• 沒有找到結果。

習慣領域、可變空間下的決策及創新動態學

N/A
N/A
Protected

Academic year: 2021

Share "習慣領域、可變空間下的決策及創新動態學"

Copied!
105
0
0

加載中.... (立即查看全文)

全文

(1)國立交通大學 資訊管理研究所 博. 士. 論. 文. 習慣領域、可變空間下的決策及創新動態學 Habitual Domains, Decision Making in Changeable Spaces, and Innovation Dynamics. 研 究 生: 陳彥曲 指導教授: 游伯龍 博士. 中華民國九十九年十一月.

(2) 習慣領域、可變空間下的決策及創新動態學 Habitual Domains, Decision Making in Changeable Spaces, and Innovation Dynamics. 研 究 生: 陳彥曲. Student: Yen-Chu Chen. 指導教授: 游伯龍. Advisor: Po-Lung Yu. 國立交通大學 資訊管理研究所 博士論文. A Dissertation Submitted to Institute of Information Management College of Management National Chiao Tung University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information Management November 2010 Hsinchu, Taiwan, the Republic of China. 中華民國九十九年十一月.

(3) 習 慣 領 域 、 可 變 空 間 下 的 決 策 及 創 新 動 態 學. 學生:陳彥曲. 指導教授:游伯龍 國立交通大學資訊管理研究所博士班 摘. 要. 人類行為乃由動態且複雜的流程所組成。重要的決策行為係人類行為的一部 份,因此亦與含有許多動態變化的參數。這些參數互相影響,且會隨著時間、情 境,乃至於決策者的心理狀態變化而有所改變。根據習慣領域理論,決策行為雖 因不同參數的變化而改變,卻會隨著時間的經過而達到穩定狀態,並且具有習慣 性;這使得人們常不自覺地假設決策參數的維度或範圍是固定的。然而在現實生 活中,決策參數的變化並非固定在某特定範圍,甚至可能不為人所注意。具備這 種動態特性的決策,稱為可變空間下的決策。企業創新問題即屬於可變空間下的 決策問題。 企業創新本身是一個動態過程,包含了能力集合的擴展轉化,提供產品及服 務以解除特定族群的痛苦與煩惱,創造價值並進一步分配價值等環節;其中每個 環節都涉及可變空間之決策制定。過去的創新研究中,尚缺乏整體性的架構以描 述此一動態流程。 本研究以習慣領域理論與相關之能力集合分析為基礎,探討決策問題的動態 本質,並提出「創新動態學」此一動態循環架構,探討企業如何深入潛在領域, 有效獲取、轉化其能力集合,滿足顧客需求,並且創造價值。該架構著重於潛在 領域裏參數的動態變化,強調企業的創新流程中各環節皆涉及可變空間下的決策 問題。本研究針對五個企業個案進行探討,發現企業創新成功的關鍵因素皆與創 新動態學相吻合。藉由檢視架構中各環節的相關活動與議題,企業可瞭解其在創 新過程中是否適切地關照到各參數的變化,以便持續不斷地提升其產品或服務, 解除目標族群潛在領域裏的痛苦與煩惱,進而創造最大的價值。因此,本研究所 提出之觀念性架構,可做為企業組織,甚至個人,在創新及創造價值時之重要參 考。 關鍵字: 習慣領域, 可變空間下之決策, 能力集合分析, 創新動態學. i.

(4) Habitual Domains, Decision Making in Changeable Spaces, and Innovation Dynamics. Student:Yen-Chu Chen. Advisor:Po-Lung Yu. Institute of Information Management National Chiao Tung University ABSTRACT 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. Keywords: Habitual Domain, Decision Making in Changeable Space, Competence Set Analysis, Innovation Dynamics. ii.

(5) 誌. 謝. 「因為需要感謝的人太多了,就感謝天罷。無論什麼事,不是需要先人的遺愛與遺產, 即是需要眾人的支持與合作,還要等候機會的到來。越是真正做過一點事,越是感覺 自己的貢獻之渺小。」 -- 陳之藩,謝天。. 本論文得以完成,我首要、也最要感謝的人是我的指導教授,游伯龍教授。 他引領我進入習慣領域的學習殿堂,不只在學術研究上給我最多的指導,更鼓勵 我突破自我,勇敢飛翔。他開拓我的視野,是我生命中的貴人。我會永遠記住並 努力實踐他說的成功十六字箴言: 「堅忍不拔,恆心毅力,刻苦耐勞,全力以赴。」 感謝我的學位論文口試委員:黎漢林教授、曾國雄教授、姜林杰祐教授、李 永銘教授及林明宏教授。黎教授提供了極具創意的想法,讓我受益匪淺;曾教授 提點我從事學術研究應關注的諸多事項,他的指導使論文結構更完備;姜林教授 的建議使本論文分析更完整;李教授對於本論文未來研究方向的意見,讓我收獲 良多;林教授的建議使本論文的論述更臻完善。謝謝他們的指導與啟發。 感謝習慣領域研究室一起奮鬥的夥伴:宗智、靜芳、鴻順、子玉,以及交大 資管所前後期的同學:泊寰、瓊芬、亞梅、勇劭、易霖。這麼多年的研究生涯, 謝謝有他們相互扶持,陪我一起朝著共同的目標前進。 感謝研究室的兩位助理,韻嵐及芠林。謝謝她們一路相挺,口試時期她們的 細心協助更讓我感動莫名。如果不是她們的幫忙,我的口試無法如此順利進行。 感謝修平技術學院校方的支持與配合,允許我在博士生涯的最後一年留職停 薪,專注於博士論文的撰寫。也特別感激資管系謝志明主任、盧志偉院長、曉芸、 俐麗和所有同仁們的鼓勵。 特別感謝摰友們一路幫我加油打氣。在博士班修業這麼多年期間,是若珩和 潛瑞的支持,才讓我有勇氣和信心走到今天;在「天這麼冷,風這麼大」的新竹, 謂立、嘉輝、阿結、唯晴、嘉惠的鼓勵讓我備感溫暖。當我處在低潮時,這些好 朋友常成為我抒發壓力的對象,如今終於畢業了,我願將這份快樂也與他們一同 分享。 最後,我要感謝我的家人。謝謝我的父親陳振賢先生與母親賴幸慧女士,這 麼多年來,在我於學業、家庭、工作三者之間疲於奔命時,他們兩位總是在第一 時間解除我生活上的壓力、痛苦與煩惱,做我最堅強的後盾。我何其有幸能身為 他們的女兒,也希望今天他們能以我為榮。謝謝我的先生甫文長久以來的包容與 體諒,並始終如一地支持我;也謝謝可愛的兒子奕箴,在我無暇照顧他的情況下, 還能努力長成一個品學兼優的兒童,沒讓我多操心。對於他們,我有無限的感恩, 願將這份榮耀與他們共享。 陳彥曲. iii. 謹識於新竹交大 九十九年十一月.

