隨著企業對企業(B2B)、企業對消費者(B2C)電子商務技術的成熟,加上愈來愈多的企業進行內部流程電子化、合理化,為各產業中的企業間資訊流動及合作、競爭模式開啟了新貌。產業電子化之興起促使產業界建立新的營運模式,使價值鏈中各成員緊密連結,以提昇產業整體競爭力。 台灣旅遊產業亦於電子商務熱潮中受到不小的衝擊,面臨新通路中更透明、快速的資訊傳遞,及更多的潛在競爭者,再加上近年來的大環境不景氣,消費市場萎縮,更加重了業者經營上的壓力。因此,能夠讓體系整體競爭力提昇的產業電子化,就成為各體系價值鏈眼中的明日之星。不過由於旅遊業先天上的產業性質特殊,導入方法似乎不如製造業或半導體業等產業般明確。 本研究以國內旅遊業之各級旅行社為研究對象,期望建構「產業電子化能力評估模式」以研究旅行業在導入產業電子化時應衡量的關鍵能力指標及國內旅行社的電子化能力表現。在經過因素分析後得到六項基本因素構面,分別為:「交易電子化及資訊分享」、「對新電子商務模式的接受程度」、「產品及資訊提供」、「企業環境狀況」、「顧客導向程度」、「資訊基礎設施狀況」。 藉由六項構面指標對樣本旅行社進行群集分析及多重比較後,本研究得出五大類型,分別命名為「保守型」、「消極型」、「觀望型」、「嘗試導入型」及「高度發展型」。最後針對專家及領導廠商訪談得出旅行業產業電子化應具備能力,並對各類型旅行社進行比較及建議。
After the maturity of e-commerce technology (B2B,B2C) and more corporations begin process reengineering, the information flow, cooperation and competition models between companies lead into new confines. The evaluation of Electronic Business (e-business) urges the industries to redefine the business models, making members in supply chain to cooperate more closely, and improve the competence of whole industry. Travel agents in Taiwan face a great compact of electronic commerce because of more transparent and faster information transformation in new channels, new competitors and depression influence. E-business which can improve industry competence then become a hot topic. But the travel service have some special properties cause the implement method is not as sure as other industries like manufacturing industry and semiconductor industry. This study chose “travel agents in Taiwan” as our object of research. We tried to establish a “e-readiness measurement model” to research key competencies that should be measured before implementing e-business and how travel agents perform on these key competencies. Through the method of factor analysis, six factors were extracted. The factors are “level of e-business and information sharing”, ”adoption of new e-commerce models”, ”supply of production and information”, ”business environment”, ”level of customize” and “information infrastructure”. After getting these factors, we processed cluster analysis. Using six factors as input variables generated five clusters. There were “conservative”, “negative”, “wait and see”, “trier” and “highly developer”. Finally we generalize the required level of every factor through interviews with experts and leader quadrant, making compare and suggestions for every cluster of travel agents.