Content uploaded by Yang Yang
Author content
All content in this area was uploaded by Yang Yang on Nov 05, 2014
Content may be subject to copyright.
Chinese Geographical Science 2007 17(2) 173–178
DOI: 10.1007/s11769-007-0173-2
www.springerlink.com
Shift-share Analysis on International Tourism Competitiveness
—A Case of Jiangsu Province
SHI Chunyun1, 2, ZHANG Jie1, YANG Yang3, ZHOU Zhang4
(1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;
2. School of Urban and Environmental Sciences, Xuzhou Normal University, Xuzhou 221116, China;
3. Center for Recreation and Tourism Research, Peking University, Beijing 100871, China;
4. Jiangsu Tourism Administration, Nanjing 210003, China)
Abstract: Shift-share analysis has been confirmed a useful approach in the study of regional economics and many kinds
of extended shift-share models have been advanced and put into practice in economic studies, but few have hitherto been
introduced and applied to the tourism research in China. Moreover understanding the spatially competitive relationship is
of paramount importance for marketers, developers, and planners involved in tourism strategy development. Based on
international tourism receipts from 1995 to 2004, this study aims at probing into the spatial competitiveness of interna-
tional tourism in Jiangsu Province in comparison with its neighbors by applying a spatially extended shift-share model
and a modified dynamic shift-share model. The empirical results illustrate that exceptional years may exist in the ap-
plication of dynamic shift-share models. To solve this issue, modifications to dynamic shift-share model are put forward.
The analytical results are not only presented but also explained by the comparison of background conditions of tourism
development between Jiangsu and its key competitors. The conclusions can be drawn that the growth of international
tourism receipts in Jiangsu mainly attributes to the national component and the competitive component and Zhejiang is
the most important rival to Jiangsu during the period of 1995–2004. In order to upgrade the tourism competitiveness, it is
indispensable for Jiangsu to take proper positioning, promoting and marketing strategies and to cooperate and integrate
with its main rivals.
Keywords: international tourism competitiveness; spatially extended shift-share analysis model; comparative static
shift-share analysis; modified dynamic shift-share analysis; Jiangsu Province
1 Introduction
The original formulation of shift-share method was first
advanced by Creamer (1943) and then was summarized
and induced by Dunn (1960). Shift-share analysis has
generally been used for describing regional and industrial
economic growth and examining the structural effect and
regional or industrial competitiveness underlining the
changes. It has been a very powerful tool for measuring
the changes over time in regional economics, marketing,
urban studies, etc. Stevens and Moore (1980) put forward
that the factor to account for its popularity is the techni-
cally simple procedure. Shift-share analysis requires only
less data that are generally accessible. Despite its sim-
plicity, it does well in capturing the underlining changes
in the variables under consideration (Nazara and Hew-
ings, 2004) and making the analysis fast and reasonably
accurate.
Shift-share analysis has just been applied to tourism
industry in recent years (Sirakaya et al., 1995; Fuchs et
al., 2000; Alavi and Yasin, 2000; Sirakaya et al., 2002;
Toh et al., 2001; 2003; 2004; Yasin et al., 2004). Em-
ployment, arrivals and receipts are usually used as vari-
ables to measure changes in the shift-share models (Shi et
al., 2007). Only in recent years have a few studies using
shift-share analysis focused on sectoral structure and
competitiveness within tourism industry in China (Yang
et al., 2005; Wen and Wang, 2005; Chu, 2005; Li and
Cheng, 2004; Wang et al., 2004). Moreover, although
many kinds of extended shift-share models have been
Received date: 2006-06-25; accepted date: 2007-03-18
Foundation item: Under the auspices of the National Natural Science Foundation of China (No. 40371030)
Biography: SHI Chunyun. E-mail: shichunyun@163.com
SHI Chunyun, ZHANG Jie, YANG Yang et al.
174
advanced, the application of the models to tourism re-
search in China mainly limits to the comparative static
model of shift-share analysis. Thus this study aimed at
applying both spatially extended shift-share analytical
approach and modified dynamic model to tourism spatial
competitiveness of Jiangsu Province based on interna-
tional tourism receipts from 1995 to 2004.
