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Computing, Information and Control ICIC International c 2012 ISSN 1349-4198

Volume 8, Number 10(B), October 2012 pp. 7451–7465

EVALUATING INTERTWINED EFFECTS OF TEAM INTERNAL FACTORS ON PROJECT SUCCESS: A HYBRID METHOD

COMBINING EXPLORATORY FACTOR ANALYSIS AND THE DEMATEL TECHNIQUE

Don Jyh-Fu Jeng

Institute of International Management National Cheng Kung University

No. 1, University Road, Tainan City 70101, Taiwan jeng@mail.ncku.edu.tw

Received April 2011; revised September 2011

Abstract. Technology projects typically carry a high rate of failure. Project

manage-ment refers to disciplines that enhance managemanage-ment of inherent strengths and weaknesses of a project. In contrast to external factors, project management frequently ignores inter-nal factors. Such factors, involving interinter-nal services within the team, focus on working with people, ensuring customer satisfaction, and creating a conducive environment for the project team to deliver high quality products, which meet stakeholder expectations. This research investigated the intertwined effects of project team internal factors, and proposes a hybrid method that combines exploratory factor analysis and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to solve an empirical case. Exploratory factor analysis was applied for extracting the dimension and criteria structure of internal factors. The DEMATEL technique was then used to analyze the intertwined effect. This research found, in the dimensional level, attitude highly influ-ences other internal factors towards project success, while work loading is a key factor in criteria level that greatly influences all others. The proposed method has proven to be effective for analyzing the complex interrelation of human psychological concerns.

Keywords: Decision making trial and evaluation laboratory (DEMATEL), Exploratory factor analysis, Internal service, Project critical success factors, Project management

1. Introduction. Project management is important to control projects throughout the entire project life cycle for successful and enhanced project performance. Management can also have “strategic value when a clear connection is made between how efficiently and effectively a project is done and how the project’s products and services provide business value” [26] (p.19). Understanding controllable factors and the intertwined effects that affect performance of the project team is necessary to properly manage a project.

A significant amount of research has been conducted on project success factors within Western cultural settings (e.g., [1, 6, 43, 44]). However, most of these researches have focused on external factors of the team and rarely discuss how internal factors may in-fluence overall project success. External factors relate to factors which individual project group members cannot control, while internal factors relate to teamwork and interper-sonal skills. Previous studies have frequently neglected internal factors; however, they play a significant role in project success.

Because of the effect of culture on values and norms [17, 22], research needs to consider the cultural setting when investigating impact factors in non-Western settings. Research has not investigated the effect of internal factors within a Chinese cultural setting on project performance, and the literature on internal factors of project management is rare.

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Understanding the intertwined effect of internal factors on project success is critical to managers conducting projects. These criteria affecting project success are numerous and exhibit mutual influence.

This paper first reviews and identifies the hierarchical structure of internal factors that influence project success and then analyzes intertwined effects between the criteria. Ex-ploratory factor analysis is applied to extract the independent factors/criteria. Then, the DEMATEL technique [11, 12] is adopted to generate the impact relation map. The DE-MATEL technique is commonly used to illustrate the interrelations among criteria, which avoid “overfitting” in the Structural Equation Modeling (SEM) method of quantitative research [55]. The hybrid method proposed in this study uses a top-down approach that evades the mis-assumption of hypothesis development in social science studies.

The remainder of this paper is organized as follows. The research background and literature review on factors that affect project performance are presented in Section 2. Section 3 briefly introduces exploratory factor analysis and the DEMATEL technique. Section 4 presents an empirical study of internal factors on project success, and proposes a hierarchy structure with dimension and criteria and analyzes its intertwined effects by DEMATEL. Section 5 discusses the analysis result and draws implications. Finally, Section 6 presents concluding remarks.

2. Internal Factors Affecting Project Performance. Project performance metrics are key attributes and objectives which must be met or reached to consider a project successful [30]. Most researchers (i.e., [1, 6, 7, 30, 33, 43, 54]) agree that time, cost, and quality should be used as performance metrics and key determinants of project success. However, many scholars agree that success criteria should not be limited to time, cost, and quality [1, 30, 32, 54]. For instance, internal factors, cultural involved, highly influence the project performance of a team.

2.1. Cultural context. Culture, both national and corporate, can be defined as “the collective programming of the mind which distinguishes the members of one group or society from those of another” [18] (p.82). Each nation consists of dominant and non-dominant groups. All groups possess their own, and sometimes similar group-ideologies, beliefs, and values, but the national culture will resemble the largest or more influential dominant group. Therefore, understanding the underlying views of the dominant group is vital to understanding the views of people within that culture [51]. The findings of previous studies conducted in Western cultural settings have not been adequate when applied to the Chinese cultural context, which is highly influenced by the teachings of Confucius. “Confucian social theory is concerned with the question of how to establish a harmonious secular order in the man-centered world” [28] (p.65). The term guanxi (role-relationship) [21] is deeply embedded in Confucian social theory and King [28] uses the term architect to refer to Confucian individuals who build guanxi throughout their lifetime, creating their own social networks outside their family structure.