(6)

(7) 目 摘. 錄. 要 ........................................................................................................................i. ABSTRACT..................................................................................................................ii 誌 謝 ..................................................................................................................... iii 目 錄 .......................................................................................................................v Chapter 1. Introduction...............................................................................................1 Chapter 2. Literature Review .....................................................................................7 2.1. Dynamic decision making...............................................................................7 2.2. Innovation concept..........................................................................................8 2.3. New direction for innovation study ..............................................................11 Chapter 3. Habitual Domain and Decision Makings in Changeable Spaces........13 3.1. Definition and Elements of Habitual Domains.............................................13 3.2. Decision Makings in Changeable Spaces .....................................................17 3.3. Habitual domains and corporate innovation .................................................18 Chapter 4. Competence Set Analysis........................................................................21 4.1. The concept of competence sets ...................................................................21 4.2. Decision blinds and decision traps................................................................21 4.3. Acquirement, expansion and transformation of competence sets.................23 4.4. Research Issues of Competence Set Analysis...............................................25 Chapter 5. Innovation Dynamics..............................................................................27 5.1 Competence sets expansion and transformation ............................................29 5.2. Providing product/service to release the pain and frustration of target customers .............................................................................................................31 5.3. Creating charge and releasing charge ...........................................................33 5.4. Creating values..............................................................................................33 5.5. Value distribution and reinvestment..............................................................35 5.6. Summary .......................................................................................................36 Chapter 6. Verification of Innovation Dynamics with Case Studies .....................39 6.1. Case I: Super Girl..........................................................................................39 6.1.1. Case review........................................................................................39 6.1.2. Case analysis......................................................................................41 6.1.2.1. Game analysis .........................................................................41 6.1.2.2. Analysis of the charge structure ..............................................43 6.1.2.3. Discussion of habitual domains ..............................................45 6.1.2.4. Competence set transformation and value creation ................46 v.

(8) 6.1.2.5. Postscript.................................................................................49 6.1.3. Summary ............................................................................................50 6.2. Case II: Wretch .............................................................................................51 6.2.1. Case review........................................................................................51 6.2.2. Case analysis......................................................................................52 6.2.2.1. Analysis of the charge structure..............................................52 6.2.2.2. Competence set analysis .........................................................54 6.2.2.3. From charge release to value creation ....................................55 6.2.3. Summary ............................................................................................56 6.3. Case III: YouTube .........................................................................................58 6.3.1. Case review........................................................................................58 6.3.1.1. Introduction to YouTube .........................................................58 6.3.1.2. Motivation to set up YouTube.................................................59 6.3.1.3. Development process ..............................................................59 6.3.2. Case analysis......................................................................................60 6.3.2.1. Competence set analysis .........................................................60 6.3.2.2. Analysis of the charge structure ..............................................62 6.3.2.3. Value creation..........................................................................63 6.3.2.4. Value reinvestment and distribution........................................64 6.3.3. Summary ............................................................................................65 6.4. Case IV: Wii ..................................................................................................66 6.4.1. Case Review.......................................................................................66 6.4.2. Case Analysis.....................................................................................68 6.4.2.1. Competence set analysis .........................................................68 6.4.2.2. Charge structure in potential domains ....................................69 6.4.2.3. Nintendo’s innovation dynamics ............................................69 6.4.3. Summary ............................................................................................70 6.5. Case V: 85°C Bakery Café............................................................................72 6.5.1. Case review (Data source: 85°C Bakery Café official website) ........72 6.5.2. Case analysis......................................................................................73 6.5.2.1. Expanding and transforming competence sets........................73 6.5.2.2. Releasing pains and frustrations in the potential domain .......75 6.5.2.3. Creating and distributing value...............................................77 6.5.2.4. Creating and releasing charges ...............................................77 6.5.2.5. Creating a win-win situation...................................................78 6.5.3. Summary ............................................................................................79 6.6. Discussion and Implication...........................................................................80. vi.

(9) Chapter 7. Contributions and Conclusions .............................................................83 7.1. Contributions.................................................................................................83 7.2. Conclusions...................................................................................................84 References ..................................................................................................................... I Appendix 1: A Structure of Goal Functions ........................................................... VI Appendix 2: Eight Common Behaviors .................................................................VII. vii.

(10) Tables Table 1: Four Hypotheses of Brain Operation .............................................................16 Table 2: Four Hypotheses of Mind Operation .............................................................17 Table 3: Innovation Dynamics and fields of management...........................................37 Table 4: Comparison of “Super Girl” with traditional talent competition shows........41 Table 5: Charge Structure of the Participants of "Super Girl" .....................................44 Table 6: Potential and Reachable Domains .................................................................45 Table 7: Competence Sets of "Super Girl"...................................................................47 Table 8: Changes of YouTube’s Competence Sets.......................................................61 Table 9: Competence Set Analysis for YouTube Founders and Other Participants .....62 Table 10: Analysis of the Charge Structure..................................................................63 Table 11: Launch Times for Different Language Versions of the YouTube Interface .65 Table 12: Nintendo Price and Earnings History ..........................................................67 Table 13: Creating a Win-Win Situation .....................................................................79. viii.

