評估歐洲城市旅游的意義外文翻譯

1、<p><b>　　中文3168字</b></p><p><b>　　2154單詞</b></p><p>　　本科畢業(yè)論文外文翻譯</p><p>　　外文題目：Assessing the Significance of City Tourism in Europe </p><p>

2、　　出 處：2010， Analysing International City Tourism， Part 2， Pages 43-58 </p><p>　　作 者：Ulrike Bauernfeind， Irem Arsal， Florian Aubke and Karl Wöber </p><p>　　1. Purpose and objective&l

3、t;/p><p>　　This chapter continues the focus on city tourism, by assessing the signi?cance of city tourism in Europe compared to European tourism overall. In doing so, the focus is not only on the current situat

4、ion but also on possible future developments, thus the chapter follows two distinct objectives. Firstly, to provide a comprehensive analysis of the role city tourism played in Europe in past and present, and secondly, to

5、 provide some outlook into the future development of European city tourism. In pa</p><p>　　2. Introduction</p><p>　　The popular voice often states that tourism is a signi?cant – if not the most

6、signi?cant –industry sector for most European countries, in addition city tourism is often viewed as a major contributor. For example, a study com-missioned by the German Federal Ministry of Economics and Technology view

7、ed city tourism as the largest growth sector for the past 10 years with a growth rate of more than 40 % (German Federal Ministry of Economics and Technology, 2006). Although city tourism is certainly es</p><p&

8、gt;　　The previous chapters introduced some more generic concepts and sources of city tourism statistics and TourMIS as a marketing information system. This chapter builds on the previous, and thus readers are encouraged

9、to review the challenges of compiling and using city tourism statistics. The rationale behind measuring the signi?cance of city tourism in Europe is mainly to critically question the popular voice stated above. </p>

10、;<p>　　The remainder of the chapter is organized as follows: First, the sources of data for the current analysis are described, and the methods of data compilation and cleaning are outlined. Then, the status quo o

11、f European city tourism is portrayed, ?rstly on an aggregated level, then with a focus on the top 20 city destinations in Europe. Before the share of European city tourism is forecasted until 2020, most commonly applied

12、forecasting methods are introduced and their appropriateness is determined</p><p>　　3.European city tourism compared to overall tourism – the status quo</p><p>　　City tourism is often seen as a

13、signi?cant or even major part of overall European tourism. Some indication of volume and direction of travel ?ows in European city tourism exists, yet the scope and impact remains largely un-known. There is little doubt

14、that a high percentage of tourism volume and a much higher percentage of European business and professional travel volume were absorbed by European metropolises; however, these assumptions have not yet been empirically c

15、on?rmed. This chapter demons</p><p>　　European tourism overall increased by 76 % from 231.6 million arrivals in 1988 to 407 million in 2002. Although development of city tourism was similarly favourable in t

16、his time period (85 million arrivals in 1988 and 137 million in 2002) the rise in demand was only 61 %, thus signi?cantly lower than for tourism overall (see city tourism share in Figure ). In 2002, 379 cities generated

17、137 million arrivals which accounts for 33.5 % of overall tourism in Europe.</p><p>　　City tourism traditionally experiences shorter length of stays than other forms of tourism, which is illustrated in Figur

18、e 2 (3.4 days in cities whereas 5.8 days in overall Europe in the year 2002). The average duration of stay decreased from 1988 until 2002. The average length of stay dropped from 6.3 in 1988 to 5.8 in 2002 when looking a

19、t tourism in Europe overall. The average duration of city trips has decreased by 0.2 days (from 3.6 days in 1988 to 3.4 days in 2002). </p><p>　　For the more recent years until 2006, the data for this large

20、sample of almost 400 cities is not yet available. Therefore, a smaller sample was analyzed with a focus on recent developments of tourism bed nights in the respective destinations. Bed night data compiled by the Eurostat

21、, the European Cities Marketing (ECM) and statistics available on TourMIS were used to compare the changes in the performance of European city tourism to European tourism in general for the time period 1990 until 2006.&l

