O., Yalçin, E. C. (2021). How does the digital economy and society index (DESI) affect labor market indicators in EU countries? Human Systems Management, 40(4), 503-512. https://doi.org/10.3233/HSM-200904 Go to original source...
    6. Blancas, F. J., Contreras, I., Lozano-Oyola, M. (2023). Evaluating destinations' efforts to improve sustainability in tourism using the inter-temporal decomposition of a composite indicator. Environmental Impact Assessment Review, 98, 106947. https://doi.org/10.1016/j.eiar.2022.106947 Go to original source...
    7. Booysen, F. (2002). An Overview and Evaluation of Composite Indices of Development. Social Indicators Research, 59, 115-151. https://doi.org/https://doi.org/10.1023/A:1016275505152 Go to original source...
    8. Calp, M. H. (2020). The Role of Artificial Intelligence Within the Scope of Digital Transformation in Enterprises (pp. 122-146). https://doi.org/10.4018/978-1-5225-9550-2.ch006 Go to original source...
    9. 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/10.1016/0377-2217(78)90138-8 Go to original source...
    10. Chen, C.-M. (2013). A critique of non-parametric efficiency analysis in energy economics studies. Energy Economics, 38, 146-152. https://doi.org/10.1016/j.eneco.2013.03.009 Go to original source...
    11. Chen, L. (2022). How CO2 emissions respond to changes in government size and level of digitalization? Evidence from the BRICS countries. Environmental Science and Pollution Research, 29(1), 457-467. https://doi.org/10.1007/s11356-021-15693-6 Go to original source...
    12. Chen, X., Teng, L., Chen, W. (2022). How does FinTech affect the development of the digital economy? Evidence from China. The North American Journal of Economics and Finance, 61, 101697. https://doi.org/10.1016/j.najef.2022.101697 Go to original source...
    13. Chen, X., Wang, Y. (2022). Research on financing efficiency of China's strategic emerging industries based on super efficiency DEA and tobit model. International Journal of Emerging Markets, 17(2), 485-504. https://doi.org/10.1108/IJOEM-02-2020-0188 Go to original source...
    14. Cherchye, L., Moesen, W., Rogge, N., Puyenbroeck, T. Van. (2007). An Introduction to 'Benefit of the Doubt' Composite Indicators. Social Indicators Research, 82(1), 111-145. https://doi.org/10.1007/s11205-006-9029-7 Go to original source...
    15. Ciocoiu, C. N. (2011). Integrating Digital Economy And Green Economy: Opportunities For Sustainable Development. Theoretical and Empirical Researches in Urban Management, 6(1), 33-43.
    16. de Souza, M., Pereira, G. M., Lopes de Sousa Jabbour, A. B., Chiappetta Jabbour, C. J., Trento, L. R., Borchardt, M., Zvirtes, L. (2021). A digitally enabled circular economy for mitigating food waste: Understanding innovative marketing strategies in the context of an emerging economy. Technological Forecasting and Social Change, 173, 121062. https://doi.org/10.1016/j.techfore.2021.121062 Go to original source...
    17. Del Río Castro, G., González Fernández, M. C., Uruburu Colsa, Á. (2021). Unleashing the convergence amid digitalization and sustainability towards pursuing the Sustainable Development Goals (SDGs): A holistic review. Journal of Cleaner Production, 280, 122204. https://doi.org/10.1016/j.jclepro.2020.122204 Go to original source...
    18. Diaz-Sarachaga, J. M., Jato-Espino, D., Castro-Fresno, D. (2018). Is the Sustainable Development Goals (SDG) index an adequate framework to measure the progress of the 2030 Agenda? Sustainable Development, 26(6), 663-671. https://doi.org/10.1002/sd.1735 Go to original source...
    19. Drago, C., Gatto, A. (2022). Policy, regulation effectiveness, and sustainability in the energy sector: A worldwide interval-based composite indicator. Energy Policy, 167, 112889. https://doi.org/10.1016/j.enpol.2022.112889 Go to original source...
    20. Dragulanescu, I. V., Androniceanu, A. (2017). Considerations Relating the Italian e-Commerce Development in a Global Economy. New Challenges of Economic and Business Development - Digital Economy, 177-188.
    21. Ekinci, R. (2021). The Impact of Digitalization on Financial Sector Performance. In The Impact of Artificial Intelligence on Governance, Economics and Finance. Volume I. (pp. 99-119). https://doi.org/10.1007/978-981-33-6811-8_6 Go to original source...