(11) Figures Figure 1: JOYFUL .......................................................................................................13 Figure 2: The Behavior Mechanism ............................................................................16 Figure 3: Decision blinds .............................................................................................22 Figure 4: Decision blind reduces as we move our AD from A to B then to C.............23 Figure 5: Two Domains of Competence Set Analysis .................................................25 Figure 6: Innovation Dynamics ...................................................................................39 Figure 7: Innovation Dynamics of Case I (Super Girl)................................................39 Figure 8: “Super Girl” Participants' Charge Structure and Supply Demand. ..............44 Figure 9: Mengniu Dairy Company Competence Sets Transformation ......................48 Figure 10: Innovation Dynamics of Case II (Wretch) .................................................51 Figure 11: The Expansion of Wretch's Competence Set..............................................54 Figure 12: The Rising Number of Wretch Members. ..................................................55 Figure 13: Innovation Dynamics of Case III (YouTube) .............................................58 Figure 14: Innovation Dynamics of Case IV (Wii)......................................................66 Figure 15: Ten-Year Trend of Nintendo's ADR Price .................................................67 Figure 16: Innovation Dynamics of Case V (85°C Bakery Café)................................72 Figure 17: Competence Set Expansion of 85°C Bakery Café .....................................75 Figure 18: 85°C Bakery Café Beverage Menu. ...........................................................76. ix.

(12) x.

(13) Chapter 1. Introduction 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 1.

(14) 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. 2.

(15) 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 3.

(16) 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. 4.

(17) 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.. 5.

(18)

(19) Chapter 2. Literature Review 2.1. Dynamic decision making Human history is full of literatures recording dynamic decision making events. However, putting dynamic decision making problems into mathematical analysis started in the 19th century by economists and applied mathematicians including Pareto, Edgeworth, Von Neumann, Morgenstern and many more. Typically, the studies of dynamic decision making are based on the following three patterns of logic. The first is “simple ordering” which states that a good decision should be such that there is no other alternative that can be better in some aspects and not worse in every aspect of consideration. This concept leads to the famous Pareto optimality and nondominated solutions. The second one is based on human goal-setting and goal-seeking behavior, which leads to satisficing and compromise solution. The third pattern is based on value maximization, which leads to the study of value function (Yu 1985 and quoted therein). The three types of logic lead to an abundant literature of dynamic decision making or multiple criteria decision making (Dong et al. 2005; Dyer et al. 1992; Ehrgott 2006; Jaramillo et al. 2005; Junker 2004; Kou et al. 2005; Shi 2001; Wallenius et al. 2008; Yu 1985 and quoted therein). Most of them assume that the parameters involved in decision problems such as the set of alternatives, the set of criteria, the outcome of each choice, the preference structures of the decision makers, and the players are, more or less, fixed and steady. In reality, for most nontrivial decision problems, these parameters could change dynamically. In fact, great solutions are located only when those parameters are properly restructured. This observation prompts us to study decision making in changeable spaces (Yu & Chiang-Lin 2006; Yu & Chen 2010a, 2010b, 2010c). Note that the term “dynamic” could have diverse meanings. From the viewpoint of social and management science sense, it carries the implication of “changeable, unpredictable”; however, from the hard science and technological sense, it may also mean “changing according to inner laws of a dynamic process”, which might, but not necessarily, imply unpredictability. Much works in dynamic decision making were motivated by applying multiple criteria analysis to dynamic processes (in the second type of meaning), for example, see the concept of ideal point, nondominated decision, cone convexity and compromise solutions in dynamic problems of Yu and Leitmann (1974a, 1974b), and in technical control science of Salukvadze (1971a, 1971b). In this dissertation, the term “dynamic” is used to imply “changes with time and situation”. The dimensions and structures of decision making could dynamically change with 7.

(20) time and situations, consistent with the changes of psychological states of the decision makers and new information. 2.2. Innovation concept People have always engaged in innovative activities to improve their lives, and allow life to be richer and more interesting. Whether they are tangible products or intangible services, all great inventions or ideas are proof that people engage in innovation. In 1934, scholar Schumpeter proposed the interpretation of “innovation”. It was his belief that innovation is related to economic development, and defined innovation as “the re-combination of productive resources” (Schumpeter, 1934). Since then, the study of “innovation” has prosperously developed. In recent years the concept of innovation has become more integrated, and is no longer just the result of a specific activity. We have organized the related literatures and found some of the descriptions in the library database, and listed them as follows. These scholars’ descriptions of the innovation concept may not be the most complete, but can still be used for reference. Please see the cited literature for more details. „ „ „. „ „. „. „. Innovation is a “problem solving” process (Dosi, 1982). Innovation is an interactive process; it is related to the relationship between itself, the enterprise and different individuals (Kline and Rosenberg, 1986). Innovation is a diverse learning process. Learning uses different methods: learning while applying, learning while working, and leaning while sharing. It is also the result of absorbing and integrating internal and external knowledge (Cohen & Levinthal, 1990; Dogson, 1991). Innovation is an expressed or implied knowledge exchange process (Patel & Pavitt, 1994). Innovation is a learning and exchanging interaction process between the “innovation system” or “innovation group” creator and an individual (Edquist, 1997). Effective business innovation refers to “the process of an individual responding to the environment with his/her innovative capacity due to environmental changes. This process may go through technical and production procedure improvement, and new product design and development to allow the product, process, or procedure to become different or better” (McAdam, 2000) . Innovation is used to improve a product, service or technology. The enterprise will have the competitive advantage and continue to survive and grow through the innovation of products, processes and services (Tidd et al., 8.

