Developing an Expert Systems Strategy

Braden, Barbara; Kanter, Jerome; Kopsco, David C.

doi:10.2307/248733

Cited by 17 publications

(5 citation statements)

References 6 publications

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“…A case study identified important aspects of the design and development of the system. (Braden, 1989) In the data set representing 1992-1996, our analysis indicates that the themes of 'information', 'systems', and 'use' are the strongest themes (see Figure 4d). The context of 'systems' still includes concepts of development, but now additionally has a strengthened focus on decision support.…”

Section: Analysis and Resultsmentioning

confidence: 86%

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Indulska

Hovorka²,

Recker

2012

European Journal of Information Systems

110

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Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

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Section: Analysis and Resultsmentioning

confidence: 86%

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Indulska

Hovorka²,

Recker

2012

European Journal of Information Systems

110

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show abstract

“…It is well recognized that securing the support of top management is a prerequisite to the long-term success of ES projects (Braden et al, 1989;Leonard-Barton and Sviokla, 1988;Meyer and Curley, 1989;Sipior and Volonino, 1991;Wong, 1996). Broad support for technological innovation from the top individual alone is insufficient unless it is translated into support for specific applications of ES technology by management levels below him.…”

Section: Secure the Support Of Top Managementmentioning

confidence: 99%

Expert System Stalemate

Sipior

2000

Information Resources Management Journal

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Research on project champions has focused on the characteristics of this individual and how to provide encouragement and support. An understanding of the role of project champion is shortsighted, however, without a realization of what can happen to an expert system (ES) project, and what can be done, should this individual depart. This paper discusses the ES project champion by examining the experiences of Ciba-Geigy Corporation with an ES project, impeded by the departure of the project champion. The OpBright Expert System, developed to support the identification of appropriate optical brightener products by sales representatives, was intended to provide a competitive advantage through superior customer service. With the promotion and transfer of the vital force committed to the project’s success, the ES encountered a stalemate. The difficulties in maintaining momentum for the ES without a project champion are discussed. Finally, suggestions are presented to guide organizations away from the same fate.

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“…Second, the introduction of KBS may be examined concerning their potential to create a competitive edge for the company (this is usually called 'strategic opportunities'). Strategic benefits of KBS have been reported by various authors [15,[61][62][63][64]. It should, however, also be established that the introduction of KBS may involve strategic threats, for instance, because of an enhanced risk of valuable knowledge leaking to the competition or because KBS may impair the creative powers of the organisation [4].…”

Section: A Knowledge Perspective For Valuing Knowledge-based Systemsmentioning

confidence: 99%

The organisational impact of knowledge-based systems: a knowledge perspective

Hendriks¹

1999

Knowledge-Based Systems

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Developing an Expert Systems Strategy

Cited by 17 publications

References 6 publications

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Expert System Stalemate

The organisational impact of knowledge-based systems: a knowledge perspective

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