• DocumentCode
    1246416
  • Title

    Organizational visions for technology assimilation: the strategic roads to knowledge-based systems success

  • Author

    Martinsons, Maris G. ; Schindler, Frederick R.

  • Author_Institution
    Dept. of Bus. Manage., City Univ. of Hong Kong, Kowloon, Hong Kong
  • Volume
    42
  • Issue
    1
  • fYear
    1995
  • fDate
    2/1/1995 12:00:00 AM
  • Firstpage
    9
  • Lastpage
    18
  • Abstract
    Despite the dramatically increased application of knowledge-based systems (KBS) technology, most of the enormous potential to leverage expert knowledge remains unrealized. The vast majority of KBS initiatives in industry and commerce have ended with unsatisfactory results. These failures can be primarily attributed to strategic mismanagement rather than technological shortcomings. Inspirational leadership and a needs-driven organizational vision are crucial for the effective assimilation of a new or emerging technology. KBS are no exception. A roads metaphor is identified as a basis for crafting and communicating such an organizational vision. Three alternative approaches for achieving a strategic impact with a technology are identified and described: the user-driven low road; the technostructure-driven high road; and the team-based road network. The relative merits of these strategic roads, and their suitability to different organizational and knowledge structures are considered using a case-based methodology. Based on their research of the KBS technology assimilation processes at DuPont, Digital Equipment, and Xerox, the authors offer management advice to practitioners and recommend future areas for study
  • Keywords
    knowledge based systems; research and development management; software development management; case-based methodology; emerging technology; expert knowledge; knowledge-based systems; leadership; management; organization; recommendations; strategic impact; team-based; technology assimilation; technostructure-driven; user-driven; Application software; Artificial intelligence; Business; Expert systems; Humans; Job shop scheduling; Knowledge based systems; Problem-solving; Roads; Technology management;
  • fLanguage
    English
  • Journal_Title
    Engineering Management, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9391
  • Type

    jour

  • DOI
    10.1109/17.366399
  • Filename
    366399