神經網路與非線性模式的求解(1/2)

行政院國家科學委員會補助國內專家學者出席國際學術會議報告

92 年 5 月 6 日

附

件

三

報告人姓名

蔡瑞煌

服務機構

_及職稱

國立政治大學資訊管理學系

教授

時間

會議

地點

From 1 to 3 August 2002

Los Angle

本會核定

補助文號

NSC-91-2416-H-004-009

會議

名稱

(中文)2002 年旅美管理學界華人學術研討會

(英文)ACME2002

發表

論文

題目

(中文) 混沌時間序列資料之預測

(英文) The Management of Chaotic time-series data

報告內容應包括下列各項：

一、參加會議經過

會議行程請參考附件.在 Q&A 時, 很多學者針對我的文章發言, 討論熱烈.

二、與會心得

此會議提供了一個良好的機會, 讓亞太地區 (以美國為主體) 的管理科學學者共聚一堂,

探討彼此都感興趣之議題. 我是收獲良多.

三、考察參觀活動(無是項活動者省略)

無.

四、建議

可以多鼓勵學者參與類似的會議.

五、攜回資料名稱及內容

a CD for the proceeding papers of ACME2002 conference.

六、其他

THE MANAGEMENT OF CHAOTIC TIME-SERIES DATA

Ray Tsaih

Department of MIS, College of Commerce, National Chengchi University 64, Chih-Nan Road, Sect 2, Wenshan,

11623 Taipei, Taiwan Phone: 886-2-29387243

ABSTRACT

There are no studies probed into a multilayered Perceptron with Back Propagation learning algorithm (BP system) after it has learned chaotic time-series data, nor any studies on whether BP system can effectively manage a chaotic time-series data. This study examines a BP system and explores if it can effectively manage a chaotic time-series data. We find that the BP system may display various qualitative types of behavior for different values of weights: periodic cycles of different lengths and chaos. Also, chaotic time-series data with a large fluctuation will lead the BP system to yield a chaotic time-series data with a poor prediction effect. It seems that a BP system may manage badly a chaotic time -series data.

keywords : Back Propagation learning algorithm, Time-series Data, Chaos

INTRODUCTION

In modern finance, derivatives such as futures and options play increasingly prominent roles in risk management and price speculative activities. Owing to the high-leverage characteristic involved in derivative trading, investors can gain enormous profits with a small amount of capital if they can accurately predict the market’s direction. Financial markets, however, can be influenced by many factors, such as, political events, general economic conditions, and traders’ expectations. Predicting the financial market’s movements is considered to be rather difficult in general . Movements in market prices are not random. Rather, they behave in a highly nonlinear, dynamic manner. The standard random walk assumption of futures prices may merely be a veil of randomness that shrouds a messy nonlinear process (see, for example, Blank, 1991; DeCoster, Labys & Mitchell, 1992; Grudnitski & Osburn, 1993). To make the forecasting of futures prices more reliable, the application of Artificial Neural Networks (ANN), especially the multi-layered feed-forward network (Rumelhart, et. al., 1986), have received extensive attention (Grudnitski & Osburn, 1993; Hutchinson, Lo & Poggio, 1994; Tsaih, Hsu & Lai, 1998).

Since 1984, deterministic chaos has been hailed as a revolution in thought and attracted ever increasing atte ntion of many scientists and technologists from diverse disciplines including biology, computation, engineering, economics, mathematics, meteorology, physics, statistics and many others. At the same time, since 1986, many researchers and practitioners have recognized that ANN is one of the ideal tools for managing the nonlinear environment. In the context of traditional statistical methods, the ANN can be considered as a multivariate nonlinear non-parametric inference technique that is data driven and model free. “Multivariate” implies that the ANN inputs

350

resurgence of ANNs because it can solve nonlinearly separable problems that remained unsolved by the previously invented Neural Networks, such as Perceptron (Rosenblatt, 1958).

There have been research and applications of the BP system to chaotic time-series data (Wong, 1991) (Matsuba, Masui & Hebishima, 1992) (Adachi et. al., 1992), time-series forecasting of financial markets (Azoff, 1994), and uncovering nonlinear structure in a stock market (Abhyankar et. al., 1997). Nevertheless, they have not examined the BP system after being trained on (chaotic) time-series data, and made a further study of whether it is proper to apply a BP system to such a time-series data.

Suppose we train the BP system with chaotic time-series data. Its purpose is to predict the sequence xm+1 ~ xm+q

based on the current input sequence x1 ~ xm. The BP system may have m+q-1 input nodes, p hidden nodes and q

output nodes, and all hidden and output nodes use the following hyperbolic tangent (tanh) activation function (cf. (Rumelhart, et. al., 1986)):

tanh(x) ≡

e

e

e

e

x -x -x x

+

−

(1)

That is, the following output value of the lth output node tries to estimate xm+l:

Ol≡tanh(3wl0+ p 1 i= ∑ 3wli tanh(2wi0+ 1 -q m 1 j + =

∑

2wij xj)) (2)

where 2wi0 is the bias of the ith hidden node, 2wij is the weight between the variable xj and the ith hidden node, 3wl0 is

the bias of the lth output node, and 3wli is the weight between ith hidden node and the lth output node. The BP

system tries to catch the time structure embedded in time-series data. A question for such application is that, suppose the training time-series data is chaotic, can the BP system after learning generate exactly the same chaotic time-series data?

The learning algorithm of the BP system adopts the generalized delta rule. That is, the learning algorithm is defined to minimize an objective function to find the optimal arrangement of weights via using the gradient descent method. The sum of error square is usually adopted as the objective function. The highly nonlinear property of the objective function leads to the notorious predicament of the relatively optimal learning result.

Hornik et. al., (1989) mention that the BP system acts just as an approximator. This conclusion comes from the fact that the value of the error term at the conclusion of learning is usually not zero. Even if the error term value at the end of learning is zero, it merely means that the BP system has perfectly learned the training data, not that the BP system has any perfect prediction ability. (Barron, 1991; Barron, 1992) mention that “when the network is exposed to test data that has not been seen before, the network function acts as an estimator of new points of the target function.” Due to the facts that the BP system is an estimator, and that the chaos has the property of sensitive dependence on initial condition, it seems the BP system will not generate the same chaotic time -series data.

