HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS
Sažetak
Veliki podaci imaju ogroman uticaj na urbano planiranje i morfologiju gradova. Veliki podaci se koriste za procenu zahteva zajedničke transportne strukture, fokusirajući se na finansiranje i planove prenosivosti unutar ključnih gradova. Istraživanje pruža sistem za donošenje preporuka (RMS) fokusiran na sugerisanje transportnih metoda za automobilsku potrošnju tako što detaljno opisuje ogroman broj informacija o metodama transporta koje potiču od različitih proizvoda. Istraživanje se fokusira na korišćenje velikih podataka kako bi se došlo do zajedničkog transporta i predstavlja strukturno razumevanje za prikupljanje, kombinovanje, agregiranje, inkorporiranje, širenje i kontrolu informacija iz brojnih izvora. Koriste se metode ekstrakcije informacija koje omogućavaju procenu organizovanih velikih podataka, koji prate razvijena merila kao što je CRISP-DM, i neorganizovanih, lako ponuđenih velikih podataka. Istražne informacije su prikupljene od predstavnika telefona i automatskih uređaja za lociranje vozila u regionu. Predloženi RMS je omogućio da se ispita vremenski i prostorni obim zajedničkih transportnih objekata i predložio planove za unapređenje transporta.
Reference
Alrumiah, S. S., & Hadwan, M. (2021). Implementing big data analytics in e-commerce: Vendor and customer view. IEEE Access, 9, 37281-37286. https://doi.org/10.1109/ACCESS.2021.3063615
Antons, D., & Breidbach, C. F. (2018). Big data, big insights? Advancing service innovation and design with machine learning. Journal of Service Research, 21(1), 17-39. https://doi.org/10.1177/1094670517738373
Aversa, J., Hernandez, T., & Doherty, S. (2021). Incorporating big data within retail organizations: A case study approach. Journal of retailing and consumer services, 60. https://doi.org/10.1016/j.jretconser.2021.102447
Ayed, A. B., Halima, M. B., & Alimi, A. M. (2015). Big data analytics for logistics and transportation. 4th international conference on advanced logistics and transport (pp. 311-316). IEEE. https://doi.org/10.1109/ICAdLT.2015.7136630
Babar, M., & Arif, F. (2019). Real-time data processing scheme using big data analytics in internet of things based smart transportation environment. Journal of Ambient Intelligence and Humanized Computing, 10(10), 4167-4177. https://doi.org/10.1007/s12652-018-0820-5
Balbin, P. P., Barker, J. C., Leung, C. K., Tran, M., Wall, R. P., & Cuzzocrea, A. (2020). Predictive analytics on open big data for supporting smart transportation services. Procedia Computer Science, 176, 3009-3018. https://doi.org/10.1016/j.procs.2020.09.202
Biuk-Aghai, R. P., Kou, W. T., & Fong, S. (2016). Big data analytics for transportation: Problems and prospects for its application in China, (pp. 173-178). https://doi.org/10.1109/TENCONSpring.2016.7519399
Brajesh, S. (2016). Big data analytics in retail supply chain. In Big Data: Concepts, Methodologies, Tools, and Applications (pp. 1473-1494). IGI Global.
Bresciani, S., Ciampi, F., Meli, F., & Ferraris, A. (2021). Using big data for co-innovation processes: Mapping the field of data-driven innovation, proposing theoretical developments and providing a research agenda. International Journal of Information Management, 60, 102347. https://doi.org/10.1016/j.ijinfomgt.2021.102347
Chiang, L. L., & Yang, C. S. (2018). Does country-of-origin brand personality generate retail customer lifetime value? A Big Data analytics approach. Technological Forecasting and Social Change, 130, 177-187. https://doi.org/10.1016/j.techfore.2017.06.034
Fiore, S. E. (2019). An integrated big and fast data analytics platform for smart urban transportation management. IEEE Access, 7, 117652-117677.
Ghasemaghaei, M., & Calic, G. (2020). Assessing the impact of big data on firm innovation performance: Big data is not always better data. Journal of Business Research, 108, 147-162. https://doi.org/10.1016/j.jbusres.2019.09.062
Ghofrani, F., He, Q., Goverde, R. M., & Liu, X. (2018). Recent applications of big data analytics in railway transportation systems: A survey. Transportation Research Part C: Emerging Technologies, 90, 226-246. https://doi.org/10.1016/j.trc.2018.03.010
Gobble, M. M. (2013). Big data: The next big thing in innovation. Research-technology management, 56(1), 64-67. https://doi.org/10.5437/08956308X5601005
Gohar, M., Muzammal, M., & Rahman, A. U. (2018). SMART TSS: Defining transportation system behavior using big data analytics in smart cities. Sustainable cities and society, 41, 114-119. https://doi.org/10.1016/j.scs.2018.05.008
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317. https://doi.org/10.1016/j.jbusres.2016.08.004
Hao, S., Zhang, H., & Song, M. (2019). Big data, big data analytics capability, and sustainable innovation performance. Sustainability, 11(24), 7145.
He, G. (2021). Enterprise E-commerce marketing system based on big data methods of maintaining social relations in the process of E-commerce environmental commodity. Journal of Organizational and End User Computing (JOEUC), 33(6), 1-16.
Hussein, W. N., Kamarudin, L. M., Hussain, H. N., Zakaria, A., Ahmed, R. B., & Zahri, N. A. (2018). The prospect of internet of things and big data analytics in transportation system. Journal of Physics: Conference Series. IOP Publishing.
