資料的給定

首先，根據實際資料表的資訊，我們以成對比較的方式，來評斷評估目標間 的大小關係，並以二元變數T_ij來表示A_i與A_j間的絕對關係，我們將關係的定義

與標記整理成《表 6-1》。

《表 6-1：A_i與A_j間的絕對關係表示》

表示 標記

T = 1 ij A 絕對劣勢於_i A_j A_i A_j

T = 0 ij A 與_i A_j無絕對優劣關係 A_i A_j

我們沿用之前選出的 27 間學校，使用其中最重要的四個評估準則，並假設

四個評估準則全大於 的評估準則時， =1，意即 絕對優於 ，否則 =0，

表示彼此間的絕對優劣關係未定。整體的決策流程以《圖 6-1》來表示。以此規 則下，我們會得到評估目標間的競賽矩陣﹝見表 6.3﹞。

Ai

Aj T_ji A_i A_j T_ji

依據《圖 6-2》的判斷規則，我們將《表 6-8》的資料萃取出學校間已存在 的絕對關係，如以下所示。

學校代號如下所示

<表 6-2>

學校名稱 學校

代號

Faculty of Business Administration, Chinese Univ. of Hong Kong 1

Faculty of Business and Economics, Univ. of Hong Kong 2

Aetna School of Management, Shanghai JiaoTong University 3

Yonsei School of Business, Yonsei Univ., Seoul, South Korea 4

College of Management, National Chiao Tung University 5

College of Commerce, National Chengchi University 6

Indian Institute of Management, Ahmedabad 7

Indian Institute of Management, Bangalore 8

Indian Institute of Management, Calcutta 9

Faculty of Management Studies, Univ. of Delhi 10

Birla Institute of Technology & Science, Pilani, Rajasthan 11

Amity Business School, New Delhi 12

NUS Business School, Singapore 13

Nanyang Business School, Nanyang Technological Univ., Singapore 14

Asian Institute of Technology (AIT) School of Management, Thailand 15

Asian Institute of Management, Philippines 16

Sasin Graduate Institute of Business Administration, Chulalongkorn Univ.,

Thailand 17

Australian Graduate School of Management, Univ. of NSW 18

Macquarie Graduate School of Management, Macquarie Univ. 19

Monash Univ. Graduate School of Business 20

Brisbane Graduate School of Business Queensland, Univ. of Technology 21

Graduate School of Business, Curtin Univ. of Technology 22

Graduate School of Business, Univ. of Technology, Sydney 23

Centre for Executive Education, Waikato Management School, New Zealand 24

Adelaide Graduate School of Business, Univ. of Adelaide 25

Deakin Business School, Deakin Univ. 26

Victoria Graduate School of Business 27

以下是學校間的絕對優劣關係矩陣(競賽矩陣)

<表 6-3>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 17 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 24 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 25 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 26 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 27 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0

以下將一步步說明簡化過程的具體步驟與演算法。

《步驟一》

依據上述的競賽矩陣來建立每個評量目標A_i的優勢表。

所以，依照上述的演算法，我們可以得到學校原始的優勢表。各個學校右方 所列的學校代號，是表示與之相較之下具有絕對優勢的所有學校。

《表 6-4》偏好支援系統：未簡化之優勢表─2004 年 Asia Inc 所列學校為例

代號 學校 優於這些學校

1 Faculty of Business Administration, Chinese Univ. of Hong Kong 15、24、26、27 2 Faculty of Business and Economics, Univ. of Hong Kong 15、17、24、25、26、

27 3 Aetna School of Management, Shanghai JiaoTong University 26、27 4 Yonsei School of Business, Yonsei Univ., Seoul, South Korea 17、26 5 College of Management, National Chiao Tung University

6 College of Commerce, National Chengchi University

7 Indian Institute of Management, Ahmedabad 12、16 8 Indian Institute of Management, Bangalore 12 9 Indian Institute of Management, Calcutta