Yet further questions remain: Will the time-series data yielded from the BP system be a chaotic one? If the time-series data yielded from the BP system is a chaotic one, how well does this time-series data mimic the time-series data the BP system just learns? If the BP system yields a non-chaotic time-series data, how large will the error be? These questions are unsolved, and motivate this study.

For this study, we set up an experiment with the following finite-difference equation (cf. (Kaplan & Glass, 1995b)) adopted to derive time -series data that are used as the trai ning data for the BP system:

xt+1 = f(xt) ≡ R xt (1 - xt) (3)

To answer the questions mentioned above, we examine the time-series data yielded from the BP system after learning, and see how well it predicts the behavior of the trained time-series data. To examine if the BP system yields a chaotic time-series data, we verify the value of Lyapunov exponent of the time-series data gene rated from the BP system.

Experimental Design

Equation (3) with variant values of R is used here, and the experimental design is arranged as five blocks of variant values of R: (1) less than 3.5, (2) 3.56 to 3.65, (3) 3.72 to 3.76, (4) 3.81 to 3.86, and (5) greater than 3.9. For each value of R, there are 2000 training data1 generated from equation (3). That is, the pairs of input and its associated desired output of training data are {(xt, xt+1), t = 0, 1, …, 1999}, where xt+1 = R xt (1 - xt).

The BP system tries to catch the time structure embedded in the training time-series data. The output value Ot of

BP system is arranged as follows:

Ot≡tanh(3w0+ 3

1 i=

∑ 3wi tanh(2wi0+2wi1xt)) (4)

After learning, Ot is a function of xt, and tries to estimate xt+1 of equation (3).

For each case, each network system has 10 repetitions with different initial weights. The stopping rule for learning is the satisfaction of either the value of

1999 0 t∑=

(xt+1 – Ot)2 less than 10-25 or learning iterations greater than

250000.

After learning, we assess the following MRE (mean ratio of error) with respect to the learning and the prediction. To test the learning effect, the pairs of input and its associated desired output are {(xt, xt+1), t = 0, 1, …, 1999}

generated from equation (3) with x0 being designed as in Table 1; to test the prediction effect, the pairs of input and

its associated desired output are {(xt, xt+1), t = 0, 1, …, 1999} generated from equation (3) with x0 = 0.49999. In

principle, the smaller MRE, the better the result.

2 / 1 1999 0 2 1 1 2000                       − =

∑

= + + t t t t X O X MRE (5)

To examine if the BP system g yields a chaotic time -series data, we generate a time-series data from the BP system, i.e., {Ot, t = 0, 1, …, 2000}, with O0 equals x0 designed as in Table 1 and

Ot+1≡tanh(3w0+ 3

1 i=

∑3witanh(2wi0+2wi1 Ot)) (6)

The Lyapunov exponent (i.e., λ1) regarding the time-series data generated from the BP system is calculated with the

following equation:

λ1 = log || J1．J2 ．．． J2000|| (7)

where Jt is the derivative of Ot, i.e.,

Jt≡(1-Ot2) 3

1 i∑=

(1-(tanh(2wi0+2wi1Ot-1))2)3wi 2wi1 (8)

If the value of λ1 is positive, we say the time-series data generated from the BP system is a chaotic one.

Table 2 shows the test summary if the time-series data generated from the BP system is chaotic, and the ave rage MRE values regarding the learning and the prediction. The following facts are obtained from the experimental results:

352

2. From Table 2, when the trained time-series data is non-chaotic, the BP system after learning may yield a non-chaotic or chaotic time -series data; as for the cases of chaotic training time-series data, the BP system after learning may also yield a non-chaotic or chaotic time-series data.

3. Most of the non-chaotic training time-series data lead to yielding a non-chaotic time-series data. Ho wever, in the cases of R = 3.74, 3.83 or 3.84, where the characteristic of the time-series data is a stable cycle of odd period, most of λ1 of the BP system are positive. As for the cases of chaotic training time-series data, there

is no pattern.

4. The average MRE values of all cases are rather small, except the case of R = 4.0. It seems that the chaotic time-series data with a large fluctuation leads the BP system, after learning, to generate a chaotic time -series data with a poor prediction effect.

5. With respect to non-chaotic time-series data, the average MRE values of learning and prediction were almost the same.

In summary, the multi-dimensional finite-difference equation (6) (i.e., the BP system) may display various qualitative types of behavior for different values of 2wij and 3wi: periodic cycles of different lengths and chaos. It

seems that the BP system may yield a non-chaotic or chaotic time -series data is relevant to the complexity of the family of equation (6).

REFERENCES

[1] Abhyankar, A., Copeland, L. & Wong, W. Uncovering nonlinear structure in real-time stock-market indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100. Journal of Business & Economic Statistics, 1997, 15, 1-14.

[2] Adachi, M., Aihara, K. & Kotani, M. Learning Strange At tractors by Back-Propagation Neural Networks. Proceedings of IJCNN, Beijing, 1992, II, 569-574.

[3] Azoff, E. Neural Network Time -series Forecasting of Financial Markets. John Wiley & Sons, West Sussex, England, 1994.

[4] Barron, A. R. Complexity regularization with application to artificial neural networks. In G. Roussas (Eds.), Nonparametric Functional Estimation and Related Topics,1991, 561 -576.

[5] Barron, A. R. Neural net approximation. Proceedings of the Seventh Yale Workshop on Adaptive and Learning Systems, 1992, 69-72.

[6] Blank, S. Chaos in futures market? A nonlinear dynamical analysis. J. Futures Markets, 1991, 11, 711 － 728.

[7] DeCoster, G., Labys, W., & Mitchell, D. Evidence of chaos in commodity futures prices. J. Futures Markets, 1992, 12, 291-305.

