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27.2 14.7v7.3zm22.9-135c-23.3 0-32.2-15.7-32.2-32.2V167c0-12.2 8.8-30.4 34-30.4s30.4 17.9 30.4 17.9l-10.7 7.2s-5.5-12.5-19.7-12.5c-7.9 0-19.7 7.3-19.7 19.7v26.8c0 13.4 6.6 23.3 17.9 23.3 14.1 0 21.5-10.9 21.5-26.8h-17.9v-10.7h30.4c0 20.5 4.7 49.9-34 49.9zm-116.5 44.7c-9.4 0-13.6-.3-20-.8v-69.7c6.4-.6 15-.6 22.5-.6 23.3 0 37.2 12.2 37.2 34.5 0 21.9-15 36.6-39.7 36.6z\"><\/path><\/svg>\t\t\t\t\t<\/a>\n\t\t\t\t<\/span>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-9396753 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"9396753\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-82bd76a elementor-widget elementor-widget-text-editor\" data-id=\"82bd76a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.22.0 - 26-06-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Overview <\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-39c869e elementor-widget elementor-widget-text-editor\" data-id=\"39c869e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Dr. Pisit Jarumaneeroj is an Associate Professor at the Department of Industrial Engineering, Chulalongkorn University. His research focuses not only on the applications of optimization in the field of Logistics and Supply Chain Management but also the analysis of complicated transportation networks, where one of his publications concerning a development of new connectivity index for container ports is awarded a prize from the publisher.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-e90f508 e-flex e-con-boxed e-con e-parent\" data-id=\"e90f508\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-921b7f0 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"921b7f0\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1bbfa79 elementor-widget elementor-widget-text-editor\" data-id=\"1bbfa79\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Education<\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e26a24 elementor-widget elementor-widget-text-editor\" data-id=\"3e26a24\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Ph.D. Supply Chain Engineering<br \/>Georgia Institute of Technology, United States, 2014<\/p><p>M.S. Industrial Engineering<br \/>Georgia Institute of Technology, United States, 2009<\/p><p>B.Eng Industrial Engineering (First Class Honours)<br \/>Chulalongkorn University, Thailand, 2004<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-b43563c e-flex e-con-boxed e-con e-parent\" data-id=\"b43563c\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-2484244 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"2484244\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-85ced04 elementor-widget elementor-widget-text-editor\" data-id=\"85ced04\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Expertise<\/span><\/strong><\/h4>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a7004c8 elementor-widget elementor-widget-text-editor\" data-id=\"a7004c8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span class=\"ant-typography StyledText css-1oc51h5\">Operations Research<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-dd10e04 e-flex e-con-boxed e-con e-parent\" data-id=\"dd10e04\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-f3bff30 e-con-full e-flex elementor-invisible e-con e-parent\" data-id=\"f3bff30\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;animation&quot;:&quot;fadeIn&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-70ddead elementor-widget elementor-widget-text-editor\" data-id=\"70ddead\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4><strong><span class=\"ant-typography StyledText css-15ni9ka\">Publications<br \/><\/span><\/strong><\/h4><p><div class=\"teachpress_pub_list\"><form name=\"tppublistform\" method=\"get\"><a name=\"tppubs\" id=\"tppubs\"><\/a><\/form><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">37 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 4 <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=5612&amp;limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=5612&amp;limit=4&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"last page\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><div class=\"teachpress_publication_list\"><h3 class=\"tp_h3\" id=\"tp_h3_2026\">2026<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Garavig Tanaksaranond, Pisit Jarumaneeroj<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('656','tp_links')\" style=\"cursor:pointer;\">Spatio-temporal characteristics of taxis in Bangkok, Thailand, across multiple pandemic waves<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transportation Research Interdisciplinary Perspectives, <\/span><span class=\"tp_pub_additional_volume\">vol. 37, <\/span><span class=\"tp_pub_additional_year\">2026<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 1; All Open Access, Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_656\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('656','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_656\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('656','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_656\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Tanaksaranond2026,<br \/>\r\ntitle = {Spatio-temporal characteristics of taxis in Bangkok, Thailand, across multiple pandemic waves},<br \/>\r\nauthor = {Garavig Tanaksaranond and Pisit Jarumaneeroj},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034329235&doi=10.1016%2fj.trip.2026.101975&partnerID=40&md5=add49958afbc3db3e5a78c4b6fc6418d},<br \/>\r\ndoi = {10.1016\/j.trip.2026.101975},<br \/>\r\nyear  = {2026},<br \/>\r\ndate = {2026-01-01},<br \/>\r\njournal = {Transportation Research Interdisciplinary Perspectives},<br \/>\r\nvolume = {37},<br \/>\r\nnote = {Cited by: 1; All Open