Human behaviors involve dynamic, evolving, interactive, adaptive processes.
Important decision making, as a part of human behaviors, is usually dynamic and involves changeable parameters. Decision blinds, decision traps, and fuzziness unavoidably occur in the process of dealing with challenging decision problems.
Although human behavior is dynamic, it gradually stabilizes. Therefore, people will have habitual concepts and ways of thinking, acting, judging, and responding (generally called ideas and operators). The collection of these ideas and operators together with their operation is called habitual domains (HDs) (Yu 1990, 2002, 2009).
Because of different HDs, when making decisions, different people might have different frames to perceive problems and generate different solutions. As decision makers’ perception frames are enlarged, they can see problems more clearly, and the fuzziness is reduced. In terms of HDs, as one’s HD expands, one can see problems more clearly with reduced fuzziness.
Decision problems can be characterized by various dimensions of parameters, which involve a number of elements such as decision alternatives, decision criteria, decision outcomes, decision preferences, and decision information inputs. They also involve the following four environmental facets: decisions as a part of the behavior mechanism, stages of the decision process, the players involved, and unknowns in decision making. These parameters can interact with each other and vary with time, the situation, and changes in the psychological states of the decision makers involved.
Although dynamic in nature, decision making, as a part of human behaviors, may reach a steady state and exhibit habitual patterns as time goes by. As a consequence, in mathematical programming or ordinary decision-making problems, we may unwittingly assume that the decision parameters (or variables) 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 these features is called “decision making in changeable spaces” (Yu & Chiang-Lin 2006; Yu & Chen 2010a, 2010b, 2010c). Many corporate management problems are of this type.
Corporation innovation itself, which involves setting corporate goals, evaluating states, understanding customers’ needs, producing and providing products and services, and creating value for targeted customers and themselves, is of the type of challenging decision-making problems in changeable spaces. If corporate decision
makers are not aware of the existence and changing nature of the relevant parameters in decision making, they may fall into decision blinds and traps (Yu & Chiang-Lin 2006) and make serious mistakes.
According to Yu (1990, 2002), “superior strategists find the best strategies by changing the relevant parameters, while ordinary strategists find optimal solutions within some fixed parameters.” In the corporate management field, “corporate competitiveness” has always been a hot topic. To be competitive, corporations must continually innovate to provide faster and more-effective products or services that satisfy the needs of customers than their competitors, and be capable of creating value and distributing value to all stakeholders. Clearly, innovation is a process which involves a number of decision parameters and decision making in changeable spaces.
Understanding the behavioral dynamics and HDs of one's self and others can enable decision makers to study, search, and identify the best changes of the relevant parameters to become a superior strategist and avoid making mistakes in the process of corporate innovation. To illustrate this point, let us consider the following two cases (details of which are given in Chapter 6).
At the end of 2006, a 1.5-year-old video-sharing company, YouTube, was purchased by Google, the well-known search engine, at a price of US$1.65 billion.
This high-profile event was the biggest merger case for Google at that time. It generated a great deal of discussion and attention.
The three YouTube founders originally intended to provide their product to eBay as a way to introduce auction products, in addition to pictures and text descriptions.
The idea appeared to meet a demand, but never succeeded. They then extended their product to potential domains (PDs, one of the four sub-concepts of HDs described in Chapter 3) (Yu, 1990, 2002, 2009) of potential users, and found a large number of people with a strong desire to express themselves to online friends. Those desires in the PDs were not discovered until YouTube dropped their original idea and explored real needs in the PDs of potential customers.
From the initial garage venture to a website worth over US$1.6 billion, the growth and development of YouTube involved a process of continual integration and transformation of competence sets. In the process, they released people’s potential pains and frustrations by providing effective products and services that others could or would not. By doing so, they enhanced their corporate competitiveness and used it to create value.
Take Wii (Nintendo) as another example. Nintendo began working in the game console industry in the 1970s, when there were not many design alternatives for game consoles. Players had to operate a gamepad with two hands, and they could only use their thumbs to control movement. That was until 2006, when Satoru Iwata, who had been the president of Nintendo for less than five years, led Nintendo to break with the three-decade old design. Wii, with the simple creativity of “operate with one hand”, was born. The appearance of Wii created a new generation of games. It brought a new entertainment experience, and the innovative interface of the game control successfully reduced the time needed for new players to learn how to play a game.
The remote control is equipped with sound effects, vibrates, and has orientation functionality. It allows players to simulate the behavior of real games and brings users an unprecedented gaming experience.