2 Methodology
2.1 Comparative static model and its extended models
Traditional shift-share analysis is used to decompose
regional growth over time into three effects: the national
growth effect, the industry-mixed effect, and the com-
petitive effect, which is generally applied in a study pe-
riod of several years and examines conditions only at the
beginning and the end years. In such a comparative static
approach, the subtle swings during the study periods
were lost (Sirakaya et al., 1995). The inherent limitations
of this comparative static method, however, can be
overcome by calculating the shift-share effects on a
multiple-year data on the basis of creating dynamic,
time-series-like data (Sirakaya et al., 2002). The dynamic
shift-share analysis is an extension of Thirlwall’s (1967)
suggestion that the study period be divided into two or
more sub-periods to reduce the severity of the changes. It
provides a more accurate allocation of changes to cal-
culate the national growth effect, the industry-mixed
effect, and the competitive effect on an annual basis and
then sum the results over the study period. One of the key
advantages of this dynamic shift-share analysis is that it
enables changes to be tracked over the years without
losing information in those periods and allows unusual
years and years of economic transition to be identified
(Sirakaya et al., 2002).
The current decomposition posits a strictly hierarchi-
cal view of influence—the nation influences the regions,
but regions do not influence each other. However, the
general idea is that the decomposed effects are not spa-
tially independent, and the performance of surrounding
regions, of regions with similar structures, or of regions
that are dominant trading partners will all have an in-
fluence on the growth performance of a particular region
(Nazara and Hewings, 2004). Here an extended
shift-share model newly put forward by Nazara and
Hewings should be emphasized on for the further study.
They first incorporate spatial structure within shift-share
analysis, to take interregional interaction into account in
the decomposition analysis. Given the relatively recent
conceptualization of such an extended model, it is not
surprising that the approach is needed to be tested em-
pirically.
2.2 Methods in this study
Nazara-Hewings’ extended industrial model of the
shift-share formulation can be represented into three
distinct effects as Equation (1).
''
()()
ii ii ii
g
GgG gg=+ − + − (1)
where gi denotes the actual growth of international tour-
ism receipts in the study region, i
g
′, that in the
neighboring regions, i
G denotes the national counterpart,
and i, the peculiar sector, i.e. international tourism re-
ceipts in the study. Here, Jiangsu Province is the study
unit while its neighboring regions are used as benchmark
areas. Compared with the traditional shift-share analysis,
Equation (1) reflects two changes. First, only sectoral
growth over time is measured here, which can be called
purely industrial model. Nazara-Hewings’ extended
model offers varied forms so that appropriate form may
be selected in terms of the study’s requirement. Second,
besides the whole nation and peculiar area, neighboring
region is included here, which can reflect how the
study unit interacts with its neighbor and which region
is on earth the most important competitor to the study
unit.
Figure 1 denotes the formulation and explanation of
shift-share analysis in this study, where 0,
j
R0,
G
R0
g
R
represent international tourism receipts of neighbor-
ing region, nation and the study region at the beginning
year respectively, while ,
tj
R,
t
G
Rt
g
Rdenote the am-
ount at the end of the period. Actual growth of interna-
tional tourism receipts in Jiangsu Province from 1995 to
2004 can be decomposed into three components, the
national sectoral shift effect, neighbor-national sectoral
shift effect and regional-neighbor sectoral shift effect
(also called competitive effect).
Fig. 1 Shift-share formulation
Shift-share Analysis on International Tourism Competitiveness
175
3 Case Study
3.1 Study area and data
The eastern coastal China has always been considered an
interesting and relevant location. Six provinces in the
eastern coastal China are chosen as samples for this study.
The study area includes Jiangsu, the target region, and its
neighboring regions, such as Shanghai, Zhejiang, Anhui,
Shandong and Henan. The study period spans ten years
from 1995 to 2004 during which continuous time series
data are available for all the provinces under examination.
In 2004 Jiangsu positioned the fourth international des-
tination in China. The persistent augment trend of inter-
national tourism receipts in both Jiangsu and its
neighbors can be clearly seen from Table 1. Jiangsu’s
share of Chinese international tourism receipts increased
from 3.15% to 8.39% during 1995–2004 while the whole
study area’s share from 20.37% to 33.15%. Thus Jiangsu
and its neighbors are regarded as one of the most sig-
nificant international destinations and foreign exchange
earners in China.