In terms of Taiwan, the study of Hofstede [17] found that Confucianism regarding unequal relationships ranked on the higher end of power distance, meaning hierarchal structures are common. For Confucianism concerning the importance of upholding ‘he’, or harmony, Hofstede [17] showed that the Taiwanese culture leans toward collectivism rather than individualism, meaning that individuals focus on group interest rather than their individual self. This is further supported by the findings of Gao [13], who conducted a study to understand Chinese speaking practices, and found that the self in Chinese culture, involves and is made up of multiple relationships. The last two dimensions (i.e., uncertainty avoidance and masculinity) in the Hofstede study [17] indicate that Taiwanese

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prefer to avoid uncertainty and demonstrate both masculine and feminine characteristics, as the masculinity score is modest. Further studies have confirmed that the work ethic of Taiwanese employees reflects both Confucian values and cultural dimensions [18, 19]. 2.2. Internal impact factors. The project performance of a team depends heavily on how well the team works together. The factors that affect these dynamics are the rela-tionships between team members, and the perceived quality of “internal services” between team members as workflows between them. The scope of internal-team factors for this study is limited to interactions and relationships between project group members.

In terms of workflow, the McGrath [37] paper on the theory of the group assumes groups to be “complex, intact social systems. . . that engage in purposeful activity at three partially nested levels: projects, tasks, and steps” (p.151). Work may flow from one team member to the next at the steps and tasks level. This workflow is an internal service between team members, and the interaction related to the work passed on to the next step is the service encounter. The service encounter is the “dyadic interaction between an internal customer and an internal service provider” [14] (p.35).

An internal customer evaluates the perceived quality of the service encounter by as-sessing individual internal service quality attributes to gain an overall perception of its quality [14]. Improving and managing perceived quality is important for organiza-tions. Researchers have found connections between high levels of internal service qual-ity and higher productivqual-ity, improved relationships between departments and groups, lower employee turnover, increased external customer satisfaction, and increased profits [14, 23, 41, 42, 45, 49].

Previous studies have mainly applied Western internal service quality attributes to the Taiwanese setting (e.g., [8, 9, 31, 36]), as organizational culture. However, culture, which is based largely on national culture, has a direct effect on internal service providers and internal customer values, norms, behavior, and thinking [4, 22, 47]. Applying Western attributes to an Eastern cultural setting could produce inadequate results, because cul-tural differences create unique workplaces with diverse views, values, and practices [18]. To overcome this limitation, Stanworth et al. [50] developed the Taiwanese based internal service quality (ISQ) attribute, derived from 29 service quality attributes.

Confucianism has shown to have an undisputable impact on the national and organiza-tional culture of Taiwan, where it is important to maintain harmony within relationships [18]. Studies related to group project performance within the Chinese context have shown that focusing on creating friendly relationships within organizations and groups can pos-itively affect project performance by increasing their odds of success [25, 27]. Bromiley and Cummings [2] found that a harmonious relationship based on trust lowers costs and shortens the time spent conducting business. Thus, relationships play a major role within Taiwan due to Confucian influence. Katz [27] found that high levels of internal commu-nication between all project members lead to higher project performance.

Based on the above literature reviews, this research adopted and slightly modified the ISQ structure of Stanworth et al. [50] as follows. Two items were removed when changing attributes from negative to positive (Incomplete Professional Knowledge and Quarrel), because they were polar opposites of positives already present (Detailed Pro-fessional Knowledge and Consensus), and one item was expanded into two separate items (Work Loading to Work Loading and Accessible) to better capture attribute complex-ity. This left 26 remaining attributes. Two trouble-shooting attributes from Pinto and Prescott [43] (trouble-shooting and handle deviations), and seven relationship attributes from Jin and Ling [25] were added to our list. Thus, the final scale investigated in this study was composed of 35 team internal factors, including friendly (chin-chieh), polite

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(ke-chi), patient, positive/proactive (jiji), responsible, trouble-shooting, able to handle deviations, please supervisor, competent, effective, detailed and professional knowledge, consensus, show empathy, shared objective, considerate, reliable, internal efficiency, ex-ternal efficiency, harmony, personnel connection, emotionally stable, inex-ternal communi-cation, litigation, risk exposure, change orders and claims, mutual understanding, client satisfaction, learning culture, help each other, cooperation, coordination, work loading, accessible, bureaucracy, and exchange thoughts.

3. Building a Hybrid Model for Intertwined Effects Analysis. This section in-troduces the concepts for establishing the intertwined effects structural model, combined factor analysis, and the DEMATEL technique. Quantifying a precise value in human psychological emotion is difficult. However, the complex phenomenon can be divided into many criteria to more easily judge differences or measure scores. The exploratory factor analysis method is commonly used to divide criteria into groups. These criteria may have interdependent relationships; therefore, the DEMATEL technique was used to construct interrelations between criteria.

3.1. Finding independent factors for building a hierarchical system. Based on a suitable measuring method, the criteria can be categorized into distinct aspects. When the evaluated criteria are too large to determine the dependent or independent relation with others, factor analysis can verify independent factors.

Exploratory factor analysis is a dimension reduction method of multivariate statistics, which explores the latent variables from manifest variables to uncover the underlying structure of a relatively large set of variables. This method explicitly breaks down the variability of criteria into a part attributable to the dimensions and shared with other cri-teria, while the other part is specific to a particular unrelated criterion to the dimensions. With the feature of exploratory factor analysis, a clear hierarchical structure in dimension and criteria can be extracted. The main procedure of exploratory factor analysis can be described in the following steps:

Step 1: Find the correlation matrix (R) or variance-covariance matrix for the objects

to be assessed.

