THE ANALYSIS AND DESIGN OF A C2C TRAVEL MATCHING SYSTEM

ABSTRACT

               In recent years, the quantity of world tourism increases quickly According to the latest United Nation World Tourism Organization (UNWTO) World Tourism Barometer, the number of international tourist arrival grew by 4% in the first half of 2015 compared to the same period of 2014 Traditionally, there are two ways to travel: joining a tour package or being a backpacker The former only has a few options, with everything organized by travel agents, who provide different packages to choose In this method, customized travel is highly unlikely The latter, on the other hand, is fully personalize It requires lots of before-travel effort, so that tourists can find related information and make their own choices or combinations by referring to their preferences.

               As we all know, experiencing local culture is the true meaning of traveling The transformation of tourism demand expedites a new tourism mode so called in-depth travel However, none of the above methods provides deep understanding in local culture Therefore, we would like to offer another solution of travel by designing and providing a new platform and methodology In order to analyze and implement, our research uses technology acceptance model (TAM) to understand how the system should be designed and how our pilot users feel after using. To determine user’s acceptance before and after using our system, we choose perceived usefulness, perceived ease of use, attitude toward using and behavioral intention to use as four dimensions in our questionnaires’ major subject.

               Our platform system allows visitors to find a suitable “Local”, who is the city resident, with required skill that visitors are interested in and feasible language skill to communicate For example, if a Japanese visitor is going to Taiwan, and would like to visit the Japanese old buildings in Taipei, he or she can set their requirements to search for a Local The request user can personally communicate to every Local on the list in order to find a preferred one Every member in our system can be both visitor and Local It is a kind of C2C business concept and also combines the idea of Sharing Economy The idea is the Local knows their neighborhood the best, and human culture experience are the most valuable part in every city .

               The core tech and main contribution in our research is a new matching method To find the optimal results for visitors, users should fill in their requirements However, it’s annoying for users to go through so many steps, so we create our own unique algorithm to solve this problem. Furthermore, our system can record users’ experience, the longer they use, the more precise results they can get By using Android operate system, according to International Data Corporation (IDC), the biggest in market with share of 828% in 2015 Q2, our service can bring more convenience and meaning to travel. Consider of mobile device’s computing ability, all member and eigenvalue data will be stored in the cloud server In client part, we create an intuitive user interface based on the questionnaires’ results from TAM. After signing up and becoming our member, users can easily find nearby Local through Google Map And with only one click, qualifying results compiled by our own algorithm’s processing through the cloud server will be displayed on user’s mobile devices. The process is computed on our server, so the user’s devices can keep their battery status and computing ability. Once the list is compiled, the result is sent to user’s device. So the user can have the latest and the most suitable information in the short time. Then the user can personally “talk to” all the Local on the list one by one by sending a private message, until he or she find a preferred one Besides, in order to catch users’ interest and protect their personal safety, we involve the idea of gamification into our system Through ranking and evaluation for both sides of our users, visitors and Local can give their feedback as rating for each other after the whole trip or consultation And those results can be referred in next matching.

               Through our research and mobile application, we can create a unique and effective model in touring field. By using technology acceptance model as our questionnaires’ core, we realize users are satisfied with our system Combining C2C business concept and our own matching algorithm, traveling can be easier, more spontaneous and more meaningful to all tourists.