3.2 Results
Table 2 provides the analytical results of the comparative
static and dynamic shift-share models. Due to the ab-
normal severity resulted from typical exogenous factor of
Severe Acute Respiratory Syndrome (SARS) outbreak in
2003, such abnormal changes, which are extraordinarily
different from those in normal milieu, will be not as the
basis of measuring the swings of industries accurately
and truly. In order to eliminate such abnormal impact, the
data of 2003 are omitted and a two-year interval from
2002 to 2004, associated with other annual interval, is
included. We term it modified dynamic model, which can
not only overcome the inherent limitations of the tradi-
tional comparative static method, but also avoid the se-
vere and abnormal changes of individual year in general
dynamic model.
3.2.1 National sectoral shift effect
From the results in Table 2, 26.7% of the actual growth in
comparative static model is attributable to the national
sectoral shift effect while 41.3% in modified dynamic
model, 50.9% in general dynamic model. Such findings
Table 1 International tourism receipts in 1995–2004 (US$106)
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Jiangsu 260
317 408 529 620 724 822 1050 1132 1763
Shanghai 939
1171 1317 1218 1364 1613 1808 2275 2053 3041
Zhejiang 236
292 345 361 410 514 699 928 873 1300
Anhui 31
42 64 51 67 86 106 124 83 141
Shandong 154
196 204 220 265 315 382 472 3703 567
Henan 60
73 95 101 114 124 133 145 64 160
China 8249
9476 10428 10760 12009 14327 15968 18531 14410 21031
Source: National Bureau of Statistics of China, 2006
Table 2 Results comparisons of dynamic and comparative static shift-share models in 1995–2004 (US$106)
are identical to conclusions advanced by Barff and Knight
(1988) that the national growth effect is underestimated
by the comparative static approach during periods when
regional growth rate exceeds the national rate. Both the
dynamic and comparative static approaches show that
Jiangsu Province has an actual growth of US$1503.44×106
Dynamic shift-share
model Static shift-share
model Modified shift-share
model
Actual growth 1503.44 1503.44 1503.44
National sectoral shift effect 765.98 402.86 621.09
Net shift 737.46 1100.58 882.35
Shanghai-nation 226.11 179.23 282.14
Zhejiang-nation 623.59 769.86 697.51
Anhui-nation 493.02 517.12 345.65
Shandong-nation 296.62 293.65 277.80
Neighbor-national sectoral
shift effect
Henan-nation 793.04 30.52 -85.74
Jiangsu-Shanghai 511.35 921.35 600.20
Jiangsu-Zhejiang 113.88 330.72 184.84
Jiangsu-Anhui 244.44 583.46 536.70
Jiangsu-Shandong 440.84 806.93 604.55
Regional-neighbor sectoral
shift effect
Jiangsu-Henan -55.57 1070.06 968.09
SHI Chunyun, ZHANG Jie, YANG Yang et al.
176
and a positive net shift, which means that Jiangsu performs
better relative to the whole country in the development of
the international tourism industry. Indeed, the national
sectoral shift effect has been positive, which indicates that
the international tourism receipts are secured due to the
national growth trend and implies that tourism industry is
one of the most flourishing sectors in China.
3.2.2 Neighbor-national sectoral shift effect
From the neighbor-national sectoral shift effect, all the
neighbors of Jiangsu except Henan have positive value
both in dynamic model and in static model, which sug-
gests that the development of international tourism in-
dustry is faster than the average of national growth and
tourism industry has been becoming one of the industries
with a high propensity to grow in the study area. Par-
ticularly, the growth of Zhejiang and Anhui are well in
excess of that of the others. Despite a relative uniformity
in most of neighbor-national sectoral shift effects, He-
nan’s effect by general dynamic approach reveals a much
stronger growth (US$793.04×106) than those (US$
30.52×106, US$–85.74×106) do by static approach and
modified model because of the exceptional year of 2003
in Henan.
