消費者人格特質、民宿特色與民宿類型選擇關係之研究

The Study on Relationship among Consumer Personality Trait, Home-Stay Characteristics and Choices of Home-Stay Pattern

張耀堂(Yao-Tang Chang)

指導教授 ： 曾義民

淡江大學/商學院/國際商學碩士在職專班/碩士(2011年)

https://doi.org/10.6846/TKU.2011.00857

摘要

台灣地區民宿之發展迄今已二十餘年，從原先農舍型的簡屋，不斷的轉型成為一種休閒體驗，並且越來越精緻化，目前發展朝向特色民宿與優質民宿為主，特色民宿是一種特別的住宿體驗。本研究發現目前缺少從人格特質、民宿特色以及人口統計變數來探討其與民宿類型選擇之相關研究。因此希望透過遊客認定的民宿特色、遊客的人格特質、遊客的人口統計變數來瞭解與不同類型民宿選擇之間的關係，期望對民宿業者之經營與其產業之發展有所貢獻。

本研究以住宿「藝術創作型」、「復古經營型」、「賞景渡假型」、「農村體驗型」及「社區文化體驗型」等類型之民宿至少一晚之遊客為研究調查對象，共發出問卷550份，回收500份，其中有效問卷439份。研究結果發現不同「年齡、職業、教育程度、個人月收入、居住地區」之遊客在民宿類型選擇上有顯著差異。遊客認定的民宿特色計有「室內空間與服務」、「地點與建築特色」、「業者風格與環境感受」、「業者經營管理」、「地方人文特色」等五構面與民宿類型選擇上有顯著差異。人格特質之「親和性」、「勤勉正直性」、「外向性」、「神經質」與「開放學習性」等五大人格特質與民宿類型選擇上有顯著差異。

本研究建議民宿經營者讓遊客體驗新奇事務或精心安排導覽解說與休閒活動，並設計結合當地特有的民俗活動，讓遊客於住宿期間相互交流，有愉快的回憶、美好的體驗，以提升遊客忠誠度。對於不同人格特質之遊客提供結合當地自然賞景、藝術品製作活動與文化體驗活動，以及客製化的旅遊行程。更重要的是確認自身民宿特色，進行適當行銷，提高與競爭對手的差異性。建議後續研究者調查時可擴大研究範圍、兼顧民宿淡旺季，並思考適宜之民宿分類方式。也建議研究時思考抽樣民宿之合法與非法民宿之關連性。

關鍵字

人格特質 ； 民宿特色 ； 人口統計變數 ； 民宿類型

並列摘要

Taiwanese Home-Stays over a twenty year period, have evolved constantly from traditional farm houses into a much more leisure experience. The current Home-Stays’ appeal is in its sense of characteristics and higher quality. One of the essestial for Home-Stays’ characteristics is its unique accommodation experience. Research has found that lack of personality traits, Home-Stays’ characteristics, and demographic variables are all related to the choice of patterns of Home-Stays. The recognition of Home-Stays’ characteristics via tourists, personality traits and demographic variables of tourists are all included in order to understand the relationship between the choice of patterns of Home-Stays. It is expected that the study can contribute to the management and development of Home-Stays.

The study was aimed at the accommodation of tourists spending at least one night in which patterns of “Art-Creation”, “Nostalgia-Business”, “Sightseeing-Holiday”,“Rural-Experiences”, and “Community-Based cultural Experiences”were all identified. There were a total 550 questionnaires distributed, with 500 questionnaires responses, of which 439 of those were valid. The findings demonstrated the following demographic varabiles :“Age”, “Occupation”, “Educational Level”, “Personal Monthly Income”, and “Area of Residence”towards the tourists’ choices of patterns of Home-Stays were all points of prominent difference. The recognition of Home-Stays’ characteristics via tourists, including “Interior Space and Service”, “Operators’ Style and Environmental Ambience”, “Location and Architectural Feature”, “Local Cultural Characteristic”have all demonstrated the tourists’ choices of patterns of Home-Stays as key points of prominent difference. Prominent differences were demonstrated by the big five personalities:“Agreeableness”, “Conscientious”, “Extraversion”, “Neuroticism”and“Open to Experience”towards the tourists’ choices of patterns of Home-Stays.
The study suggested that Home-Stays’ operators should make tourists’experiences better by arranging well- arranged guided tours and leisure activities, combined with well-designed activities with a particular focus on local folk custom. Loyal tourists could be sought particularly if the experience during their period of accommodation was positive. Tourists with different personality traits provided activities which combined local natural scenery, art-making, cultural experience and customized tours.

However, the most important thing is to identify their own individual characteristics in order to successfully implement proper marketing, as well as to enhance differences between competitors. Follow-up research would be helpful in expanding the scope of the research, and would consider factors such as in season and off season periods, thus identifying suitable classification of Home-Stays. Additional follow-up research was suggested to include the relationship between the sampling survey of both legal and illegal of Home-Stays.

並列關鍵字

Personality Trait ； Home-Stay Characteristics ； Demographic Variables ； Home-Stay Pattern

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