Asia Pacific Management Review (2007) 12(3), 151-160
Key Factors for Successful Evaluation and Screening of Strategic Alliance:
A Case Study in the Telecommunications Industry
Ming-Kuen Wang and Kevin P. Hwang*
Department of Transportation and Communication Management Science, National Cheng Kung University, Tainan, Taiwan, R.O.C.
Accepted in June 2007
Available online
Abstract
This research uses the Analytical Hierarchy Process (AHP) to analyze key factors in evaluating and screening strategic alliance partners in the telecommunications industry. Telecommunications companies can utilize key factors of strategic alliances to
provide self-growth and obtain competitive advantage opportunities for expanding global market share. This research summarizes
the evaluation and screening criteria of strategic alliance partners via a questionnaire of 30 Chunghwa Telecom executives who
had actually participated in alliance decisions or related tasks and who had employed AHP screening criteria. Findings include
three key factors in evaluating and screening partners: complementation of marketing channels and skills, past cooperation experience of both parties, and complementation of technology and resources. This research can provide a reference to telecommunication companies when evaluating and screening partners.
Keywords: Strategic alliance; Analytical hierarchy process; Partner evaluation and screening; Key factor
1. Introduction
communications companies will inevitably make strate-
gic plans, adopt strategic alliances, and expand to a
global telecom market aggressively to increase competitiveness and profitability.
The Taiwan telecommunications market has been
liberalized for over ten years. Market dynamics have
resulted in three dominant companies: Chunghwa
Telecom, Taiwan mobile, and Far Eastone, with each
holding about one third market share. The opening of
3G and the implementation of Mobile Number Portability (MNP) will introduce increased competition.
Because of fierce competition, limited resources, technical barriers, capital shortages, and geographical limitations, it is difficult for a company to operate independently and to profit in the global market. Therefore,
many companies have started to seek alliances with
other companies or create cooperation opportunities
with other partners in response to global competition.
Such cooperations promise to reduce operating risks, to
help obtain technical knowledge and resource complements--increasing the competitiveness of the company.
Wu (1996) offers that the basic purpose of strategic alliances is to either strengthen a businesses’ self
competitive advantage or to seek competitive balance.
Strategic alliances utilize synergistic effects to make
every partner able to take advantage of complementary
combinations, which can result in greater strength.
However, strategic alliances also present risks.
Liu (2000) shows that management complexity is increased. Therefore, the company must consider the
traits of alliance targets (products, technologies, etc.)
and decide how many companies should participate;
they must also decide the target for the participating
alliance. Designing and managing a bad alliance group
will make management difficult and cause conflicts;
this will result in the disappearance of the potential
value obtained by the alliance relationship. Because
Chunghwa Telecom is the leader of the Taiwan telecommunications industry, this research uses Chunghwa
Telecom as a example to study, compare, analyze, and
summarize the choices of strategic alliances that Taiwan telecommunications companies face. It faces
these conditions in an external environment of growing
3G and MNP policy after market liberalization and
internal environment change, due to the company's
privatization. Further, this research explores the key
Varis et al., (2005) 1 show that an international
growth strategy has become the biggest challenge a
company faces when international expansion offers a
company growth and added value. The telecommunications industry not only has the high technology and
enormous capital, but it also is a service industry.
Since such a multi-characteristic industry faces a competitive environment with various changes, global tele* Email:wmk2582@cht.com.tw
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ing skills, and experience are important. This research proposes that complementary skills should be
summarized as: alliance networks, technology resources, marketing channels, financial resources; the
partner’s previous experiences are used as the
sub-criterion level (Geringer, 1991; Stafford, 1994;
Brouthers et al., 1995; Dacin et al., 1997; Tam &
Tummala, 2001; Nielson, 2003; Holtbrugge, 2004).
factors valued by telecommunications companies when
choosing strategic alliance partners.