(21) „. 2005). Innovation is the process that introduces a new product or service to the market. The involved scope includes marketing, quality management, production management, technology management, organization behavior, product development and strategy management (Hauser et al., 2006).. A few scholars have also proposed different points of view in regards to the overall innovation idea. The representative works are listed as follows. „. „. Peter Ferdinand Drucker proposed the concept of “Knowledge Worker” in “The Age of Discontinuity. Guidelines to our Changing Society” (Drucker, 1969). Since then, knowledge has become a major force in the economic system; it is treated as a valuable resource, which can be accumulated, transformed and inherited. Enterprises need to compete for the best creativity and application of knowledge. Professional knowledge and skill, in addition to being accumulated, can also be specifically presented in the daily organization operation procedure and in software and hardware. The proposal of this book has allowed many of the innovation related studies to be related to the creation, accumulation and inheritance of knowledge. Leonard-Barton proposed an overall framework of innovation studies in her book, “Wellsprings of Knowledge” (Leonard-Barton, 1995). It describes enterprises building and sustaining innovation sources. Leonard thinks that only core or strategic capabilities will provide the company with the competitive advantage. In the innovation framework proposed by Leonard, the core capacity of an enterprise is based on the creation and accumulation of knowledge. Enterprises can strengthen their core capacity through problem solving, implementing and integrating new tools or new methods, experiment and prototype design, and introducing/absorbing external new knowledge, etc. methods. Knowledge is definitely one of the major forces of innovation. However, the innovation and value creation of enterprises is not only limited to the management and creation of knowledge. The creation and accumulation of knowledge can enrich the enterprise core capacity, improve enterprise quality, and assist enterprises to setup a good foundation in the innovation and value creation process. Leonard’s framework completely explores the creative activity and method of knowledge, and the development of core capacity, but has disregarded how to see potential domains (potential knowledge, needs and competences). As for value creation, Leonard neglected to perform in-depth exploration on “how to further develop the value of knowledge and competence”. In fact, 9.

(22) „. „. „. potential domains must be explored further to “integrate knowledge and competence, and develop value”, and satisfy people’s potential needs. Christensen proposed the concept of “Disruptive Innovation” in his book, “The Innovator’s Dilemma” (Christensen, 1997). It pointed out that the traditional enterprise operating rule is to “use all funds and technology to concentrate on the development of products that are greatly needed by existing major customers to obtain the greatest amount of profit”, however this kind of sustaining innovation is often less competitive than other “disruptive innovation” strategies applied by some new market entrants. It uses cheap and poor functioning (but adequate) products to obtain low-end customers of major manufacturers, and once the technology is improved, and the product function is gradually enhanced, they will be able to enter the high-end market with their low price advantage, and replace the old product. This kind of innovation strategy has allowed enterprises with the entrepreneurial spirit to master the industry growth trend and rise. “Disruptive innovation” stresses on looking for opportunities from non-mainstream customers. This kind of concept happens to coincide with the concept of “finding customers from potential domains, and satisfying the needs in potential domains” in habitual domains. Shapiro organized 7-R steps focusing on the organization innovation in his book, “24/7 Innovation: A Blueprint for Surviving and Thriving in an Age of Change” (Shapiro, 2001). It established an innovative framework of Rethink, Reconfigure, Re-sequence, Relocate, Reduce, Reassign and Retool, however the framework only proposed recommendations focusing on the improvement of enterprises (supply), and seldom mentioned the consumers (demand). Stan Lai (賴聲川) interpreted creativity and innovation with the perspective of an artist in his book, “Stan Lai’s Creative Learning” (賴聲川的創意學) (賴聲川, 2001). Lai proposed the concept of a “creative pyramid” to interpret the process of innovation. He divided creative learning into “creation” and “learning”, and used “wisdom” and “method” to respectively represent these two co-existing fields. Creation includes content, inspiration, and knowledge; learning includes forms, tools, and techniques. Lai explores innovation with the nature of philosophy; many of his perspectives are similar to the concept of habitual domains, such as the innovation dynamics framework proposed by the study used the habitual domains as a basis to emphasize that the process and result of innovation must be able to satisfy human nature. This perspective is very consistent with the perspective of 10.

(23) “starts from your heart”, stressed in his book. 2.3. New direction for innovation study In the field of innovation study, due to the fact that expertise and experiences of each scholar are with different habitual domains, the innovation studies proposed also have different habitual domains, and various dimensions and styles. However, whether in the exploration of the innovation framework, method or practical experience, the innovation studies in the academic field are mostly limited to specific area discussion (such as innovation thinking, innovation product design or innovation procedure, etc.). These discussions often focus on the innovation management method analysis of the corporation itself, or propose the innovation solution and strategy focusing on the organizational specific problem. They can propose a solution for the corporation while facing difficulties or problems, but they lack a holistic and comprehensive systematic model to assist corporations to focus on the customer’s/user’s potential needs, release the potential pain and frustration, and further create values. In other words, the current innovation studies indeed explore or resolve the issue observed from the actual domains of a corporation or customers, however, there is not any related in-depth exploration of the problems, charges, pains and frustrations in potential domains. To provide a comprehensive framework to compensate the incompleteness of the existing innovation studies, this study will explore corporate competence sets transformation and innovation and value creation process from the perspective of the “habitual domains theory” and “competence sets analysis”. By getting into the in-depth potential domains, an integrated framework, Innovation Dynamics, is proposed. This is a brand new research direction; there is no systematic analysis for this area in the past. This framework, in addition to providing entrepreneurs a specific operating idea and method, will assist them to continuously create value and sustainably operate in the fierce competitive environment. It can also be applied to individuals to create value, and release others’ pain and frustration through personal competences (including the relationship resource and the skills of having a good relationship, etc. in potential domains), and further create one’s own value. This kind of research direction will create a new vision and situation for the corporate innovation research field.. 11.

(24)

(25) Chapter 3. Habitual Domain and Decision Makings in Changeable Spaces To illustrate the impact of habitual domain on decision making, let us consider Figure 1 as an example. Example 1: What is it inside the frame?. Figure 1: JOYFUL Assume the frames of perception are represented by the “lighted” (white) area as illustrated in Figure 1(a) to 1(e). In Figure 1(a), we can see something fuzzy, but do not understand what is in the frame, the lighted area; but when our frame is expanded, as in Figure 1(b), we might be able to guess it is “JOY”. Progressively, as the lighted area gets larger, we see “JOY” with an asterisk in Figure 1(c), “JOYFUL” in Figure 1(d), and then “NOT JOYFUL” as in Figure 1(e). 3.1. Definition and Elements of Habitual Domains Example 1 illustrates that one’s judgment is greatly affected by his/her perception frames, the size and shape of the lighted areas of Figure 1. The perception frames are largely determined by the parameters of our human behavioral systems. Being able to understand and utilize these parameters is therefore a vital step to making decisions efficiently and effectively in changeable spaces.. 13.