Access, Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('656','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_656\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034329235&amp;doi=10.1016%2fj.trip.2026.101975&amp;partnerID=40&amp;md5=add49958afbc3db3e5a78c4b6fc6418d\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034329235&amp;doi=10.1016[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034329235&amp;doi=10.1016[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.trip.2026.101975\" title=\"Follow DOI:10.1016\/j.trip.2026.101975\" target=\"_blank\">doi:10.1016\/j.trip.2026.101975<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('656','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Sanyapong Petchrompo, Bhapisut Wangprasertkul, Atipong Sungsee, Watcharapong Piyaphanee, Punyisa Asawapaithulsert, Wasin Padungwech, Chattarin Wangwittaya, Pisit Jarumaneeroj<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('657','tp_links')\" style=\"cursor:pointer;\">A Data-Driven Framework for Vaccine Demand Forecasting and Inventory Simulation in a Hospital Travel Clinic<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">IEEE Access, <\/span><span class=\"tp_pub_additional_volume\">vol. 14, <\/span><span class=\"tp_pub_additional_pages\">pp. 63536 \u2013 63552, <\/span><span class=\"tp_pub_additional_year\">2026<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0; All Open Access, Gold Open Access, Green Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_657\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('657','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_657\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('657','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_657\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Petchrompo202663536,<br \/>\r\ntitle = {A Data-Driven Framework for Vaccine Demand Forecasting and Inventory Simulation in a Hospital Travel Clinic},<br \/>\r\nauthor = {Sanyapong Petchrompo and Bhapisut Wangprasertkul and Atipong Sungsee and Watcharapong Piyaphanee and Punyisa Asawapaithulsert and Wasin Padungwech and Chattarin Wangwittaya and Pisit Jarumaneeroj},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105036518131&doi=10.1109%2fACCESS.2026.3685781&partnerID=40&md5=6dbebd322ab7b33d634bb476becbbb5e},<br \/>\r\ndoi = {10.1109\/ACCESS.2026.3685781},<br \/>\r\nyear  = {2026},<br \/>\r\ndate = {2026-01-01},<br \/>\r\njournal = {IEEE Access},<br \/>\r\nvolume = {14},<br \/>\r\npages = {63536 \u2013 63552},<br \/>\r\nnote = {Cited by: 0; All Open Access, Gold Open Access, Green Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('657','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_657\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105036518131&amp;doi=10.1109%2fACCESS.2026.3685781&amp;partnerID=40&amp;md5=6dbebd322ab7b33d634bb476becbbb5e\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105036518131&amp;doi=10.1109[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105036518131&amp;doi=10.1109[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ACCESS.2026.3685781\" title=\"Follow DOI:10.1109\/ACCESS.2026.3685781\" target=\"_blank\">doi:10.1109\/ACCESS.2026.3685781<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('657','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2025\">2025<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Xuri Xin, Yuhao Cao, Pisit Jarumaneeroj, Zaili Yang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('614','tp_links')\" style=\"cursor:pointer;\">Vulnerability assessment of International Container Shipping Networks under national-level restriction policies<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transport Policy, <\/span><span class=\"tp_pub_additional_volume\">vol. 167, <\/span><span class=\"tp_pub_additional_pages\">pp. 191 \u2013 209, <\/span><span class=\"tp_pub_additional_year\">2025<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 16; All Open Access, Hybrid Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_614\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('614','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_614\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('614','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_614\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('614','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_614\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Xin2025191,<br \/>\r\ntitle = {Vulnerability assessment of International Container Shipping Networks under national-level restriction policies},<br \/>\r\nauthor = {Xuri Xin and Yuhao Cao and Pisit Jarumaneeroj and Zaili Yang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105001506707&doi=10.1016%2fj.tranpol.2025.03.020&partnerID=40&md5=d8c405f7ceba6804f4a0adbda508eaaa},<br \/>\r\ndoi = {10.1016\/j.tranpol.2025.03.020},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {Transport Policy},<br \/>\r\nvolume = {167},<br \/>\r\npages = {191 \u2013 209},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {This study develops a systematic methodology to assess the vulnerability of International Container Shipping Networks (ICSNs) amid national-level restriction policies potentially caused by the increasing international trade disputes and health crises. It designed a holistic vulnerability assessment framework that explores the impact of two disruption scenarios\u2014direct and complete trade restrictions, which incorporates new measures of vulnerability and centrality to evaluate a country's susceptibility to international restrictions and its impact on other countries' ICSNs. Subsequently, correlation and dependence analyses are conducted to explore relationships between vulnerability\/centrality and eight international network characteristics, identifying key