2. Definition of Strategic Alliance
Aaker (1992) contends that the strategic alliance
is a long-term cooperation relationship between two or
more companies; and it combines an advantageous
leverage to achieve strategic goals. It is one kind of
tactic; it also includes the cooperation of mutually
needed resources and technologies; furthermore, it
generates strategic value. Wu (1996) believes that the
strategic alliance is the non-market oriented company
deals between competitors to participate in activities of
existing potential competitors via technology transfer
to each other, consignment sale contract, minority or
equal shares investment (i.e., joint venture company),
capacity swap, joint marketing, cooperative research
and development, cooperative production, or a combination of each of the above activities. Therefore, exchanges, product co-sharing or co-development, and
autonomic affiliations of technology and services between companies also belong to strategic alliances
(Gulaty, 1998). Spekman et al., (1998) considers the
strategic alliance as the close, long-term, and mutual
beneficial agreement relationship between two or more
partners; in the agreement, resources, knowledge and
skills are shared in order to strengthen each partner’s
position. A strategic alliance occurs when two or more
organizations agree to use each other’s resource to
achieve the strategic goals that one single company
would not be able to reach (Ahwireng-Obeng, 2001).
(2) Cooperative culture between partners
The primary key of creating cooperative culture
lies in symmetry. When the size difference between
alliance partners is small or financial resources and the
internal work environment are compatible, the strategic
alliance will tend to succeed. Symmetry should exist in
each other’s top management team; namely, top management teams between partners should establish peer
relationships. Brouther et al., (1995) argue that organizational culture, trust, commitment, and past cooperative experiences are important; while Chen (2002)
proposes to add cooperative vision to constitute the
fourth sub-criteria for constructing cooperative culture.
(3) Compatible goals of cooperative partners
A clear goal is indispensable to successful strategic alliances. In order to avoid vague and different
goals, achievement levels of original goals also must
be regularly reviewed. Brouther et al. (1995) and Gonzalez (2001) contend that strategic goals need to be
compatible; this research adopts the view that the
compatibility of the management team is also an important factor in a successful strategic alliance, as
Stadfford (1994), Lin & Chen (2004), propose. Liu
(1996) states that the compatibility of operational policy between organizations must be stressed in order to
have compatible strategic alliance goals.
This research defines the strategic alliance as two
or more companies, for the purpose of sharing each
other’s market, technologies, resources, knowledge and
skills, sign a long-term mutual benefit agreement and
operate independently and freely to strengthen the
competitive abilities of alliance members.
(4) Commensurate risks sharing
At the beginning of a strategic alliance, risks distribution issue must be prudently considered. This research summarizes previous scholars’ viewpoints: Liu
(1996) thinks that reputation and renown of alliance
partners may influence the reputation and performance
of the whole alliance. Brouther et al. (1995) consid that
competition and conflict of interests in the industryand
the financial risk of extra cost incurred by the alliance
are the risks that a strategic alliance possibly faces. Wu
(1996) contends that the risk of communication barriers may occur during correspondence when a company
is investing in or seeking cooperation. Lambe and
Spekman (1997) hold that innovation of technology
will cause highly uncertain risk in the industry. Therefore, they suggest that companies should apply the
strategic alliance method to reduce this risk.
We have gathered domestic and international literature about the evaluation of strategic alliance partners and explored the conceptual criteria in relation to
Taiwan telecom companies, who are evaluating and
screening strategic alliance partners. For the main
criteria, we have adopted four main criteria of selecting
strategic alliance partners, proposed by Brouthers et al.
(1995). Combining all other scholars’ research, we
summarize the criteria structures, considered by strategic alliance decision makers of telecom industry, as
follows:
(1) Complementary skills offered by the partner
Brouthers et al., (1995) holds that the most basic
overview of a partner includes the aspects of technology and market; it also should consider the experience
of the partner and the realistic contributions; they also
contend that the partner’s financial resources, market-
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Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
second stage questionnaire. The second stage questionnaire is mainly based on results of the first stage to
build hierarchical structure; and it deploys pair-wise
comparisons, conforming to the application of rating
scales. This research uses Chunghwa Telecom as the
research subject and surveys executives who are actually responsible for alliance tasks in the three branches
of the company: Mobile Business, Data Communications, and International Business. A total of 45 questionnaires were sent out, starting on March 27, 2006.