(26) Habitual domains was first suggested in 1977 (Yu 1977) and further developed (Chan and Yu 1985; Yu 1980, 1981, 1985, 1990, 1991, 1995, 2002 and quotes therein) by Yu and his associates. It states that over a period of time, the set of ideas and concepts which we encode and store in our brain can gradually stabilize in certain domain, know as Habitual Domains (HDs); unless there is an occurrence of extraordinary events, our thinking processes will reach some steady state or may even become fixed. This phenomenon can be proved mathematically (Chan and Yu 1985; Yu 1985). Being aware of the habitual ways of our decision making is important for us to clarify fuzziness, make better decisions and avoid costly mistakes. To better understand the concept of HDs, let us briefly introduce the elements of HD, which are important parameters in the human behavioral systems. Habitual domains at time t, HDt, include the following four sub-concepts: (i). Potential domain, designated by PDt, is the collection of all ideas and operators which can be potentially activated with respect to specific events or problems by one person or by one organization at time t. In general, the larger the PDt, the more likely that a larger set of ideas and operators will be activated, holding all other things equal. (ii) Actual domain, designated by ADt, is the collection of ideas and operators which are actually activated in our minds at time t. Note that not all the ideas and operators in the potential domain can be actually activated. Also note. that the ADt is a subset of the PDt, that is ADt ⊂ PDt. (iii) Activation probability, designated by APt, is defined for each subset of PDt and is the probability that a subset of PDt is actually activated or is in ADt. For example, people who emphasize profit may be more likely to activate the idea of money, while people who study mathematics may be more likely to generate equations. (iv) Reachable domain, designated by RDt, is the collection of ideas and operators which can be generated from a given set in an ADt. In general, the larger the idea set and/or operator set in ADt, the larger the RDt. At any point in time, without specification, HDt is the collection of the above four subsets. That is, HDt = {PDt, ADt, APt, RDt} When there is no confusion, the subscript “t” may be dropped as to simplify the 14.

(27) presentation. Recall that it is humans that make decisions. Understanding human behavioral systems plays a vital role in making good decisions. The complex processes of human behaviors have a common denominator resulting from a common behavior mechanism. The mechanism depicts the dynamics of human behavior. Based on the literature of psychology, neural physiology, dynamic optimization theory, and system science, Yu (1980, 1981, 1985, 1990, 2002) described a dynamic human behavior mechanism as presented in Figure 2 which is briefly explained below: (i) Box (1) is our brain and its extended nervous system. Its functions may be described by the four hypotheses (H1-H4) in Table 1. (ii) Boxes (2)-(3) represent two basic functions of our mind, explained by H5 in Table 2. (iii) Boxes (4)-(6) represent how we allocate our attention to various events, described by H6 in Table 2. (iv) Boxes (8)-(9), (10) and (14) represent a least resistance principle which humans use to release their charges, described by H7 in Table 2. (v) Boxes (7), (12)-(13) and (11) represent the information input into our information processing center (Box (1)). Boxes (11) and (14) represent internal information inputs. Boxes (7), (12)-(13) represent external information inputs, which are explained in H8 in Table 2.. 15.

(28) Internal Information Processing Center (14). Problem Solving or Avoidance Justification. Physiological Monitoring. (11). (3). (2). Goal Setting. State Evaluation. (1). (4) Comparison. (13). Unsolicited Information. (5) CHARGE STRUCTURE (6) Attention Allocation (7) Solution Obtained?. (8) (12). Solicited Information. Self-suggestion. (10). (9) Experience/ Reinforcement. Actions/Discharges. Being Observed. External. Figure 2: The Behavior Mechanism Table 1: Four Hypotheses of Brain Operation Hypotheses. H1. H2. H3. H4. Descriptions Thoughts, concepts or ideas are represented by circuit patterns of the brain. The circuit patterns will be reinforced when the Circuit Pattern corresponding thoughts or ideas are repeated. Furthermore, the Hypothesis stronger the circuit patterns, the more easily the corresponding thoughts or ideas are retrieved in our thinking and decision making processes. Unlimited Capacity Practically every normal brain has the capacity to encode and Hypothesis store all thoughts, concepts and messages that one intends to. The encoded thoughts, concepts and messages (H1) are Efficient organized and stored systematically as data bases for efficient Restructuring retrieving. Furthermore, according to the dictation of attention Hypothesis they are continuously restructured so that relevant ones can be efficiently retrieved to release charges. The perception of new events, subjects, or ideas can be learned primarily by analogy and/or association with what is already known. When faced with a new event, subject, or idea, the brain first investigates its features and attributes in order to establish Analogy/Association a relationship with what is already known by analogy and/or Hypothesis association. Once the right relationship has been established, the whole of the past knowledge (preexisting memory structure) is automatically brought to bear on the interpretation and understanding of the new event, subject or idea.. 16.

