the empirical study of derivation effect of website information flow

1、<p>　　The Empirical Study of Derivation Effect of Website Information Flow</p><p>　　Abstract. Taking the information flow of website as a starting point， this thesis calculated the derivation effect of

2、group of study-abroad and immigration to the group of VFR （visiting friends or relatives） by a quantitative method. By improving the model of gravity and virtual distance， we put forward the new concept “derivation inten

3、sity”， 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 offici</p><p>　　Key words： Information Flow of Webs

4、ite； Group of Visiting Friends/Relatives； Derivation Effect； Empirical Study </p><p>　　1. Introduction </p><p>　　In recent years， geographers gradually get rid of the "the end of geography&

5、quot; concerns brought by the information and communication technology developments， and instead， they tend to re-examine the background and geography research content changes， which makes geography school's developm

6、ent has entered a new phase. </p><p>　　2. Literature reviews </p><p>　　Research on the intangible flow of information's guiding effect on tangible material flow guiding is increasingly conce

7、rned. 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

8、 effect and enhancement effect[1]， providing valuable references for our related studies； Moss analyzed information flow structure and spatial pattern of U.S. In</p><p>　　Briefly， information flow is the flo

9、w of information， and people flow is a people's movement in real space. In this study， group of study-abroad and immigration understand study immigrant population， immigration， visa and other information through the

10、Internet and succeed 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 m

11、ore information flow in the </p><p>　　Study object has the following properties. First， for the Australian Immigration （especially skilled migrants） crowd， they are generally in good economic conditions， wel

12、l 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

13、telephone communications medium. Third， it is particularly the selection of the tourist crowds. We chose touris</p><p>　　4. The research process </p><p>　　4.1 The purpose of the problem </p&g

14、t;<p>　　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

15、 36%， which are 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 i

16、mmigrants studying in Australia， the Australian tourism website visitor number </p><p>　　From immigration from Australia's top 10 crowds， Australia travel site visits to Australia's top 10 and top to

17、urists visiting friends 10， there are six countries which were in the top ten in these three terms. They are Japan， UK， USA， China， Hong Kong， and Singapore. Ranking relationship between the three indicates that the deri

18、ved 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 "Aust</p><p>　　4.2 Review and establi

19、sh of the research model </p><p>　　This section is， in the joint action of virtual network and realistic geospatial， countries immigration crowds' attracting of travelers visiting friends and relatives i

20、n the country， namely the strength of the derivative， referred derivative strength. </p><p>　　Derivative intensity represents a crowd of people's attracting to another， so in essence they are all gravita

21、ting 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 u

22、sed by the British scientist Newton made in 1687， such as （1） formula. </p><p>　　In this study， the gravity model of innovation lies in the application： the virtual distance in the model is used to calculate

23、 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 r1， and define the virtual distance as r2. Therefore， （1） is transf

24、ormed 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 </p><p>　　This study， with the influence of the websi

25、te information flow， is on the crowd relationship between 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

26、number of immigrants studying in Australia from New Zealand， Japan， UK， USA and China ―R1， and the number of people visiting friends and relatives from New Zealand， Japan， UK， USA and China ― R 2. Among them， r1 is the a

27、ctual distance fr</p><p>　　4.3 Data preparation and calculation </p><p>　　We chose the seven years 2006-2012 as the research object data. These data includes the total number of tourism from New

28、 Zealand， Japan， UK， USA， China five countries to Australia， the total number of internet travel guides proportion and the ratio derived by the Internet and the number of persons and immigration， etc.， which are shown in

29、 Table 2 and Figure 1. It should be noted that： </p><p>　　First， in order to facilitate the calculation， we dispose the actual distance from the capitals of New Zealand， Japan， UK， USA and China to Sydney. W

30、e 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. </p&g

31、t;<p>　　Table 2： The distance and process result of the capital of five countries to Sydney </p><p>　?。╱nit： km） </p><p>　　Second， in data for individual years， the proportion of people v

32、isiting 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. Therefo

33、re， according to research experience， the proportion of people visiting friends and relatives is stable， so the proportion in the calculation of the ratio is fixed. New Zealand： 28%， Japan： 5%， United Kingdom： 36%， U<

34、/p><p>　　4.4 Forecasting and inspection </p><p>　　According to data of derived intensity calculation of New Zealand， Japan， UK， USA and China from 2006 to 2012， we use SPSS13.0 software for regress

35、ion analysis， and get fitted equation of derived strength， as the following： </p><p>　　Fitted equation of derivative intensity of New Zealand Studying Immigration flow to their tourism flow visiting friends

36、and relatives to Australia： </p><p>　　Fitted equation of derivative intensity of Japanese Studying Immigration flow to their tourism flow visiting friends and relatives to Australia： </p><p>　　F

37、itted equation of derivative intensity of British Studying Immigration flow to their tourism flow visiting friends and relatives to Australia： </p><p>　　Fitted equation of derivative intensity of U.S. Studyi

38、ng Immigration flow to their tourism flow visiting friends and relatives to Australia： </p><p>　　Fitted equation of derivative intensity of Chinese Studying Immigration flow to their tourism flow visiting fr

39、iends and relatives to Australia： </p><p>　　In order to verify the reasonableness of the proposed concept derived strength and the strength derived fitted equation or whether it can be applied in a wider ran

40、ge， we tested the equation. </p><p>　　Specific methods are as follows： First， make use of data derived strength obtained by fitting regression equation of the seven countries on 2006-2012 to predict the next

41、 three years （2013-2015） derivative intensity changes of New Zealand， Japan， UK， USA， China immigration flow stream to their respective countries to travel to Australia （see Table 6）. Second， according to part of the dat

42、a of the future population projections published by Australian Travel Network in April 2012， we calculate visit</p><p>　　5. Results </p><p>　　5.1 Although with the question of the flow of inform

43、ation on the site and immigration crowd， derivative action is there， but due to the other factors， derivative intensity manifested by different countries is different. Particularly， distance as a factor in the reality st

44、ill exists and plays an important role. </p><p>　　5.2 Research of derived strength and forecasts of population of people visiting friends and relatives in Australia official tourism is largely consistent. 　

45、　The specification is as follows： ① Table 6， derived intensity projections on the Japanese in next three years small amplitude rises （0.67 to 0.70）， or essentially the same （0.70 to 0.71）， according to the Australian Tou

46、rism Forecasting Committee data （Table 7 ）， the increase rate of tourists to Australia visiting relatives and friends in th</p><p>　　5.3 Discussion about derived intensity changes and travel flow rate change

47、s to Australia </p><p>　　From Table 6 and Table 7， it can be seen derived strength in New Zealand is increased rapidly， about 30； but the growth rate of people from New Zealand to Australia to visit relative

48、s and friends is very small （about 1%）. This is mainly due to the large base of New Zealand visitors to Australia. Meanwhile， China's derived strength grows slowly， while the growth rate of Australia to visit relativ

49、es and friends is great （greater than 10%）， which is due to the small base of Chinese tourists. </p><p>　　6. Description of Source </p><p>　　This study has the following two main sources of info

50、rmation. The first part is gathered from the relevant data provided by the Chinese Ministry of Education， Australian Department of Immigration and Multicultural and Indigenous Affairs and the Australian Bureau of Statist

51、ics. The second part is mainly based on the data of the Australian tourism research network， which is survey of international tourists conducted by ACNielsen Research on behalf of TRA， which is taken one time per year. T

52、he rese</p><p>　　This article was financially supported by the Hainan Provincial Department of Education Scientific Research Project funded by National Backbone Vocational College Construction （Grant NO. Hjs

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