The response deadline was May 3, 2006; 30 responses
were valid, with a response rate of 67%.
3. Methodology
3.1 Structure
Because each evaluation criterion obtained by
this research is a qualitative, it is difficult to quantify
for practical application. Therefore, this research deploys two-stages of expert questionnaires to find out
the criteria of evaluating and screening strategic alliance partners, which Chunghwa Telecom uses. In the
first stage, we use a fuzzy Dephi method to screen
relevant influence factors and utilize the concept of
threshold value to select proper evaluation criteria. In
the second stage, we utilize evaluation criteria obtained
from screening, fitting Analytic Hierarchy Process, to
get the relative weight of evaluation criteria. The hierarchical structure is shown in Figure 1.
3.3 Analytic Hierarchy Process (AHP)
Due to rapid environmental changes, aspects of
consideration by decision makers have become more
complicated and varied. In order to solve this problem, Saaty (1980) proposes the Analytic Hierarchy
Process (AHP). AHP can offer decision makers sufficient information about selecting the appropriate
scheme. The more weighted value the scheme has, the
higher priority for scheme adoption. AHP can be used
to reduce the risks of making wrong decisions and
helping decision makers to make sound judgments
(Deng & Tseng, 1989).
3.2 Questionnaire Design and Analysis
Questionnaire analysis mainly consists of a fuzzy
Dephi method and an Analytic Hierarchy Process in
two stages. The first stage questionnaire inquires of
expert opinion. Items result from summarizing geometric means of above mentioned items of literature
review, and items that reach the threshold value from
each dimension are used as the base of developing
Figure 1. Research Structure
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Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
AHP retrieves majority opinions of experts and
deploys pair-wise comparisons to find the relative importance of decision elements; it further selects the
biggest relative weighted scheme as the best scheme by
linking hierarchy levels.
After summarizing opinions of evaluators, we
evaluate items via a nominal scale to give proper comparison values. In general, a geometric mean is used to
serve as a basis for forming the comparison matrix.
(5) Establishment of a pair-wise comparison matrix
3.4 Analytic Hierarchy Process (AHP) Procedure
While conducting pair-wise comparison among
elements for n elements, n (n-1)/2 comparisons are
needed. Next, we put the measure of n elements
comparison results in the upper triangular part of the
comparison matrix, while the bottom triangular part
serves as the reverse value of the upper triangular
part’s relative value. Then, we can obtain a pair-wise
comparison matrix A as shown in Equation (1):
a12 L a1n ⎤
⎡ 1
⎢1 a
1
L a 2 n ⎥⎥
(1)
A = ⎢ 12
⎢ M
M
O M ⎥
⎢
⎥
⎣1 a1n 1 a 2 n L 1 ⎦
The AHP procedure can be divided into the following steps:
(1) Definition of decision problems
While using AHP, for evaluating the hierarchy of
key factors, the direction of the problem must be fully
grasped. First of all, the problem must be clarified,
and the scope of the problem must be defined clearly.
(2) List of every evaluating factor
When listing every evaluating factor, relevant
literature, group brainstorming, and Delphi methods
are used to assemble opinions of scholars and experts.
Their professional knowledge and practical experience
are used to list every evaluating factor.
Where aij denotes the relative importance of element
i as compared with element j
(3) Development of hierarchy structure
(6) Finding eigen vector and maximized eigenvalue
Every evaluating factor is compartmentalized to
a hierarchy layer, according to the relevant relationship
of each factor and independent level. Saaty (1980) suggested that each layer has no more than seven items so
as to avoid conflicts that affect evaluating results.