[8] Devaney, R. An Introduction to Chaotic Dynamical Systems. 2nd edition, Addison-Wesley, Inc, 1989 [9] Grudnitski, G., & Osburn, L. Forecasting S&P and gold futures prices: an application of neural networks. J.

Futures Ma rkets, 1993, 13, 631－643.

[10] Hornik, K., Stinchcombe, M. and White, H. Multi-layer feedforward networks are universal approximators. Neural Networks, 1989, 2, 359-366.

[11] Hutchinson, J., Lo, A., & Poggio, T. A nonparametric approach to pricing and hedging derivative securities via learning networks. J. Finance , 1994, 49 (3), 851- 889.

[12] Kaplan, D., and Glass, L. Understanding Nonlinear Dynamics. New York: Springer-Verlag, 1995a, 27-28. [13] Kaplan, D., and Glass, L. Understanding Nonlinear Dynamics. New York: Springer-Verlag, 1995b, 29-31. [14] Kaplan, D., and Glass, L. Understanding Nonlinear Dynamics. New York: Springer-Verlag, 1995c,

314-318.

[15] Kaplan, D., and Glass, L. Understanding Nonlinear Dynamics. New York: Springer-Verlag, 1995d, 324-327.

[16] Ott, E., Sauer, T. & Yorke, J. Coping With Chaos – Analysis of Chaotic Data and the Exploitation of Chaotic Systems . 1st edition, Wiley Inc, 1994.

[17] Matsuba I., Masui H. & Hebishima S. Prediction of Chaotic Time -Series Data using Optimized Ne ural Networks. Proceedings of IJCNN, 1992, vol. I, 340-345, Beijing.

Psychological Review, 1958, 65, 386-408.

[19] Rumelhart, D.E., Hinton, G.E., & Williams, R. Learning internal representation by error propagation. Parallel Distributed Processing, 1986, Vol. 1, 318-362. Cambridge, MA: MIT Press.

[20] Tsaih, R., Hsu, Y., & Lai, C. Forecasting S&P 500 Stock Index Futures with the Hybrid AI system. Decision Support Systems, 1986, Vol. 23, No. 2, 161-174.

[21] Wong, F.S. (1991). Time-series Forecasting Using Back-Propagation Neural Ne tworks. Neurocomputing, 1991, 2, 147-159.

CONFERENCE PROGRAM

THE XII ACME INTERNATIONAL CONFERENCE ON

PACIFIC RIM MANAGEMENT

2002 ANNUAL MEETING PROGRAM

12

th

Annual Meeting

August 1-3, 2002

Los Angeles, U.S.A.

Sponsored by

Association for Chinese Management Educators (ACME)

Chinese Accounting Professors Association in North America

Chinese Finance Association International

International Chinese Information Systems Association (ICISA)

National Tsing-Hua University

National Chung Cheng University

National Sun Yat-sen University

Eastern Michigan University

California State University - Chico

Illinois State University

University of North Carolina - Pembroke

National Youth Commission

Overseas Chinese Affairs Commission

Taipei Economic and Cultural Office in Los Angeles, USA

ACME 2002 XII ANNUAL CONFERENCE IN LOS ANGELES

Program Chair’s Message

H. Joseph Wen

Illinois State University

Welcome to Los Angeles and the 12

th

ACME international conference on Pacific Rim

Management. This conference is a forum for researchers and practitioners from all over

of the world. This year we had a total of 125 regular paper submissions from Australia,

Canada, China, Finland, Hong Kong, Taiwan, and USA.

Each paper that was submitted to ACME 2002 was sent for blind review to members of

the program committee and track chairs. I am grateful to the proceeding editor and track

chairs, for maintaining the schedule and delivering the reviews on time in order to meet

our aggressive timetable. The 78 contributed papers to be presented at the conference

were selected from the 125 submissions received from over 165 authors – an all-time

high for the conferences in this series-yielding a very competitive 62% rate of acceptance.

This year's conference features 2 keynote addresses, 6 special panels, and 22 contributed

paper sessions which cover most of the key areas in management, such as Accounting,

E-commerce, Enterprise Information Systems, Finance, Marketing, Management Science,

Regional and Global Economics, Web Technology, Management Information Systems,

and Transportation Management.

A conference of this magnitude cannot be organized without the tireless effort of many

individuals. I'd like to thank all the conference volunteers for their enormous contribution

towards the success of this conference. In particular, I wish to thank the proceedings

editor Dr. Binshan Lin (Louisiana State University – Shreveport) and conference local

coordinator Dr. Hsing Fang (California State University – Los Angeles) for their help in

assembling this program and their ongoing efforts to make this conference a value that

you simply cannot pass up. I am deeply grateful to Dr. Yea-Mow Chen (San Francisco

State University), the conference Chair, for his support and suggestions. Also, I would

like to express my gratitude to the authors for submitting their works to ACME 2002, and

to the track chairs and the reviewers for their contribution and effort to produce an

excellent program.

We look forward to seeing you, meeting with you, and talking with you in Los Angeles in

August.

2

THE XII ACME INTERNATIONAL CONFERENCE ON

PACIFIC RIM MANAGEMENT

CONFERENCE COMMITTEE

Conference Chair: Yea-Mow Chen San Francisco State University Program Chair: H. Joseph Wen Illinois State University

Proceedings Editor: Binshan Lin Louisiana State University Local Coordinator: Hsing Fang California State University

PROGRAM COMMITTEE

Otto Chang California State University Chia-Hao Chang University of Michigan Alex Chen University of North Carolina David C. Chou Eastern Michigan University David C. Yen Miami University

Hung-Lian Tang Eastern Michigan University Bernard T. Han Western Michigan University

TRACK CHAIRS

Accounting Otto Chang California State University

Lee-Hsuan Lin Yuan-Ze University

Business Education Ming-Te Lu Lingnan University K. Caleb Chan Spring Arbor College

Business Issues in China Xing-Hua Dang Xian University of Technology DSS/AI Yufei Yuan McMaster University

