| Adoption is one of the most important concepts in the diffusion of innovations (DOI) literature, yet certain aspects of it are poorly understood. In particular, causal adoption process theory (CAPT) has been stagnant for decades and seldom subjected to critical scrutiny. In consequence, DOI research is unstable – different studies identify different factors as important.;What emerges is the Motive-Technology-Belief (MTB) framework, a theory that conceptualizes adoption in terms of motives (inner mental reasons), technologies (tools that pertain to motives) and beliefs (associations between motives and/or technologies.) Motives and technologies are self-similar and exhibit fractal structure. The atomic unit of adoption is the temor, a belief that associates a technology with a particular motive.;Three conscious processes govern the behavior of these structures. "Selecting" chooses a tool to satisfy an immediate need. "Evaluating" constructs beliefs about a tool. Selecting and evaluating are complementary ceteris paribus processes that operate in tandem. "Maintaining" determines the functional status of a tool. Five unconscious auxiliary processes – "perceiving," "framing," "focusing," "categorizing," and "acting" – govern motivation.;This study makes important contributions to several fields by cracking open two black boxes – one theoretical, the other methodological. The theoretical contribution is a coherent and empirically grounded framework that exposes the inner mental processes of adoption. The methodological contribution is to combine qualitative field research with UML to make consumer agent modeling more systematic, clear, and insightful. The substantive contribution is a grounded agent model that is well-suited to guide the construction of simulated consumer agents. Aggregations of calibrated consumer agents may be able to identify new markets before they exist and model DOI with greater accuracy. Consequently, this dissertation lays the foundation for a totally new approach to research on DOI and the formation of markets.;This dissertation introduces grounded agent modeling, a hybrid methodology drawing on existing software engineering and social science techniques to construct a step-by-step explanation of how consumers make technology adoption decisions. Inductive case studies, grounded theory, and sequence analysis are used to investigate transportation mode adoption and build a theoretical framework that is sufficiently precise to guide its implementation in Unified Modeling Language (UML). |