factors. Finally, an enhanced k-means algorithm classifies the impact degrees of various countries' restrictive policies on a country of interest, and examines the effects of both partial and collective disruptions of identified critical countries. Experimental results demonstrate the effectiveness in revealing the varied impacts of different restrictive policies on distinct performance metrics, identifying critical factors that influence vulnerability and centrality, and precisely classifying different countries' restriction impacts to help identify key influential countries. These insights not only deepen understanding of ICSNs under national-level disruptions but also aid in optimizing international shipping from an operational perspective and providing strategic guidance for proactive disruption management from a preventative standpoint. \u00a9 2025 The Authors},<br \/>\r\nnote = {Cited by: 16; All Open Access, Hybrid Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('614','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_614\" style=\"display:none;\"><div class=\"tp_abstract_entry\">This study develops a systematic methodology to assess the vulnerability of International Container Shipping Networks (ICSNs) amid national-level restriction policies potentially caused by the increasing international trade disputes and health crises. It designed a holistic vulnerability assessment framework that explores the impact of two disruption scenarios\u2014direct and complete trade restrictions, which incorporates new measures of vulnerability and centrality to evaluate a country&#8217;s susceptibility to international restrictions and its impact on other countries&#8217; ICSNs. Subsequently, correlation and dependence analyses are conducted to explore relationships between vulnerability\/centrality and eight international network characteristics, identifying key factors. Finally, an enhanced k-means algorithm classifies the impact degrees of various countries&#8217; restrictive policies on a country of interest, and examines the effects of both partial and collective disruptions of identified critical countries. Experimental results demonstrate the effectiveness in revealing the varied impacts of different restrictive policies on distinct performance metrics, identifying critical factors that influence vulnerability and centrality, and precisely classifying different countries&#8217; restriction impacts to help identify key influential countries. These insights not only deepen understanding of ICSNs under national-level disruptions but also aid in optimizing international shipping from an operational perspective and providing strategic guidance for proactive disruption management from a preventative standpoint. \u00a9 2025 The Authors<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('614','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_614\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105001506707&amp;doi=10.1016%2fj.tranpol.2025.03.020&amp;partnerID=40&amp;md5=d8c405f7ceba6804f4a0adbda508eaaa\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105001506707&amp;doi=10.1016[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105001506707&amp;doi=10.1016[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.tranpol.2025.03.020\" title=\"Follow DOI:10.1016\/j.tranpol.2025.03.020\" target=\"_blank\">doi:10.1016\/j.tranpol.2025.03.020<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('614','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Passawich Boonnuch, Manida Swangnetr Neubert, Pisit Jarumaneeroj, Kultida Rojviboonchai, Peerapon Vateekul, Nuksit Noomwongs, Pramual Suteecharuwat<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('654','tp_links')\" style=\"cursor:pointer;\">Machine Learning &#8211; Based Analysis of Driving Performance and Fatigue &#8211; Induced Behavioral Factors<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_year\">2025<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_654\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('654','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_654\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('654','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_654\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{Boonnuch2025260,<br \/>\r\ntitle = {Machine Learning - Based Analysis of Driving Performance and Fatigue - Induced Behavioral Factors},<br \/>\r\nauthor = {Passawich Boonnuch and Manida Swangnetr Neubert and Pisit Jarumaneeroj and Kultida Rojviboonchai and Peerapon Vateekul and Nuksit Noomwongs and Pramual Suteecharuwat},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034905574&doi=10.1109%2fICCR67607.2025.11372072&partnerID=40&md5=8e5e244c6dde6f633c13fa287619bc2b},<br \/>\r\ndoi = {10.1109\/ICCR67607.2025.11372072},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {2025 7th International Conference on Control and Robotics, ICCR 2025},<br \/>\r\npages = {260 \u2013 264},<br \/>\r\nnote = {Cited by: 0},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('654','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_654\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034905574&amp;doi=10.1109%2fICCR67607.2025.11372072&amp;partnerID=40&amp;md5=8e5e244c6dde6f633c13fa287619bc2b\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034905574&amp;doi=10.1109[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105034905574&amp;doi=10.1109[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1109\/ICCR67607.2025.11372072\" title=\"Follow DOI:10.1109\/ICCR67607.2025.11372072\" target=\"_blank\">doi:10.1109\/ICCR67607.2025.11372072<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('654','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Yuhao Cao, Xuri Xin, Pisit Jarumaneeroj, Huanhuan Li, Yinwei