Jim Chen St. Cloud State University

E-commerce T.P. Liang National Sun Yat-Sen Univ. Michael Tarn Western Michigan University Economics/Management Ben-Chieh Liu Chicago State University

Chwen-Chi Liu Feng-Chia University

Enterprise Info. Systems Diana Kao University of Windsor

Chia-Hao Chang University of Michigan Finance K.C. Chen California State University Hypermedia & Web App. Chang-Yang Lin Eastern Kentucky University

Chang-Tseh Hsieh University of South Mississippi Marketing Management T.S. Chan Lingnan University

Douglas Tseng Portland State University

Yu-Peng Wang Shih Chien University

MIS David C. Yen Miami University David C. Chou Eastern Michigan University Management Science Bernard T. Han Western Michigan University Technology Management Ray Tsai St. Cloud State University

Houn Gee Chen National Chung Cheng Univ. Transportation Management Steven I-Jy Chien NJ Institute of Technology

INTERNATIONAL LIAISONS

Taiwan Hong-Gee Chen National Chung Cheng Univ. Ting-Peng Liang National Sun Yat-sen University Hong Kong T. S. Lee Chinese Univ. of Hong Kong

Ming-Te Lu Lingnan University

Chia-hao Chang Lingnan University

China Zhang Pengzhu Xi'an Jiaotong University

THE XII ACME INTERNATIONAL CONFERENCE ON

PACIFIC RIM MANAGEMENT

August 1-3, 2002

12

th

ACME Annual Meeting, Los Angeles, USA

THURSDAY, AUGUST 1

ST

, 2002

1:00-5:00 P.M. CONFERENCE REGISTRATION 4:00-5:30 P.M. BOARD MEETING 6:00-7:30 P.M. PRESIDENT’S RECEPTION 7:30-8:30 P.M. MEMBERSHIP MEETING

FRIDAY, AUGUST 2

ND

, 2002

7:00-8:30 A.M. BREAKFAST

FRIDAY, AUGUST 2ND, 2002 CONCURRENT SESSIONS: 8:45-10:15 A.M.

FINANCE-I Room: 210

Session Chair: K. C. Chen, California State University, Fresno

CENTRAL BANK INTERVENTION AND PROPERTIES OF THE 1920S CURRENCY MARKETS

Richard T Baillie, Michigan State University Young-Wook Han, City University of Hong Kong

THE MAIN FUNCTION OF REDISCOUNT IS STABILIZATION, NOT REGULATION

Hai-ou Hu, Shanghai Jiao-Tong University

COSTS AND OPTIMAL SHARE ALLOCATION IN IPOS AND SEOS: THE HONG KONG CASE

K. C. Chen, California State University, Fresno Lifan Wu, California State University, Los Angeles

E-COMMERCE-I Room: 211

Session Chair: Dave C. Yen, Miami University

4

3D DIGITAL HUMAN BODY MODELING FOR E-COMMERCE

Wen-Ko Chiou, Chang Gung University Tyan-Yu Wu, Chang Gung University Thu-Hua Liu, Chang Gung University

3D SCANNING AND THE MASK INDUSTRY IN TAIWAN: A NEW BUSINESS PARADIGM

Thu-Hua Liu, Chang Gung University Wen-Ko Chiou, Chang Gung University Yi-Xue Yang, National Tsing Hua University Chi-Yuan Yu, National Tsing Hua University

ISSUES IN THE WIRELESS MEDICAL SYSTEMS

Huei Lee, Eastern Michigan University

Kuo Lane Chen, University of Southern Mississippi

ACCOUNTING-I Room: 215

Session Chair: Otto Chang, California State University

A NOTE ON DATA ERRORS OF ACCOUNTING DATABASES

David C. Yang, University of Hawaii Miklos A. Vasarhelyi, Rutgers University Caixing Liu, University of Hawaii

VALUATION ALLOWANCE FOR DEFERRED TAX ASSETS AND EARNINGS MANAGEMENT

Zhou(Joe) Lu, University of Hong Kong

HUMANISTIC BUDDHISM AND BUSINESS ETHICS

Otto Chang, California State University

MIS-I Room: Seminar

Session Chair: Chang-Yang Lin, Eastern Kentucky University

ANALYZING IT-BASED ALLIANCES IMPACT IN THE SUPPLY CHAIN CONTEXT

Karen Hsu,National Kaohsiung First University of Science and Technology Sun-Quae Lai,National Taipei University

Echoh Huang,National Kaohsiung First University of Science and Technology

A CUSTOMER-ORIENTED INFORMATION REQUIREMENT ANALYSIS

Adam S. Huarng, California State University – Los Angeles Doris Christopher, California State University – Los Angeles

CAN WE BREAK THE KNOWLEDGE MANAGEMENT SPELL IN ASIA AND INCREASE FORTUNES

Todd Huseby, University of Chicago

Seng-cho T. Chou, National Taiwan University

RELATIONAL DATABASE MIGRATION: MANAGERIAL CONSIDERATIONS

FRIDAY, AUGUST 2ND, 2002 CONCURRENT SESSIONS: 10:30-12:00 NOON

MANAGEMENT/MARKETING-I Room: 210

Session Chair: Wann-Yih Wu, National Cheng Kung University PRODUCT DURABILITY AND MANAGERIAL COMPENSATION

Clement Kong Wing CHOW, Lingnan University Kit Pong WONG, University of Hong Kong

AN ANTICIPATION MODEL FOR PREDICTING THE INTERNET’S GLOBAL DIFFUSION

Wann-Yih Wu, National Cheng Kung University Shih-Wen Hsiao, National Cheng Kung University Shuo-Pei Chen, National Cheng Kung University

PHYSICIANS IN TQM: A SURVEY IN TAIWAN

Fenghueih Huarng, Southern Taiwan University of Technology Huei-min Hsei, Kaohsiung Medical University

