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    LUẬN VĂN Information engineering implementation issues: An information systems manager s perspective

    Linh Napie Linh Napie Đang Ngoại tuyến (4058 tài liệu)
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  6. Information engineering implementation issues: An information systems manager s perspective

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    There have been a number of individuals who have made this endeavor possible. My supervising professor, Dr. M. K. Raja, has been a key individual in my development from early in the doctoral program. As part of the dissertation project, we drove to many corporate meetings relating to Information Engineering. Without the contribution of his many contacts in industry and his excellent insights on systems development, this thesis would not have been possible.
    The other members of the dissertation committee raised thought-provoking questions, provided useful suggestions and supported the project in many ways. Dr. L. L. Schkade has always encouraged me, and has provided me with the conceptual foundation in systems with which to conduct this study. He was instrumental in my entry to the doctoral program, and began to cultivate a research spirit in me from those early days.
    Dr. Peter Mykytyn has always made time to answer my questions, and has raised critical and important questions of his own about the study which have been very helpful in focusing my research efforts.
    Dr. Craig Slinkman has provided me with a thorough background in data modeling, which is necessary to perform research in Information Engineering. With regards to this
    dissertation study, his suggestions, especially in the area of factor studies research, as well as methodology and data analysis, were extremely useful.
    Dr. John Hassell has always had an open door and has welcomed my seemingly endless questions during the doctoral program. He has shared his professional contacts unselfishly, and has truly enabled me to seek my own level of success. As the graduate advisor and my minor field representative for the dissertation, his suggestions have been worthwhile and saved me a great deal of effort.
    I would like to express my gratitude to Dr. Frank Navratil and the Wasmer Fund at John Carroll University for their support and for partially funding the research conducted in this study.
    I would also like to express my gratitude to the many corporate systems analysts and data modelers who consented to interviews during the development of this research, as well as the many IS managers who participated in this project. I am especially thankful to Kent Anderson, without whose contributions the research project could not have been completed.
    It is very difficult to accomplish a professional endeavor without support from one’s family. My wife, Terry, supported me in so many ways. Throughout the doctoral program, when I was working without pause, she would try to make sure that all the other family details were taken care of. I am thankful to have had her by my side. My children, Lindsay and Brian, have given up the company of their father on many occasions. I certainly appreciate the many sacrifices of my family.
    While my late father will not be able to see me complete a Ph.D., I’m sure that he is proudly watching over the process. Education and achievement have always been an important part of his life’s ambitions. My dear mother has stood by my decision to return to graduate school and has provided support throughout the program.

    Publication No.
    Patrick T. Hogan, Ph.D.
    The University of Texas at Arlington, 1994 Supervising Professor: M. K. Raja
    Many companies have experienced high failure rates in software development for large complex systems. In order to improve systems development, some companies have turned to the technical innovation Information Engineering. This new concept is an approach to software development which imposes a rigorous discipline on the systems development process. The practitioner press has provided experiences of success and failure in Information Engineering implementation, but these are anecdotal in nature and are not the results of scientific study. To remedy this situation, this study systematically searches a broad base of literature to develop a comprehensive model to represent the implementation of a technical innovation like Information Engineering. The model includes many of the significant factors found in the studies reviewed in the literature. The model was empirically tested in a field study through the use of a pre-tested questionnaire, and the results statistically analyzed with the method bivariate regression.

    ABSTRACT . vi
    The General Issue 1
    The Specific Issue . 9
    Innovation Theory . 10
    Prior Implementation Research . 10
    Research Question . 12
    Research Plan and Organization of the Study 13
    Introduction 14
    Background 14
    Methods and Methodologies . 15
    Methodology Defined . 15
    Impact of Methodologies 17
    A Need for Increased Rigor . 19
    Information Engineering 20
    Prior Research 26
    Innovation 28
    Innovation Defined 28
    Technical versus Administrative Innovations . 29
    Initiation versus Implementation 30
    An Organizational Change/Process Model of the Implementation of a
    Technological Innovation . 31
    Process Studies 31
    Process Theory of Change . 32
    Organizational Change Issues 34
    Organizational Change Research 36
    Information Engineering as Organizational Change 37
    Normative Research Model . 39
    Development of the Model . 40
    Factor Studies 43
    Management Support . 43
    Management Support-Model 1 . 45
    User Participation . 45
    User Participation -Model 2 . 50
    Training and Education 50
    Training and Education-Model 3 51
    Change Agency . 52
    Change Agency-Model 4 . 53
    Task Changes . 53
    Task Changes-Model 5 59
    Measures of Success in Implementation Research 59
    Nature Of The Research 60
    The Research Question 60
    The Research Model . 61
    Hypotheses 64
    Management Support-Hypothesis 1 . 64
    User Participation-Hypothesis 2 64
    Training and Education-Hypothesis 3 64
    Change Agency-Hypothesis 4 . 64
    Task Changes-Hypothesis 5 64
    Design Of The Survey Instrument 65
    Measurement . 67
    Management Support . 67
    Commitment 67
    Participation 68
    Acceptance/Utilization 68
    User Participation . 69
    Needs Solicitation 69
    Buy-in 69
    Acceptance/Utilization 69
    Change Agency . 70
    Change Agency Cycle . 70
    Training and Educational Requirements . 71
    Overview 72
    Knowledge Transfer . 72
    Technical Training 72
    User Training and Support 72
    Continuing Education . 73
    Task Changes . 73
    IE-Based Management 74
    Increased Interaction 74
    Reinforcement . 74
    IE-Based Development . 75
    Successful Implementation of Information Engineering . 75
    Level of Success 76
    Research Strategy . 76
    Research Method . 80
    Survey Measures . 80
    Pilot Study 81
    Sample . 84
    Validity And Reliability 85
    External Validity 86
    Content and Construct Validity . 87
    Reliability . 90
    Double tests . 90
    S ingle test (internal consistency) . 91
    Reliability Calculations . 92
    Internal Validity . 94
    Statistical Methods 95
    Administration Of The Questionnaires 96
    Overview Of Analytical Approach 100
    Bivariate Regression Analysis 100
    Method 100
    Results . 101
    Summary of Results 104
    Overview . 106
    Observed Empirical Relationships 106
    Management Support . 106
    U ser Participation 107
    Training and Education 107
    Change Agency . 108
    Task Changes 109
    F uture Research . 109