22、t;/p><p>　　The outcome is shown in Figure 3 which illus- Figure 3 which illus- 3 which illustrates the changes in the performances of one year compared to the previous year. The country peak in 2000 was mainly

23、due to major bed night increases in Spain and Italy. Figure 3 also demonstrates how different the city and country performance may be from each other. </p><p>　　Next, the top 20 European urban destinations a

24、re investigated. The TourMIS data entered by the cities themselves or provided by the ECM served as the data basis for a further comparison between the development of the top 20 and the other 67 cities included in the To

25、urMIS sample.</p><p>　　4. Development of the top 20 European tourism cities</p><p>　　First, the arrivals data from 2006 are compared to the bed night data from the same year for the top 20 citie

26、s and comparatively ranked. London, Paris and Rome lead the table in both measures, bed nights and total arrivals, yet the further down in the ranking one goes, differences become apparent e. g. Dublin is better performi

27、ng when looking at the bed nights, the same is true for Prague or Budapest. Remark-able in total numbers is London, accounting for more than triple the bed nights of Paris</p><p>　　When the performance of th

28、e 67 cities sample is compared to the top 20 European city destinations (Figure 4), the trend is very similar. City tourism had increased, but experienced a decline in 2001 and 2002, possibly due to September 11. The oth

29、er earlier decline in 1991 may have certainly been caused by the Gulf crisis. Another remarkable observation is that it seems that the gap between the two samples seems to grow, suggesting the city tourism destinations’

30、overall sample is registering slig</p><p>　　5. Forecasting European City Tourism</p><p>　　The objective of this chapter is not to convey the fundamentals of statistical forecasting; instead we r

31、efer the reader to the seminal work on statistical forecasting in tourism “Forecasting Tourism Demand, Methods and Strategies” by Douglas C. Frechtling for a refresher. Nonetheless, in order to provide a logical entry in

32、to the chain of arguments made in this chapter, a brief overview of purpose and practices of forecasting tourism demand is made.</p><p>　　Forecasting is an attempt to foresee the future by examining the past

33、. Naturally, historical data is the basis for forecasting, yet what distinguishes a forecast from a mere manipulation of numerical functions is a judgmental component. Any quality forecast, however, is derived in an obje

34、ctive and systematic fashion and combines objective data with subjective guesses and hunches of the analyst. Forecasts are generally classi?ed into two general categories, qualitative and quantitative forecastin</p>

35、;<p>　　Qualitative methods are based on individuals’ judgements e. g. the often used and widely known Delphi method relies on experts’ opinions as data basis. The World Tourism Organisation uses in its UNWTO World

36、 Tourism Barometer a panel of tourism experts not only for rating current performances but also for giving opinions on future developments. The qualitative method of the jury of expert opinions relies on experts meeting

37、and reaching consensus on a certain forecasting question (Frechtling, 2001</p><p>　　The combination of objective and subjective forecasting methods goes in line with the view that a mere extension of histori

38、cal data into the future alone does not yet constitute forecasting, but that a judgmental component is necessary to create meaningful and worthwhile forecasts. A preference for combined forecasting methods (i. e. improve

39、d forecasting accuracy) is repeatedly expressed in the literature (Song and Li, 2008). In this chapter, the focus lies on assessing the signi?cance of city t</p><p>　　As for the quantitative forecasting meth

40、ods, one commonly distinguishes between time series, or extrapolative methods and causal methods. Causal methods establish a cause-and-effect relationship by identifying the explanatory variable and building a mathematic

41、al expression that explains the effect on the forecast variable. For example, tourism managers who consider expanding the transport network to a city may wish to ?rst establish a causal relationship between transport opt

42、ions to the city and</p><p>　　As far as the forecasting methods are concerned there is no common conclusion in the research community on which models are optimal in which situations, not even on whether to u

43、se complex models or just stick to naïve models and exponential smoothing (Frechtling, 1996). In practice, the problems faced by tourism managers are so complex that simple heuristics are applied, following the phil