3.2.3 Competitive effect
Jiangsu also has positive competitive effects over all its
neighboring regions, meaning that it is more competi-
tively positioned with respect to its neighbors. However,
Zhejiang has the least value both in comparative static
and in modified dynamic model, which means Zhejiang
develops much proximate to Jiangsu in international
tourism industry. Furthermore, it can be inferred that
Zhejiang is the most important competitor to Jiangsu.
Detailed results are listed in Table 3. In fact, changes
during these ten years have greatly fluctuated. The net
shifts seemed to be too modestly positive in 1999 and
2001 and even displayed negative in 2000, meaning that
the performance of international tourism industry in Ji-
angsu was so poor that its actual growth was even less
than that of the whole China in 2000. Nevertheless, in-
ternational tourism receipts in Jiangsu has been increas-
ing explosively since 2002, even in the exceptional year
of 2003 when the SARS outbreak almost devastated the
whole national tourism and the study area, all but Jiangsu
have endured a negative gain. Jiangsu has experienced
fluctuations, but still followed a rising trend.
International tourism industrial competitiveness in
Jiangsu has been expected to increase gradually with the
time by the spatial-temporal series analysis of the de-
Table 3 Dynamic shift-share analysis of
Jiangsu Province (US$106)
Actual growth
National sec-
toral shift effect Net shift
1995–1996 57.05 38.68 18.37
1996–1997 90.95 31.84 59.11
1997–1998 121.00 12.99 108.01
1998–1999 91.00 61.41 29.59
1999–2000 104.00 119.67 –15.67
2000–2001 98.02 82.90 15.12
2001–2002 227.98 131.97 96.01
2002–2003 81.87 –233.49 315.36
2003–2004 631.57 520.00 111.57
velopment trend of regional competitive component
(Table 4). Compared with Anhui Province, most of the
annual regional competitive components before 2001 are
negative, which indicates that Anhui has done a better job
in attracting more international tourists or encouraging
much more consumption than Jiangsu has. However,
Jiangsu has been experiencing a much swifter increase
than Anhui since 2002 and has well exceeded Anhui
since then. Compared with Zhejiang Province, regional
competitive components were negative from 2000 to
2002. The international tourism industry in Zhejiang has
been one of those industries with a high propensity to
grow since 2000 and displays advantages both in the
whole country and in the prosperous eastern China. Due
to the swift development of international tourism in Ji-
angsu in 2003 and 2004, Zhejiang failed to exhibit any
more competitive advantage. In conclusion, Jiangsu has
greater competitiveness in the international tourism in-
dustry in terms of the analytical results, while Zhejiang
Province can be viewed as the most important rival for
Jiangsu among all the neighboring regions both by
comparative static and by modified dynamic shift-share
models. Although dynamic shift-share model can over-
come some temporal limitations of comparative static
model, it cannot answer the perplexing questions and
make any judgments about the likely causes for com-
petitive advantages or disadvantages (Yasin et al., 2004).
To seek explanations for this, we would need to carry out
further analysis in comparison with local conditions.
3.3 Discussion
It is of very importance for marketers, developers, and
planners involved in strategy development to clearly
understand the spatially competitive situation for the
development of international tourism industry in Jiangsu.
Shift-share Analysis on International Tourism Competitiveness
177
Table 4 Regional competitive effect by modified dynamic model
1995-1996 1996-1997 1997-1998 1998-1999 1999-2000 2000-2001 2001-2002 2002-2004
Jiangsu-Shanghai –7.08 51.30 151.67 27.59 –9.18 10.62 15.49 359.79
Jiangsu-Zhejiang –4.47 33.20 102.08 19.20 –53.27 –162.41 –41.49 292.00
Jiangsu-Anhui –35.21 –75.12 203.88 –74.96 –71.82 –67.66 85.48 572.11
Jiangsu-Shandong –14.69 78.83 89.00 –17.20 –12.98 –56.92 35.40 503.11
Jiangsu-Henan 1.15 –5.17 95.23 22.91 49.61 43.37 156.23 604.75
Actually, further analysis of the background and condi-
tions in Jiangsu and Zhejiang can not only empirically
prove the findings of the above shift-share analytical
results, but also lay a foundation for making strategies for
the development of the tourism industry.
