This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Barzizza, E., Biasetton, N., Ceccato, R., Salmaso, L. (2023) Big Data Analytics and Machine Learning in Supply Chain 4.0: A Literature Review. Stats 2023, 6, 596–616. https://doi.org/10.3390/stats6020038Search in Google Scholar
Bazaras, D., Skrickij, V., Šakalys, A., Šakalys, R. (2022) Relevance of Regulatory and Data Availability Issues to Transport and Logistics Processes, Based on the Insights of the Epicenter Project. Transport and Telecommunication Journal, 23(4), 2022, 344–351. https://doi.org/10.2478/ttj-2022-0028Search in Google Scholar
Bigliardi, B., Filippelli, S., Petroni, A., Tagliente, L. (2022) The digitalisation of supply chain: a review. Procedia Computer Science 200, 1806–1815, https://doi.org/10.1016/j.procs.2022.01.381Search in Google Scholar
Ma, C., Wang, X., Wu, J., Cheng, X., Xia, L., Xue, F., Qiu, L. (2020) Real-World Big-Data Studies in Laboratory Medicine: Current Status, Application, and Future Considerations. Clinical Biochemistry. 84, 21–30.Search in Google Scholar
Hoffman, A.J. (2015) Isolated Scholars: Making Bricks, Not Shaping Policy. Chronicle of Higher Education, 13, A48.Search in Google Scholar
Jena, S. K., Singhal, D. (2023) Optimising the competitive sustainable process and pricing decision of digital supply chain: A power-balance perspective. Computers & Industrial Engineering, 177, 109054. https://doi.org/10.1016/j.cie.2023.109054.Search in Google Scholar
Liachovičius, E., Skrickij, V., Podviezko, A. (2020) MCDM Evaluation of Asset-Based Road Freight Transport Companies Using Key Drivers That Influence the Enterprise Value. Sustainability, 12(18), 7259. https://doi.org/10.3390/su12187259.Search in Google Scholar
Kendall, M. (1970) Rank Correlation Methods. Griffin: London, UK, 272 p.Search in Google Scholar
Kolagar, M., Parida, V., Sjödin, D. (2022) Ecosystem transformation for digital servitization: A systematic review, integrative framework, and future research agenda. Journal of Business Research, 146, 176–200. https://doi.org/10.1016/j.jbusres.2022.03.067.Search in Google Scholar
Mallick, P. K., Salling, K. B., Pigosso, D.C.A., McAloone, T.C. (2023) Closing the loop: Establishing reverse logistics for a circular economy, a systematic review. Journal of Environmental Management, 328, 117017. https://doi.org/10.1016/j.jenvman.2022.117017.Search in Google Scholar
Montreuil, B. (2011) Towards a Physical Internet: Meeting the Global Logistics Sustainability Grand Challenge. Logistics Research, 3(2–3), 71–87.Search in Google Scholar
Podvezko, V. (2005) Determining the level of agreement of expert estimates. Technological and Economic Development of Economy, 11, 101–107.Search in Google Scholar
Rahman, H.U., Zahid, M., Ullah, M., Al-Faryan, M.A. (2023) Green supply chain management and firm sustainable performance: The awareness of China Pakistan economic corridor. Journal of Cleaner Production, 414, 137502. https://doi.org/10.1016/j.jclepro.2023.137502.Search in Google Scholar
Saaty, T. (1980) The Analytical Hierarchy Process. McGraw-Hill: New York, NY, USA.Search in Google Scholar
Saaty, T. (2000) Fundamential of The Analytical Hierarchy Process. RWS Publications: Pittsburg, PA, USA.Search in Google Scholar
Šabanovič, E., Žuraulis, V., Prentkovskis, O., Skrickij, V. (2020) Identification of Road-Surface Type Using Deep Neural Networks for Friction Coefficient Estimation. Sensors, 20(3), 612.Search in Google Scholar
Šakalys, R., Sivilevičius, H, Miliauskaitė, L., Šakalys, A. (2019) Investigation and evaluation of main indicators impacting synchromodality using ARTIW and AHP methods. Transport, 34(3), 300–311.Search in Google Scholar
Skrickij V., Šakalys R., Bazaras D., Šakalys A. (2023) The role of government and research organisations in the development of logistics networks as an integral area of physical internet. Transportation Research Procedia, 00 (2022) 000–000 (in press)Search in Google Scholar
Song, H., Jo, K., Cho, J., Son, Y., Kim, C., Han, K. (2022) A Training Dataset for Semantic Segmentation of Urban Point Cloud Map for Intelligent Vehicles. ISPRS Journal of Photogrammetry and Remote Sensing, 187, 159–170.Search in Google Scholar
Ušpalytė-Vitkūnienė, R., Bureika, G., Burinskienė, M., Vabuolytė, V., Skrickij, V. (2022) Sharing mobility solutions in remote touristic area: case study of Lithuania. Transport, 37(4), 241–250.Search in Google Scholar
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., Haenlein, M. (2021) Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901.Search in Google Scholar
Yang, M., Lim, M.K., Qu, Y., Ni, D., Xiao, Z. (2023) Supply chain risk management with machine learning technology: A literature review and future research directions. Computers & Industrial Engineering, 175, 108859. https://doi.org/10.1016/j.cie.2022.108859.Search in Google Scholar
Zinn, W., Goldsby, T.J. (2017) The Role of Academic Research in Supply Chain Practice: How Much are We Contributing? Journal of Business Logistics, 38(4), 236–237.Search in Google Scholar
Beshelev, S. D., Gurvich, F. G. (1974) Mathematical and Statistical Methods of Expert Assessments. Moscow: Statistics.Search in Google Scholar