44、osophy of rather being ‘a(chǎn)pproximately right’ than being ‘precisely wrong’. In general, the concept of parsim</p><p>　　6.Conclusions</p><p>　　Tourism, as one of the most important industry sector

45、s in Europe, is the focus of many research endeavours. However, the scope and importance of city tourism has hardly been researched empirically. A reason might be that when trying to assess the signi?cance of city touris

46、m, several dif?culties, such as data availability or comparability, appear. In an attempt to assess the signi?cance of city tourism in Europe, data for almost 400 European cities with a population of at least 100,000 was

47、 collec</p><p>　　Future studies could try to ?nd out whether this will be true solely for European city tourism or if this negative prediction applies to city tourism around the world. Furthermore, future re

48、search could concentrate on particular cities to ?nd out which urban destinations will lose their signi?cance to be able to implement counter-actions.</p><p><b>　　譯 文：</b></p><p>　

49、　評估歐洲城市旅游的意義</p><p><b>　　目標和宗旨</b></p><p>　　本章通過對城市旅游發(fā)展的重點，評估歐洲的城市旅游，以及歐洲旅游的整體意義。這樣做，不僅是對當前局勢，而且也是對未來可能的發(fā)展，做出分析。因此本章以下兩個不同的目標。第一，要提供有關在歐洲重要城市在過去和現(xiàn)在的旅游資源綜合分析，第二，提供一些歐洲城市旅游的未來發(fā)展前景。特別是，

50、本章試圖提供一個的問題：關于過去和現(xiàn)在的經(jīng)驗基礎上，如何對待城市旅游在未來的發(fā)展？為此，運用了一些常見的預測方法，并對城市旅游的預測進行了分析。在本章的最后，讀者應當對以下幾方面有一個正確的理解，a) 歐洲城市旅游數(shù)據(jù)，b）一般預測方法及其應用的適宜性，c）歐洲旅游城市與整體旅游。</p><p><b>　　簡介</b></p><p>　　在大多數(shù)歐洲國家中，旅游

51、業(yè)往往是一個重要的部門，城市旅游經(jīng)常被視為城市經(jīng)濟發(fā)展的一個主要因素。例如，德國聯(lián)邦經(jīng)濟與技術部通過過去10年，城市旅游業(yè)作為最大的生長部門增長率超過40％（德國聯(lián)邦經(jīng)濟與技術部，2006年）。年增長速度最大的是城市旅游部門。盡管城市旅游對整個歐洲都很重要，對旅游業(yè)有重大貢獻，但對城市旅游的歐洲總量和比較整體旅游幾乎沒有任何研究報告（霍爾2003年；范登貝爾赫，凡得博格，馮德爾米爾，1995年）。</p><p>

52、;　　前面的章節(jié)介紹了一些比較通用的概念和城市旅游統(tǒng)計和旅游作為營銷信息系統(tǒng)。本章是建立在之前的，因此我們鼓勵讀者審查編制和使用城市旅游統(tǒng)計。理解歐洲旅游城市基本原理的重要性，主要是為了批判傳統(tǒng)意義上的聲音。本章的其余部分組織如下：首先，當前的分析數(shù)據(jù)的來源進行了描述，并匯編數(shù)據(jù)和整理方法進行了概述。然后，描繪城市旅游在歐洲的現(xiàn)狀和地位，然后在同一水平上的，用最頂尖的20個歐洲城市最比較。用最常見的預測方法進行了介紹和應用適合性測定歐洲

53、城市旅游的份額預計到2020年。本章分析了歐洲城市旅游的未來前景，包括目前的經(jīng)濟危機這一個因素。</p><p>　　歐洲城市旅游與整體旅游現(xiàn)狀相比</p><p>　　城市旅游往往被視為歐洲整體旅游的一個部分，甚至是重要組成部分。一些旅行社的數(shù)量和流量，在范圍和影響在很大程度上仍然不能體現(xiàn)歐洲城市旅游。毫無疑問，大部分旅游和更大比例的歐洲商業(yè)和專業(yè)旅行被歐洲大都市吸收。但是，這些假設還沒