Nintendo had lost its leading position in the gaming industry before Wii entered the market, which had caused the company's market share to fall behind. Wii was Nintendo’s innovative breakthrough. Its innovation was not only in “subverting traditional design”, but more importantly, it satisfied the desire of people “wanting to experience realistic gaming” in PDs. In the past, the game console industry was always committed to pursuing exquisite graphics, and sound and light effects, attempting to satisfy the desires of player. However, luxurious graphics and sound and light effects are needs in the “actual domains” (ADs, one of the four sub-concepts of HDs described in Chapter 3) for gamers (desire for audio and visual aspects).
Allowing body movements and feeling the speed, direction, and even power with the game are strong needs hidden in players’ PDs. By satisfying the needs in the PDs, Wii recreated the interaction between gamers and games, which not only created value for Nintendo, but also allowed the company to regain its competitive advantage.
As illustrated in the two examples above, to innovate and enhance competitiveness, one must understand decision making in the changeable spaces of parameters. Innovation must be able to release the potential pains and frustrations of target customers, and satisfy their potential needs. In the past decades, there was abundant research regarding the definition, methods, tools, and value creation of innovation. However, those related studies on innovation seldom explored the key factor of successful innovation from the perspective of “satisfying or releasing potential needs, pains, and frustration”. Innovation itself is a dynamic process which includes transforming a competence set for innovation, producing products or services to release the pains and frustrations of target groups, and creating and distributing values. In the field of innovation studies, there previously was no framework that
systematically described these processes. This research is the first attempt to integrate these components into a single system.
Based on HD theory and its related competence set analysis, this study examines PDs in depth to explore the expansion of competence sets and creation of value, and proposes an integrated framework, innovation dynamics. The major links of the framework, which can be interpreted both clockwise and counterclockwise, include: (i) the expansion and transformation of competence sets; (ii) the provision of products/services to release the pains and frustrations of target customers; (iii) creation and release of charge; (iv) creation of value; and (v) distribution and reinvestment of the created value. It describes the dynamics of how to solve a set of problems with existing or acquired competence (to relieve the pains and frustrations of targeted customers or decision makers in certain situations) so as to create value, and how to distribute this created value so that one can continuously expand and enrich the competence set to solve more challenging problems and create greater value.
Unlike usual innovation studies, innovation dynamics emphasizes decision making in changeable spaces and focuses on exploring parameters in PDs. If a corporation is aware of innovation dynamics, it can avoid stepping into decision traps.
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 of customers in the PDs, as illustrated in the two examples of YouTube and Nintendo. This framework also points out that each and all links must be properly examined and developed. Omitting any one of them can lead to serious mistakes.
This dissertation is organized as follows. Chapter 1 is the introduction. In Chapter 2, the important literature and related innovation studies are surveyed, from which we find that they lack a holistic and comprehensive model to assist corporations with focusing on customers’ potential needs, releasing potential pains and frustrations, and further creating value. These involve the dynamics of human behavior and decision making in changeable spaces, which is described in Chapter 3.
The stability of behavioral dynamics leads to the concept of the HD. The important elements of HDs are also sketched out. As an important application of HDs, the concept of competence set analysis is introduced in Chapter 4. Decision blinds and decision traps are closely related to the concepts of HDs and competence set analysis;
this relationship is also explored.
In Chapter 5, the anatomy of innovation dynamics is described. Innovation dynamics consists of a number of key components. Graphically these components are linked together. Each link contains a sequence of activities. Based on the habitual domain theory and competence set analysis, the contents of each link in the framework are explored and discussed. Activities over each link of innovation dynamics usually involve decision-making problems in changeable spaces. To verify innovation dynamics, five corporate case studies are discussed in Chapter 6, including
Super Girl (Section 6.1), Wretch (Section 6.2), YouTube (Section 6.3), Wii (Section
6.4), and 85 C Bakery Café (Section 6.5). It shows that these cases are all consistent with innovation dynamics. The executives of each corporation might not be aware of innovation dynamics, but unwittingly, they followed the pattern of innovation dynamics which resulted in the success of their business.Finally in Chapter 7, the contributions and conclusions of this dissertation are provided. This dissertation introduces the concepts of HDs and decision making in changeable spaces by describing the dynamics of human behavior and the changing nature of decision-making problems. Understanding the dynamic features of related parameters in decision making can enable people to study, search, and identify the best changes in the relevant parameters so as to become superior strategists and decision makers. By looking in depth at PDs to acquire and master the needed competence sets, decision makers can reduce decision blinds, avoid decision traps, and obtain better solutions for decision problems in changeable spaces. In addition, innovation dynamics proposes an integrated model which has not previously been explored in the study of innovation. It provides a systematic framework for corporations to innovate and create value, and also can be applied by individuals to continually expand and enrich their HDs and maximize the value of their lives.