Saaty and Vargas (1982) propose four approximate eigen vector solution characteristics. This research adopts the row vector geometric mean standard
method, as shown in Equation (2); this is also called
normalization of the geometric mean of the rows
(NGM) method; this method is often used and also has
the best accuracy.
(4) Pair-wise comparison and evaluation
Pair-wise comparison is conducted according to
the relative importance of each evaluating factor.
This can lighten the decision makers’ burden of thinking; it can even more clearly present the relative importance of decision factors. AHP employs a nominal
scale as the evaluating indicator of pair-wise comparisons, which can be divided into nine scales as shown in
Table 1:
n
n
Wi =
Definition
1
Equal Importance
3
Weak Importance
5
Essential Importance
7
Very Strong Importance
9
2, 4, 6, 8
Absolute Importance
Intermediate Values of
Neighborhood Scales
ij
i，j=1,2,…,n
j =1
(2)
n
n
∑ ∏a
n
i =1
ij
j =1
Next, we further calculate the maximized eigen
value λ max . First, we multiply pair-wise the comparison matrix A by eigen vector Wi to get a new
vector Wi ' , as shown in Equation (3), where each
vector value of Wi ' is divided by each vector value
that corresponds to the original vector Wi . Then,
use all obtained values to calculate an arithmetic average, deriving λ max , as shown in Equation (4).
Table 1. Meanings and Explanation of AHP Scale
Evaluating
Scale
∏a
Explanation
Contributions of two criteria
are equally important
Experience and judgment
moderately favor one scheme
over another
Experience and judgment
strongly favor one scheme
over another
In practice, a scheme is favored very strongly over
another
Experience and judgment
favor one scheme over another
When compromise judgment
values are needed
a12
⎡ 1
⎢1 a
1
Wi ' = A × Wi = ⎢ 12
⎢ M
M
⎢
⎣1 a1n 1 a2n
1⎛
n
W' ⎞
λmax = ⎜⎜ ∑ i ⎟⎟
n
W
⎝ i =1
i
⎠
(7) Consistency test
(A) Consistency index
Source: Saaty (1980)
154
L a1n ⎤ ⎡W1 ⎤ ⎡W '1 ⎤
L a2n ⎥⎥ ⎢⎢W2 ⎥⎥ ⎢⎢W ' 2 ⎥⎥ (3)
×
=
O M ⎥ ⎢M ⎥ ⎢ M ⎥
⎥ ⎢ ⎥ ⎢ ⎥
L 1 ⎦ ⎣Wn ⎦ ⎣W ' n ⎦
(4)
Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
C .I . =
λmax − n
where n j denotes the number of elements contained in
j level, Wij is the comprehensive weight value of i
element in j level; U i , j +1 means the consistency index of j+1 level toward the i element in j level; and
Ri , j +1 is the random index of j+1 level toward the i
element in j level. If CRH≦0.1, the overall hierarchy
of the developed comparison evaluation has consistency.
(5)
n −1
The smaller C.I. the value is, the higher the consistency is-- while C.I.=0 means total consistency.
Generally speaking, C.I.≦0.1 denotes acceptable
evaluating values within the matrix. If C.I.＞0.1, we
re-calculate the pair-wise comparison matrix until the
C.I. value improves to an acceptable level.
(B) Consistency ratio
C.R. =
C.I .
R.I .
(9) Calculating total priority vector of the overall hierarchy
After the consistency of the overall hierarchy
reaches an acceptable level, the last AHP step is to
combine the relative weights of the elements of each
level to obtain each decision scheme that corresponds
to the relative priority order of the decision goal.
(6)
When C.R.≦0.1, the results of data judgment
have consistency. If C.R. ＞0.1, we re-calculate the
matrix until C.R. the value improves to an acceptable
level. The random index (R.I.) is as shown in Table
2:
4. Results and Discussions
4.1 Strategic Alliance Main Criterion
Table 2. Random Index
n
R.I.