Step 2: Find the eigenvalues (λk, k = 1, 2,· · · , m) and eigenvectors (βk = [β1k,· · · , βlk,

· · · , βpk]) for assessing the factor loading (alk =

λkβlk) and the number of factors (m).

Step 3: Consider the eigenvalue ordering (λ1 > · · · > λk > · · · > λm; λm > 1) to decide the number of common factors, and select the number of common factors to be extracted by a predetermined criterion.

Step 4: To facilitate the interpretation of factors, choose a rotation method. In this

study, the promax rotation method was applied, which allows the factors to be correlated.

Step 5: Name the factor referring to the combination of manifest variables.

When a large set of variables is factored, the method first extracts the combinations of variables, explaining the greatest amount of variance, and then proceeds to combinations that account for progressively smaller amounts of variance. Two types of criteria are used for selecting the number of factors: latent root criterion and percentage of variance criterion. The former criterion is that any individual factor should account for the variance

(V ar(Yk) = λk) of at least a single variable if it is to be retained for interpretation. In this

criterion, only the factors having eigenvalues greater than 1 (i.e., λk≥ 1, k = 1, 2, · · · , m)

are considered significant. The latter criterion is based on achieving a specified cumulative percentage of total variance extracted by successive factors. Its purpose is to ensure the

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extracted factors can explain at least a specified amount of variance. Practically, to be satisfactory, the total amount of variance explained by factors should be at least 95% in the natural sciences, and 60% in the social sciences. However, no absolute threshold has been adopted for all applications [15].

3.2. DEMATEL technique for building the structural model. DEMATEL [11, 12] is a comprehensive method for building and analyzing a structural model involving causal relationships between complex factors. The method was developed with the assump-tion that properly used scientific research methods could facilitate comprehension of the specific problematique, the cluster of intertwined problems, and contribute to recogni-tion of practical solurecogni-tions by a hierarchical structure. The methodology, according to the characteristics of objective affairs, can verify the interdependence among the vari-ables/attributes/criteria and confine the relation that reflects the characteristics with an essential system and evolution trend [5, 20]. The method is a practical and useful tool, especially for visualizing the structure of complex causal relationships with matrices or digraphs. The matrices or digraphs show a contextual relation between the elements of the system, in which a numeral represents the strength of influence of each element. Thus, the DEMATEL technique converts the relationship between the causes and effects of cri-teria into an intelligible structural model of systems [55]. Recently, DEMATEL technique has been widely applied in a number of disciplines, including airline safety [34], e-learning [53], decision-making [16, 33], knowledge management [48], operations research [39], tech-nology and innovation management [20], marketing and consumer behavior [55], theory validation [24], and others. The structure of DEMATEL and the calculation steps are described as follows.

Step 1: Calculate the direct-influence matrix by scores (depending on the views of

ex-perts) and evaluate the relationship among elements (called variables/attributes/crit-eria) of mutual influence, using the scale ranging from 0 to 4 (indicating “no influence (0),” to “very high influence (4)”). Subjects are asked to indicate the direct effect

they believe each element i exerts on every other element j, as indicated by dij. The

matrix D of direct relations is thus obtained, which shows the pairwise comparison of causal relationship. Assume there are n variables that impact the system, the direct-influence matrix D is illustrated as follows.

D =     0 d12 · · · d1n d21 0 · · · d2n .. . ... . .. ... dn1 dn2 · · · 0    

Step 2: Normalize the direct-influence matrix: based on the direct-influence matrix D , the normalized direct-relation matrix N is acquired using Equations (1) and (2).

N = D /u (1) u = max i,j { max i nj=1 dij, max j ni=1 dij } ; i, j ∈ {1, 2, · · · , n} (2)

Step 3: Attain the total-influence matrix: once the normalized direct-influence matrix N by summation for i or j is obtained, the total-influence matrix T is arrived at

through Equation (3), in which the I is denoted as the identity matrix.

T = N + N2+· · · + Nq

= N (I + N + N2+· · · + Nq−1) [(I − N )(I − N )−1]

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If q → ∞, then limq→∞Nq = [0]n×n, where N = [dij]n×n, 0 ≤ dij < 1, 0 <

(∑nj=1dij,

n

i=1dij)≤ 1, and either

n

j=1dij or

n

i=1dij equals 1, but not all. Based

on Equation (3), we may obtain

T = N (I − N )−1 (4)

Step 4: Analyze the results: in the stage, the sum of rows (given influence) and the

sum of columns (received influence) are separately expressed as influential vector d = (d1,· · · , di,· · · , dn)0 by factor j (j = 1, 2,· · · , n) and influential vector r = (r1,· · · , rj,· · · , rn)0 by factor i (i = 1, 2,· · · , n) using Equations (5)-(7). Then,

when i, j ∈ {1, 2, · · · , n} and i = j the horizontal axis vector (d + r) is made

by adding vector d to vector r , which exhibits total important influence of each

criterion. Similarly, the vertical axis vector (d − r) is built by deducting vector d

from vector r , which may separate criteria into a cause group and an effect group.