(29) Table 2: Four Hypotheses of Mind Operation Hypotheses H5. Goal Setting and State Evaluation Hypothesis. H6. Charge Structure and Attention Allocation Hypothesis. H7. Discharge Hypothesis. H8. Information Inputs Hypothesis. Descriptions Each one of us has a set of goal functions and for each goal function we have an ideal state or equilibrium point to reach and maintain (goal setting). We continuously monitor, consciously or subconsciously, where we are relative to the ideal state or equilibrium point (state evaluation). Each event is related to a set of goal functions. When there is an unfavorable deviation of the perceived value from the ideal, each goal function will produce various levels of charge. The totality of the charges by all goal functions is called the charge structure and it can change dynamically. At any point in time, our attention will be paid to the event which has the most influence on our charge structure. To release charges, we tend to select the action which yields the lowest remaining charge (the remaining charge is the resistance to the total discharge) and this is called the least resistance principle. Humans have innate needs to gather external information. Unless attention is paid, external information inputs may not be processed.. Note that there are four hypotheses (H1-H4 of Table 1) describing the information processing functions of the brain and four hypotheses (H5-H8 of Table 2) describing the general framework of our mind. From the behavior mechanism of Figure 2 and the eight hypotheses, we notice that human’s behavioral system involves the following parameters: goal setting, state evaluation, charge structure, attention allocation, information inputs, physiological monitoring, memory, etc. Each parameter also involves complex subsystems. For instance, goal setting involves the following subparameters: survival and security, perpetuation of the species, feelings of self-importance, social approval, sensuous gratification, cognitive consistency and curiosity, self-actualization, etc. As people change any or some of these parameters, his or her perception will change. Awareness of the existence and changes of the relevant parameters play an important role in understanding human behavior and making good decisions. For more details, see Yu (1990, 2002, 2009) and Yu & Chiang (1999). 3.2. Decision Makings in Changeable Spaces Mathematically, decision makings in changeable spaces can be described as follows: Assume that changeable decision parameters involve the following decision 17.

(30) elements (extension to include other parameters can be done similarly): (i) the alternative set at time t, denoted by Xt; (ii) the criteria at time t, denoted by Ft; (iii) the outcome measured in terms of the criteria at time t, denoted by Ft; (iv) the preference of decision maker at time t, denoted by Dt; and (v) the information inputs at time t, denoted by It. Each decision element is a set which can vary with time, situation, and the decision maker’s perception to the decision problems. The alternative set at time t+∆t can be denoted by Xt+∆t = G(Xt, Ft, Ft, Dt, It, HDt). (1). where HDt consists of actual domains (ADt), reachable domains (RDt), potential domains (PDt) and activation probability (APt). As in (1), Xt+∆t not only depends on Xt, but also on the other decision elements, Ft, Ft, Dt, It as well as HDt. Note that Xt and Xt+∆t can be set functions, and the difference between Xt and Xt+∆t would describe the changes due to time and situation. Also note that Xt and Xt+∆t can have different dimensionality. Similarly, we can write the dynamic change of other parameters as follows: Ft+∆t = H(Xt, Ft, Ft, Dt, It, HDt). (2). Ft+∆t = J(Xt, Ft, Ft, Dt, It, HDt). (3). Dt+∆t = K(Xt, Ft, Ft, Dt, It, HDt). (4). It+∆t = L(Xt, Ft, Ft, Dt, It, HDt). (5). Note, (1) – (5) describe the fact that the decision elements (or parameters) not only vary with time, but also mutually interact with each other through time. For further discussion see Ch 7-8 of Yu (1990, 2002). 3.3. Habitual domains and corporate innovation Regarding to a product or service provided by a corporation, the value it created 18.

(31) can be described in one sentence: “Whose pain and frustration are released by the product or service in a specific circumstance?” In other words, we must explore from the following two directions when estimating values: (i) Targets: who are the customers? Whom will the products or services be served to, currently and potentially? (ii) Functions: what kind of pains and frustrations, both in actual and potential domains, can the products and/or services help release? Whether they are targets or functions, they both have their actual domains, reachable domains and potential domains. Take the aforementioned YouTube case as an example (see Chapter 1 and Section 6.3 for details). In view of the target group dimension, at the beginning, the target objects to be served by YouTube were eBay sellers, which is the customers that the corporation can see (and want to serve) in the actual domains at that time. After it failed, it expanded the target customers to “all internet users”, who in fact existed in the potential domains. Looking from the functional perspective, the problem that a product or service can solve will also have actual domains, reachable domains and potential domains. Most corporations are devoted to solving the urgent problems, which are initiated from the actual domains, such as that YouTube is created to provide a useful platform to solve the difficulty of video sharing. However, we need to discover and effectively release the charge in the potential domains to truly create value, and bring happiness and satisfaction to customers. The potential domains not only exist in people (target customers), but also exist in affairs (problem sets or competence sets). Therefore, in addition to thinking about who the potential customers are, a corporation should also try to figure out what the target customers’ potential pain and frustration are. Besides, the resource or competences in the potential domains shall be deeply searched and properly applied so as to enrich and empower one’s competence sets (see Chapter 4 for further discussion).. 19.

(32)

(33) Chapter 4. Competence Set Analysis 4.1. The concept of competence sets The study on Competence Set Analysis began with Yu (1989), as a derivative of HD theory. Its mathematic foundation was built by Yu & Zhang (1989, 1990, 1993). The competence set (CS) for a given decision problem is defined as a collection of ideas, knowledge, skills, resources and efforts for its effective solution. Such a set, like HD, implicitly contains potential domain, actual domain, reachable domain, and activation probability as discussed in Chapter 3. Anything or anyone, including a product or service that can release the pain, frustration and charge, has competence. Everyone, and every corporation, has its competence sets. One will set up the goal and evaluate what competence sets (including people, techniques and resource) are needed, and whether the existing competence sets can assist him/her to effectively solve the problem when a spontaneous or triggered creativity causes an event input in the competence sets transformation process (Yu & Lai, 2004). If the existing competence sets are inadequate to solve the problem effectively, one will start thinking about what competence sets are necessary, but not yet obtained, and how these competence sets should be effectively obtained. The competence sets transformation process of a corporation or producer is also the same. To analyze the competence sets of individuals or corporations, we can decompose the CS as follow:. CSt = (CSt1 , CSt2 , CSt3 ,..., CStn ). (6). where CStk denotes the kth item of the CS at time t. Note that CS will be dynamically changed as time (t) goes by. 4.2. Decision blinds and decision traps. Because of HDs and being unaware of the decision parameters and their changing nature, people would easily have decision blinds or even get into decision traps. Recall in Example 1, we might not be able to know or misunderstand the complete word or situation because we are trapped by our perception frame (the lighted area). The dotted area outside the frame is our blind.. 21.

