1、1The Empirical Study of Derivation Effect of Website Information FlowAbstract. Taking the information flow of website as a starting point， this thesis calculated the derivation effect of group of study-abroad and immigration to the group of VFR （visiting friends or relatives） by a quantitative metho
2、d. By improving the model of gravity and virtual distance， we put forward the new concept “derivation intensity”， calculated the derivation intensity. In order to test the feasibility of the model， we forecast the human flows in 2013-2015and draw an analogy with official forecast of the Australian G
3、overnment. The results show that they are accountable to a large extent. Key words： Information Flow of Website； Group of Visiting Friends/Relatives； Derivation Effect； Empirical Study 1. Introduction In recent years， geographers gradually get rid of the “the end of geography“ concerns brought by th
4、e information and communication technology developments， and instead， they tend to re-examine the background and geography research content changes， which makes geography schools development has 2entered a new phase. 2. Literature reviews Research on the intangible flow of informations guiding effec
5、t on tangible material flow guiding is increasingly concerned. Abroad， Graham and other authorities summarized the role played by information technology and the information industry in cities and regions into four effects， namely synergy effect， substitution effect， derivative effect and enhancement
6、 effect1， providing valuable references for our related studies； Moss analyzed information flow structure and spatial pattern of U.S. Internet infrastructure 2， Malecki studied the world internet infrastructure from the perspective of economic geography 3， and from the new ICTs geographic perspectiv
7、e， Adams took qualitative analysis of the Internets real effect of promoting Indian immigrants to the United States4. In China， Hong Zhen and other authorities carried out in-depth study on the information flow and transport-related theory5； Shimou Yao explained with the example analysis on the abov
8、e-mentioned synergies， the substitution effect， derivative effect and the enhancement effect6； Zhongwei Sun provided flow space background support for the basic properties such as convection space geography perspective 3study 7； especially Shifeng Wu took quantitative study of website information fl
9、ow on realistic flow of partial substitution effect and obtained important conclusions that information flow on the flow of the substitution effect and gradually increase with a lag through China Internet Network Development Statistics Report8. By reviewing the relevant literature， we find that most
10、 of the domestic research is still in the “dematerialization“ level and the external level such as research information technology， the Internet information and so on， lack of virtual space， geography and other internal aspects of cyberspace research. 3. The interpretation of the relevant concepts a
11、nd selection of study subject Briefly， information flow is the flow of information， and people flow is a peoples movement in real space. In this study， group of study-abroad and immigration understand study immigrant population， immigration， visa and other information through the Internet and succee
12、d to immigrate to Australia does not mean the end of information flow and pedestrian movement. They will continue to log in various virtual communities to exchange information in order to achieve the more information flow in the virtual space， which is called the flow of 4information derived from th
13、e information flow. The flow of information derived from the flow will bring about a corresponding flow， capital flow and other substances in the stream flow. Study object has the following properties. First， for the Australian Immigration （especially skilled migrants） crowd， they are generally in g
14、ood economic conditions， well educated， and in higher level of application of the Internet. Second， the connection way among immigration crowd and their relatives， friends， classmate is still Internet， and this proportion is much higher than other telephone communications medium. Third， it is partic
15、ularly the selection of the tourist crowds. We chose tourist crowds who travel to Australia to visit relatives and friends. On one hand， this is because they need to keep in touch and the Internet is commonly applied between them； on the other hand， the identity of tourist crowds shows that they are
16、 tourists， but more important is that “the purpose of visiting friends and relatives“ indicates their choice of travel destination has been largely affected by immigration populations. Based on this， we define tourist people “aiming at visiting relatives and friends“ as tourist crowds derived from t
17、he role of web site traffic. 54. The research process 4.1 The purpose of the problem By 2012， the average annual growth rate of international tourists in Australia was 6.2%， which is mainly accounted for 58% of the leisure crowd； followed by visiting friends population， accounting for 36%， which are
18、 the fastest growing tourist crowds. And in people aiming at visiting relatives and friends is most closely related to immigration crowds in Australia. Therefore， we separately analyze from the number of immigrants studying in Australia， the Australian tourism website visitor number and the number o
19、f people traveling abroad in Australia three factors effect on the flow of information. As the number of immigrants to study in Australia， the number of site visitors and the number of people traveling abroad in Australia have great differences in the figures， it is not easy to see its laws. Thus we
20、 select the rank to examine the relationship between them， in Table 1. From immigration from Australias top 10 crowds， Australia travel site visits to Australias top 10 and top tourists visiting friends 10， there are six countries which were in the top ten in these three terms. They are Japan， UK， U
