The Auto-ID Trajectory - Abstract

Traditionally the approach used to analyse technological innovation focused on the application of the techno-economic paradigm with the production function as its foundation. This thesis explores the rise of the evolutionary paradigm as a more suitable conceptual approach to investigating complex innovations like automatic identification (auto-ID) devices. Collecting and analysing data for five auto-ID case studies, (bar codes, magnetic-stripe cards, smart cards, biometrics and RF/ID transponders), it became evident that a process of migration, integration and convergence is happening within the auto-ID technology system (TS). The evolution of auto-ID is characterised by a new cluster of innovations, primarily emerging through the recombination of existing knowledge. Using the systems of innovation (SI) framework this study explores the dynamics of auto-ID innovation, including organisational, institutional, economic, regulatory, social and technical dimensions. The results indicate that for a given auto-ID innovation to be successful there must be interaction between the various stakeholders within each dimension. The findings also suggest, that the popular idea that several technologies are superseded by one dominant technology in a given selection environment, does not hold true in the auto-ID industry. 

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The Auto-ID Trajectory - Chapter Three Research Design

A qualitative research strategy was chosen over a quantitative one due to the complexity of the research problem. The study grants the qualitative researcher the ability to focus in on a grand tour question throughout the thesis, followed by subquestions within (Anderson & Kanuka 2003, p. 35). In this instance the investigation is mainly preoccupied with the auto-ID trajectory. This type of strategy allows the researcher unlimited inquiry in areas that he/she believes is required, finding synchronicity with the systems of innovation (SI) framework underlying the study. Intrinsic to this type of research, as stated by Creswell (1998, pp. 16-17), is a commitment to collect extensive data. This researcher has chosen to conduct data analysis using categories or like themes to make sense of the large amount of data collected. In this thesis, long quoted passages also characterise the style of presentation, not only to substantiate claims made by the researcher but also to show the diverse positions held by the various auto-ID stakeholders, pointing to key pieces of evidence throughout.

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