Feng, Jin Wang, Xinjian Wang, Robyn Pyne, Zaili Yang<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('615','tp_links')\" style=\"cursor:pointer;\">Data-driven resilience analysis of the global container shipping network against two cascading failures<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transportation Research Part E: Logistics and Transportation Review, <\/span><span class=\"tp_pub_additional_volume\">vol. 193, <\/span><span class=\"tp_pub_additional_year\">2025<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 58; All Open Access, Hybrid Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_615\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('615','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_615\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('615','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_615\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('615','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_615\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Cao2025,<br \/>\r\ntitle = {Data-driven resilience analysis of the global container shipping network against two cascading failures},<br \/>\r\nauthor = {Yuhao Cao and Xuri Xin and Pisit Jarumaneeroj and Huanhuan Li and Yinwei Feng and Jin Wang and Xinjian Wang and Robyn Pyne and Zaili Yang},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85212391651&doi=10.1016%2fj.tre.2024.103857&partnerID=40&md5=d4cd91c89a48a5c737afcac571e12bc5},<br \/>\r\ndoi = {10.1016\/j.tre.2024.103857},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {Transportation Research Part E: Logistics and Transportation Review},<br \/>\r\nvolume = {193},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {Being a fundamental link in the global supply chain and logistics system, the global container shipping network (GCSN) is highly interconnected, which causes the network resilience challenges by the cascading failures triggered by extreme events (e.g., COVID-19 and regional conflicts). Within this dynamic process, the load redistribution behaviour is the core countermeasure for the propagation of cascading failures, however the diversified mechanism has not been systematically studied. To fill in these gaps, this study aims to develop a pioneering resilience analysis framework against cascading failures, to comprehensively explore the impact of port disruptions on the shipping network resilience. By pioneering the influence analysis of port betweenness, weight, and connectivity on load determination and target selection, a port importance assessment method is applied as the foundation for load redistribution decisions. Based on the global service routes data from 2020 to 2023, the GCSN resilience against the sequential cascading failures of 686 ports worldwide is quantified by three metrics. A scenario analysis is conducted to simulate the effects of cascading failures triggered by 5 historical port disruption events (e.g., the COVID-19 port lockdowns and the 2024 bridge collision at Baltimore port) on resilience of the network. Determining the identified critical capacity threshold is pivotal for effectively enhancing the system's resilience and preventing the likelihood of cascading failures. Additionally, this study offers cutting-edge perspectives to the global shipping industry stakeholders. It presents distinct strategies and preferences, offering actionable advice for port authorities in their risk response decisions. Moreover, this study delivers an economic rationale and critical evaluations, instrumental for the strategic maintenance, planning and augmentation of port infrastructures to prevent unforeseen risks. \u00a9 2024 The Author(s)},<br \/>\r\nnote = {Cited by: 58; All Open Access, Hybrid Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('615','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_615\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Being a fundamental link in the global supply chain and logistics system, the global container shipping network (GCSN) is highly interconnected, which causes the network resilience challenges by the cascading failures triggered by extreme events (e.g., COVID-19 and regional conflicts). Within this dynamic process, the load redistribution behaviour is the core countermeasure for the propagation of cascading failures, however the diversified mechanism has not been systematically studied. To fill in these gaps, this study aims to develop a pioneering resilience analysis framework against cascading failures, to comprehensively explore the impact of port disruptions on the shipping network resilience. By pioneering the influence analysis of port betweenness, weight, and connectivity on load determination and target selection, a port importance assessment method is applied as the foundation for load redistribution decisions. Based on the global service routes data from 2020 to 2023, the GCSN resilience against the sequential cascading failures of 686 ports worldwide is quantified by three metrics. A scenario analysis is conducted to simulate the effects of cascading failures triggered by 5 historical port disruption events (e.g., the COVID-19 port lockdowns and the 2024 bridge collision at Baltimore port) on resilience of the network. Determining the identified critical capacity threshold is pivotal for effectively enhancing the system&#8217;s resilience and preventing the likelihood of cascading failures. Additionally, this study offers cutting-edge perspectives to the global shipping industry stakeholders. It presents distinct strategies and preferences, offering actionable advice for port authorities in their risk response decisions. Moreover, this study delivers an economic rationale and critical evaluations, instrumental for the strategic maintenance, planning