Habitual Domains, Decision Making in Changeable Spaces, and Innovation Dynamics

• Main Author: 陳彥曲
• Other Authors: 游伯龍
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/63308385034805741965

博士 === 國立交通大學 === 資訊管理研究所 === 99 === Human behaviors involve dynamic, evolving, interactive, adaptive processes. Important decision making, as a part of human behaviors, is usually dynamic and involves changeable parameters. These parameters can interact with each other and vary with time, the situation, and changes in the psychological states of the decision makers involved. According to the habitual domains theory, decision making can reach a steady state and exhibit habitual patterns as time passes. As a consequence, people may unwittingly assume that the decision parameters have fixed known dimensions and ranges. However, in real life, the parameters might or might not be noticed. Even when they are noticed, their dimensions and ranges cannot be predetermined. Decision making with this kind of feature, is called “decision making in changeable spaces”. Corporate innovation problems are of this type. Innovation itself is a dynamic process, which includes transforming competence sets for innovation, producing products or services to release the pains and frustrations of target groups, and creating and distributing value. In the field of innovation studies, no framework has systematically described these processes in the past. This research is the first attempt to integrate these components into a single system. Based on habitual domains theory and its related competence set analysis, this dissertation introduces the concepts of habitual domains and decision making in changeable spaces in order to describe the dynamics of human behaviors and the changing nature of decision-making problems. It goes in depth into potential domains to explore the expansion of competence sets and creation of value, and proposes an integrated framework, innovation dynamics, which emphasizes decision making in changeable spaces and focuses on the exploration of parameters in potential domains. To verify innovation dynamics, five corporate case studies are discussed herein. It shows that these cases are all consistent with innovation dynamics. By examining the operations of each link in innovation dynamics, corporations can understand if each and all links are properly developed, so that they can continually upgrade their products/services and create maximal value by releasing the pains and frustrations in potential domains of customers.