(34) At time t, let us denote the truly needed CS for solving problem E successfully by CSt(E), and its perception by decision makers, by CSt*(E). Then CSt(E)\CSt*(E) would be the decision blinds, the set of all the competences required but not seen by the decision makers at time t. See the illustration of Figure 3. Note that the larger the decision blind is, the more likely decision makers might make dangerous mistakes. Refer to Example 1. Suppose that the perception frame of Figure 1(e) is CSt(E). Then the shaded areas of Figure 1(a) to 1(d) are the decision blinds. Note that as the blinds are progressively reduced, the picture becomes progressively clearer, and eventually the fuzziness disappears.. Figure 3: Decision blinds Usually, CSt(E) and CSt*(E) can be changed with time. Suppose that CSt*(E) is fixed or trapped in a certain domain and CSt(E)\CSt*(E) is large, then we tend to make mistake in decision and we are in a decision trap. Decision trap (i.e. CSt*(E) is fixed, independent of t) can lead to dangerous mistake, especially when CSt(E) changes rapidly with time and CSt(E)\CSt*(E) becomes very large. Note that CSt*(E) being fixed or trapped in a certain domain is equivalent to the corresponding actual domain (ADt) and reachable domain (RDt) being fixed or trapped in a certain domain. This can occur when we are in a very highly charged state of mind or when we are over confident, which makes us respond quickly, and unwittingly and habitually commit the behavior of decision traps. Recall in Chapter 1, suppose that YouTube was in highly charged state of serious financial difficulty, it might fall into a decision trap, and sell the services to less interested customers with much less value created. By changing our actual domains (ADs), we can change and expand our reachable domains (RDs). We can reduce decision blinds and/or avoid decision traps by systematically changing the ADs. For illustration, assume that CS(E) and RDs are given, as depicted in Figure 4. Then as we move the AD from A to B, then to C, our 22.

(35) decision blind reduces progressively from CS(E)\RD(A) to CS(E)\(RD(A)∪RD(B)) then CS(E)\(RD(A)∪RD(B)∪RD(C)).. ‧A. RD(A). ‧B. RD(B). CS(E). ‧C. RD(C). RD: Reachable. Figure 4: Decision blind reduces as we move our AD from A to B then to C For challenging decision problem, we can treat the decision parameters as different points for ADs. Systematically moving over the parameters and pondering their possible RDs can expand our RDs for dealing with the challenging problems. As a consequence, CS*(E) is expanded and our decision blinds, CS(E)\CS*(E), reduced. In additions, the HD tools (Yu 1990, 1995, 2002, 2009) can work with the individual decision parameters as to reduce the decision blinds and avoid decision traps. They can expand and enrich our actual domains and reachable domains and look into the depth of the potential domains, they can also expand and enrich our perception on the decision problem and its related parameters. 4.3. Acquirement, expansion and transformation of competence sets. When confronting a decision problem, a corporation needs to evaluate its current competence sets to see if they are adequate for solving the problem. If the current competence sets are inadequate, then competence sets transformation or expansion must be processed. Competence sets transformation can be shown in the following equations:. CSt +1 = Tt (CSt , Et ). (7). where Et denotes the events, decision problems, or environment that the corporation or individual is confronted. It may be a challenge or information that a corporation faces, or a motivation that promotes a corporation to change. After transforming by the function Tt, the original competence set CSt is expanded into a new one, CSt+1. 23.

(36) By adding new functions or capabilities on the original products or services, corporations can expand their old competence sets into new ones. For simplicity, let us drop the notation of time (t). Suppose CS k denotes the original competence sets of products/services provided by corporations, and CS k * denotes the competence sets after transformation and expansion. The transformation of competence sets can be presented as follow:. CS k * = CS k ⊕ Δ k = T k (CS 1 , CS 2 ,...CS n ; E ). (8). where Δ k denotes new functions or capabilities. It could be some single item/ function, or some comprehensive competence set. After transforming by the function Tk, the original competence set CS k is expanded into a new one, CS k * . For instance, a traditional grocery store added information technology, operation management capability, and modern equipment to its own competence sets, and transformed into a convenience store, which can serve more customers and release more people’s pain and charge. Also, Google originally specialized in information searching technology, but after it merged with YouTube and DoubleClick, its competence sets further expanded, and become a complex web portal with more equipped functions. For a corporation, when the goal is set, the next step is to process competence sets transformation, and allow equation (8) to be possible. Competence sets expansion and transformation can be processed in the following two methods: (i) Internal adjustment or development: Improve or transform the original competence sets to achieve the goal or solve problems by adjusting corporation resource, time or management procedure or method. (ii) Integrate with external competences: Expand or transform the original competence sets to assist the corporation to solve problems through borrowing, proper application or sharing external resource or competence sets. As an example, China Mengniu Dairy Company Limited (蒙牛乳業) cooperated with television media, telecommunication operators, and network operators to improve the sales performance of its dairy products through the spread of “Super Girl” and the power of the audience, which successfully achieved its goal of improving the sales performance (see Section 6.1 for details). In addition, through outsourcing, strategic alliance or merging, the competence sets can be also expanded by obtaining external ones. 24.

(37) Equations (6), (7), and (8) described the decomposition, transformation and expansion concept of competence sets. To allow the study to focus on the corporate cases, we will not explore the mathematical model and proof of competence sets analysis in detail here. 4.4. Research Issues of Competence Set Analysis. Competence set analysis has two inherent domains: competence domain and problem domain. Like HD, each domain has its actual domain and potential domain, as depicted in Figure 5.. (ii) To create value effectively. Competence. Problem. Domain. Domain. potential competence domain. potential problem domain. (i) To acquire needed CS efficiently and effectively. Figure 5: Two Domains of Competence Set Analysis From these two domains, there are two main research directions: (i) Given a problem or set of problems, what is the needed competence set? and how to acquire it? For example, how to produce and deliver a quality product or service to satisfy customers’ needs is a main problem of supply chain management. To successfully solve this problem, each participant in a supply chain including suppliers, manufacturers, distributors, and retailers must provide the chain with its own set of competence, so that the collected set of competence can effectively achieve the goal of satisfying customers’ needs. How to expand the existent competence set to the needed competence set in most effective and efficient way? A mathematical foundation for such competence analysis is provided by Yu & Zhang (1990). Under some suitable assumptions, the problem can be formulated and solved by decision tree, graph theory, spanning trees, spanning tables and mathematical programming (Feng & Yu 1998; Huang et al. 2004; Li&Yu 25.