and augmentation of port infrastructures to prevent unforeseen risks. \u00a9 2024 The Author(s)<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('615','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_615\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85212391651&amp;doi=10.1016%2fj.tre.2024.103857&amp;partnerID=40&amp;md5=d4cd91c89a48a5c737afcac571e12bc5\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85212391651&amp;doi=10.1016%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85212391651&amp;doi=10.1016%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.tre.2024.103857\" title=\"Follow DOI:10.1016\/j.tre.2024.103857\" target=\"_blank\">doi:10.1016\/j.tre.2024.103857<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('615','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Pawaris Wachwanakijkul, Supawit Junsiritrakhoon, Nantachai Kantanantha, Gopalakrishnan Narayanamurthy, Pisit Jarumaneeroj<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('655','tp_links')\" style=\"cursor:pointer;\">Data-driven approaches to predicting customer churn in a non-contractual car-sharing company<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transportation Research Interdisciplinary Perspectives, <\/span><span class=\"tp_pub_additional_volume\">vol. 33, <\/span><span class=\"tp_pub_additional_year\">2025<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 1; All Open Access, Gold Open Access, Green Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_655\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('655','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_655\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('655','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_655\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Wachwanakijkul2025,<br \/>\r\ntitle = {Data-driven approaches to predicting customer churn in a non-contractual car-sharing company},<br \/>\r\nauthor = {Pawaris Wachwanakijkul and Supawit Junsiritrakhoon and Nantachai Kantanantha and Gopalakrishnan Narayanamurthy and Pisit Jarumaneeroj},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105014126233&doi=10.1016%2fj.trip.2025.101600&partnerID=40&md5=840fad6fc4a5a11ec8d5cc66922b21b2},<br \/>\r\ndoi = {10.1016\/j.trip.2025.101600},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {Transportation Research Interdisciplinary Perspectives},<br \/>\r\nvolume = {33},<br \/>\r\nnote = {Cited by: 1; All Open Access, Gold Open Access, Green Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('655','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_655\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105014126233&amp;doi=10.1016%2fj.trip.2025.101600&amp;partnerID=40&amp;md5=840fad6fc4a5a11ec8d5cc66922b21b2\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105014126233&amp;doi=10.1016[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-105014126233&amp;doi=10.1016[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.trip.2025.101600\" title=\"Follow DOI:10.1016\/j.trip.2025.101600\" target=\"_blank\">doi:10.1016\/j.trip.2025.101600<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('655','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Pisit Jarumaneeroj, Supisara Krairiksh, Puwadol Oak Dusadeerungsikul, Dong Li, \u00c7a\u011fatay Iris<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('616','tp_links')\" style=\"cursor:pointer;\">Eco-friendly long-haul perishable product transportation with multi-compartment vehicles<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Computers and Industrial Engineering, <\/span><span class=\"tp_pub_additional_volume\">vol. 202, <\/span><span class=\"tp_pub_additional_year\">2025<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 4; All Open Access, Hybrid Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_616\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('616','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_616\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('616','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_616\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('616','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_616\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Jarumaneeroj2025,<br \/>\r\ntitle = {Eco-friendly long-haul perishable product transportation with multi-compartment vehicles},<br \/>\r\nauthor = {Pisit Jarumaneeroj and Supisara Krairiksh and Puwadol Oak Dusadeerungsikul and Dong Li and \u00c7a\u011fatay Iris},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85217719766&doi=10.1016%2fj.cie.2025.110934&partnerID=40&md5=c69a7e194c2581a7efb0eaa0834acf4f},<br \/>\r\ndoi = {10.1016\/j.cie.2025.110934},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-01-01},<br \/>\r\njournal = {Computers and Industrial Engineering},<br \/>\r\nvolume = {202},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {Multi-compartment refrigerated vehicles (MCVs) have been recently utilized in long-haul perishable product transportation, thanks to their flexibility in storage capacity with different temperature settings. To better understand trade-offs between economic and environmental aspects of long-haul transportation of perishable products with refrigerated vehicles, a Multi-Compartment Vehicle Loading and Scheduling Problem (MCVLSP) that minimizes three objectives\u2014transportation cost, carbon emissions, and total food loss\u2014is herein solved by mathematical modeling and genetic algorithm (GA) approaches. Our computational results indicate that larger MCVLSP instances cannot be solved to optimality using the mathematical model with off-the-shelf optimization software packages. The proposed GA delivers strong computational performance for MCVLSP with respect to solution quality and computational time. We