MANAGEMENT SCIENCE-I Room: 211

Session Chair: Xing-Hua Dang, Xian University of Technology

A UNIVERSITY TIMETABLING SYSTEM WITH BOTH HARD & SOFT CONSTRAINTS: A CASE STUDY

Li-Yen Shue, National Kaoshiung First University of Science & Technology Sun-Tung Li, National Kaoshiung First University of Science & Technology

AN EOQ MODEL FOR VENDOR AND BUYER WITH DETERIORATING ITEMS

Chinho Lin, National Cheng Kung University Yihsu Lin, National Cheng Kung University

SOCIOECONOMIC DEVELOPMENT RANKING OF WEST VIRGINIA COUNTIES: AN APPLICATION OF GIS

Haixiao Huang, University of Illinois at Urbana-Champaign

SPECIAL PANEL - I Room: 215

SPECIAL PANEL IN BUSINESS EDUCATION

Panel Chair: Dr. Caleb Chan, Spring Arbor University

Panelists: Dr. Dalen Chiang, Dean, College of Business, California State University – Chico

6

TECHNOLOGY MANAGEMENT-I Room: Seminar

Session Chair: Ray J. Tsai, St. Cloud State University

CONSTRUCTING A SEMICONDUCTOR MANUFACTURING INFORMATION SYSTEM FOR PRODUCTION MANAGEMENT

Chen-Fu Chien, National Tsing Hua University Li-Ming Hsiao, National Tsing Hua University Hsin-Jen Wang, National Tsing Hua University Yi-Cheng Shih, Macronix International Co., Ltd.

ENVIRONMENTALLY CONSCIOUS PRODUCT EVALUATION USING AHP AND ECO-EFFICIENCY

Li-Hsing Shih, National Cheng Kung University

USING SYSTEM DYNAMICS APPROACH TO CONSTRUCT A PERFORMANCE MEASUREMENT MODEL FOR PHARMACY SUPPLY CHAIN MANAGEMENT

Jin-po Wu, Tamkang University

Chia-ti Fang, Fareast Tone Telecommunications, Inc. Ray J. Tsai, St. Cloud State University

ASPECTS OF KNOWLEDGE CREATION BASED ON INFORMATION MANAGE-MENT AND LEARNING MECHANISMS

Shih-Wei Chou, National Kaohsiung First University of Science of Technology Su-Ju Wang, National Kaohsiung First University of Science of Technology Hsing-Pang Chen,National Kaohsiung First University of Science of Technology

KEYNOTE SPEECH AND AWARD LUNCH: 12:00-1:45 P.M.

Keynote Speech: “Evaluation of the University Libraries in Taiwan: Total Measure Versus Ratio Measure”

Speaker: Dr. Chiang Kao, President of National Cheng Kung University

FRIDAY, AUGUST 2ND, 2002 CONCURRENT SESSIONS: 2:00-3:30 P.M.

ENTERPRISE INFO SYSTEMS-I Room: 210

Session Chair: Chia-hao Chang, University of Michigan-Dearborn

AN EMPIRICAL STUDY OF THE IMPLEMENTATION OF ENTERPRISE SYSTEMS (ES) IN CHINA: A NON-TECHNOLOGICAL ASPECT

Shaobo Ji, Carleton University

COLLABORATIIVE E-SUPPLY CHAIN MANAGEMENT

Chia-hao Chang, University of Michigan-Dearborn Yubao Chen, University of Michigan-Dearborn Jane Chang, Wayne State University

STRATEGIC IMPLEMENTATION OF AN SAP LAB AT A CANADIAN UNIVERSITY

Diana Kao, University of Windsor Peiji Shao, University of Windsor

INTEGRATED SIMULATION/EXPERT SYSTEM FOR LIBRARY RESOURCE MANAGEMENT

P. Pete Chong, University of Houston-Downtown Ming Chang, University of Houston-Downtown Jie Yin, University of Houston-Downtown

MIS - II Room: 211

Session Chair: K. Caleb Chan, Spring Arbor University

THE SURVEY OF FACTORS IMPACTING UPON ACCOUNTING INFORMATION QUALITY

Hongjiang Xu,University of Southern Queensland

TOWARD A GREATER UNDERSTANDING OF HOW NEW MIS PROFESSIONALS’ JOB ATTITUDES IMPACT ON THEIR TURNOVER INTENTIONS AT SOCIALIZATION STAGE

Tzu-Chuan Chou, National Kaohsiung First University of Science and Technology Huey-Chi Chiou, National Kaohsiung First University of Science and Technology

INSTRUCTIONAL TECHNOLOGY USE AND PERFORMANCE: A STUDY OF END-USER SATISFACTION AND FACTORS ATTRIBUTING TO SUCCESS IMPLEMENTATION

K. Caleb Chan, Spring Arbor University

SPECIAL PANEL - II Room: 215

ADMINISTRATION IN HIGER EDUCATION PANEL: GLOBALIZATION IN HIGHER EDUCATION – NEW FORCES, NEW LEADERSHIP

Panel Chair: Dr. Ting-Peng Liang, Provost National Sun Yat-Sen University

Panelists: Dr. Shy-Ming Ju, Vice President National Kaohsiung First University of Science & Technology

Dr. Alexander N. Chen, Associate Vice Chancellor for International Programs, University of North Carolina – Pembroke

8

Her-Kun Chang, Chang Gung University Thu-Hua Liu, Chang Gung University Yu-Chun Hsu, Chang Gung University

INFORMATION CONCEPTUALIZATION AND INFORMATION CHANGE TRACKING OVER THE INTERNET

Te-Min Chang, National Yat-Sen University Chi-Ming Lai, National Yat-Sen University

INTERNET PROGRAMMING, HELP SYSTEMS AND PERCEIVED SKILL: The Effects of Help Systems and Previous Experience on Markup Language Learning

Jeffrey Hsu, Fairleigh Dickinson University

EMPIRICAL ANALYSIS OF HERD BEHAVIOR IN ONLINE AUCTIONS

Y. Alex Tung, University of Connecticut

FRIDAY, AUGUST 2ND, 2002 CONCURRENT SESSIONS: 3:45-5:15 P.M.

