Understanding IT Innovations through Discourse Analysis

Wang, Ping; Tsui, Chia-jung; Fleischmann, Kenneth R.; Oard, Douglas W.; Wang, Lidan

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https://hdl.handle.net/2142/15327 Copy

Description

Title

Understanding IT Innovations through Discourse Analysis

Author(s)

• Wang, Ping
• Tsui, Chia-jung
• Fleischmann, Kenneth R.
• Oard, Douglas W.
• Wang, Lidan

Issue Date

2009-02-08

Keyword(s)

• Information technology innovation
• discourse analysis
• popularity
• information management
• information policy

Abstract

The dynamic information field is characterized by the constant ebbs and flows of innovations in information technologies (IT). Accordingly, managing information and formulating policies in the iField require understanding IT innovations – what they are and will be, who develops and/or adopts them, and how innovations may be effectively developed, implemented, and used. Despite a relatively sustained research literature on IT innovations [2], our knowledge of innovations is still inadequate to effectively inform strategic information management and policy-making in the iField. For instance, the field is filled with numerous buzzwords and acronyms, making it hard to differentiate true progress from mere change. And most research and practice are focused on highly popular innovations such as Web 2.0 and cloud computing; little is known about why only some innovations come to be popular while others do not. The lack of understanding is in part caused by limited research designs that focus on only one or a few innovations, owing to the difficulty in analyzing large-scale data on multiple innovations. The present study seeks to address these limitations by offering a theoretical foundation and an analytical method for understanding the dynamic interactions among IT innovations. Theoretically, we posit that innovations emerge and evolve in an ecosystem. Each innovation can be likened to a species competing with or supporting others in a resource space. One important resource that every innovation relies on is attention from people and organizations. A certain innovation requires a certain type of attention. For example, the innovation of computer-aided software engineering (CASE) asks for attention mainly from system analysts and programmers. Their attention may also be “nutritious” to the innovation of object-oriented programming (OOP), but not so much to customer relationship management (CRM), which thrives on the attention from a different group of people. Because CASE and OOP “consume” the same type of attention (i.e., from the same group of people), the two innovations are related. Innovations may be related for other reasons as well. For example, different innovations may be developed to solve similar problems, require common knowledge for understanding the problems or similar skills to implement the solutions, or share the practices or roles to be affected by the innovations. To the extent two innovations are related, attention may flow from one to the other. The relationship between a pair of innovations may take on different forms: They may compete with each other or they may complement each other.

Type of Resource

text

Language

en

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http://hdl.handle.net/2142/15327

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