Issa, N. T., Byers, S. W., & Dakshanamurthy, S. (2014). Big data: the next frontier for innovation in therapeutics and healthcare. Expert review of clinical pharmacology, 7(3), 293-298. https://doi.org/10.1586/17512433.2014.905201
Ittmann, H. W. (2015). The impact of big data and business analytics on supply chain management. Journal of Transport and Supply Chain Management, 9(1), 1-9. https://hdl.handle.net/10520/EJC169773
Kayser, V., Nehrke, B., & Zubovic, D. (2018). Data science as an innovation challenge: From big data to value proposition. Technology Innovation Management Review, 8(3), 16-25. http://doi.org/10.22215/timreview/1143
Keskar, V., Yadav, J., & Kumar, A. (2021). Perspective of anomaly detection in big data for data quality improvement. Materials Today: Proceedings, 51(1), 532-537. https://doi.org/10.1016/j.matpr.2021.05.597
Lee, H. L. (2018). Big data and the innovation cycle. Production and Operations Management, 1642-1646.
Lee, J., Kao, H. A., & Yang, S. (2014). Service innovation and smart analytics for industry 4.0 and big data environment. Procedia cirp, 16, 3-8. https://doi.org/10.1016/j.procir.2014.02.001
Lekhwar, S., Yadav, S., & Singh, A. (2019). Big data analytics in retail. In Information and communication technology for intelligent systems (pp. 469-477). Springer, Singapore.
Leveling, J., Edelbrock, M., & Otto, B. (2014, December). Big data analytics for supply chain management. In 2014 IEEE international conference on industrial engineering and engineering management (pp. 918-922). IEEE. https://doi.org/10.1109/IEEM.2014.7058772
Li, L., & Zhang, J. (2021). Research and analysis of an enterprise E-commerce marketing system under the big data environment. Journal of Organizational and End User Computing (JOEUC), 33(6), 1-19.
Montoya-Torres, J. R., Moreno, S., Guerrero, W. J., & Mejía, G. (2021). Big data analytics and intelligent transportation systems. IFAC-PapersOnLine, 54(2), 216-220. https://doi.org/10.1016/j.ifacol.2021.06.025
Morabito, V. (2015). Managing change for big data driven innovation. In Big Data and Analytics (pp. 125-153). Springer, Cham.
Neilson, A., Ben Daniel, I., & Tjandra, S. (2019). Systematic Review of the Literature on Big Data in the Transportation Domain: Concepts and Applications. Big Data Research, 17, 35-44. https://doi.org/10.1016/j.bdr.2019.03.001
Nguyen, T., Li, Z. H., Spiegler, V., Ieromonachou, P., & Lin, Y. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers & Operations Research, 80, 254-264. https://doi.org/10.1016/j.cor.2017.07.004
Niebel, T., Rasel, F., & Viete, S. (2019). BIG data–BIG gains? Understanding the link between big data analytics and innovation. Economics of Innovation and New Technology, 28(3), 296-316. https://doi.org/10.1080/10438599.2018.1493075
Shakya, S., & Smys, S. (2021). Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications. Journal of ISMAC, 3(3), 235-249. https://doi.org/10.36548/jismac.2021.3.005
Silva, E., Hassani, H., & Madsen, D. (2020). Big Data in fashion: transforming the retail sector. Journal of Business Strategy, 41(4), 21-27. https://doi.org/10.1108/JBS-04-2019-0062
Trabucchi, D., & Buganza, T. (2018). Data-driven innovation: Switching the perspective on Big Data. European Journal of Innovation Management, 22(1), 23-40. https://doi.org/10.1108/EJIM-01-2018-0017
Wise, J. (2022). How much data is created everyday in 2022? https://earthweb.com/ (21.05.2022).
Wright, L. T., Robin, R., Stone, M., & Aravopoulou, D. E. (2019). Adoption of big data technology for innovation in B2B marketing. Journal of Business-to-Business Marketing, 26(3-4), 281-293. https://doi.org/10.1080/1051712X.2019.1611082
Yang, C., Huang, Q., Li, Z., Liu, K., & Hu, F. (2017). Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth, 10(1), 13-53. https://doi.org/10.1080/17538947.2016.1239771
Yu, R., Wu, C., Yan, B., Yu, B., Zhou, X., Yu, Y., & Chen, N. (2021). Analysis of the impact of big data on e-commerce in cloud computing environment. Complexity, 1-12. https://doi.org/10.1155/2021/5613599
Zhang, X., & Guo, P. (2021). Research on E-Commerce Logistics and Traditional Industry Integration Mode Based on Big Data. Journal of Physics: Conference Series (p. 042052). IOP Publishing.
Zheng, X., Chen, W., Wang, P., Shen, D., Chen, S., Wang, X., & Yang, L. (2015). Big data for social transportation. IEEE Transactions on Intelligent Transportation Systems, 17, 620-630.
Zhu, L., Yu, F. R., Y., W., Ning, & Tang, B. T. (2019). Big Data Analytics in Intelligent Transportation Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems, 20(1), 383-398.
Zhuang, W., Wang, M. C., Nakamoto, I., & Jiang, M. (2021). Big Data Analytics in E-commerce for the US and China Through Literature Reviewing. Journal of Systems Science and Information, 9(1), 16-44. https://doi.org/10.21078/JSSI-2021-016-29