21、SA， China， Hong Kong， and Singapore. Ranking relationship between 6the three indicates that the derived effect largely exists， but which not exactly corresponds to the three rankings. This is because： （1） the data not fully correspond to each other. Especially the “Australian tourist site traffic ra
22、nking“， this is just data from one of the travel Web site. The “visitors to Australia to visit relatives and friends ranking“ refers to the whole of Australia oversea visiting friends and relatives tourist market. （2） The relationship between them is complex. Because the generation of travel behavio
23、r and population displacement is the result of the combined effects of many factors， the impact of the flow of information is just one very important aspect. In addition， there are more important factors such as the actual distance， transportation accessibility， tourist income， leisure time， and fac
24、tors such as political relations between the two countries. Next， we get some of the data to calculate the crowd on Immigration in Australia for the purpose of visiting friends and relatives tourism crowd derivative action. 4.2 Review and establish of the research model This section is， in the joint
25、 action of virtual network and realistic geospatial， countries immigration crowds attracting of travelers visiting friends and relatives in the 7country， namely the strength of the derivative， referred derivative strength. Derivative intensity represents a crowd of peoples attracting to another， so
26、in essence they are all gravitating basic category. Therefore， in this study， we draw the gravity model， and put appropriate modifications and variations on it， aiming to quantify the research object. Gravity model or gravitational formula was first used by the British scientist Newton made in 1687，
27、 such as （1） formula. In this study， the gravity model of innovation lies in the application： the virtual distance in the model is used to calculate the derivative intensity. As the tourist groups are the results of both real geospatial and the virtual cyberspace， so we define the actual distance as
28、 r1， and define the virtual distance as r2. Therefore， （1） is transformed into： We believe that virtual distance r2 is influenced by two factors. First is the proportion of tourists who guided by the Internet， which is represented by P； the second is the proportion of tourists visiting friends of th
29、is part， which is represented by Q. Both factors have a direct proportional relationship with the virtual distance. And r2 is the denominator； therefore， the r2 is processed as follows， 8see （3） form. This study， with the influence of the website information flow， is on the crowd relationship betwee
30、n immigrant students and tourist groups of derived action， which is derived strength F. Therefore， the M1 and M2 in formulation （2） are respectively defined as the number of immigrants studying in Australia from New Zealand， Japan， UK， USA and China R1， and the number of people visiting friends and
31、relatives from New Zealand， Japan， UK， USA and China R 2. Among them， r1 is the actual distance from New Zealand， Japan， UK， USA， and China to Australia. In order to facilitate the conduct of research， we define interpersonal distance as the distance from the capitals of New Zealand， Japan， UK， USA，
32、 and China to Sydney， represented by S. The acquisition of the actual distance is calculated based on specific longitude and latitude in Wellington， Tokyo， London， Washington and Beijing with computer software （Table 4-5）. Therefore， the derivative strength formula used in this study is transformed
33、into formulation （4） ， as follows： 4.3 Data preparation and calculation We chose the seven years 2006-2012 as the research object data. These data includes the total number of tourism from New 9Zealand， Japan， UK， USA， China five countries to Australia， the total number of internet travel guides pro
34、portion and the ratio derived by the Internet and the number of persons and immigration， etc.， which are shown in Table 2 and Figure 1. It should be noted that： First， in order to facilitate the calculation， we dispose the actual distance from the capitals of New Zealand， Japan， UK， USA and China to
35、 Sydney. We define the actual distance from Wellington to Sydney as 1， and then make the actual distance from Tokyo， London， Washington and Beijing to Sydney Wellington divided by it， and the results are shown in Table 2. Table 2： The distance and process result of the capital of five countries to S
36、ydney （unit： km） Second， in data for individual years， the proportion of people visiting relatives and friends in Australia is not easy to obtain. But through the contrast ratio since 2004， in addition to a 2% change in the United States， the ratio of the other four countries has not changed. Theref
37、ore， according to research experience， the proportion of people visiting friends and relatives is stable， so the proportion in the calculation 10of the ratio is fixed. New Zealand： 28%， Japan： 5%， United Kingdom： 36%， USA： 22%， China： 12% （see Figure 1）. According to the improved gravity model formu
38、la （4） as well as the data in Table 3 we calculate derivative intensity of Australias major source countries for each year 2006-2012 （Table 4）. 4.4 Forecasting and inspection According to data of derived intensity calculation of New Zealand， Japan， UK， USA and China from 2006 to 2012， we use SPSS13.
39、0 software for regression analysis， and get fitted equation of derived strength， as the following： Fitted equation of derivative intensity of New Zealand Studying Immigration flow to their tourism flow visiting friends and relatives to Australia： Fitted equation of derivative intensity of Japanese S
40、tudying Immigration flow to their tourism flow visiting friends and relatives to Australia： Fitted equation of derivative intensity of British Studying Immigration flow to their tourism flow visiting friends and relatives to Australia： Fitted equation of derivative intensity of U.S. Studying Immigration flow to their tourism flow visiting friends and