    22. Elmassah, S., Hassanein, E. A. (2022). Digitalization and subjective wellbeing in Europe. Digital Policy, Regulation and Governance, 24(1), 52-73. https://doi.org/10.1108/DPRG-05-2021-0060 Go to original source...
    23. European Commission. (2020). A fair and competitive digital economy. The European Digital Strategy. http://bit.ly/2VdWQgf
    24. European Commission. (2021). The Digital Economy and Society Index (DESI). In Shaping Europe's Digital Future. https://bit.ly/3Irptwq
    25. Ferracane, M. F., Kren, J., Marel, E. (2020). Do data policy restrictions impact the productivity performance of firms and industries? Review of International Economics, 28(3), 676-722. https://doi.org/10.1111/roie.12467 Go to original source...
    26. Fusco, E. (2022). Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model. Socio-Economic Planning Sciences, 85,101447. https://doi.org/10.1016/j.seps.2022.101447 Go to original source...
    27. Herman, E. (2022). The Interplay between Digital Entrepreneurship and Sustainable Development in the Context of the EU Digital Economy: A Multivariate Analysis. Mathematics, 10(10), 1682. https://doi.org/10.3390/math10101682 Go to original source...
    28. Hidalgo, A., Gabaly, S., Morales-Alonso, G., Urueña, A. (2020). The digital divide in light of sustainable development: An approach through advanced machine learning techniques. Technological Forecasting and Social Change, 150, 119754. https://doi.org/10.1016/j.techfore.2019.119754 Go to original source...
    29. Huguenin, J.-M. (2012). Data Envelopment Analysis (DEA): a pedagogical guide for decision makers in the public sector.
    30. Jasiñska-Biliczak, A. (2022). E-Commerce from the Customer Panel: the Phenomenon of the Pandemic Increase and Future Challenge. Business, Management and Economics Engineering, 20(1), 139-151. https://doi.org/10.3846/bmee.2022.16752 Go to original source...
    31. Ji, Y., Lee, C. (2010). Data Envelopment Analysis. The Stata Journal: Promoting Communications on Statistics and Stata, 10(2), 267-280. https://doi.org/10.1177/1536867X1001000207 Go to original source...
    32. Jiménez-Fernández, E., Sánchez, A., Sánchez Pérez, E. A. (2022). Unsupervised machine learning approach for building composite indicators with fuzzy metrics. Expert Systems with Applications, 200, 116927. https://doi.org/10.1016/j.eswa.2022.116927 Go to original source...
    33. Jin, S., Zhang, Y., Wang, K., Zheng, C., Song, L. (2021). Global environmental changes slow down the pace of globalization highlighted by a new composite indicator. Journal of Cleaner Production, 318, 128538. https://doi.org/10.1016/j.jclepro.2021.128538 Go to original source...
    34. Johnes, J., Portela, M., Thanassoulis, E. (2017). Efficiency in education. Journal of the Operational Research Society, 68(4), 331-338. https://doi.org/10.1057/s41274-016-0109-z Go to original source...
    35. Jollands, N. (2006). Concepts of efficiency in ecological economics: Sisyphus and the decision maker. Ecological Economics, 56(3), 359-372. https://doi.org/10.1016/j.ecolecon.2005.09.014 Go to original source...
    36. Jovanoviæ, M., Dlaèiæ, J., Okanoviæ, M. (2018). Digitalization and society's sustainable development - Measures and implications. Zbornik Radova Ekonomskog Fakulteta u Rijeci: Èasopis Za Ekonomsku Teoriju i Praksu/Proceedings of Rijeka Faculty of Economics: Journal of Economics and Business, 36(2), 905-928. https://doi.org/10.18045/zbefri.2018.2.905 Go to original source...
    37. Kamel, M. A., Mousa, M. E.-S., Hamdy, R. M. (2022). Financial efficiency of commercial banks listed in Egyptian stock exchange using data envelopment analysis. International Journal of Productivity and Performance Management, 71(8), 3683-3703. https://doi.org/10.1108/IJPPM-10-2020-0531 Go to original source...
    38. Karadaº, K., Külekçi, M. (2020). Optimization of energy consumption for sunflower production using data envelopment analysis approach. Journal of Environmental Biology, 41(2(SI)), 505-513. https://doi.org/10.22438/jeb/41/2(SI)/JEB-32 Go to original source...