find that, among three objectives, the environmental objective is the most sensitive one as slight difference in either vehicle loading or scheduling decisions could result in solutions with significantly varying carbon emissions. Moreover, solutions with fewer MCVs are not necessarily environmentally sustainable. Rather, deploying larger MCV fleets could potentially result in lower carbon emissions and food weight loss for perishable products\u2014albeit a slight increase in total transportation cost\u2014due to the changes in vehicle loading and scheduling decisions. \u00a9 2025 The Author(s)},<br \/>\r\nnote = {Cited by: 4; All Open Access, Hybrid Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('616','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_616\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Multi-compartment refrigerated vehicles (MCVs) have been recently utilized in long-haul perishable product transportation, thanks to their flexibility in storage capacity with different temperature settings. To better understand trade-offs between economic and environmental aspects of long-haul transportation of perishable products with refrigerated vehicles, a Multi-Compartment Vehicle Loading and Scheduling Problem (MCVLSP) that minimizes three objectives\u2014transportation cost, carbon emissions, and total food loss\u2014is herein solved by mathematical modeling and genetic algorithm (GA) approaches. Our computational results indicate that larger MCVLSP instances cannot be solved to optimality using the mathematical model with off-the-shelf optimization software packages. The proposed GA delivers strong computational performance for MCVLSP with respect to solution quality and computational time. We find that, among three objectives, the environmental objective is the most sensitive one as slight difference in either vehicle loading or scheduling decisions could result in solutions with significantly varying carbon emissions. Moreover, solutions with fewer MCVs are not necessarily environmentally sustainable. Rather, deploying larger MCV fleets could potentially result in lower carbon emissions and food weight loss for perishable products\u2014albeit a slight increase in total transportation cost\u2014due to the changes in vehicle loading and scheduling decisions. \u00a9 2025 The Author(s)<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('616','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_616\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85217719766&amp;doi=10.1016%2fj.cie.2025.110934&amp;partnerID=40&amp;md5=c69a7e194c2581a7efb0eaa0834acf4f\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85217719766&amp;doi=10.1016%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85217719766&amp;doi=10.1016%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.cie.2025.110934\" title=\"Follow DOI:10.1016\/j.cie.2025.110934\" target=\"_blank\">doi:10.1016\/j.cie.2025.110934<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('616','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2024\">2024<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Mark Ching-Pong Poo, Zaili Yang, Yui-yip Lau, Pisit Jarumaneeroj<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('380','tp_links')\" style=\"cursor:pointer;\">Assessing the impact of Arctic shipping routes on the global container shipping network\u2019s connectivity<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Polar Geography, <\/span><span class=\"tp_pub_additional_year\">2024<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 0; All Open Access, Hybrid Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_380\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('380','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_380\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('380','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_380\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Poo2024,<br \/>\r\ntitle = {Assessing the impact of Arctic shipping routes on the global container shipping network\u2019s connectivity},<br \/>\r\nauthor = {Mark Ching-Pong Poo and Zaili Yang and Yui-yip Lau and Pisit Jarumaneeroj},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85203686839&doi=10.1080%2f1088937X.2024.2399775&partnerID=40&md5=45ce2c427892e7fd6ef29fc7d2daf112},<br \/>\r\ndoi = {10.1080\/1088937X.2024.2399775},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Polar Geography},<br \/>\r\nnote = {Cited by: 0; All Open Access, Hybrid Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('380','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_380\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85203686839&amp;doi=10.1080%2f1088937X.2024.2399775&amp;partnerID=40&amp;md5=45ce2c427892e7fd6ef29fc7d2daf112\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85203686839&amp;doi=10.1080%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85203686839&amp;doi=10.1080%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1080\/1088937X.2024.2399775\" title=\"Follow DOI:10.1080\/1088937X.2024.2399775\" target=\"_blank\">doi:10.1080\/1088937X.2024.2399775<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('380','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Thadathibesra Phuthong, Tanarat Borisuth, Zaili Yang, Pisit Jarumaneeroj<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('373','tp_links')\" style=\"cursor:pointer;\">Identifying factors influencing electric vehicle adoption in an emerging market: The case of Thailand<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transportation Research Interdisciplinary Perspectives, <\/span><span class=\"tp_pub_additional_volume\">vol. 27, <\/span><span class=\"tp_pub_additional_year\">2024<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 19; All Open