1
0
2
0
3
0.58
4
0.9
5
1.12
6
1.24
Table 3 shows each pair-wise comparison matrix
and the weight for the strategic alliance main criterion:
7
1.32
From Table 3 results, C.I. and C.R. values are all
smaller than 0.1, showing this pair-wise comparison
matrix has consistency; namely, every interviewee
shows consistency toward the evaluation of this dimension. The importance sequencing is as follows:
complementary skills > risks and risks sharing > cooperative culture > compatible goals. Therefore, the
results show strategic alliances emphasize complementary skills.
Source: Saaty (1980)
(8) Finding the overall consistency ratio hierarchy
(CRH)
First, calculate the overall consistency ratio hierarchy (CIH) and overall random index hierarchy (RIH),
the algorithms for which are as shown in Equation (7)
~ Equation (9):
h
nj
CIH = ∑∑ WijU i , j +1
(7)
4.2 Complementary Skills
j =1 i =1
h
Results of Table 4 show C.I. and C.R. values are
both smaller than 0.1, meaning this comparison matrix
has consistency; that is, every interviewee shows consistency toward comparisons of complementary skills.
The importance sequence is as follows: marketing
channel and skills complementation > technology and
resource complementation > alliance network complementation.
nj
RIH = ∑∑ Wij Ri , j +1
(8)
CIH
RIH
(9)
j =1 i =1
CRH =
Table 3. Pairwise Comparison Matrix of Main Criterion
Main Criterion
Complementary Skills Compatible Goals
Cooperative Culture
Risks and Risks
Sharing
Weight of Each
Dimension
Complementary Skills
1.00000
2.33030
1.63143
1.03186
(1)0.34391
Compatible Goals
0.42913
1.00000
1.12260
0.96068
(4)0.20155
Cooperative Culture
0.61296
0.89079
1.00000
1.05524
(3)0.21290
Risks and Risks Sharing
0.96912
1.04093
0.94765
1.00000
(2)0.24163
λmax = 4.07101, C.I.= 0.02367, C.R.= 0.02630
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Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
Table 4. Pair-wise Comparison Matrix of Complementary Skills
Technology and ReMarketing Channel and Weight of
source ComplementaSkills Complementation Each Item
tion
Alliance Network
Complementation
Complementary Skills
Alliance Network Complementation
Technology and Resource Complementation
Marketing Channel and
Skills Complementation
Relative Weight
1.00000
0.84795
0.46073
0.23137
(4)0.07957
1.17931
1.00000
0.59365
0.28104
(3)0.09665
2.17048
1.68450
1.00000
0.48759
(1)0.16769
λmax =3.00087，C.I.= 0.00044，C.R.= 0.00075
Table 5. Pairwise Comparison Matrix of Compatible Goals
Compatible Goals
Compatibility of
Operational Policies
Compatibility of
Management
Teams
Compatibility of
Strategic Goals
Weight of Each Item
Relative Weight
1.00000
1.18942
0.86716
0.33675
(7)0.06787
0.84075
1.00000
1.11806
0.32649
(9)0.06581
1.15319
0.89441
1.00000
0.33675
(8)0.06787
Compatibility of
Operational Policies
Compatibility of
Management
Teams
Compatibility of
Strategic Goals
λmax =3.02035，C.I.=0.01017，C.R.=0.01754
exhibits consistency toward comparisons of cooperative culture. Its importance sequencing is as follows:
both parties’ past cooperation experience > trust and
commitment > cooperative visions.
4.3 Comaptible Goals
From the results of Table 5, we know that both
C.I. and C.R. values are smaller than 0.1-- showing
that this pair-wise comparison matrix has consistency;
this means every interviewee exhibits consistency toward comparisons of compatible goals. Its importance
sequencing is as follows: compatibility of operational
policies=compatibility of strategic goals > compatibility of management teams.