    39. Keshavarz, E., Toloo, M. (2020). A hybrid data envelopment analysis and multi-attribute decision making approach to sustainability assessment. Expert Systems, 37(4). https://doi.org/10.1111/exsy.12347 Go to original source...
    40. Khan, M. H., Wang, D. (2019). The Impact of Green HRM Practices on Job Satisfaction and Resource Efficiency. Education Excellence and Innovation Management through Vision 2020, 6565-6575.
    41. Kolinski, A. (2017). The Impact of Eco-efficiency in Production on Availability of Machines and Equipment. In Efficiency in Sustainable Supply Chain (pp. 161-177). https://doi.org/10.1007/978-3-319-46451-0_10 Go to original source...
    42. Lacko, R., Hajduová, Z., Zawada, M. (2021). The Efficiency of Circular Economies: A Comparison of Visegrád Group Countries. Energies, 14(6), 1680. https://doi.org/10.3390/en14061680 Go to original source...
    43. Lafortune, G., Fuller, G., Moreno, J., Schmidt-Traub, G., Kroll, C. (2018). SDG Index and Dashboards 2018. In Global Responsibilities. Implementing the Goals (Issue September).
    44. Li, Y., Dai, J., Cui, L. (2020). The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model. International Journal of Production Economics, 229, 107777. https://doi.org/10.1016/j.ijpe.2020.107777 Go to original source...
    45. Li, Y., Yang, X., Ran, Q., Wu, H., Irfan, M., Ahmad, M. (2021). Energy structure, digital economy, and carbon emissions: evidence from China. Environmental Science and Pollution Research, 28(45), 64606-64629. https://doi.org/10.1007/s11356-021-15304-4 Go to original source...
    46. Liu, T. (2021). Digital policy in European countries from the perspective of the Digital Economy and Society Index. Policy & Internet. 14(1), 202-218. https://doi.org/10.1002/poi3.274 Go to original source...
    47. Lo-Iacono-Ferreira, V. G., Garcia-Bernabeu, A., Hilario-Caballero, A., Torregrosa-López, J. (2022). Measuring urban sustainability performance through composite indicators for Spanish cities. Journal of Cleaner Production, 359, 131982. https://doi.org/10.1016/j.jclepro.2022.131982 Go to original source...
    48. Loske, D., Klumpp, M. (2020). Simulating the impact of digitalization on retail logistics efficiency. Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), 77-111. https://doi.org/10.15480/882.3126 Go to original source...
    49. Ma, Q., Tariq, M., Mahmood, H., Khan, Z. (2022). The nexus between digital economy and carbon dioxide emissions in China: The moderating role of investments in research and development. Technology in Society, 68, 101910. https://doi.org/10.1016/j.techsoc.2022.101910 Go to original source...
    50. Meng, W., Dou, R., Han, Y., Wang, N. (2018). The Management Efficiency of PPP Projects in Rural China. 7th International Conference on Industrial Technology and Management (ICITM 2018), 179-183.
    51. Mitroviæ, Ð. (2020). Measuring the efficiency of digital convergence. Economics Letters, 188, 108982. https://doi.org/10.1016/j.econlet.2020.108982 Go to original source...
    52. Mondejar, M. E., Avtar, R., Diaz, H. L. B., Dubey, R. K., Esteban, J., Gómez-Morales, A., Hallam, B., Mbungu, N. T., Okolo, C. C., Prasad, K. A., She, Q., Garcia-Segura, S. (2021). Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet. Science of The Total Environment, 794, 148539. https://doi.org/10.1016/j.scitotenv.2021.148539 Go to original source...
    53. Moreira, S. B., Crespo, N. (2017). Composite Indicators of Development (pp. 140-162). https://doi.org/10.4018/978-1-5225-0714-7.ch007 Go to original source...
    54. Nesterenko, N., Pakhomova, N., Richter, K. K. (2020). Sustainable development of organic agriculture: Strategies of Russia and its regions in context of the application of digital economy technologies. St Petersburg University Journal of Economic Studies, 36(2), 217-242. https://doi.org/10.21638/spbu05.2020.203 Go to original source...