(38) 1994; Li et al. 2000; Lin 2006; Shi & Yu 1996; Yu & Zhang 1989). Most earlier researches have focused only on the deterministic situation. However, one could remove this assumption to include uncertainty, fuzziness, and unknowns. In the recent studies, some heuristic methods, such as genetic algorithm (GA), hybrid genetic algorithm (hGA), multicriteria genetic algorithm, multi-objective evolutionary algorithm (MOEA), data mining technology, and forest learning technique have also been incorporated into the analysis of competence set expansion (Chen 2002; Hu et al. 2003; Huang et al. 2004; Lin 2006; Opricovic&Tzeng 2003, 2009). (ii) Given a competence set, how to locate a set of problems to solve as to maximize the value of the competence? Given a competence set, what is the best set of problems that can be solved by the competence set as to maximize its value? If someone has already acquired a particular competence set, what are the problems he/she should focus to solve as to maximize its value? For instance, if we get a doctoral degree from certain university, which symbolize we have a certain set of competence, how do we maximize the value of this degree? Think of the opportunities in actual domains and potential domains. There are lots of studies of competence sets analysis working in this direction. For example, Chen (2001) established several indices that have impact on consumers decision making and provided a framework for helping firms in expanding the benefits of their products to fully address the consumer’s needs. Hu et al. (2002, 2004) generate learning sequences for decision makers through competence sets expansion to help them make better decisions. Chang & Chen (2009) develop an analytical model of competence sets to assist drivers in routing decisions. Chiang-Lin et al. (2007) studied the change of value when competence set are changed in linear patterns so that the corporations can create value by taking loss at the ordering time and making profit at the delivery time. Competence sets expansion and transformation play a vital role in the corporation innovation process. The follow-up cases explored in the study all have a close relationship with the aforementioned two directions. We will inspect how each corporation case obtained its required competence sets to solve problems, and will also analyze how these corporations utilize their competence sets and create values.. 26.

(39) Chapter 5. Innovation Dynamics According to the HD theory and CS analysis, all humans and things can release pains and frustrations for certain group of people at certain situations and time. Thus, all humans and things carry the competence (in broad sense, including skills, resources, functionalities, even attitudes). If we regard all humans and things as a set of different CSs, then producing new products or services can be regarded as a transformation of the existent CS to a new form of CS. Based on this, we could depict a comprehensive and integrated framework, called the Innovation Dynamics (see Figure 6), to help people understand corporate innovation and creation of maximal values for the targeted customers and themselves. The dynamics can be interpreted clock-wise, according to the indices of Figure 6, as follows: (i) According to HD Theory, when there exists unfavorable discrepancies between the current states and the ideal goals of individuals or organizations (for instance, the corporations are losing money instead of making money, or they are technologically behind, instead of ahead of the competitors), it will create charges which can prompt the individuals or corporations to work harder to reach their ideal goals; (ii) The transformation of CSs will be presented in visible or invisible ways, which results in a new set of the products or services produced by the corporations; (iii)The products or services produced by corporations must carry the capability to relieve / release the pain and frustration of targeted customers. Note that there are actual domains, reachable domains, and potential domains for the targeted customers, and for their pains, frustrations, and problems; (iv) Besides discharge, corporations or organizations can create charges to the targeted customers by means of marketing, advertisement or promotion, and vice versa; (v) The targeted customers will experience the change of charges. When their pains and frustrations are relieved, the customers become happy. By their buying the products or services, the products and services create their value; (vi) The value will be distributed to the participants such as employees, stakeholders, suppliers, society, etc. In addition, to gain the competitive edge, products and services have to be continuously upgraded and improved. The reinvestment therefore is needed in order to develop and produce new products and services.. 27.

(40) Decision Making in Changeable Spaces. Actual Domains, Potential Domains, and Reachable Domains. (ii) CS transformation. products / services. (C). (i). (B). (iii). (iv). Internal Charge External Charge. relieve / release. (D). create or release charges. individual / organizations. pain/frustration of targeted customers. (A). (E) reinvestment. (vi). value distribution. create value. (v). participants: employees, stakeholders, suppliers, society, etc.. Figure 6: Innovation Dynamics. 28.

數據

Figure 1: JOYFUL
Figure 2: The Behavior Mechanism  Table 1: Four Hypotheses of Brain Operation
Table 2: Four Hypotheses of Mind Operation
Figure 3: Decision blinds
+7

參考文獻

相關文件

In particular, the parabolic second-order directional differentiability of projec- tion operator was used to establish the expression of second-order tangent sets, which plays

//if it does not connect it starts an access point with the specified name //here "AutoConnectAP". //and goes into a blocking loop awaiting

It clarifies that Upāyakauśalya, in the process of translation, has been accepted in Confucian culture, and is an important practice of wisdom in Mahāyāna Buddhism which

The PROM is a combinational programmable logic device (PLD) – an integrated circuit with programmable gates divided into an AND array and an OR array to provide an

Having regard to the above vision, the potential of IT in education and the barriers, as well as the views of experts, academics, school heads, teachers, students,

Microphone and 600 ohm line conduits shall be mechanically and electrically connected to receptacle boxes and electrically grounded to the audio system ground point.. Lines in

It is interesting that almost every numbers share a same value in terms of the geometric mean of the coefficients of the continued fraction expansion, and that K 0 itself is

/** Class invariant: A Person always has a date of birth, and if the Person has a date of death, then the date of death is equal to or later than the date of birth. To be