Modeling Academic ERP Issues and Innovations with AST

Modeling Academic ERP Issues and Innovations with AST

Harold W. Webb (The University of Tampa, USA)
Copyright: © 2015 |Pages: 11
DOI: 10.4018/978-1-4666-5888-2.ch081
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Background

Adaptive structuration theory (AST), an extension of structuration theory (Giddens, 1982), has been used as a framework to study organizational change processes during advanced information technology adoption (Poole & DeSanctis, 1992). Adaptive structuration takes a socio-technical perspective. Human actors and organizational context are introduced within this perspective as moderators of technology impact. The adoption of an advanced technology, therefore, is a process of organizational change resulting from the mutual influence of the technology and social processes. While first introduced to information systems research in the 1990’s, AST continues to be one of several social theories that focuses understanding on how groups interact with and adopt technology (Hirschheim & Klein, 2012). Structuration theory, the basis for AST, has also been suggested as a foundation for understanding how firms attend and respond to unexpected use of IT (Swanson & Ramiller, 2004).

The premise of AST is that in academic settings, human actors and organizational context collectively moderate the processes by which ERPs are appropriated. Such dynamic processes affect not only institutional and industry outcomes resulting from the appropriation, but also the evolution of the relationship between industry and academia. The number of academic institutions adopting ERPs has been increasing rapidly since the 1990s (Rosemann & Maurizo, 2005; Leyh, 2012). The SAP University Alliance Program (UAP) now reports over 1,350 universities (SAP, 2013) and the Microsoft Dynamics Academic Alliance (DynAA) lists over 1100 universities (Microsoft, 2013). Open-source ERP platforms are now an alternative (Ayyagari, 2011). However, use is not a perfect proxy for effectiveness as ERPs serve some institutions better than others (Antonucci et al., 2004).

Key Terms in this Chapter

Joint Outcomes: The direct output and by-products of the education process including student learning, employable work force, market exposure, and contributions to research.

Technology Infrastructure: Required supporting activities and facilities including network, hardware, software, development, and maintenance.

Structure of Academic/Industry Collaboration: Representation of social practices among the stakeholders affecting academic/industry collaboration that result in the establishment of rules of practice and the provision of resources.

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