3.3.1 Competition analysis
(1) Similar location conditions. Both these two regions
are situated at the Changjiang River estuary and facing
with the sea, being important belt of eastern China’s
reform and opening up. They are also close to and de-
pendent on Shanghai, China’s biggest industrial base and
trade port. Findings from Zhang et al. (2000) indicated
that Shanghai is the significant distributing center for the
inbound and outbound tourists flow for both Jiangsu and
Zhejiang.
(2) Same culture milieu. These two regions belong to
the WU and YUE cultural districts well known as the
“first prosperous cultural relic” (Hu and Sun, 2005).
Elites in politics, culture, science, technology, art, etc.,
have come forth in great number since the Tang Dynasty,
which is profound and is responsible for the whole Chi-
nese history and for the prosperity nowadays in the fa-
mous Changjiang River Delta to a large degree.
(3) Similar tourism resources and characteristics.
These two regions are famous for the “water country”
because of its numerous lakes, rivers, streams and estu-
aries, and are usually referred to as “lands of fish and
rice” because of abounding in rice paddies, mulberry
orchards and fishponds. An old saying in China, “There
is a paradise in the heaven and Suzhou, Hangzhou on the
earth”, tells us both the scenic beauty and the similar
resources and tourism image in the two regions.
(4) Similar tourism development impetus. About
39.3% of the inbound tourists in Jiangsu and 47.1% in
Zhejiang were for business-related activities in 2004,
which particularly illustrates the importance of the eco-
nomic impetus to tourism development in the two regions.
The remarkable economic and trade growth have been
accompanied by persistent inbound tourist flows to the
study region.
(5) Similar origin market structure. The main tourists
origin markets in two provinces are much alike. Their
Spearman’s correlation coefficient is 0.829 and signifi-
cant at the 0.01 level (2-tailed). However, they all have
lower correlation coefficient with the whole China, 0.521
and 0.648 respectively and only significant at the 0.05
level, which means the two regions have similar structure
of tourist origins though they are some different from the
whole China.
3.3.2 Strategy development
As described above, there is little doubt that Jiangsu and
Zhejiang share much similarity in terms of the devel-
opment of tourism industry and exhibit close competitive
relation to each other. Therefore, understanding com-
petitors and taking proper strategies are of great signifi-
cance. With these considerations in mind, we can make
several recommendations. First, from supply-side per-
spective comes recognition of the importance of the
tourism product positioning in carrying out differentia-
tion and individuation strategies due to so many simi-
larities in the two provinces. Second, from market-side
perspective comes recognition of the importance of
promoting and marketing in attracting more inbound
tourists to retain the sustainable development of the in-
ternational tourism industry. Finally, cooperation will be
an effective way to improve the competitiveness for each
other. Starting with exploiting the tourism market, con-
stituting tourism policy and laws and constructing tour-
ism standardization, Jiangsu, Zhejiang and Shanghai
have set out to build the cooperation framework of re-
gional tourism, reinforce the policy auspice for regional
economic integration, eliminate regional administrative
and policy wall, and establish regional non-obstacle
travel pattern among Jiangsu, Zhejiang and Shanghai.
4 Conclusions
In the empirical application, the findings reflect that
tourism industry is booming and has continuous pros-
perity in China. Both Jiangsu and most of its neighboring
SHI Chunyun, ZHANG Jie, YANG Yang et al.
178
regions have positive growth rates in comparison with
the whole China, which suggests that these regions are
becoming one of the fastest-growing markets in China.
Moreover, Jiangsu has positive competitive effect over
all its neighboring regions, meaning that it was more
competitively positioned with respect to its entire
neighbor. Zhejiang is the most important rival to Jiangsu
as far as international tourism industry is concerned since
these two provinces share many similarities with each
other, which can be considered as the key reasons for
competitive relationship.
However, the shift-share analysis has its inherent
limitations. The model can not give the mechanism and
explanation underlying the changes but describe and
reflect the spatially competitive state. In order to make it
clear, further study and analysis should be needed.
References
Alavi J, Yasin M, 2000. A systematic approach to tourism policy.
