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Agent-Based Modeling on Traveler Behavior and Travel Destination Development with Case Study of Indonesian Tourism
Santoso T.A.P.a, Yusuf R.a, Irawan K.a, Juhana A.a, Elindriyani R.V.a, Dermawan K.F.a
a Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 IEEE.Tourism is one of the important factors to increase foreign exchange, especially in Indonesia, where the competitiveness index is always increasing every year. According to The Travel and Tourism Competitiveness Report released by WEF (World Economic Forum) in 2019, the tourism competitiveness index in Indonesia increases to 40 in 2019 from 42 in 2017. Therefore, the competitiveness between travel destinations is also increasing. Some factors which affect travel destination development are visitors’ types and travel destination spot types. Therefore, this paper gives a modeling technique using agent-based modeling to get the effective ratio of the sum of each visitors’ type and the sum of each spot type in the travel destination. In this paper, we used two visitors’ types based on psychographic personality types, venturer visitor and dependable visitor. In addition, we used three spot types, namely venue spots, rest spots, and photo spots. The modeling could be used on some tourism places in Indonesia which have tourism facilities such as the main tourism superstructure (venue spots and rest spots) and the supplementing tourism superstructure (photo spots). This simulation has a result of a ratio and could be executed with various scenarios so that the travel destinations’ owners could determine the exact ratio to get a maximum satisfaction level of every visitor.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Agent-based model,Competitiveness indices,Foreign exchange,Maximum satisfactions,Modeling technique,Personality types,Travel and tourism,Traveler behaviors[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]agent-based modeling,indonesian tourism,travel destination,visitors’ types[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICIDM51048.2020.9339680[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]