Startup companies have had a significant influence on the growth of the economy. Nevertheless, they are prone to failure. Resources, both tangible and intangible, are essential for the sustainable growth of start-up companies. The main objective of this study is to gain a thorough comprehension of the classification of agricultural startup companies in ASEAN countries, taking into account their available resources. This study employs data sourced from Crunchbase, a comprehensive database including information on 201 agricultural startup companies operating in ASEAN countries. The study primarily focuses on analyzing two main variables: tangible and intangible sources. The study employed the K-means clustering algorithm to analyze the attributes of agricultural startup companies. The study’s results indicate that startup companies in ASEAN countries can be categorized into three distinct clusters. The first cluster is made up of players who have a great deal of experience and who have the highest levels of income, funding, and personnel count. The second cluster is made up of players with a moderate amount of experience who have a low CB Rank, Funding, and Estimated Revenue, but they have a moderate number of employees. Inexperienced players make up the third cluster, which has a higher total quantity of investment and income but a very small number of employees. This group is characterized by greater total investment and income
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