Journal of Business Research, 48: 147–156.
Barff R A, Knight III P L, 1988. Dynamic shift-share analysis.
Growth and Change, 19: 1–11.
Chu Xinzheng, Li Yanhong, Jin Wangui, 2005. Analysis on inter-
national tourism industry structure and benefit in Xinjiang.
Journal of Arid Land Resources and Environment, 19(4):
119–124. (in Chinese)
Creamer D, 1943. Shifts of manufacturing industries. In: Industrial
Location and National Resources. Washington, D C: Govern-
ment Printing Office.
Dunn J E S, 1960. A statistical and analytical technique for re-
gional analysis. Papers of the Regional Science Association, 6:
97–112.
Fuchs M, Rijken L, Peters M et al., 2000. Modeling asian incoming
tourists: A shift-share approach. Asia Pacific Journal of Tourism
Research, 5(2): 1–10.
Hu Zhaoliang, Sun Huishu, 2005. Outline of Cultural Geography
in China. Beijing: People’s Education Press, 261. (in Chinese)
Li Deming, Cheng Jiumiao, 2004. On the structure and optimiza-
tion measures of international tourism industry in Anhui Prov-
ince. Resources Development and Market, 20(5): 390–392. (in
Chinese)
National Bureau of Statistics of China, 2006. China Statistical
Yearbook. Beijing: China Statistics Press. (in Chinese)
Nazara S, Hewings G J D, 2004. Spatial structure and taxonomy of
decomposition in shift-share analysis. Growth and Change,
35(4): 476–490.
Shi Chunyun, Zhang Jie, Gao Wei et al., 2007. Review of
shift-share analysis and its extended models abroad. Inquiry into
Economic Issue, 3: 133–136.
Sirakaya E, Choi Hwan-Suk, Var T, 2002. Shift-share analysis in
tourism: examination of tourism employment change in a region.
Tourism Economics, 8(3): 303–24.
Sirakaya E, Uysal M, Toepper L, 1995. Measuring the perform-
ance of South Carolina’s tourist industry from shift-share
analysis: A case study. Journal of Travel Research, 33(2):
55–62.
Stevens B H, Moore C L, 1980. A critical review of the literature
on shift-share as a forecasting technique. Journal of Regional
Science, 20: 419–437.
Thirlwall A P, 1967. A measure of the proper distribution of in-
dustry. Oxford Economic Papers, 19(March): 46–58.
Toh R S, Khan H, Koh Ai-Jin, 2001. A travel balance approach for
examining tourism area life cycles: the case of Singapore.
Journal of Travel Research, 39(3): 426–432.
Toh R S, Khan H, Lim L L, August 2004. Two-stage shift-share
analyses of tourism arrivals and arrivals by purpose of visit: the
Singapore experience. Journal of Travel Research, 43(1):
57–66.
Toh R S, Khan H, Yap I, 2003. An empirical validation of the travel
balance approach as an alternative to the tourism area life cycle.
Tourism Analysis, 7: 207–215.
Wang Changyan, Liu Yuntong, Zhang Xinhuan, 2004. Analysis on
structural efficiency of tourism industry for overseas tourists in
Xinjiang. Journal of Xinjiang Normal University (Natural Sci-
ences Edition), 23(2): 74–79. (in Chinese)
Wen Fei, Wang Juan, 2005. Integrated analysis of the competitive
state in domestic tourism industry of Anhui Province. Journal of
Huangshan University, 7(4): 17–30. (in Chinese)
Yang Xinjun, Ma Xiaolong, Huo Yunpei, 2005. A SSM analysis
rationality of sector structure of tourism industry. Human Ge-
ography, 20(1): 49–52. (in Chinese)
Yasin M, Alavi J, Sobral F et al., 2004. A shift-share analysis
approach to understanding the dynamic of the Portuguese tour-
ism market. Journal of Travel and Tourism Marketing, 17(4):
11–22.
Zhang Hong, Li Jiuquan, Yang Zhaoping et al., 2000. A study on
the structure features and spatial and temporal dynamic mode of
overseas tourists in Xi’an. Arid Land Geography, 23(2):
165–169. (in Chinese)