SPECIAL PANEL - III Room: 210

SMALL & MEDIUM ENTERPRISE PANEL: SMALL & MEDIUM ENTERPRISES IN PACIFIC RIM COUNTRIES

Panel Chair: Director General Sun-Quae Lai. Small & Medium Enterprise Adm, Ministry of Economic Affairs, Taiwan

Panelists: Dr. Yan-Ping Chi, Director National Chengchi University Dr. Chang-tseh Hsieh, University of Southern Mississippi Dr. Kwei Tang, Purdue University

Dr. Helio Yang, San Diego State University

Mr. George R. Boyajian, Chairman of the United State Pacific Rim Chamber Dr. Karen Hsu, National Kaohsiung First University of Science & Technology Dr. Binshan Lin, Louisiana State University –Shreveport

FINANCE - II Room: 211

Session Chair: Hsing Fang, California State University, Los Angels

A CORRELATIVITY ANALYSIS OF THE STOCK MARKET AND TECHNOLOGY DEVELOPMENT

Jinxian Chen, Xi’an Jiaotong University Xinfa Liu, Xi’an Jiaotong University Jun Chen, Xi’an Jiaotong University Yajie Wang, Xi’an Jiaotong University

THE ESTABLISHMENT OF THE CORE COMPETENCE OF COMMERCIAL BANKS

Xunlian Si, Xi’an Jiaotong University Xinfa Liu, Xi’an Jiaotong University

FINANCIAL DEEPENING UNDER FINANCIAL REPRESSION: THE CASE OF CHINA

Chun Xin Jia, Peking University Philip C. Chang, University of Calgary

THE PERFORMANCE OF INTERNATIONAL I SHARES

Hsing Fang, California State University, Los Angels

SPECIAL PANEL - IV Room: 215

DEAN’S PANEL: MANAGEMENT EDUCATION IN PACIFIC RIM COUNTRIES

Panel Chair: Dr. Soushan Wu, Dean, College of Management, Chang Gung University Panelists: Dr. Dalen Chiang, Dean, College of Business, California State University –

Chico

Dr. T.S. Lee, Dean, College of Business, The Chinese University of Hong Kong Dr. Wann-Yih Wu, Dean, College of Management, National Cheng Kung University

E-COMMERCE - II Room: Seminar

Session Chair: J. Michael Tarn, Western Michigan University

A CONCEPTUAL FRAMEWORK FOR SUPER-HYBRID AFTERMARKET SERVICE SUPPLY CHAIN AND E-COMMERCE INTEGRATION

Stephen C. Shih, Southern Illinois University

A STUDY ON STUDENT’S ONLINE ETHICAL BEHAVIOR: THE CASE OF TAIWAN

Judy Chuan-Chuan Lin, Soochow University

Hsipeng Lu, National Taiwan University of Science and Technology

EXPLORING WIRELESS LAN SECURITY

J. Michael Tarn, Western Michigan University Tarinee Lerttanapoke, Western Michigan University

THE EFFECTS OF E BUSINESS ON SUPPLY CHAIN MANAGEMENT: A MODEL ANALYSIS

Ming Chang, University of Houston-Downtown Ta-Tao Chuang, Gonzaga University

Jason C.H. Chen, Gonzaga University

10

SATURDAY, AUGUST 3

RD

, 2002

7:00-8:30 A.M. BREAKFAST

SATURDAY, AUGUST 3RD, 2002 CONCURRENT SESSIONS: 8:45-10:15 A.M.

TRANSPORTATION MANAGEMENT-I Room: 210

Session Chair: Steven Chien, New Jersey Institute of Technology

DEFINING SERVICE DISTRICTS FOR A REVERSE DISTRIBUTION NETWORK

Soheila Jorjani, California State University San Marcos Yow-yuh Leu, California State University San Marcos Sheldon Lou, California State University San Marcos

A GENETIC-ANNEALING APPROACH TO THE SCHEDULING OF OIL TANKS

Sheng -Tun Li, National Kaoshiung First University of Science & Technology Ly-Yen Shue, National Kaoshiung First University of Science & Technology Ray L. Sun, Oridus, Inc.

PREDICTING TRAVEL TIME FOR SOUTH JERSEY REAL-TIME MOTORIST INFORMATION SYSTEMS

Steven Chien, New Jersey Institute of Technology Xiaobo Liu, New Jersey Institute of Technology

INTERNATIONAL/BUSINESS IN CHINA-I Room: 211 Session Chair: Lianlian Lin, California State Polytechnic University Pomona MYTHS AND CHARACTERISTICS OF CHINA’S CONSUMER MARKET

David K. Tse, The University of Hong Kong

ON RELATIVE VALIDITY ESTIMATION OF TECHNOLOGY INNOVATION PERFORMANCE OF AUTOMOBILE INDUSTRY IN CHINA

Xing-hua Dang, Xi’an University of Technology, China Hua-fang Liu, Xi’an University of Technology, China

THE IMPACT OF GLOBALIZATION ON CHINA

Lianlian Lin, California State Polytechnic University Pomona

BUILDING ONE EXPORT-ORIENTED VIRTUAL ENTERPRISES ALLIANCE IN CHINA

Jiang Lihui, Xi'an Jiaotong University

ECONOMICS-I Room: 215

Session Chair: Ben-Chieh Liu, Chicago State University

ENVIRONMENTAL POLICY AND TECHNOLOGY POLICY: TO COORDINATE OR NOT?

Rajeev K. Goel, Illinois State University

FINANCIAL IMPACTS OF 9-11 TERRORISTS ATTACK ON STOCK MARKETS FOR THE TOP 50 COMPANIES IN CHICAGO: AN INTER-TEMPORARY ANALYSIS

Ben-Chieh Liu, Chicago State University Ronald Byas, Chicago State University Kristen K. Manson, Chicago State University

DO CHINA A AND B SHARES MOVE TOGETHER AFTER THE DEREGULATION? THE APPLICATION OF ASYMMETRIC COINTEGRATION.