54、有被經(jīng)驗證實。本章演示了歐洲城市旅游的意義，用的數(shù)據(jù)來自379個城市，時間為從1998年至2002年。此外，還有67個歐洲城市在1991至2006年期間的數(shù)據(jù)。 另外前20名城市與其他67個目城市的也做了比較。</p><p>　　1988年至2002年，歐洲旅游整體提高了76％，231.6百萬的游客創(chuàng)造了4.07億美元。雖然城市旅游在1988年和2002年這個時間段得到了85萬人次的發(fā)展，然而需求只有61％的增

55、加，從而明顯高于旅游整體。2002年，379個城市產(chǎn)生了占整體旅游33.5％的1.37億游客。</p><p>　　城市旅游比傳統(tǒng)旅游住宿天數(shù)短，這是圖2所示（城市旅游為3.4天，而在整體旅游則為5.8天，2002年）。平均逗留時間從1988年至2002年下降。平均住宿時間在1988年的6.3下降到2002年的5.8時，在整個歐洲旅游中。在城市旅行時間平均減少了0.2天（從1988年3.6天至3.4天，2002年

56、）。</p><p>　　比較2006年前的最近的年，幾乎 400個城市的數(shù)據(jù)在這個大樣品還沒記錄。因此，在小樣本中，對旅游業(yè)最新的留宿發(fā)展成為各個城市的主要目標。留宿也的數(shù)據(jù)統(tǒng)計由歐盟統(tǒng)計局和歐洲城市市場編制而成的旅游數(shù)據(jù)系統(tǒng)，它反應了從1990年到2006年間歐洲城市旅游的現(xiàn)象。國內(nèi)外旅游研究者使用這個67 個城市和32個國家（歐盟27個成員國以及其他五個國家，例如瑞士，挪威，克羅地亞，列支敦士登和冰島）的樣

57、本。</p><p>　　如圖3表示，一年比前一年表現(xiàn)的變化。到2000年到達高峰，主要是由于西班牙和意大利的游客留宿增加。圖3還演示了在不同的國家城市旅游之間的不同。</p><p>　　接下來，對20個歐洲城市做一個目的地調(diào)查。這20個城市的確定是根據(jù)旅游數(shù)據(jù)中67個城市中的最有代表性的城市。</p><p>　　發(fā)展前20的歐洲旅游城市</p>

58、<p>　　首先，到2006年的數(shù)據(jù)中排名最高的20個城市。倫敦，巴黎和羅馬名列前茅，其中留宿游客占入境旅客的比重比往年稍有下降。如果只看留宿數(shù)量，柏林的數(shù)據(jù)是最好的，與之相同是布拉格和布達佩斯。注釋1中顯示倫敦的留宿數(shù)量是巴黎的3倍，這在歐洲城市旅游非官方統(tǒng)計中的數(shù)據(jù)。</p><p>　　當這67個城市數(shù)據(jù)與排名最高的20個城市最比較，情況非常相似。城市旅游在2001和2002的得到增加，但是中間經(jīng)

59、歷了一個發(fā)展的低谷，最低點是9月11日。另一個歷史最低點是1991年，那時由于當年的波斯灣危機所引起的。另一個值得注意的現(xiàn)象是，兩個樣本之間的差距似乎在逐漸拉大，這表明城市旅游的總體樣本比排名前20的城市的發(fā)展快。但是，排名前20的城市的旅游留宿量仍占總城市的67%-86%。</p><p>　　五、歐洲城市旅游預測</p><p>　　本章的目的并不是要傳達的統(tǒng)計預測的基礎，而是我們?yōu)樽x