4.5 Risks and Risks Sharing
From the results of Table 7, we know both C.I.
and C.R. values are smaller than 0.1, showing this
pair-wise comparison matrix has consistency; that is,
every interviewee has consistency toward comparisons
of risks and risks sharing. Its importance sequencing is:
competitiveness or conflict of interests in the industry
> past reputation and renown > risk sharing of task
environment uncertainty > potential communication
barrier.
4.4 Cooperative Culture
In the results of Table 6, both C.I. and C.R. values
are smaller than 0.1, showing this pair-wise comparison matrix has consistency, namely; every interviewee
Table 6. Pair-wise Comparison Matrix of Cooperative Culture
Cooperative Culture
Both Parties’ Past
Cooperation Experi- Cooperative Visions
ence
Trust and Commitment
Weight of Each Item
Relative Weight
Both Parties’ Past
Cooperation Experience
1.00000
3.59124
2.08514
0.56422
(2)0.12012
Cooperative Visions
0.27846
1.00000
0.47979
0.14743
(13)0.03139
Trust and Commitment
0.47958
2.08424
1.00000
0.28835
(10)0.06139
λmax = 3.00404, C.I. = 0.00202, C.R. = 0.00349
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Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
Table 7. Pair-wise Comparison Matrix of Risks and Risks Sharing
Risks and Risks
Sharing
Past Reputation and
Renown
Competitiveness or
Conflict of Interests
in the Industry
Potential Communication Barrier
Risk Sharing of Task
Environment Uncertainty
Past Reputation
and Renown
Competitiveness or
Conflict of Interests in
the Industry
Potential Communication Barrier
Risk Sharing of
Task Environment Uncertainty
Weight of
Each Item
Relative Weight
1.00000
1.17430
1.38397
1.19476
0.29042
(6)0.07017
0.85157
1.00000
2.07582
1.20578
0.29726
(5)0.07183
0.72256
0.48174
1.00000
1.20578
0.19802
(12)0.04785
0.83699
0.82934
0.82934
1.00000
0.21430
(11)0.05178
λmax = 4.06252, C.I. = 0.02084, C.R. = 0.02316
reasons for undertaking strategic alliances. Accordingly, companies often combine each other’s complementary technologies and resources via strategic alliances to increase competitive advantages of companies
(Tsang, 1998; Hitt & Dacin, 2000; Schilling, 2005). A
strategic alliance is created when companies cooperate
because of mutual needs and risks sharing to achieve
common goals (Kogut, 1988). This verifies and supports the viewpoints of scholars. In addition, the first
five key factors that are most stressed are: marketing
channels and skills complementation; both parties’ past
cooperation experience; technology and resource complementation; alliance network complementation; and
competitiveness or conflict of interests in the industry.
The least emphasized factors are cooperative visions;
potential communication barriers; risk sharing of task
environment uncertainty; trust and commitment; and
compatibility of the management team. Chunghwa
Telecom, the biggest telecommunications company in
Taiwan, faces the saturation of market scale economy
after privatization and is now aggressively turning to
developing countries in the Asia-Pacific region to seek
strategic alliances of trans-investments in the international market; it seeks to solicit strategic alliance partners who can co-invest to develop telecommunications
markets in Asia-Pacific countries. Findings of this research can act as a reference for Taiwan telecommunications companies when seeking trans-investments
strategic alliance partners. This is a solid contribution
of this research to telecommunications industry. This
study considers only the case of Chunghwa Telecom;
furthermore, in order to improve the reliability of the
survey, only executives and employees whom are familiar with partnering strategies are included in the
survey; so, in terms of generality, there are some limitations. However, since most companies have adopted
differing but similar policies, the results of the survey
are still relevant to other telecommunications companies.
Regarding the consistency of the whole level,
relevant indices are as follows:
CIH=0.031338
RIH=1.557322
CRH=0.020123
CRH is smaller than 0.1, showing this pair-wise
comparison matrix has consistency; this implies that
every interviewee has consistency toward the comparison of this item.