Chung-Hua Shen, National ChengChi University ChienFu Chen, DoHwa University

Li-Hsueh Chen, California State University – Los Angles

MIS-III Room: Seminar

Session Chair: David C. Chou, Eastern Michigan University

AN ACTION SPACE PERSPECTIVE TO EXPLORING THE RESTRICTING FACTORS FOR PARTICIPATORY DESIGN

Roman Wong, Barry University Tarja Tiainen, University of Tampere

MAKE BUSINESS SENSE OF E-CORPORATIONS

Abhishek Singh, Miami University David C. Yen, Miami University

David C. Chou, Eastern Michigan University

Alex Chen, University of North Carolina at Pembroke

THE MANAGEMENT OF CHAOTIC TIME-SERIES DATA

Ray Tsaih, National Chengchi University

THE EFFECTS OF LEADERSHIP AND COGNITIVE STYLES ON THE PREFERENTIAL TASK IN GSS

I-Chiu Chang, National Chung Cheng University Chi-Yuan Chen,National Chung Cheng University Jia-Iun Chang,National Chung Cheng University

SATURDAY, AUGUST 3RD, 2002 CONCURRENT SESSIONS: 10:30-12:00 NOON

MARKETING / FINANCE Room: 210

Session Chair: L.P. Douglas Tseng, Portland State University

MEASURING THE OPERATING PERFORMANCE OF FOREIGN BANKS IN SHANGHAI AREA

12

RESEARCH PRODUCTIVITY OF THE BUSINESS AND MANAGEMENT PROFESSION IN TAIWAN

Fu-Ju Yang, Chinese Culture University Soushan Wu, Chang Gung University Her-Jiun Sheu, National Chi Nan University

ACCOUNTING-II Room: 211

Session Chair: Sunn Y. Cho, Drexel University

AN EMPIRICAL STUDY OF THE RELATION BETWEEN AGENCY COSTS AND CAPITAL STRUCTURE AND THEIR DETERMINANTS

Jia-Jye Yu, Yuan-Ze University Lyinn Chung, Yuan-Ze University

THE INFLUENCE OF PRODUCT MARKET COMPETITION ON THE QUALITY OF CORPORATE FINANCIAL DISCLOSURE

Sunn Y. Cho, Drexel University H. T. Hao, McMaster University

WHAT HAVE WE LEARNT FROM THE EARLY EXPERT SYSTEMS IN AUDITING?

Roman Wong, Barry University

AN EMPIRICAL ANALYSIS OF ACCOUNTING POLICY-MAKING, RESEARCH AND PRACTICE ISSUES IN CHINA

Thomas Lin, University of Southern California

SPECIAL PANEL - V Room: 215

FINANCE CHALLENGES IN PACIFIC RIM COUNTRIES

Panel Chair: Dr. K.C. Chen, Chair, California State University – Fresno

Panelists: Mr. Harold Chuang, Senior Vice President, First Union Securities, USA Dr. Hsing Fang, Chair, California State University – Los Angeles Mr. Edward Lo, Chairman & CEO, United National Bank, USA Dr. Robert Su, Chair, National Chengchi University, Taiwan

MIS -IV Room: Seminar

Session Chair: Diana Kao, University of Windsor

IMPLEMENTATION OF A PROTOTYPE EXECUTIVE SUPPORT SYSTEM

Jim Q. Chen, St. Cloud State University Sang M. Lee, University of Nebraska-Lincoln

THE INFORMATIONIZATION PROCESS IN CHINA

Peiji Shao, University of Windsor Diana Kao, University of Windsor

ADAPTIVE SOFTWARE DEVELOPMENT: THE E-SYSTEMS DEVELOPMENT METHODOLOGY

H. Joseph Wen, Illinois State University Aditi Desai, Illinois State University

J. Michael Tarn, Western Michigan University

KEYNOTE SPEECH AND LUNCH: 12:00-1:45 P.M.

Keynote Speech: “Information Technology Management: Perspective, Focus, and Change in the Twenty-First Century”

Speaker: Peter Chen, Louisiana State University

SATURDAY, AUGUST 3RD, 2002 CONCURRENT SESSIONS: 2:00-3:30 P.M.

MANAGEMENT SCIENCE Room: 210

Session Chair: Yu-Peng Wang, Shih Chien University

A COMPARATIVE STUDY ON AN INTERNATIONAL SURVEY OF ISO 9000 AND ISO 14000 CERTIFICATION

Jeh-Nan Pan, National Cheng Kung University

A STUDY ON THE OPTIMAL EXPLOITATION POLICY OF MINERAL RESOURCES

Wei Xiaoping, China University of Mining and Technology

THE STUDY OF THE IMPACT OF SALES PROMOTION STRATEGY ON TAIWAN CONSUMERS’ PURCHASE INTENTION

Yu-Peng Wang, Shih Chien University Chung-Hui Tseng, Shih Chien University

INTEGRATING THE DOCTRINE OF THE MEAN INTO NETWORKING MANAGEMENT

Ping Lan, University of New Brunswick Saint John

ACCOUNTING / FINANCE Room: 211

Session Chair: Lee-Hsuan Lin, Yuan Ze University

THE DIFFERENCE BETWEEN CHINA AND US IN INTEREST RATE MECHANISM AND THE ADJUSTING EFFECT OF TREASURY BOND RATE

Hu Hai-ou, Shanghai Jiaotong University Dang Yi-fei, Shanghai Jiaotong University

14

SPECIAL PANEL - VI Room: 215

SPECIAL PANEL IN ENTERPRISE INFORMATION SYSTEMS

Panel Chair: Dr. Diana Kao, University of Windsor, Canada

Panelists: Dr. Chia-hao Chang, University of Michigan-Dearborn Dr. David Yen, Miami University

Dr. Hung-Lian Tang, Eastern Michigan University Dr. Binshan Lin, Louisiana State University –Shreveport Dr. Bernard Han, Western Michigan University