In general, when the value of di − ri is higher, the criterion belongs to the cause

group. On the contrary, if the value of di− ri is lower, the criterion belongs to the

effect group. Therefore, the impact relation map can be achieved by plotting the

data set of{(di+ ri, di− ri)|i = 1, 2, · · · , n}, which provides a valuable approach for

decision-making. T = [tij]n×n, i, j ∈ {1, 2, · · · , n} (5) d = [ nj=1 tij ] n×1 = [ti]n×1 = [di]n×1 (6) r = [ ni=1 tij ]0 1×n = [tj]n×1 = [rj]n×1 (7)

where vector d = (d1,· · · , di,· · · , dn)0 and vector r = (r1,· · · , rj,· · · , rn)0 express

the sum of rows and the sum of columns based on total-influence matrix T = [tij]n×n,

separately.

4. Empirical Study: Case of Project Success. The empirical experiment focused on firms that composed the project group. The study included two parts, the exploratory factor analysis, and DEMATEL analysis, described below.

4.1. Exploratory factor analysis to obtain independent criteria groups. The questionnaire was sent to several Taiwanese companies that have project groups consisting of Taiwanese working professionals, and it was explained that through the study, they can receive a clearer understanding of which factors are perceived to lead to greater project performance, which ultimately increases the probability of project success. Totally 224 questionnaires were collected for this study; 16 questionnaires were invalid, making 208 useable feedbacks.

In exploratory factor analysis, a clear structure emerged on the third iteration using a kappa rotation of 7. The Kaiser-Meyer-Olkin (KMO) and the Bartlett test are both acceptable on each iteration, with the lowest KMO being 0.949 and the highest Bartlett being 0.000. The Cronbach’s α and Pearson Correlation were also both acceptable on each iteration with the lowest α being 0.851 and the lowest correlation being 0.618. After iterations one and two, the original 35-item list reduced to a final 26 items, categorized into eight dimensions. Eigenvalues were all greater than 1 and all item-to-total correlations of items were above the cutoff value 0.5. Table 1 shows the exploratory factor analysis final iteration result, which lists the dimension and criteria extracted from our original 35 internal factors.

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Table 1. Dimension and criteria extracted Extracted Dimensions Items/Criteria Factor Loading Eigenvalues (Rotated) Item-to-Total Correlation Synergy (D1) Work Loading (C11) 1.22 14.27 0.79 Accessible (C12) 0.95 0.84 Reliable (C13) 0.90 0.79 Considerate (C14) 0.87 0.83 Coordination (C15) 0.83 0.87

Help each other (C16) 0.81 0.84

Cooperation (C17) 0.74 0.86 Consensus (C18) 0.68 0.83 Shared objective (C19) 0.63 0.75 Competence (D2) Trouble-shooting (C21) 0.95 12.08 0.80 Handle deviations (C22) 0.93 0.86 Positive/proactive (jiji) (C23) 0.86 0.85 Responsible (C24) 0.80 0.81 Attitude (D3) Polite (ke-chi) (C31) 1.08 9.93 0.77 Friendly (chin-chieh) (C32) 0.86 0.79 Patience (C33) 0.69 0.70 Relationship (D4) Learning culture (C41) 1.04 11.62 0.69 Client satisfaction (C42) 0.81 0.79 Bureaucracy (C43) 0.59 0.68 Consideration (D5) Shows empathy (C51) 0.85 10.43 0.75 Competent (C52) 0.84 0.73 Effective (C53) 0.53 0.69 Risk Exposure (D6) Risk exposure (C61) 0.86 4.92 N/A

Change orders and claims (C62) 0.80 N/A

Litigation (D7) Litigation (C71) 0.91 3.71 N/A

Personnel Connection (D8)

Personnel connection (C81) 0.84 2.49 N/A

4.2. DEMATEL method to find the interrelation between entwined criteria. According to the factor analysis results, 50 experts were invited to discuss the relationship and influence level of criteria under the same factor, and to score the relationship among criteria based on the DEMATEL method. These experts were the certified Project Man-agement Professional (PMP) of the Project ManMan-agement Institute (PMI) with at least ten years’ project management experience.

The initial direct-influence matrix D was then produced as shown in Table 2. Based on the direct-influence matrix, according to Equation (2), u = 60.64. The normalized direct-influence matrix N , as shown in Table 3, was then retrieved based on Equation (1). Subsequently, the total-influence matrix T was calculated as displayed in Table 4. The degree of influence in dimension level and criteria level are presented in Table 5 and Table 6, respectively. Based on the above analysis, the comprehensive impact relation map can be generated as illustrated in Figure 1.

5. Discussion and Implication. The proposed hybrid method combining exploratory factor analysis and the DEMATEL technique has proven to be an effective model for

evaluating complex psychological intertwined effects. Based on our empirical

experi-ments, exploratory factor analysis was used to classify each element/criteria into eight independent factors/dimensions. Those criteria under the same dimension had some in-terrelations with each other. The direct/indirect influential relationship of criteria was figured using the DEMATEL technique.