    55. OECD. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. https://www.oecd-ilibrary.org/economics/handbook-on-constructing-composite-indicators-methodology-and-user-guide_9789264043466-en
    56. OECD. (2009). The impact of the crisis on ICTs and their role in the recovery.
    57. Omrani, H., Valipour, M., Emrouznejad, A. (2021). A novel best worst method robust data envelopment analysis: Incorporating decision makers' preferences in an uncertain environment. Operations Research Perspectives, 8, 100184. https://doi.org/10.1016/j.orp.2021.100184 Go to original source...
    58. Osmanbegovic, E., Piric, N. (2019). Contemporary approaches to measuring digital economy. 6th International Scientific Conference Economy of Integration (ICEI 2019), 189-199.
    59. Owusu Kwateng, K., Osei-Wusu, E. E., Amanor, K. (2019). Exploring the effect of online banking on bank performance using data envelopment analysis. Benchmarking: An International Journal, 27(1), 137-165. https://doi.org/10.1108/BIJ-06-2018-0154 Go to original source...
    60. Pan, W., Xie, T., Wang, Z., Ma, L. (2022). Digital economy: An innovation driver for total factor productivity. Journal of Business Research, 139, 303-311. https://doi.org/10.1016/j.jbusres.2021.09.061 Go to original source...
    61. Peyrache, A., Rose, C., Sicilia, G. (2020). Variable selection in Data Envelopment Analysis. European Journal of Operational Research, 282(2), 644-659. https://doi.org/10.1016/j.ejor.2019.09.028 Go to original source...
    62. Prieger, J. E. (2013). The broadband digital divide and the economic benefits of mobile broadband for rural areas. Telecommunications Policy, 37(6-7), 483-502. https://doi.org/10.1016/j.telpol.2012.11.003 Go to original source...
    63. Rakicevic, J., Rakicevic, A., Poledica, A. (2019). Logical clustering approach for analysing digital economy and society performance of countries. Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), 550-557. Go to original source...
    64. Rakshit, I., Mandal, S. K. (2020). A global level analysis of environmental energy efficiency: an application of data envelopment analysis. Energy Efficiency, 13(5), 889-909. https://doi.org/10.1007/s12053-020-09857-5 Go to original source...
    65. Robaina, M., Murillo, K., Rocha, E., Villar, J. (2020). Circular economy in plastic waste - Efficiency analysis of European countries. Science of The Total Environment, 730, 139038. https://doi.org/10.1016/j.scitotenv.2020.139038 Go to original source...
    66. Rovan, J. (2011). Composite Indicators. In International Encyclopedia of Statistical Science (pp. 275-276). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_15 Go to original source...
    67. Sachs, J., Schmidt-Traub, G., Kroll, C., Durand-Delacre, D., Teksoz, K. (2017). SDG Index and Dashboards Report 2017.
    68. Saisana, M. (2014). Composite Indicator(s). In Encyclopedia of Quality of Life and Well-Being Research (pp. 1156-1161). Springer Netherlands. https://doi.org/10.1007/978-94-007-0753-5_504 Go to original source...
    69. Saisana, M., Tarantola, S. (2002). State-of-the-art report on current methodologies and practices for composite indicator development.
    70. Sánchez-Ortiz, J., Rodríguez-Cornejo, V., Del Río-Sánchez, R., García-Valderrama, T. (2020). Indicators to measure efficiency in circular economies. Sustainability 12(11), 4483. https://doi.org/10.3390/su12114483 Go to original source...
    71. Sandkuhl, K., Wißotzki, M., Schmidt, R., Zimmermann, A. (2019). On the Effect of Digitalization of Products and Services on Enterprise Architectures. Information Systems Development: Information Systems Beyond 2020 (ISD2019 Proceedings).
    72. Simar, L., Wilson, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31-64. https://doi.org/10.1016/j.jeconom.2005.07.009 Go to original source...
    73. Stan, S. E., Oprean-Stan, C., Țîțu, A. M. (2020). Digitalization - sustainable development convergence: metrics and effects in Romania. Management of Sustainable Development, 12(1), 10-16. https://doi.org/10.54989/msd-2020-0002 Go to original source...
    74. Stankova, M., Hampel, D. (2019). Bankruptcy Prediction Based on Data Envelopment Analysis. 37th International Conference on Mathematical Methods in Economics 2019, 31-39.
    75. Stavytskyy, A., Kharlamova, G., Stoica, E. A. (2019). The Analysis of the Digital Economy and Society Index in the EU. Baltic Journal of European Studies, 9(3), 245-261. https://doi.org/10.1515/bjes-2019-0032 Go to original source...