60、者的旅游統(tǒng)計的開創(chuàng)性工作的而作的旅游需求預測，方法和戰(zhàn)略的復習。簡要概述提出的論點和做法，預測旅游需求，作出合乎邏輯的條目。</p><p>　　預測是嘗試通過審查過去預見未來。自然，歷史數(shù)據(jù)是為預測的依據(jù)，從單純的數(shù)值函數(shù)來看，預測是一個判斷的組成部分。任何質量預報，是源于客觀和系統(tǒng)的方式，并結合主觀猜測和預感的客觀數(shù)據(jù)分析。預測一般分為兩大類，定性和定量預測。這兩者的結合被稱為“政策制定的預測” (蔡1984

61、年)。</p><p>　　定性方法是基于個人的判斷的，例如德爾菲法把專家的意見作為數(shù)據(jù)依據(jù)。世界旅游組織在它的世界旅游晴雨表中，不僅規(guī)定當前表現(xiàn)，也發(fā)表了未來的發(fā)展意見。對專家意見的陪審團定性方法依賴于專家會議，并達成一定的預報問題（弗雷希特林，2001年，第213頁）的共識。其他方法就是消費者的消費意向調(diào)查，詢問他們是否有計劃前往（弗雷希特林，2001年，第227頁）。</p><p>

62、;　　客觀和主觀預測相結合的方法認為，歷史數(shù)據(jù)僅僅擴展到未來尚不構成單獨的預測，而是一種判斷組件是要創(chuàng)造有意義和有價值的預測。一種組合預測方法的優(yōu)先考慮（即提高預報準確度），這一再被用文獻（宋，李，2008年）表示。在這一章中，重點在于評估城市旅游的意義，因此，決策的研究部分是相對較小。最后，本章將重點放在定量預測方法并留下主觀解釋給讀者。</p><p>　　至于定量預測方法，一種常用的方法是分析時間序列之間的

63、區(qū)別，或外推法和因果方法。通過識別方法建立因果解釋變量，建立一個數(shù)學表達式，解釋了對預測變量的影響的原因和結果的關系。例如，旅游經(jīng)理考慮擴大運輸網(wǎng)絡，不妨以一個城市先建立城市的交通選擇和旅客人數(shù)的因果關系。一旦這樣的因果關系成立后，決策者可以通過預測旅客總數(shù)來調(diào)整運輸變量。另一種是外推法，不注重外部變量的預測能力，而是利用歷史資料，繪制未來的目標圖片。</p><p>　　就預測方法而言，沒有哪一種方法是在最佳的

64、研究模型。其中不管是使用復雜的模型或只是使用平滑模型（弗雷希特林，1996年）。然而在實踐中，旅游管理人員所面臨的問題非常復雜，簡單的啟發(fā)被應用是“大約權利”，而不是“精確的錯誤”。在一般情況下，簡約的概念盛行，這意味著最簡單的模式可能具有最佳預測能力（尼可洛普洛斯，古德溫，帕特里斯和埃斯馬克波羅，2007年）。因此，預測準確度被認為是決定最終依據(jù)，預測方法是能被應用的。</p><p><b>　　六

65、、結論</b></p><p>　　旅游業(yè)作為歐洲最重要的產(chǎn)業(yè)部門之一，是許多研究工作的重點。然而，在城市旅游研究方面，幾乎沒有涉及。一個原因可能是，當試圖去評估城市旅游時，遇到一些困難，如數(shù)據(jù)的可用性或可比性，意義，法律性。其次是試圖評估在歐洲旅游城市的意義。幾乎400個至少10萬人口的歐洲城市的數(shù)據(jù)的收集時間是1998-2002年。通過這些數(shù)字，其目的是采用不同的預測方法，能夠給城市在歐洲旅游方面

66、的預測。雖然聯(lián)合國世界旅游組織公布了大陸上的平均水平，但是這對歐洲城市旅游的預測是沒有用的。這項研究是為了填補這一空白。當您通過一個近15年（1988-2002年）的樣本時間內(nèi)和未來18年的預測，可以看來，城市旅游的份額在下降。雖然在1988年，城市旅游的份額有36.4％，但是到2020年大概會減少10%，只剩26.9％的份額。</p><p>　　如果對歐洲城市旅游未來的研究預測是正確的，那么它同樣適用于世界各