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T able 2. Direct-influence matrix D C11 C12 C13 C14 C15 C16 C17 C18 C19 C21 C22 C23 C24 C31 C32 C33 C41 C42 C43 C51 C52 C53 C61 C62 C71 C81 C11 0 3.38 1.32 3.18 2.96 3.56 3.22 2.16 0.98 2.5 3.2 1.04 1.9 2.68 2.56 3.64 0.78 1.64 2.8 2.92 1.52 3.52 3.38 2.58 2.74 0.48 C12 0.96 0 1.44 1.92 1.62 2.84 1.66 2.52 1.44 0.68 0.62 0.78 0.7 0.48 0.6 0.5 2.96 3.38 0.08 0.58 0.42 0.46 0.2 0.1 0.18 3.76 C13 2.1 0.98 0 0.38 0.4 0.44 0.4 0.3 0.36 0.68 0.86 1.02 3.6 1.64 1.9 1.46 0.52 3.58 0.04 0.96 2.5 0.78 0.06 0.04 0.08 3.08 C14 0.4 3.18 0.62 0 1.04 3.52 2.9 2.54 0.78 0.48 1.02 0.44 0.4 1.04 1.9 1.32 0.4 2.78 0.06 3.6 0.38 0.36 0.18 0.04 0.02 3.24 C15 2.12 0.74 0.42 1.04 0 3.34 2.68 3.02 2.84 3.14 3.2 1.1 0.76 1.26 0.84 2.78 0.78 3.32 0.06 1.52 2.3 2.82 0.04 0.04 0.1 1.58 C16 2.62 3.26 1.22 3.44 0.92 0 3.58 0.94 0.66 0.92 0.68 1 0.7 0.72 1.52 0.78 1.58 1.38 0.04 0.82 0.5 0.8 0.22 0.08 0.12 3.38 C17 0.78 0.6 0.3 0.4 0.68 3.18 0 3.36 3.5 0.72 0.48 0.26 0.84 0.44 0.34 0.24 2.54 1.72 0.06 0.2 0.38 2.88 0.12 0.06 0.84 2.76 C18 0.62 0.4 0.32 0.7 0.8 0.66 0.84 0 3.12 0.62 0.72 0.06 0.32 0.28 0.1 0.08 2.24 2.58 0.08 0.22 0.2 2.86 0.1 0.06 0.04 0.66 C19 0.32 1.46 0.48 0.26 1.06 1.38 1.46 2.38 0 0.74 0.96 0.1 0.68 0.1 0.06 0.08 0.9 2.94 0.1 0.06 0.12 3.1 0.06 0.08 0.02 0.32 C21 1.9 0.26 0.4 0.28 2.36 0.86 0.56 0.38 0.28 0 1.14 0.5 0.58 0.38 0.32 3.32 0.32 2.88 0.1 0.42 3.36 1.46 0.08 1.32 0.26 0.38 C22 0.48 0.52 0.3 0.98 2.56 0.46 0.82 0.74 1.38 2.26 0 0.9 0.44 0.94 0.66 1.28 0.56 2.78 0.04 0.36 3.06 0.94 0.06 0.08 0.96 0.5 C23 2.46 0.56 0.38 0.34 0.32 1.04 0.68 0.44 0.32 0.16 0.36 0 1.76 0.44 0.4 0.26 2.18 2.7 0.04 0.2 2.54 1.9 0.22 0.04 0.78 1.84 C24 1.98 0.4 0.46 0.32 0.34 0.42 0.36 0.34 0.3 0.22 0.24 0.96 0 0.26 0.24 0.12 1.06 1.58 0.06 0.16 0.52 0.3 0.08 0.06 0.2 0.66 C31 0.9 3.18 0.42 0.64 2.96 0.78 0.48 0.5 0.38 0.16 0.66 0.42 0.28 0 2.1 0.74 2.28 3.34 0.04 0.26 0.14 0.4 0.1 0.06 0.04 3.52 C32 0.94 3.62 0.86 0.74 0.64 0.82 0.86 0.6 0.64 0.38 0.42 0.54 0.58 1.34 0 0.64 1 3.3 0.04 1.06 0.5 0.7 0.1 0.06 0.02 3.78 C33 0.96 1.18 0.54 0.4 1.38 0.36 0.24 0.2 0.16 0.1 1.84 0.2 0.4 0.3 0.26 0 1.52 2.36 0.08 0.42 0.36 1.22 0.06 0.04 0.04 2.58 C41 0.4 0.62 0.3 0.2 0.96 1.58 1.82 1.7 2.02 0.32 0.66 0.1 0.2 0.18 0.14 0.06 0 2.12 1 0.1 0.16 1.38 1.34 1.4 0.86 0.5 C42 2.16 0.26 0.1 0.14 1.84 0.72 1.76 0.48 2.58 0.56 0.62 0.4 0.28 0.38 0.5 0.36 2.16 0 0.04 0.28 0.54 0.7 0.06 0.04 0.04 2.7 C43 3.36 0.02 0 0 0.22 0 0.32 0.38 0.1 0.22 0.2 0 0.04 0 0 0 0.7 0 0 0 0 0.02 1.64 3.7 3.8 0 C51 0.58 2.3 0.38 3.58 0.44 3.12 1.04 0.62 0.48 0.26 0.44 0.5 0.38 1.16 1.32 0.74 1.44 2.1 0.04 0 0.3 0.56 0.12 0.06 0.04 3.12 C52 1.92 0.22 0.12 0.08 0.18 0.92 0.68 0.24 0.32 2.26 1.96 0.38 0.52 0.08 0.08 0.1 1.44 2.92 0.04 0.12 0 1.78 0.06 0.04 0.06 0.56 C53 0.66 0.38 1.02 0.28 0.62 0.22 0.54 0.64 0.44 0.32 1.42 1.36 0.38 0.12 0.1 0.4 1.62 2.4 0.04 0.18 1.08 0 0.1 0.04 0.06 0.2 C61 2.12 0.08 0.06 0.08 0.06 0.04 0.06 0.04 0.04 0.16 0.06 0.04 0.06 0.04 0.02 0.04 0.8 0 2.38 0.06 0.04 0.04 0 3.52 3.62 0 C62 3.54 0 0 0.16 1.58 0.12 1.38 1.32 1.16 2.16 2.1 0 0.06 0 0 0.3 1.1 0 0.3 0.1 0.04 0.2 3.6 0 3.5 0 C71 0.1 0 0 0 0 0 0 0 0 0.06 0 0 0 0 0 0 0 0 0.88 0 0 0 3.9 3.4 0 0 C81 1.06 3.16 1.38 1.28 3.6 1.7 1.52 2.92 1.3 1.18 1.58 0.84 0.64 2.58 2.06 0.4 1.46 3.02 0.04 1.16 0.5 0.86 0.1 0.06 0.04 0