10 Faculty of Management Studies, Univ. of Delhi

11 Birla Institute of Technology & Science, Pilani, Rajasthan

12 Amity Business School, New Delhi

13 NUS Business School, Singapore 11、27

14 Nanyang Business School, Nanyang Technological Univ., Singapore 11 演算法

For i =1 to Total_Alternative-1 { For j = i+1 to Total_Alternative

{ If T =-1 _ij

{ i.child.add(j) ; // 將 node j 加入 node i 的 child_list 中 } elseif T =1 _ij

{ j.child.add(i) ; // 將 node i 加入 node j 的 child_list 中 } else T_ij =0

} }

15 Asian Institute of Technology (AIT) School of Management, Thailand 26、27 16 Asian Institute of Management, Philippines

17 Sasin Graduate Institute of Business Administration, Chulalongkorn Univ., Thailand

18 Australian Graduate School of Management, Univ. of NSW 16、22、24、25、26 19 Macquarie Graduate School of Management, Macquarie Univ. 16、17、21、22、25

20 Monash Univ. Graduate School of Business 16、17、21、22、23、

24、25、26、27 21 Brisbane Graduate School of Business Queensland, Univ. of Technology

22 Graduate School of Business, Curtin Univ. of Technology

23 Graduate School of Business, Univ. of Technology, Sydney 24、25、26 24 Centre for Executive Education, Waikato Management School, New

Zealand

25 Adelaide Graduate School of Business, Univ. of Adelaide

26 Deakin Business School, Deakin Univ.

27 Victoria Graduate School of Business

《步驟二》

為了使資訊量更精簡，我們利用遞迴的演算法來刪除每個評量目標 多餘

的優勢關係﹝意即可由遞移率所得到的優劣關係﹞

Ai

Remove B’ from A’s child_list ; } For each B’s child, C

{ Remove_child (A,C) ; } }

Algorithm

For each node i

For each i’s child, j For each j’s child, k

{ Remove_child (i,k) ; } Remove_child (A,B)

{

For each A’s child, B’

{ If B=B’

依照以上的演算法，我們可以將原始的亞洲學校優勢表《表 6-4》簡化成《表 6-5》。

《表 6-5》偏好支援系統：簡化後之優勢表─2004 年 Asia Inc 所列學校為例

代號 學校 優於這些學校

1 Faculty of Business Administration, Chinese Univ. of Hong Kong 15、24

2 Faculty of Business and Economics, Univ. of Hong Kong 15、17、24、25 3 Aetna School of Management, Shanghai JiaoTong University 26、27

4 Yonsei School of Business, Yonsei Univ., Seoul, South Korea 17、26 5 College of Management, National Chiao Tung University

6 College of Commerce, National Chengchi University

7 Indian Institute of Management, Ahmedabad 12、16 8 Indian Institute of Management, Bangalore 12 9 Indian Institute of Management, Calcutta

10 Faculty of Management Studies, Univ. of Delhi

11 Birla Institute of Technology & Science, Pilani, Rajasthan

12 Amity Business School, New Delhi

13 NUS Business School, Singapore 11、27

14 Nanyang Business School, Nanyang Technological Univ., Singapore 11 15 Asian Institute of Technology (AIT) School of Management,

Thailand 26、27

16 Asian Institute of Management, Philippines

17 Sasin Graduate Institute of Business Administration, Chulalongkorn Univ., Thailand

18 Australian Graduate School of Management, Univ. of NSW 16、22、24、25、26 19 Macquarie Graduate School of Management, Macquarie Univ. 16、17、21、22、25 20 Monash Univ. Graduate School of Business 16、17、21、22、23、27 21 Brisbane Graduate School of Business Queensland, Univ. of

Technology

22 Graduate School of Business, Curtin Univ. of Technology

23 Graduate School of Business, Univ. of Technology, Sydney 24、25、26 24 Centre for Executive Education, Waikato Management School, New

