TY - JOUR AU - Choopradit, Boonyarit AU - Thammachote, Pasakorn AU - Wasinrat, Sirithip PY - 2020/09/09 Y2 - 2024/03/29 TI - Classification of Provincial Cluster in Southern Region using Tourism and Area of Agricultural Holdings Statistics JF - JOURNAL OF SOUTHERN TECHNOLOGY JA - J.SCT VL - 13 IS - 2 SE - Research Manuscript DO - UR - https://so04.tci-thaijo.org/index.php/journal_sct/article/view/223614 SP - 10-19 AB - <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;The objectives of this study were to classify 14 provinces in Southern Thailand based on tourism and area of agricultural holdings statistics using cluster analysis with the hierarchical technique and to compare the outcome of classifications of provincial cluster in Southern region by using two different types of variables which are tourism and area of agricultural holdings statistics. Based on tourism statistics, the study employed dendrogram analysis by setting the squared Euclidean distance equal to nine. Fourteen provinces in Southern Thailand could be divided into three groups which are (1) Surat Thani, Krabi, Songkhla, and Phang Nga (2) Phattalung, Trang, Ranong, Chumphon, Pattani, Yala, Narathiwat, Nakhon Si Thammarat, and Satun, and (3) Phuket. Based on agricultural area of holding statistics, the study employed dendrogram analysis by setting the squared Euclidean distance equal to five, fourteen provinces in Southern Thailand could be divided into five groups which are (1) Nakhon Si Thammarat (2) Phattalung, Trang, Ranong, Phuket, Phang Nga, Yala, Krabi, Songkhla, Narathiwat, and Satun (3) Surat Thani (4) Chumphon, and (5) Pattani. As compared with the classification of provincial cluster in Southern region by provincial and cluster management policy steering committee, provinces in Southern Thailand were divided into three groups which are (1) Chumphon, Nakhon Si Thammarat, Phattalung, Surat Thani, and Songkhla (2) Krabi, Trang, Phang Nga, Phuket, Ranong, and Satun, and (3) Narathiwat, Pattani, and Yala. The study found that by using different types of statistical variables for classification of 14 provinces in Southern Thailand, number of groups and member of group were varied. The result of this study would benefit the Southern development strategic planning process to be more contextually appropriate.</p> ER -