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T able 3. Normalized direct-influence matrix N 10 4 ) C11 C12 C13 C14 C15 C16 C17 C18 C19 C21 C22 C23 C24 C31 C32 C33 C41 C42 C43 C51 C52 C53 C61 C62 C71 C81 C11 0 557 218 524 488 587 531 356 162 412 528 172 313 442 422 600 129 270 462 482 251 580 557 425 452 79 C12 158 0 237 317 267 468 274 416 237 112 102 129 115 79 99 82 488 557 13 96 69 76 33 16 30 620 C13 346 162 0 63 66 73 66 49 59 112 142 168 594 270 313 241 86 590 7 158 412 129 10 7 13 508 C14 66 524 102 0 172 580 478 419 129 79 168 73 66 172 313 218 66 458 10 594 63 59 30 7 3 534 C15 350 122 69 172 0 551 442 498 468 518 528 181 125 208 139 458 129 547 10 251 379 465 7 7 16 261 C16 432 538 201 567 152 0 590 155 109 152 112 165 115 119 251 129 261 228 7 135 82 132 36 13 20 557 C17 129 99 49 66 112 524 0 554 577 119 79 43 139 73 56 40 419 284 10 33 63 475 20 10 139 455 C18 102 66 53 115 132 109 139 0 515 102 119 10 53 46 16 13 369 425 13 36 33 472 16 10 7 109 C19 53 241 79 43 175 228 241 392 0 122 158 16 112 16 10 13 148 485 16 10 20 511 10 13 3 53 C21 313 43 66 46 389 142 92 63 46 0 188 82 96 63 53 547 53 475 16 69 554 241 13 218 43 63 C22 79 86 49 162 422 76 135 122 228 373 0 148 73 155 109 211 92 458 7 59 505 155 10 13 158 82 C23 406 92 63 56 53 172 112 73 53 26 59 0 290 73 66 43 359 445 7 33 419 313 36 7 129 303 C24 327 66 76 53 56 69 59 56 49 36 40 158 0 43 40 20 175 261 10 26 86 49 13 10 33 109 C31 148 524 69 106 488 129 79 82 63 26 109 69 46 0 346 122 376 551 7 43 23 66 16 10 7 580 C32 155 597 142 122 106 135 142 99 106 63 69 89 96 221 0 106 165 544 7 175 82 115 16 10 3 623 C33 158 195 89 66 228 59 40 33 26 16 303 33 66 49 43 0 251 389 13 69 59 201 10 7 7 425 C41 66 102 49 33 158 261 300 280 333 53 109 16 33 30 23 10 0 350 165 16 26 228 221 231 142 82 C42 356 43 16 23 303 119 290 79 425 92 102 66 46 63 82 59 356 0 7 46 89 115 10 7 7 445 C43 554 3 0 0 36 0 53 63 16 36 33 0 7 0 0 0 115 0 0 0 0 3 270 610 627 0 C51 96 379 63 590 73 515 172 102 79 43 73 82 63 191 218 122 237 346 7 0 49 92 20 10 7 515 C52 317 36 20 13 30 152 112 40 53 373 323 63 86 13 13 16 237 482 7 20 0 294 10 7 10 92 C53 109 63 168 46 102 36 89 106 73 53 234 224 63 20 16 66 267 396 7 30 178 0 16 7 10 33 C61 350 13 10 13 10 7 10 7 7 26 10 7 10 7 3 7 132 0 392 10 7 7 0 580 597 0 C62 584 0 0 26 261 20 228 218 191 356 346 0 10 0 0 49 181 0 49 16 7 33 594 0 577 0 C71 16 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 145 0 0 0 643 561 0 0 C81 175 521 228 211 594 280 251 482 214 195 261 139 106 425 340 66 241 498 7 191 82 142 16 10 7 0

