Study On The Virtual Value Chain Model Of Travel Agencies On The Background Of Big Data

By the innovative concept-driven of the Wisdom Tourism,Baidu Tourism Big Data and Big Data Marketing,travel agencies’business model is undergoing significant changes, and at the same time travel agencies’value chain is also changed. As a catalyst in the transformation of traditional travel value chain structure,and impetus of the travel agency products productivity,Big Data gradually become an important support plate in travel agency business development strategy. The combination of virtual value chain and physical value chain, makes it no longer only a part of traditional value chain extension, but also the core competitiveness and strategic value appreciation in the future travel value chain. In the era of Big Data,taking initiative action to integrate information technology in business,the traditional travel agency will usher in a new development opportunity. Whether leveraging big data to promote the optimization and upgrading of business models, fully excavating potential value in the process of business process and decision making, effectively saving the management cost, determines whether the traditional travel agency can achieve comparative advantage or not in the fierce market competition.The author thinks that, the travel agencies have entered the development stage of relying on big data-driven growth, and controlling of big data resource has become the core competitiveness of reshaping the travel agency strategic choice. Under this background,this paper can be divided into two parts, including5chapters.The first part, it expands travel agency virtual value chain theory which based on Big Data by combing the virtual value chain theory,then analyzes the characteristics and functions of the virtual value chain,and finally constructs the theoretical models and puts forward the corresponding theoretical assumptions. Specifically including domestic and foreign research about the value chain of travel agencies, information research of travel agencies and the application&development trend of big data (chapter1), tourism big data and related value chain theory (chapter2), characterized by data-driven type,data application processing as the core, realize the value activities of each link appreciation as the goal of the travel agency of virtual value chain theory, the theory hypothesis and model building (chapter3).The second part, on the basis of the theoretical hypothesis and model structure, it conducts empirical research about travel agents’ business value activities.Through dimension constructed,questions selected and scale designed&developed, it explores the virtual value chain structure of travel agents; it also uses SEM (Structural Equation Model) to analyses the relationship among the travel agents’virtual value, data purchase competence,route design competence,data marketing competence, tourists data management and data support activities, which aiming at revealing the the influence of big data in promoting the development of the travel agency business,(chapter4). Finally in this paper, the theoretical hypotheses, research conclusion and related follow-up questions are discussed(chapter5).The theoretical significance of this study include two aspects:one is that it has developed the big data contribution scale of virtual value chain of the travel agencies by following the scientific scale development of research program.The other one is that it has drawn the conclusion about the relationship among five value-added dimension and the virtual value chain of travel agencies by using EFA (Exploratory Factor Analysis) and SEM (Structural Equation Model),and it provides a certain theoretical basis for virtual value chain research of travel agencies.The practical significance of this study is that:the virtual value chain research based on the big data will help the operators to know the business model and key sectors of value-added from the perspective of big data,and it will provide a certain reference and guidance value for travel agents to achieve the transformation and upgrading key value chain optimization.