Performance evaluation on website and search engine optimization of Taiwan star hotel: web metrics analysis

• Main Authors: Sheng-Cheng Hsu, 許勝程
• Other Authors: Sheng-Hshiung Tsaur
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/446svp

碩士 === 國立嘉義大學 === 管院碩士在職專班 === 106 === With the growing popularity of Internet use in Taiwan, nearly ninety percent of Taiwanese people search travel information though the net. Moreover, the most commonly booked item online is accommodation. Currently there are 3323 domestic legal hotels, 502 of which are star hotels equipped with better facilities and service qualities. Therefore, the performance of these hotels’ official websites and their SEO performance in search engines will be worth exploring and discussing. The study aims to evaluate the performance on website and SEO of Taiwan star hotels with web metrics analysis. At present, 469 star hotels have their own official websites.The instruments used in the study include Alexa.com, Wayback Machine (WM) and Google Mobile-friendly (GMF) test. There are total 360, accounting for 78.68% star hotel official websites able to be analyzed by these instruments. Analysis was carried out by using descriptive statistics, t-test for independent samples, one way ANOVA, regression analysis. The results indicated that the website performances of star hotels in Taiwan generally underperform. The webistes of hotels with more stars have better SEO performance. Different hotel background variables (star rating, size, category, chain) and website background variables (mobile-friendly, external link, Google business listing ownership) have significance difference on the performance of the websites. Different hotel background (star rating, region, size, category, chain) variables and website background (mobile-friendly, website age, external link, Google business listing ownership) variables have significance difference on SEO performance of the websites. Time on site and bounce rate positively affect the optimal performance of search engine.