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T able 4. T otal-influence matrix T 10 4 ) C11 C12 C13 C14 C15 C16 C17 C18 C19 C21 C22 C23 C24 C31 C32 C33 C41 C42 C43 C51 C52 C53 C61 C62 C71 C81 C11 367 875 360 755 800 930 856 671 459 635 790 314 464 608 605 802 488 838 539 647 468 880 702 587 628 530 C12 344 211 324 453 467 680 495 623 444 242 258 211 215 201 225 198 686 885 53 205 188 282 92 73 89 863 C13 517 346 80 182 256 250 235 206 208 230 285 247 673 377 421 343 273 882 45 248 517 290 65 57 69 723 C14 259 754 204 187 383 818 696 635 344 209 318 163 165 300 445 330 312 817 39 691 178 263 75 48 55 846 C15 582 370 181 352 265 801 693 728 700 685 729 290 247 341 280 618 400 982 58 370 556 737 78 78 97 570 C16 608 766 304 716 374 275 811 404 320 290 282 256 229 258 392 266 485 602 56 273 213 347 109 79 96 845 C17 275 264 129 182 276 677 183 717 734 222 209 114 212 159 146 125 588 564 44 107 155 650 76 64 185 626 C18 198 163 101 177 240 224 258 120 620 173 208 59 103 98 71 76 478 609 37 86 103 588 51 45 42 228 C19 163 326 130 117 282 340 358 500 134 197 247 71 165 71 66 80 282 671 35 60 99 626 39 42 37 193 C21 469 170 125 142 530 290 244 193 181 128 339 147 167 142 132 644 206 714 53 145 652 397 76 264 106 237 C22 228 207 104 240 554 228 278 255 360 478 133 207 140 224 181 310 240 708 32 130 606 312 54 60 196 256 C23 534 224 125 150 192 313 257 202 179 127 179 63 355 152 148 125 497 661 51 105 496 448 102 67 186 450 C24 398 145 110 111 138 158 147 133 123 93 108 191 45 93 91 76 253 383 38 73 139 135 54 47 72 200 C31 302 691 151 224 662 324 267 272 241 147 249 144 125 109 446 225 549 837 39 137 127 227 64 54 54 800 C32 300 757 221 242 287 319 310 273 262 164 193 159 174 321 108 195 347 815 35 258 173 258 59 49 47 838 C33 260 302 141 145 354 183 162 153 142 103 397 87 120 124 115 73 363 579 38 130 140 306 46 40 45 553 C41 192 193 94 104 262 368 415 395 451 134 198 61 83 81 76 70 125 516 195 63 90 348 278 289 212 206 C42 464 184 79 118 441 278 433 239 554 194 223 122 114 147 163 149 481 232 44 118 174 276 63 56 60 579 C43 645 69 28 57 120 79 138 138 81 113 119 26 43 45 43 64 178 84 64 47 43 84 404 714 734 49 C51 246 582 148 715 251 706 369 289 237 144 197 155 140 296 336 216 414 633 34 112 138 237 63 48 50 761 C52 418 128 66 86 153 257 225 136 157 447 411 113 138 74 74 103 340 648 38 74 93 402 55 54 58 204 C53 198 131 199 96 187 125 178 184 163 117 302 259 113 66 64 119 356 542 27 70 247 96 47 36 44 139 C61 443 62 31 55 76 64 79 68 56 88 78 25 37 39 35 53 182 63 435 44 38 63 128 680 698 38 C62 702 105 48 114 385 157 351 338 305 458 458 49 71 71 67 160 287 188 129 87 108 184 701 137 688 102 C71 95 12 6 12 30 16 28 27 23 44 34 5 8 8 8 15 31 18 182 10 11 17 698 624 95 10 C81 380 735 322 368 803 529 484 701 443 347 434 234 216 544 469 214 480 891 45 306 233 371 73 64 68 315

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Table 5. Influence of concern factors in the dimension level di ri di+ ri di− ri D1 0.2676 0.2185 0.4861 0.0492 D2 0.1748 0.1462 0.3210 0.0287 D3 0.2083 0.1409 0.3493 0.0674 D4 0.1723 0.2468 0.4191 −0.0746 D5 0.1576 0.1567 0.3143 0.0009 D6 0.1895 0.1765 0.3660 0.0131 D7 0.0917 0.1575 0.2492 −0.0659 D8 0.2473 0.2660 0.5133 −0.0187

Table 6. Influence of concern factors in the criteria level

di ri di+ ri di− ri C11 1.6598 0.9587 2.6185 0.7011 C12 0.9005 0.8771 1.7776 0.0234 C13 0.8021 0.3812 1.1833 0.4210 C14 0.9532 0.6098 1.5630 0.3434 C15 1.1789 0.8766 2.0555 0.3024 C16 0.9657 0.9388 1.9045 0.0269 C17 0.7684 0.8949 1.6633 −0.1266 C18 0.5156 0.8601 1.3757 −0.3446 C19 0.5330 0.7920 1.3250 −0.2589 C21 0.6893 0.6211 1.3105 0.0682 C22 0.6722 0.7378 1.4100 −0.0656 C23 0.6389 0.3773 1.0162 0.2616 C24 0.3556 0.4563 0.8118 −0.1007 C31 0.7468 0.4947 1.2415 0.2521 C32 0.7163 0.5205 1.2368 0.1957 C33 0.5101 0.5650 1.0751 −0.0548 C41 0.5497 0.9320 1.4817 −0.3824 C42 0.5986 1.5364 2.1350 −0.9378 C43 0.4211 0.2386 0.6597 0.1824 C51 0.7515 0.4594 1.2109 0.2921 C52 0.4952 0.5986 1.0938 −0.1034 C53 0.4106 0.8824 1.2930 −0.4718 C61 0.3657 0.4253 0.7910 −0.0596 C62 0.6449 0.4351 1.0801 0.2098 C71 0.2067 0.4713 0.6781 −0.2646 C81 1.0068 1.1162 2.1230 −0.1093

