Cite

Al-Tit, A. A. (2020). E-commerce drivers and barriers and their impact on e-customer loyalty in small and medium-sized enterprises (SMES). Business: Theory and Practice, 21(1), 146-157. doi: 10.3846/btp.2020.11612 Search in Google Scholar

Bansal, S., & Wadhawan, S. (2021). A hybrid of sine cosine and particle swarm optimization (HSPS) for solving heterogeneous fixed fleet vehicle routing problem. International Journal of Applied Metaheuristic Computing (IJAMC), 12(1), 41-65. Search in Google Scholar

Belmecheri, F., Prins, C., Yalaoui, F., & Amodeo, L. (2013). Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows. Journal of Intelligent Manufacturing, 24(4), 775-789. Search in Google Scholar

Bent, R., & Van Hentenryck, P. (2006). A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows. Computers & Operations Research, 33(4), 875-893. Search in Google Scholar

Bruglieri, M., Mancini, S., & Pisacane, O. (2019). The green vehicle routing problem with capacitated alternative fuel stations. Computers & Operations Research, 112, 104759. Search in Google Scholar

Chen, M. C., Hsiao, Y. H., Reddy, R. H., & Tiwari, M. K. (2016). The self-learning particle swarm optimization approach for routing pickup and delivery of multiple products with material handling in multiple cross-docks. Transportation Research Part E: Logistics and Transportation Review, 91, 208-226. Search in Google Scholar

Chen, N., & Yang, Y. (2021). The impact of customer experience on consumer purchase intention in cross-border E-commerce – taking network structural embeddedness as mediator variable. Journal of Retailing and Consumer Services, 59, 102344. Search in Google Scholar

Créput, J. C., Koukam, A., Kozlak, J., & Lukasik, J. (2004). An evolutionary approach to pickup and delivery problem with time windows. In International Conference on Computational Science (pp. 1102-1108). Springer, Berlin, Heidelberg. Search in Google Scholar

Fan, H., Zhang, Y., Tian, P., Lv, Y., & Fan, H. (2021). Time-dependent multi-depot green vehicle routing problem with time windows considering temporal-spatial distance. Computers & Operations Research, 129, 105211. Search in Google Scholar

Faugère, L., & Montreuil, B. (2020). Smart locker bank design optimization for urban omnichannel logistics: Assessing monolithic vs. modular configurations. Computers & Industrial Engineering, 139, 105544. Search in Google Scholar

Fedorko, R., Fedorko, I., Riana, I. G., Rigelský, M., Oleárová, M., & Obšatníková, K. (2018). The impact of selected elements of e-commerce to e-shop recommendation. Polish Journal of Management Studies, 18(1), 107-120. doi: 10.17512/pjms.2018.18.1.09 Search in Google Scholar

Florek-Paszkowska, A., Ujwary-Gil, A., & Godlewska-Dzioboń, B. (2021). Business innovation and critical success factors in the era of digital transformation and turbulent times. Journal of Entrepreneurship, Management, and Innovation, 17(4), 7-28. doi: 10.7341/20211741 Search in Google Scholar

Foroutan, R. A., Rezaeian, J., & Mahdavi, I. (2020). Green vehicle routing and scheduling problem with heterogeneous fleet including reverse logistics in the form of collecting returned goods. Applied Soft Computing, 94, 106462. Search in Google Scholar

Fu, H., Manogaran, G., Wu, K., Cao, M., Jiang, S., & Yang, A. (2020). Intelligent decision-making of online shopping behavior based on internet of things. International Journal of Information Management, 50, 515-525. Search in Google Scholar

Goksal, F. P., Karaoglan, I., & Altiparmak, F. (2013). A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Computers & Industrial Engineering, 65(1), 39-53. Search in Google Scholar

Gregory, G. D., Ngo, L. V., & Karavdic, M. (2019). Developing e-commerce marketing capabilities and efficiencies for enhanced performance in business-to-business export ventures. Industrial Marketing, 78, 146-157. Search in Google Scholar

Gulc, A. (2021). Multi-stakeholder perspective of courier service quality in B2C e-commerce. PLoS ONE, 16(5), 1-18. doi: 10.1371/journal.pone.0251728 Search in Google Scholar

Gupta, P., Govindan, K., Mehlawat, M. K., & Khaitan, A. (2021). Multiobjective capacitated green vehicle routing problem with fuzzy time-distances and demands split into bags. International Journal of Production Research, 1-17. Search in Google Scholar

Harbaoui Dridi, I., Ben Alaïa, E., Borne, P., & Bouchriha, H. (2020). Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm. International Journal of Production Research, 58(14), 4201-4214. Search in Google Scholar

Hasle, G., & Kloster, O. (2007). Industrial vehicle routing. In G. Hasle, K.-A. Lie, E. Quak (Eds.), Geometric modelling, Numerical Simulation, and Optimization (pp.397-435). Berlin, Heidelberg: Springer. Search in Google Scholar

Jacobs, K., Warner, S., Rietra, M., Mazza, L., Buvat, J., Khadikar, A., Cherian, S., & Khemka, Y. (2019). The last-mile delivery challenge: Giving retail and consumer product customers a superior delivery experience without impacting profitability. Retrieved from https://www.capgemini.com/wp-content/uploads/2019/01/Report-Digital-%E2%80%93-Last-Mile-Delivery-Challenge1.pdf Search in Google Scholar

Lagos, C., Guerrero, G., Cabrera, E., Moltedo, A., Johnson, F., & Paredes, F. (2018). An improved particle swarm optimization algorithm for the VRP with simultaneous pickup and delivery and time windows. IEEE Latin America Transactions, 16(6), 1732-1740. Search in Google Scholar