Dr. Peiji Shao, University of Windsor, Canada

WEB TECHNOLOGY Room: Seminar

Session Chair: Yufei Yuan, McMaster University, Canada

USING WEB TECHNOLOGIES TO INTEGRATE DATA MINING, KNOWLEDGE MANAGEMENT AND DECISION SUPPORT

Shy-Ming Ju, National Kaohsiung First University of Science and Technology I.C. Ou, National Kaohsiung First University of Science and Technology C.H. Wang, National Kaohsiung First University of Science and Technology H.L. Kao, National Kaohsiung First University of Science and Technology

E-GOVERNMENT DEVELOPMENT IN CHINA: MEETING NEW CHALLENGES OF JOINING WTO

Yufei Yuan, McMaster University, Canada Jason Zhang, McMaster University, Canada

THE MAKING OF INTERNET-BASED OFFICIAL DOCUMENT EXCHANGE IN TAIWAN

僑務簡介

僑務簡介

僑務簡介

僑務簡介

㆒、簡史 ㆒、簡史㆒、簡史 ㆒、簡史 在㆗華民國開國及建國的過程㆗，海外僑胞貢獻卓著，因此國父孫㆗山先生說「華僑為革命之 母」。政府重視華僑事務，早在民國十五年，國民政府即已設立僑務委員會；民國㆓十㆒年，改 隸屬行政院，現在本會業務遍達海外各㆞。 ㆓、施政理念 ㆓、施政理念㆓、施政理念 ㆓、施政理念 本會現任委員長張富美女士於民國八十九年五月㆓十日就職，她提出：僑務要以有限的資源，來 發揮最大的實益；並表示：只要認同㆗華民國、熱愛台灣的海外僑胞，僑務委員會都將加強聯繫 與服務。希望凝聚全球華㆟對自由、民主㆗華民國的向心力，為國家爭取最大的整體利益。 ㆔、 ㆔、㆔、 ㆔、組織組織組織 組織 本會設委員長㆒㆟，副委員長㆔㆟，僑務委員㆒百八十㆟，會內設第㆒、㆓、㆔、㆕處及僑生輔 導、華僑證照服務、祕書、㆟事、會計、統計、政風等室及法規委員會，另設華僑通訊社及㆗華 函授學校等。 ㆕、主要業務 ㆕、主要業務㆕、主要業務 ㆕、主要業務 • 僑民及僑團聯繫與服務僑民及僑團聯繫與服務 僑民及僑團聯繫與服務僑民及僑團聯繫與服務 • 僑民文教工作之推展僑民文教工作之推展 僑民文教工作之推展僑民文教工作之推展 • 僑民經濟事業之輔助僑民經濟事業之輔助 僑民經濟事業之輔助僑民經濟事業之輔助 • 僑生回國升學之輔導僑生回國升學之輔導 僑生回國升學之輔導僑生回國升學之輔導 • 僑民證照之服務僑民證照之服務 僑民證照之服務僑民證照之服務 五、未來展望 五、未來展望五、未來展望 五、未來展望 華僑是「革命之母」，也是「民主改革之父」。陳總統水扁先生曾說：沒有僑胞在海外的奮鬥， 台灣自由民主的改革就沒有現在光榮的時刻：㆗華民國在台灣所奮鬥的目標，與所有海外華㆟的 期盼是㆒致的。 僑務是國力的延伸，也是拓展外交工作的第㆓軌道。未來，僑務委員會將整合運用政府與民 間資源，強化外移僑民的服務工作，協助解決其在海外發展所產生的困難問題；加強宣揚㆗華文 化，鼓勵海外僑胞落㆞生根，融入當㆞主流社會，並透過僑民展現台灣的㆟道關懷精神；以聯繫 溝通凝聚僑心，進而運用海外僑民資源，協助達成國家之政策目標。

16

海外學㆟聯繫與服務園㆞

海外學㆟聯繫與服務園㆞

海外學㆟聯繫與服務園㆞

海外學㆟聯繫與服務園㆞

我國㆟與政府㆒向重視教育，高等教育的發達，使每年青年學子負笈海外深造者甚多。早期留學生，在學成之 後大部份選擇繼續留在海外尋求發展，成為所謂的「海外學㆟」，他們都是本會海外聯繫工作所要服務的對 象。由於對學㆟個別的服務，難求其普及與週全，因此，本會亦積極輔導海外學㆟團體，以期透過學㆟團體對 其會員之服務，發揮本會整體性與普及性的服務功能。 在海外學㆟聯繫與服務方面，本會的工作重點，在建立及暢通海外華㆟與國內之聯繫與溝通管道，以使海外華 ㆟在僑居㆞及工作崗位㆖能有更好的發揮，且亦能因時時掌握國內進步與發展情形，進而直接或間接為國建言 及貢獻所學（詳情請看返國服務資訊窗口）。在學㆟團體方面，本會現階段服務海外學㆟團體的工作重點，在 協助其健全學會組織、橫向交流及辦理各種研討活動，以增進其對會員提供更好的服務。 本會聯繫與服務海外學㆟與團體的主要措施計有㆘列： （㆒） 建置海外華㆟學會資料庫。 （㆓） 輔導及補助海外學㆟團體舉辦學術研討活動。 （㆔） 辦理海外華㆟學會會長聯席會議。 （㆕） 辦理全球性華㆟學術研討會。 （五） 發行海外通訊刊物。 （六） 編製海外華㆟學會學術研討活動㆒覽表。 （七） 辦理第㆓代華裔青年回國參訪、研習活動。 歡迎各位朋友多加運用，如有任何進㆒步的詢問與服務，請與我們連絡，我們將竭誠為您服 務！ 主任委員 林芳玫 副主任委員 陳聰勝 主任秘書 廖碧英 ㆞址：台北市徐州路五號十㆕樓 電話：（０㆓）㆓㆔五六六㆓㆔㆓、㆓㆔九七六九八八 傳真：（０㆓）㆓㆔五六六㆔０七 網址： IP ：192.192.16.30 WWW: http://www.nyc.gov.tw/