Zealand

25 Adelaide Graduate School of Business, Univ. of Adelaide

26 Deakin Business School, Deakin Univ.

27 Victoria Graduate School of Business

《步驟三》

利用修改過後的優勢表，我們建立每個評量目標A_i的劣勢表。

演算法

For each node, i

For each i's child, j

{ j.parent.add (i); //將 node i 加入 node j 的 parent_list 中 }

《步驟四》

利用以上所建立的優勢表與劣勢表，我們將所有結果匯整成「優劣關係總表」

﹝表 6-6.a﹞來顯示每個評估目標間相關的絕對大小關係，其中劣勢表表示絕對 優於A_i的評估目標，優勢表則表示絕對劣勢於A_i的評估目標。

《表 6-6.a 優劣關係總表》

評量目標 劣勢表﹝parentlist﹞ 優勢表﹝childlist﹞

A1 P₁₁、P₁₂… C₁₁、C₁₂… A2 P₂₁、P₂₂… C₂₁、C₂₂…

A 3 P₃₁、P₃₂… C₃₁、C₃₂…

… … …

A n P_n1、P_n2… C_n1、C_n2…

所以，依據《表 6-5》，我們可以產生亞洲商學院之間的優劣關係總表如下：

《表 6-6.b》偏好支援系統：優劣關係總表 ─ 2004 年 Asia Inc 所列學校為例

代號 學校 劣於這些學校 優於這些學

校 1 Faculty of Business Administration, Chinese Univ. of Hong

Kong 15、24

2 Faculty of Business and Economics, Univ. of Hong Kong 15、17、24、

25 3 Aetna School of Management, Shanghai JiaoTong University 26、27 4 Yonsei School of Business, Yonsei Univ., Seoul, South Korea 17、26 5 College of Management, National Chiao Tung University

6 College of Commerce, National Chengchi University

7 Indian Institute of Management, Ahmedabad 12、16

8 Indian Institute of Management, Bangalore 12

9 Indian Institute of Management, Calcutta

10 Faculty of Management Studies, Univ. of Delhi

11 Birla Institute of Technology & Science, Pilani, Rajasthan 13、14

12 Amity Business School, New Delhi 7、8

13 NUS Business School, Singapore 11、27

14 Nanyang Business School, Nanyang Technological Univ.,

Singapore 11

15 Asian Institute of Technology (AIT) School of Management,

Thailand 1、2 26、27

16 Asian Institute of Management, Philippines 7、18、19、20 17 Sasin Graduate Institute of Business Administration,

Chulalongkorn Univ., Thailand

2、4、13、19、

20

18 Australian Graduate School of Management, Univ. of NSW 16、22、24、

25、26 19 Macquarie Graduate School of Management, Macquarie Univ. 16、17、21、

22、25

20 Monash Univ. Graduate School of Business 16、17、21、

22、23、27 21 Brisbane Graduate School of Business Queensland, Univ. of

Technology 19、20

22 Graduate School of Business, Curtin Univ. of Technology 18、19、20

23 Graduate School of Business, Univ. of Technology, Sydney 20 24、25、26 24 Centre for Executive Education, Waikato Management School,

New Zealand 1、2、18、23

25 Adelaide Graduate School of Business, Univ. of Adelaide 2、18、19、23

26 Deakin Business School, Deakin Univ. 3、4、15、18、

23

27 Victoria Graduate School of Business 3、15、20

得到以上簡化後的資訊後，可以圖形化的方式表示學校間的優劣關係，如下所列：

<圖 6-3>表示簡化後的學校代號 1、2、3、4 的優劣關係。

<圖 6-4>表示簡化後的學校代號 7、8、13、14 的優劣關係。

<圖 6-5>表示簡化後的學校代號 18、19、20 的優劣關係。

<圖 6-6>表示簡化後的學校代號 15 與 23 的優劣關係，以及與其他學校不存在絕 對優劣關係的學校。

6.4 實例探討

依照此模式，決策者可以滿足他所想要的偏好,透過 Iterative 的方式可使 得前後關係不矛盾,在下面的例子中,我們呈現一個加入偏好的評比模式。

1. 假設有位學生甲生,想要比較亞洲商學院的優劣,他心中對某些學校已經有自

己既定的偏好,因此使用此偏好系統來排名亞洲商學院,在此先他選出一個欲 給定偏好的商學院。

2. 他選定 Monash Univ. Graduate School of Business 作為偏好決策選擇。

以下是 Monash Univ. Graduate School of Business 的優劣關係圖。

代號 學校 劣於這些學校 優於這些學

校 20 Monash Univ. Graduate School of Business 16、17、21、

22、23、27 可以看出除了 16、17、21、22、23、27 這些學校之外,其他與 Monash Univ.