A clear structure of the team-internal impact factors for project performance within the Taiwanese cultural context was created through exploratory factor analysis (see Table 1). By combining the 26 attributes of ISQ from Stanworth et al. [50], two trouble-shooting attributes from Pinto and Prescott [43], and the seven relationship attributes from Jin and Ling [25], the final scale investigated in this study comprised 35 attributes. Exploratory factor analysis was then conducted to extract a final structure of eight dimensions and 26 criteria: Synergy (9 criteria), Competence (4 criteria), Attitude (3 criteria), Relationship

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Figure 1. Comprehensive dimension and criteria impact relation map

(3 criteria), Consideration (3 criteria), Risk Exposure (2 criteria), Litigation (1 criterion), and Personnel Connection (1 criterion) (see Table 1).

According to DEMATEL analysis, the factors showing greater values of di+ riintensely

affect the others, the factors showing lesser values of di− ri are intensely affected by the

others. Figure 1 shows a clear picture of intertwined effect between dimensions and

criteria.

Based on Figure 1, in the dimensional level, attitude (D3) plays a significant role that

highly influences other internal factors towards project success. However, relationship

(D4) is impacted by all dimensions. Personal connection (D8) highly relates with other

dimensions. Furthermore in cross-dimensional, work loading (C11) is a key factor that

greatly influences all other criteria, while ultimately meeting customer satisfaction (C42).

Bureaucracy (C43) and litigation (C71) show less relationship with other factors.

Project leadership requires more than mere technical competence and encompasses the ability to manage a team. Kloppenborg and Petrick [29] stated that skills in managing relationships are critical to satisfy stakeholders through all stages of the project. Creating right relationships between team members is one of the largest challenges project man-agers face [3, 40, 52]. Whitty [56] mentioned, “projects are simply a synthesis of human sensations and expectations about how multiple resources are to be used” (p.577). Rop-ponen and Lyytinen [46] indicated that personnel management is one of the major risk components in software development projects. The above evidences highlight the impor-tance of understanding the interrelation of project team internal factors. Operationally, Okuhara et al. [38] proposed a genetic algorithm method to the worker and workload assignment problem in project management. However, the approach omits the human

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factors internally within the project team which may eventually impact the success of project.

The result of this study clearly shows the intertwined effects of team internal factors on project success. Because workloading is a key influencer, when more resources such as people, are needed than are available, the project manager needs to reschedule tasks concurrently or even sequentially to manage the constraint. The project manager should apply resource leveling to resolve schedule conflicts instead of overloading work to a single resource. The project team should emphasize positive attitude to create a harmonious working environment to further build team synergy. From the internal service point of view, Jeng [23] stated that rewards and recognition can be the best strategy to enhance internal service operation of a team.

6. Concluding Remarks. This research proposed a hybrid method combining factor analysis and the DEMATAL technique. Supported by previous qualitative studies, ex-ploratory factor analysis was applied to extract a clear factor structure consisting of dimension and criteria. Then, the DEMATEL technique was utilized to analyze the in-tertwined effect between the extracted dimension and criteria. The proposed method is capable of analyzing the interrelation of complex human factors in social science research. The impact relation map provides the project manager a clear picture on the affect of internal factors on project performance. A project manager may set strategies to better manage the working environment and team atmosphere. The result provides directions to enhance team synergy, increase relationships, and ultimately achieve project success. This study also provides information for a company to further adopt an effective training agenda and employee assistance programs (EAPs) to improve the working atmosphere of a project team. Future research may extend the proposed hybrid method with multi-ple criteria decision-making (MCDM) on managing project portfolio, for instance, fuzzy MCDM algorithm [10, 23], and grey relational analysis (GRA) [20].

Acknowledgement. The author would like to thank the anonymous reviewers for their

valuable comments and suggestions to improve the quality of the paper. He is also grateful to Dr. James Stanworth for introducing the ISQ problem, along with discussion; and to Johanna Owen and Logan Reittinger for their assistance and literature survey.

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數據

Table 1. Dimension and criteria extracted Extracted Dimensions Items/Criteria Factor Loading Eigenvalues(Rotated) Item-to-TotalCorrelation Synergy (D 1 ) Work Loading (C 11 ) 1.22 14.27 0.79Accessible (C12)0.950.84Reliable (C13)0.900.79Considerate (C14)0.8
Table 5. Influence of concern factors in the dimension level d i r i d i + r i d i − ri D 1 0.2676 0.2185 0.4861 0.0492 D 2 0.1748 0.1462 0.3210 0.0287 D 3 0.2083 0.1409 0.3493 0.0674 D 4 0.1723 0.2468 0.4191 −0.0746 D 5 0.1576 0.1567 0.3143 0.0009 D 6 0.1
Figure 1. Comprehensive dimension and criteria impact relation map

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