    ITEMS . 118

    1. Organizational Change/Process Model for Management Science
    System Implementation 40
    2. Organizational Change/Process Model for Information Systems
    Implementation . 41
    3. Organizational Change/Process Model Adapted for Information
    Engineering Implementation . 42
    4. Components of the Organization 54
    5. Organizational Change/Process Model Adapted for Information
    Engineering Implementation . 62
    6. Research Model of Information Engineering Implementation 63
    7. The Variable Of Management Support Operationalized 68
    8. The Variable of User Participation Operationalized 70
    9. The Variable of Change Agency Operationalized . 71
    10. Training and Educational Requirements Operationalized 74
    11. Task Changes Operationalized . 75
    Table Page
    1. Variables and Scales in the Pilot and National Questionnaires 83
    2. Calculated Reliabilities of Independent Variable Scales In the Survey Instrument 93
    3. Comparison of Source List, Sample Used and Responses by Industry . 99
    4. Bivariate Regression Results for Independent Variable - Management Support 101
    5. Bivariate Regression Results for Independent Variable . - User Participation 102
    6. Bivariate Regression Results for Independent Variable - Training and Education. 103
    7. Bivariate Regression Results for Independent Variable . - Change Agency 103
    8. Bivariate Regression Results for Independent Variable . - Task Changes 104
    9. Summary of Bivariate Regression Results . 105

    INTRODUCTION The General Issue
    The computer industry has experienced a brief but nonetheless active life. The first workable general purpose computer, the ENIAC, was purchased by the United States government in 1946. At the time, it was believed that only six of these machines would ever be needed. In the nearly 50 intervening years, there have been continuous, and frequently major, improvements in computer hardware capability. This is particularly true in hardware development, where the history is one of astounding success. The power and speed of the hardware has continued to increase almost exponentially through successive “generations,” with no apparent end in sight. As the processing capabilities of the computer have steadily increased, so has the price-per-processing-operation steadily declined during the same period. The result has been a phenomenal growth in the acquisition of computers by business and industry.
    After organizations acquire large computer installations, their attention naturally turns to the utilization of these general purpose computing machines in their business. This deployment requires the development of software components. However, the history of software development has not enjoyed the same good fortune as that of hardware. In fact, while there are some modest advances in software development, there are many failures. The
    problems in software development became even more serious as hardware advancements enabled large, complex software systems to be contemplated Indeed, in 1968, the NATO Science Committee organized the Garmisch Conference to focus its attention on the problems of software, and to discuss possible techniques which might lead to their solution. The organizers saw a need for “software manufacture to be based on the types of theoretical foundations and practical disciplines, that are traditional in the established branches of engineering” (Naur and Randell, 1969, p. 13).
    Another approach to solve the problems of software, was the automation strategy, which has had a long history in the computing field. An early voice in this respect is the CODASYL systems committee, circa mid-1950s, whose objectives read: “To strive to build up an expertise in, and to develop, advanced languages and techniques for data processing, with the aim of automating as much as possible of the process currently thought of as systems analysis, design and implementation” (cited in Teichroew and Sayani, 1971).
    While the Garmisch Conference organizers wished for the emergence of a more rigorous form of‘software engineering,’ and the CODASYL systems committee desired full systems automation, it would be decades before these wishes and desires would be fulfilled. However, through the efforts of Dijkstra (1968) and others the field of information systems software development progressed from an ad hoc collection of techniques, to more structured methods. More recently, software development has enjoyed the rapid growth of what may be termed formal methodologies, many of which are rather sophisticated (Olle et al., 1982,
    1983). These software development methodologies act to prescribe the behavior of

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