Graduate School of Business 並無絕對的優劣關係,因此甲生給定一個偏好,給定

Faculty of Business and Economics, Univ. of Hong Kong優於 Monash Univ. Graduate School of Business。

3. 於是系統便修正競賽矩陣,我們便可依此修正亞洲商學院的優劣關係表,並成 為決策者給予下一個偏好的依據。

4. 接著,甲生再繼續給予以下的個人偏好,

.College of Management, National Chiao Tung University 優於 Nanyang

Business School, Nanyang Technological Univ., Singapore

.College of Management, National Chiao Tung University 優於 Indian

Institute of Management, Bangalore

. College of Commerce, National Chengchi University 優於 Indian Institute of Management, Calcutta

.Nanyang Business School, Nanyang Technological Univ., Singapore 優於 Indian Institute of Management, Bangalore

5. 以下是給予偏好後所修正的競賽矩陣:

<表 6-7> 給予偏好後所修正的競賽矩陣

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 17 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 24 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 25 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 26 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 27 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0

6. 我們以決策者所給的五個排序的偏好關係加入此偏好模式。根據決策者的偏 好，我們將其轉成下列限制式放入模式中，分別為：

．Faculty of Business and Economics, Univ. of Hong Kong 優於 Monash Univ.

Graduate School of Business → T_20,2 =1

．College of Management, National Chiao Tung University 優於 Nanyang Business School, Nanyang Technological Univ., Singapore → T_14,5 =1

．College of Management, National Chiao Tung University 優於 Indian Institute of Management, Bangalore → T_8,5 =1

．College of Commerce, National Chengchi University 優於 Indian Institute of Management, Calcutta → T_9,6 =1

．Nanyang Business School, Nanyang Technological Univ., Singapore 優於 Indian Institute of Management, Bangalore → T_8,14 =1

所以，經過 Rank-DEA 模式的重新計算，我們可以得到一組新的權重值為

，且針對 27 個亞洲商學院，會重新產生出一組新的排 名。

[

^{0.158,0.111,0.324,0.406}

]

經過計算後,可得到一組新的權重: <表 6-8>

SCI/SSCI Avg Tuition(US$) Avg GMAT score No of staff with PhD

0.158 0.111 0.324 0.406

並針對此 27 個商學院排名:<表 6-9>

學校 名次

Faculty of Business Administration, Chinese Univ. of Hong Kong 3

Faculty of Business and Economics, Univ. of Hong Kong 10

Aetna School of Management, Shanghai JiaoTong University 4

Yonsei School of Business, Yonsei Univ., Seoul, South Korea 16

College of Management, National Chiao Tung University 9

College of Commerce, National Chengchi University 7

Indian Institute of Management, Ahmedabad 2

Indian Institute of Management, Bangalore 5

Indian Institute of Management, Calcutta 11

Faculty of Management Studies, Univ. of Delhi 17

Birla Institute of Technology & Science, Pilani, Rajasthan 20

Amity Business School, New Delhi 13

NUS Business School, Singapore 1

Nanyang Business School, Nanyang Technological Univ., Singapore 6

Asian Institute of Technology (AIT) School of Management, Thailand 15

Asian Institute of Management, Philippines 22

Sasin Graduate Institute of Business Administration, Chulalongkorn Univ., Thailand 24

Australian Graduate School of Management, Univ. of NSW 12

Macquarie Graduate School of Management, Macquarie Univ. 14

Monash Univ. Graduate School of Business 8

Brisbane Graduate School of Business Queensland, Univ. of Technology 18

Graduate School of Business, Curtin Univ. of Technology 21

Graduate School of Business, Univ. of Technology, Sydney 19

Centre for Executive Education, Waikato Management School, New Zealand 23

Adelaide Graduate School of Business, Univ. of Adelaide 25

Deakin Business School, Deakin Univ. 27

Victoria Graduate School of Business 26

接著可用決策球模式計算出所有商學院的 X、Y、Z 值,如以下所列:

<表 6-10>

學校

代號 X Y Z

1 Faculty of Business Administration, Chinese Univ. of Hong Kong 0.6387 0.7371 -0.2206

2 Faculty of Business and Economics, Univ. of Hong Kong 0.69 0.6536 -0.3109

3 Aetna School of Management, Shanghai JiaoTong University 0.5843 0.6875 -0.4312

4 Yonsei School of Business, Yonsei Univ., Seoul, South Korea 0.7724 0.5169 -0.3691

5 College of Management, National Chiao Tung University 0.4658 0.663 -0.5861

6 College of Commerce, National Chengchi University 0.3223 0.6714 -0.6674

7 Indian Institute of Management, Ahmedabad 0.657 0.7394 0.1472

8 Indian Institute of Management, Bangalore 0.7169 0.6815 0.1471

9 Indian Institute of Management, Calcutta 0.8237 0.5622 0.0741

10 Faculty of Management Studies, Univ. of Delhi 0.858 0.5129 -0.0283

11 Birla Institute of Technology & Science, Pilani, Rajasthan 0.926 0.3627 -0.1048

12 Amity Business School, New Delhi 0.8128 0.5517 0.187

13 NUS Business School, Singapore 0.5929 0.7853 -0.1781

14 Nanyang Business School, Nanyang Technological Univ., Singapore 0.7083 0.6717 -0.2171

15 Asian Institute of Technology (AIT) School of Management, Thailand 0.7745 0.5358 -0.3361

16 Asian Institute of Management, Philippines 0.9402 0.296 -0.1686

17 Sasin Graduate Institute of Business Administration, Chulalongkorn Univ.,

Thailand 0.9108 0.2656 -0.3159

18 Australian Graduate School of Management, Univ. of NSW 0.8329 0.5529 0.0237

19 Macquarie Graduate School of Management, Macquarie Univ. 0.8432 0.5364 -0.0362

20 Monash Univ. Graduate School of Business 0.7279 0.6679 -0.155

21 Brisbane Graduate School of Business Queensland, Univ. of Technology 0.8952 0.3728 -0.2441

22 Graduate School of Business, Curtin Univ. of Technology 0.9281 0.3258 -0.1803

23 Graduate School of Business, Univ. of Technology, Sydney 0.9075 0.371 -0.1969

24 Centre for Executive Education, Waikato Management School, New Zealand 0.9318 0.2684 -0.2443

25 Adelaide Graduate School of Business, Univ. of Adelaide 0.9334 0.247 -0.2602

26 Deakin Business School, Deakin Univ. 0.9352 0.2156 -0.2808

27 Victoria Graduate School of Business 0.9181 0.2421 -0.3139

由上述實驗步驟所計算出的結果，我們可以將這些資訊繪製在一 3D 球上。

在此亞洲商學院之排序與分群模式中，我們可以清楚的看出商學院的排名。若球 面上的點越靠近北極點，則表示此商學院的排名越高。另外，商學院與商學院間 的幾何距離越近，則表示彼此間有較高的相似性與群聚關係。

圖 6-7

將商學院座標投影至球面上，由此分佈可看出,較劣的學校仍有群聚的現象 存在，而其他學校呈現較分散的情形。

第七章 結論與未來研究方向

7.1 研究成果

亞洲商學院的總排名一直以來受重視程度並不如歐美商學院,但隨著全球化 的趨勢亞洲商學院致力於維持他們自身的成長，也致力於獲得 The American Assembly of Collegiate Schools of Business ( AACSB )的認可,向全球化的 潮流邁進,以追求全球化的競爭力。

本研究主要的成果有以下幾點：

(1). 學術研究在亞洲商學院排名上佔了很重的比例。

(2). 本研究所提出的亞洲商學院評估模式，主要涵蓋了商學院排名與分群兩

(2). 本研究所提出的亞洲商學院評估模式，主要涵蓋了商學院排名與分群兩

在文檔中 亞洲商學院之排序與分群 (頁 62-0)