Access, Gold Open Access, Green Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_373\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('373','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_373\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('373','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_373\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('373','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_373\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Phuthong2024,<br \/>\r\ntitle = {Identifying factors influencing electric vehicle adoption in an emerging market: The case of Thailand},<br \/>\r\nauthor = {Thadathibesra Phuthong and Tanarat Borisuth and Zaili Yang and Pisit Jarumaneeroj},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85204469532&doi=10.1016%2fj.trip.2024.101229&partnerID=40&md5=6c02e5ca39b3840fae97798ee1d1d112},<br \/>\r\ndoi = {10.1016\/j.trip.2024.101229},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Transportation Research Interdisciplinary Perspectives},<br \/>\r\nvolume = {27},<br \/>\r\npublisher = {Elsevier Ltd},<br \/>\r\nabstract = {Electric vehicles (EVs) are considered a technological innovation that helps reduce not only fuel consumption but also air pollution and greenhouse gases that exacerbate global warming concerns. Despite these benefits, the understanding of factors influencing EV adoption remains obscure, as it varies greatly across countries and perspectives (e.g., the acceptance of EV technology, decisions to purchase and use EVs, and policies that affect user decisions to purchase and use EVs). To better comprehend the dominance of such factors \u2014 especially in an emerging market with a huge leap in EV usage, like Thailand \u2014 we devise a multi-perspective multi-criteria decision analysis (MCDA) framework and apply it to datasets of Thai EV users, including both general EV user and expert groups. Our results reveal that \u201cAttitude Toward Using EVs\u201d and \u201cSubjective Norms\u201d are crucial for the acceptance of EVs, while \u201cProduct and Service Attributes\u201d and \u201cPurchasing Incentive Policies\u201d greatly impact the adoption decisions. Besides these factors, we also identify causal-effect relationships among factors in each of these three different perspectives. This research thus allows stakeholders \u2014 including EV manufacturers, transport authorities, and governments \u2014 to properly devise relevant mechanisms supporting countrywide EV adoption in a more sustainable fashion. \u00a9 2024 The Author(s)},<br \/>\r\nnote = {Cited by: 19; All Open Access, Gold Open Access, Green Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('373','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_373\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Electric vehicles (EVs) are considered a technological innovation that helps reduce not only fuel consumption but also air pollution and greenhouse gases that exacerbate global warming concerns. Despite these benefits, the understanding of factors influencing EV adoption remains obscure, as it varies greatly across countries and perspectives (e.g., the acceptance of EV technology, decisions to purchase and use EVs, and policies that affect user decisions to purchase and use EVs). To better comprehend the dominance of such factors \u2014 especially in an emerging market with a huge leap in EV usage, like Thailand \u2014 we devise a multi-perspective multi-criteria decision analysis (MCDA) framework and apply it to datasets of Thai EV users, including both general EV user and expert groups. Our results reveal that \u201cAttitude Toward Using EVs\u201d and \u201cSubjective Norms\u201d are crucial for the acceptance of EVs, while \u201cProduct and Service Attributes\u201d and \u201cPurchasing Incentive Policies\u201d greatly impact the adoption decisions. Besides these factors, we also identify causal-effect relationships among factors in each of these three different perspectives. This research thus allows stakeholders \u2014 including EV manufacturers, transport authorities, and governments \u2014 to properly devise relevant mechanisms supporting countrywide EV adoption in a more sustainable fashion. \u00a9 2024 The Author(s)<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('373','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_373\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85204469532&amp;doi=10.1016%2fj.trip.2024.101229&amp;partnerID=40&amp;md5=6c02e5ca39b3840fae97798ee1d1d112\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85204469532&amp;doi=10.1016%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85204469532&amp;doi=10.1016%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.trip.2024.101229\" title=\"Follow DOI:10.1016\/j.trip.2024.101229\" target=\"_blank\">doi:10.1016\/j.trip.2024.101229<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('373','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Pisit Jarumaneeroj, Jorge Barnett Lawton, Morten Svindland<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('378','tp_links')\" style=\"cursor:pointer;\">An evolution of the Global Container Shipping Network: port connectivity and trading community structure (2011\u20132017)<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Maritime Economics and Logistics, <\/span><span class=\"tp_pub_additional_volume\">vol. 26, <\/span><span class=\"tp_pub_additional_number\">no. 2, <\/span><span class=\"tp_pub_additional_pages\">pp. 283 \u2013 306, <\/span><span class=\"tp_pub_additional_year\">2024<\/span><span class=\"tp_pub_additional_note\">, (Cited by: 18; All Open Access, Hybrid Gold Open