2007 Annual International CHRIE Conference & Exposition
515
In this instance
1
0
μ
≥ >
. The minimum value of
( )
g
μ
is
1
1
1
(
1)
(
) (
,
)
2
Max
B B
B B
A A
A A
A A
m n
g
m n
m n
m n m n
μ
= =
+
∈
. There are two possibilities with
δ
illustrated as the
line
1
(1)
g
δ
<
and the line
2
(1)
g
δ
>
in the figure 2.
(2)
1
1
A A
B B
m n
m n
δ
δ
>
>
(equal to
B B
B B
A A
m n
m n
m n
δ
> >
)
In this instance
1
0
μ
≥ >
.
One easily proves that
(
1)
Max
g
δ
μ
<
=
. The line
1
δ
characters this instance in the
figure 2.
(3)
1
1
B B
A A
m n
m n
δ
δ
> >
(equal to
1
1
A A
A A
m n
m n
δ
μ
> >
)
In this instance
1
0
A A
m n
μ
δ
> >
. It’s obviously that
1
(
)
Max
A A
g
m n
δ
μ
δ
>
=
. Thus, this instance is
correspondence to the line
2
δ
in the figure 2.
(4)
1
1
A A
B B
m n
m n
δ
δ
> >
(equal to
B B
B B
m n
m n
δ μ
> >
)
In this instance
0
B B
m n
δ
μ
> >
, we verify that
(
)
Max
B B
g
m n
δ
δ
μ
<
=
. Thus, this instance is
correspondence to the line
1
δ
in the figure 2.
(5)
1
1
B B
A A
m n
m n
δ
δ
>
>
and (6)
1
1
A A
B B
m n
m n
δ
δ
>
>
These two instances could not exist because of confliction existing within the conditions.
Table 2
Summary of four possible instances of supply chain loyalty
Case
1
1
A A
A A
m n
m n
δ
μ
> >
1
B B
A A
A A
m n
m n
m n
δ
> >
B B
B B
A A
m n
m n
m n
δ
> >
B B
B B
m n
m n
δ μ
> >
Line
2
δ
1
δ
or
2
δ
1
δ
1
δ
Table 2 sums up the all the existed instances. In order to give clear picture, sequence of instances is
rearranged. Notice that
A
A
B
B
C
C
α
δ
α
−
=
−
implies competence ratio of two TSCs.
δ
is bigger while
A
TSC
has larger
market scale and lower supply chain cost. Based on proposition 6, there are three managerial implementations from
above discussions. First, if two TSCs are almost with the same competences or the TSC is weaker than his rival like
in instance 2 and 4 corresponding to the line
1
δ
. The condition
1
1
(
)
2
B B
A A
m n
m n
δ
μ
μ
<
+
is always hold, which
means the performance of TSC decrease with
increment of
μ
. TSC Manager should build up supply chain loyalty.
Second, if TSC is much more powerful than his rival like in instance 3, then supply chain manager’s action depends
on current loyalty. If current loyalty is high satisfying
1
1
(
)
2
B B
A A
m n
m n
μ
δ
μ
+
>
, he should continue developing
2007 Annual International CHRIE Conference & Exposition
516
it. Otherwise, he should take opposite action. Third, if TSC is more powerful than his rival but not so much like in
instance 1, TSC manager should firstly identify situation, then take action referenced to former two cases.
CONCLUSION
This paper has formulated a multi-stage game framework for studying the collaboration and competition
dynamics in tourism supply chains for package holidays. Three sectors are considered. They are tourism operators,
hotel &
accommodation providers, and theme park operators. Three types of competition are analyzed theoretically.
They are the supplier competition between suppliers within a sector, the sector competition between sectors in
certain supply chain, and the chain competition between two TSCs. In the proposed game, the theme park operator
sector and the hotel & accommodation providers sector take their moves first, and the tour operators sector takes the
second move. Backwards induction has been proposed to solve this game. The tour operators first determine the
optimal number of tourists they served. The prices deriver from tour operator sector is for the hotel &
accommodation providers and the theme park operator make their decisions respectively. Combining the results,
then jointly considering two TSCs shows the subgame perfect Nash equilibrium.
Base upon the equilibrium results, the impacts of four systemic parameters have been studied. They are
market scale,
supply chain cost, supply chain membership, and supply chain loyalty. Four performance indexes,
namely, quantity, price, unit profit and profit, have been selected to measure their impacts. Impacts of supply chain
membership on sectoral and TSC surplus have also been investigated. Moreover, numerical studies have been
conducted to demonstrate the influences of new competitor entering a sector. The trend has been developed to
further understand the impact of supply chain loyalty in different situations.
Several managerial implications have been derived from this study. Firstly, in order to take up market
advantages, enterprises in TSC should cooperate
in broadening market scale, and reducing supply chain cost.
Secondly, more members in the tourism supply chain strengthen its overall capacity. However, increased
competition due to increased TSC membership in a sector reduces enterprise’s profit as well as sectoral surplus,
while enterprises from other sector benefit from the competition within this sector. Third, building up supply chain
loyalty does not necessarily improve performance of TSC. Loyalty buildup strategy should be taken (1) when the
TSC is weak in the sense of small market scale and high supply chain cost compared to its rival, or (2) when current
supply chain loyalty is high.
Our paper makes a unique contribution to tourism research in three ways. First, most previous studies focus
on a single tourism enterprise/sector. Our analyses explore enterprises’ behaviors in the context of supply chain,
which enlarges research scope in tourism. Second, this research is an early contribution to extending the game-
theoretic framework for studying tourism supply chains, since majority of existing literature is related to production
supply chains. Finally, this paper is an original study on collaboration and competition
dynamics in tourism supply
chains as compared with existing studies on manufacturing supply chain dynamics (Swaminathan, Smith, and Sadeh
1998; Souza, Zice, and Chaoyang 2000; Riddalls and Bennett 2002; Disney and Towill 2003).
The research can be extended further in several directions. Firstly, the model could be directly relaxed to
multiple sectors, not only tour operator, hotel & accommodation provider, and theme park operator, but also
transportation, restaurant and shopping center etc. Government could also be recognized as a player who cares about
welfare or overall profit in our framework. Secondly, in this paper, price or quantity is one and only decision
variable of tourism enterprises. However, others like service quality and advertising etc. also influent on the
performance of tourism supply chain. Multiple dimensions of enterprise’s decision model in the context of tourism
supply chain could be discussed in further research. Thirdly, the analyses could be under
different coordination
scheme. For example, there could be a dominant tour operator and a competitive fringe, or some tour operators
vertically integrate the hotel & accommodation providers. Finally, the use of constraint capacity of each tourism
sector may yield different and interesting results in the analysis for competition dynamics of tourism supply chain.
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