.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] { grid-template-columns: minmax(0, 0.995fr) minmax(0, 0.0049999999999997fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] { grid-template-columns: minmax(0, 0.995fr) minmax(0, 0.0049999999999997fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] { grid-template-columns: minmax(0, 0.175fr) minmax(0, 0.825fr);grid-row-gap: 0px;grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } @media only screen and (max-width: 781px) { .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; }  } @media only screen and (max-width: 599px) { .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="178f44913370c1a86d7a6355205fde40"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="fab8bb265f1c5e8360979431c8e7f268"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="811bf40f85c5a91d7af184a88efeae6c"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; }  } 
The world has seen a surge in extreme weather events and increased challenges of disaster response. One overlooked factor complicating the distribution of relief supplies is the immediate decisions survivors make when seeking aid, which impacts the realized demand at various points of distribution (PODs) of relief supplies. This project aims to understand these critical decisions to improve the overall disaster response framework. Understanding relief supply-seeking behavioral patterns can significantly impact the success and efficiency of relief operations. Current relief distribution models follow normative frameworks where people are expected to visit their nearest PODs, often leading to misestimating demand at PODs and ineffective relief distribution processes. For instance, during Hurricane Maria in 2017, many survivors in Puerto Rico did not receive essential supplies, while thousands of unused water bottles were left to decay at a naval base due to ineffective relief distribution. Therefore, explaining relief supply-seeking travel behaviors, i.e., the decisions related to traveling to PODs and returning from them, in the aftermath of disasters is the first step in ensuring a more effective disaster relief distribution and improving the emergency response process.
Previous research on travel behavior in the context of disasters has focused on the behaviors occurring during the emergency stages of preparedness and recovery. Primarily, past research focused on evacuation and migration, e.g., leveraging high-resolution mobility data to map mobility patterns. There is a significant knowledge gap regarding travel behavior and human decisions made during the response stage, i.e., those related to post-disaster aid-seeking behaviors, including traveling to seek shelter until it is safe to return home and searching for disaster relief supplies to take home. While recent research has focused on shelter location selection decisions, relief supplies-seeking travel behavior, i.e., decisions surrounding traveling to and from PODs, has remained unexplored. Previous studies have only collected anecdotal evidence on why individuals might prefer to travel to a POD that is not the nearest to them, but no empirical research has been formally conducted on this topic. Therefore, there still remain questions regarding where people go to search for relief supplies after a natural disaster, how people get to the PODs, and what factors influence such decisions.
This project is an empirical investigation of relief supply-seeking travel behaviors after disasters. The focus will be on the decision-making of disaster-affected populations that seek relief supplies post-event. The decisions include selecting which POD to visit and choosing a transportation mode and route to and from the POD. These decisions are influenced by preferences, attitudes, perceptions, and disaster and individual-specific factors. The target population for this study includes adults who are familiar with natural disasters and have sought relief supplies after such events. This includes people living in communities that are frequently affected by or have recently experienced a large sudden-onset natural disaster, such as hurricanes or flooding which would require the deployment of PODs during the disaster response stage. The project will leverage the PI’s previous research on state-of-the-art disaster response logistics and ongoing community-building efforts. The latter will lead to identifying the communities for the data collection effort.