Access)<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_378\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('378','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_378\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('378','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_378\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('378','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_378\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Jarumaneeroj2024283,<br \/>\r\ntitle = {An evolution of the Global Container Shipping Network: port connectivity and trading community structure (2011\u20132017)},<br \/>\r\nauthor = {Pisit Jarumaneeroj and Jorge Barnett Lawton and Morten Svindland},<br \/>\r\nurl = {https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85175660004&doi=10.1057%2fs41278-023-00273-x&partnerID=40&md5=60adba0134b1be92f558d16dd80ba83b},<br \/>\r\ndoi = {10.1057\/s41278-023-00273-x},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-01-01},<br \/>\r\njournal = {Maritime Economics and Logistics},<br \/>\r\nvolume = {26},<br \/>\r\nnumber = {2},<br \/>\r\npages = {283 \u2013 306},<br \/>\r\npublisher = {Palgrave Macmillan},<br \/>\r\nabstract = {Port connectivity and trading community structure are two fundamental network characteristics that complement one another in explaining the evolution of maritime transport networks. Although port connectivity has been widely studied in the literature, the investigations on trading community structures are rather limited. To better fill this gap, this paper aims to provide a more complete picture of the Global Container Shipping Network (GCSN)\u2019s evolution, based on our earlier works in MEL. In doing so, the GCSN, representing a snapshot of trade at the end of each quarter, from Q3\/2011 to Q3\/2017, is first constructed. The connectivity of ports and their respective trading communities are then extracted by the Container Port Connectivity Index and the Louvain algorithm, respectively. With our proposed framework, related players would be able to understand the growth of GCSN, as well as the impacts of maritime occurrences on the network of container shipping. Our computational results indicate that port connectivity and trading community structure gradually evolve according to the economic conditions that change over time and the evolution of GCSN could be well explained by these two explanatory variables. In this regard, ports in East Asia consistently dominate others in terms of both inbound and outbound connectivity, led by Shanghai and other major ports of mainland China. Furthermore, the formation of trading communities largely depends on trading patterns\u2014rather than geographical locations\u2014which is evident from the insolvency and mergers of communities in the North American region right after the expansion of the Panama Canal in 2016. \u00a9 The Author(s) 2023.},<br \/>\r\nnote = {Cited by: 18; All Open Access, Hybrid Gold Open Access},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('378','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_378\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Port connectivity and trading community structure are two fundamental network characteristics that complement one another in explaining the evolution of maritime transport networks. Although port connectivity has been widely studied in the literature, the investigations on trading community structures are rather limited. To better fill this gap, this paper aims to provide a more complete picture of the Global Container Shipping Network (GCSN)\u2019s evolution, based on our earlier works in MEL. In doing so, the GCSN, representing a snapshot of trade at the end of each quarter, from Q3\/2011 to Q3\/2017, is first constructed. The connectivity of ports and their respective trading communities are then extracted by the Container Port Connectivity Index and the Louvain algorithm, respectively. With our proposed framework, related players would be able to understand the growth of GCSN, as well as the impacts of maritime occurrences on the network of container shipping. Our computational results indicate that port connectivity and trading community structure gradually evolve according to the economic conditions that change over time and the evolution of GCSN could be well explained by these two explanatory variables. In this regard, ports in East Asia consistently dominate others in terms of both inbound and outbound connectivity, led by Shanghai and other major ports of mainland China. Furthermore, the formation of trading communities largely depends on trading patterns\u2014rather than geographical locations\u2014which is evident from the insolvency and mergers of communities in the North American region right after the expansion of the Panama Canal in 2016. \u00a9 The Author(s) 2023.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('378','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_378\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85175660004&amp;doi=10.1057%2fs41278-023-00273-x&amp;partnerID=40&amp;md5=60adba0134b1be92f558d16dd80ba83b\" title=\"https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85175660004&amp;doi=10.1057%[...]\" target=\"_blank\">https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-85175660004&amp;doi=10.1057%[&#8230;]<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1057\/s41278-023-00273-x\" title=\"Follow DOI:10.1057\/s41278-023-00273-x\" target=\"_blank\">doi:10.1057\/s41278-023-00273-x<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('378','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><\/div><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">37 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 4 <a href=\"https:\/\/ienext.eng.chula.ac.th\/?page_id=5612&amp;limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a 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