Lemke, J., Iwan, S., & Korczak, J. (2016). Usability of the parcel lockers from the customer perspective – the research in Polish Cities. Transportation Research Procedia, 16, 272-287. Search in Google Scholar

Li, H., & Lim, A. (2003). A metaheuristic for the pickup and delivery problem with time windows. International Journal on Artificial Intelligence Tools, 12(02), 173-186. Search in Google Scholar

Liu, X., Zhang, K., Chen, B., Zhou, J., & Miao, L. (2018). Analysis of logistics service supply chain for the One Belt and One Road initiative of China. Transportation Research Part E: Logistics and Transportation Review, 117, 23-39. Search in Google Scholar

Mehlawat, M. K., Gupta, P., Khaitan, A., & Pedrycz, W. (2019). A hybrid intelligent approach to integrated fuzzy multiple depot capacitated green vehicle routing problem with split delivery and vehicle selection. IEEE Transactions on Fuzzy Systems, 28(6), 1155-1166. Search in Google Scholar

Mutinda Kitukutha, N., Vasa, L., & Oláh, J. (2021). The Impact of COVID-19 on the economy and sustainable e-commerce. Forum Scientiae Oeconomia, 9(2), 47-72. doi: 10.23762/FSO_VOL9_NO2_3 Search in Google Scholar

Norouzi, N., Sadegh-Amalnick, M., & Tavakkoli-Moghaddam, R. (2017). Modified particle swarm optimization in a time-dependent vehicle routing problem: minimizing fuel consumption. Optimization Letters, 11, 121-134. Search in Google Scholar

Qin, X., Liu, Z., & Tian, L. (2021). The optimal combination between selling mode and logistics service strategy in an e-commerce market. European Journal of Operational Research, 289(2), 639-651. Search in Google Scholar

Ready, C. (2013). Environmental reporting guidelines: Including mandatory greenhouse gas emissions reporting guidance. Retrieved from https://www.gov.uk/government/publications/environmental-reporting-guidelines-including-mandatory-greenhouse-gas-emissions-reporting-guidance Search in Google Scholar

Rita, P., Oliveira, T., & Farisa, A. (2019). The impact of e-service quality and customer satisfaction on customer behavior in online shopping. Heliyon, 5(10), e02690. Search in Google Scholar

Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. In IEEE international conference on evolutionary computation proceedings. IEEE world congress on computational intelligence (Cat. No. 98TH8360) (pp. 69-73). IEEE. Search in Google Scholar

Sruthi, A., Anbuudayasankar, S. P., & Jeyakumar, G. (2019). Energy-efficient green vehicle routing problem. International Journal of Information Systems and Supply Chain Management (IJISSCM), 12(4), 27-41. Search in Google Scholar

Tsang, Y. P., Wu, C. H., Lam, H. Y., Choy, K. L., & Ho, G. T. S. (2021). Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application. International Journal of Production Research, 59(5), 1534-1556. Search in Google Scholar

Úbeda, S., Faulin, J., Serrano, A., & Arcelus, F. J. (2014). Solving the green capacitated vehicle routing problem using a tabu search algorithm. Lecture Notes in Management Science, 6(1), 141-149. Search in Google Scholar

United States. Environmental Protection Agency. Office of Policy. (1999). Inventory of US Greenhouse Gas Emissions and Sinks: 1990-1997. The Agency. Search in Google Scholar

Vakulenko, Y., Shams, P., Hellström, D., & Hjort, K. (2019). Service innovation in e-commerce last mile delivery: Mapping the e-customer journey. Journal of Business Research, 101, 461-468. Search in Google Scholar

van Lopik, K., Schnieder, M., Sharpe, R., Sinclair, M., Hinde, C., Conway, P., West, A., & Maguire, M. (2020). Comparison of in-sight and handheld navigation devices toward supporting industry 4.0 supply chains: First and last mile deliveries at the human level. Applied Ergonomics, 82, 102928. Search in Google Scholar

Xu, X., Wang, C., Li, J., & Shi, C. (2019). Green Transportation and Information Uncertainty in Gasoline Distribution: Evidence from China. Emerging Markets Finance and Trade, 57(11), 1-19. Search in Google Scholar

Yu, Y., Wang, S., Wang, J., & Huang, M. (2019). A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows. Transportation Research Part B: Methodological, 122, 511-527. Search in Google Scholar

Yu, Y., Yu, C., Xu, G., Zhong, R. Y., & Huang, G. Q. (2020). An operation synchronization model for distribution center in E-commerce logistics service. Advanced Engineering Informatics, 43, 101014. Search in Google Scholar

Yuen, K. F., Wang, X., Ma, F., & Wong, Y. D. (2019). The determinants of customers’ intention to use smart lockers for last-mile deliveries. Journal of Retailing and Consumer Services, 49, 316-326. Search in Google Scholar

Zhang, X., Zhou, G., Cao, J., & Wu, A. (2020). Evolving strategies of e-commerce and express delivery enterprises with public supervision. Research in Transportation Economics, 80, 100810. Search in Google Scholar

Zhou, M., Zhao, L., Kong, N., Campy, K. S., Xu, G., Zhu, G., Cao, X., & Wang, S. (2020). Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery. Journal of Retailing and Consumer Services, 52, 101911. Search in Google Scholar

Zhu, L., & Hu, D. (2019). Study on the vehicle routing problem considering congestion and emission factors. International Journal of Production Research, 57(19), 6115-6129. Search in Google Scholar