    76. Sustainable Development Solutions Network. (2022). SDG Index and Monitoring.
    77. Tang, L., Lu, B., Tian, T. (2021). Spatial Correlation Network and Regional Differences for the Development of Digital Economy in China. Entropy, 23(12), 1575. https://doi.org/10.3390/e23121575 Go to original source...
    78. Tapscott, D. (1997). The Digital Economy: Promise and Peril in the Age of Networked Intelligence. McGraw-Hill.
    79. The United Nations. (2021). The 17 goals.
    80. Titko, J., Stankevièienė, J., Lāce, N. (2014). Measuring Bank Efficiency: DEA Approach. Technological and Economic Development of Economy, 20(4), 739-757. https://doi.org/10.3846/20294913.2014.984255 Go to original source...
    81. UNCTAD. (2021). COVID-19 and E-commerce: a Global Review. In United Nations publication.
    82. UNCTAD - United Nations Conference on Trade and Development. (2019). Digital Economy Report 2019: Value creation and capture: Implications for developing countries.
    83. United Nations. (2021). Digital Economy Report UNCTAD 2021 (Issue September).
    84. van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577-588. https://doi.org/10.1016/j.chb.2017.03.010 Go to original source...
    85. Villa, G., Lozano, S., Redondo, S. (2021). Data Envelopment Analysis Approach to Energy-Saving Projects Selection in an Energy Service Company. Mathematics, 9(2), 200. https://doi.org/10.3390/math9020200 Go to original source...
    86. von der Leyen, U. (2019). A Union that strives for more: My agenda for Europe - Political Guidelines for the next European Commission 2019-2024. https://bit.ly/30d4NnH
    87. Wang, Z., Wang, X. (2022). Research on the impact of green finance on energy efficiency in different regions of China based on the DEA-Tobit model. Resources Policy, 77, 102695. https://doi.org/10.1016/j.resourpol.2022.102695 Go to original source...
    88. Yalçin, E. C. (2021). Efficiency Measurement of Digitalization on EU Countries: A Study Based on Data Envelopment Analysis. International Journal of Management, Knowledge and Learning, 10, 323-333. https://doi.org/10.53615/2232-5697.10.323-333 Go to original source...
    89. Yang, S., Wang, H., Wang, Z., Koondhar, M. A., Ji, L., Kong, R. (2021). The Nexus between Formal Credit and E-Commerce Utilization of Entrepreneurial Farmers in Rural China: A Mediation Analysis. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 900-921. https://doi.org/10.3390/jtaer16040051 Go to original source...
    90. Yeganehfar, M., Zarei, A., Isfandyari-Mogghadam, A. R., Famil-Rouhani, A. (2018). Justice in technology policy. Journal of Information, Communication and Ethics in Society, 16(2), 123-137. https://doi.org/10.1108/JICES-06-2017-0038 Go to original source...
    91. Yousefi, S., Hassanzadeh, A., Saen, R. F., Mousavi Kashi, Z. (2021). Assessing sustainability of Islamic countries via data envelopment analysis (DEA). Clean Technologies and Environmental Policy. 24, 1129-1143. https://doi.org/10.1007/s10098-020-02002-x Go to original source...
    92. Yu, Y., Zhu, W., Shi, Q., Zhuang, S. (2022). Common set of weights in data envelopment analysis under prospect theory. Expert Systems, 38(1). https://doi.org/10.1111/exsy.12602 Go to original source...
    93. Zhang, Y., Xu, B. (2021). How Should E-Commerce Platforms Subsidize Retailers with Logistics Constraints during an Epidemic Scenario? Considering Power Structure and Altruistic Preference. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1680-1701. https://doi.org/10.3390/jtaer16050095 Go to original source...
    94. Zhou, P., Poh, K. L., Ang, B. W. (2016). Data Envelopment Analysis for Measuring Environmental Performance. In Handbook of Operations Analytics Using Data Envelopment Analysis (pp. 31-49). https://doi.org/10.1007/978-1-4899-7705-2_2 Go to original source...
    95. Zhu, W., Chen, J. (2022). The spatial analysis of digital economy and urban development: A case study in Hangzhou, China. Cities, 123, 103563. https://doi.org/10.1016/j.cities.2022.103563 Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY NC ND 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content