5. Conclusions
Successful strategic alliances can help companies
obtain competitive advantages in the market. Therefore,
an organization’s important strategic issue is how to
select the optimum alliance partner in the hope of
minimizing input to achieve maximum output. Nevertheless, when a company makes a decision, it is quite
common that changes of organizational environment
and the complexity of decision factors are intermingled
in the decision making process. Therefore, it is appropriate to form an evaluating project team within the
organization to select the solving scheme. While
choosing the strategic alliance partner, it is usual to
face the problem of multiple criteria and many decision
makers. Because this problem has the characteristics of
unstructured openness, complex environmental factors
need to be included when making decisions. Some
criteria are often qualitative and are deeply influenced
by accumulated experience and the subjective judgment of the decision makers, causing criteria weights
to often be changed due to environmental variations at
the time of decision making. We invited Chunghwa
Telecom middle and higher level executives to conduct
comparisons, and we employed AHP to understand the
crucial factors of evaluating and screening strategic
alliance partners in the telecommunications industry
resulting in actual effects and meanings.
Research results show complementary skills with
partners, risks reduction, and risks sharing are the main
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Appendix: Questionnaire
Strategic Alliance Partners
Factors
9：1
8：2
Importance of one factor over another
7：3 6：4 5：5 4：6 3：7
2：8
1：9
Complementary skills
offered by the partner
Complementary skills
offered by the partner
Complementary skills
offered by the partner
Cooperative culture
between partners
Cooperative culture
between partners
Compatible goals of
cooperative partners
Factors
Cooperative culture
between partners
Compatible goals of
cooperative partners
Commensurate risks
sharing
Compatible goals of
cooperative partners
Commensurate risks
sharing
Commensurate risks
sharing
Complementary Skills
Factors
9：1
8：2
Importance of one factor over another
7：3 6：4 5：5 4：6 3：7 2：8
1：9
Alliance Network Complementation
Alliance Network Complementation
Technology and Resource
Complementation
Factors
Technology and Resource
Complementation
Marketing Channel and
Skills Complementation
Marketing Channel and
Skills Complementation
Compatible Goals
Factors
9：1
8：2
Importance of one factor over another
7：3 6：4 5：5 4：6 3：7
2：8
Factors
1：9
Compatibility of
Operational Policies
Compatibility of
Operational Policies
Compatibility of
Management
Teams
Compatibility of Management
Teams
Compatibility of Strategic Goals
Compatibility of Strategic Goals
Cooperative Culture
Factors
9：1
8：2
Importance of one factor over another
7：3 6：4 5：5 4：6 3：7
Both Parties’ Past Cooperation Experience
Both Parties’ Past Cooperation Experience
Cooperative Visions
2：8
1：9
Factors
Cooperative Visions
Trust and Commitment
Trust and Commitment
159
Ming-Kuen Wang et al.,/Asia Pacific Management Review (2007), 12(3), 151-160
Risks and Risks Sharing
Factors
9：1
8：2
Importance of one factor over another
7：3 6：4 5：5 4：6 3：7
2：8
Factors
1：9
Competitiveness or Conflict of
Interests in the Industry
Potential Communication Barrier
Risk Sharing of Task Environment Uncertainty
Past Reputation and Renown
Past Reputation and Renown
Past Reputation and Renown
Competitiveness or Conflict of
Interests in the Industry
Competitiveness or Conflict of
Interests in the Industry
Potential Communication Barrier
Risk Sharing of Task Environment Uncertainty
Risk Sharing of Task Environment Uncertainty
Potential Communication Barrier
Questionnaire sample scale respondents
Corporation
Mabile Telcos
Data Telcos
International
Telcos
President
Director
1
1
3
2
Depart.
Director
1
3
1
160
Supervisor
Manager
Forman
Total
2
2
1
1
2
5
1
4
10
10
10