許多新概念或新技術的擴散通常不僅耗時甚長、擴散範圍十分廣泛，再加上社會網路在其中扮演了重要的角色，使得創新擴散本質上就屬於一種動態、非線性的複雜現象，事實上，近來研究發現，創新擴散的諸多特徵，包括「動態、非線性的複雜行為」，「正向回饋的自我組織現象」，以及「對初始狀態一些微小因素的敏感度」等，都與複雜理論中所強調「複雜系統」中的諸多特徵不謀而合。 另一方面，近來創新擴散研究逐漸將擴散視為一個創新者與採用者雙向互動的傳播過程，在擴散過程中，創新的演化與成員間的動態互動成為主要焦點。過去的擴散研究較少討論個體與總體層次間的結構化過程，亦即成員如何互動而產生系統層次的創新秩序，而系統層次的創新結果又如何進一步影響成員的互動，而複雜理論正好可以提供跨層次架構來回應此一理論缺口。 因此，本論文的研究問題包括以下兩者：一、由複雜理論觀點來看，概念型創新擴散的動態過程為何？二、由複雜觀點來看，在概念型創新的擴散過程中，相關因素如何影響創新擴散的動態過程？這些因素間存在何種互動與回饋關係？承上所述，本研究的範圍界定為「概念型創新」，在此「概念型創新」指的是近似於典範的一種具有複雜多元內涵的創新。 在研究方法上，本論文採用序列性多元方法的研究設計。利用歷史法、實驗法與個案法三種研究方法，針對相同的兩項問題，總共進行三項實證性研究，透過「質性方法--量化方法--質性方法」三種研究方法的截長補短，提高本研究的理論效度。 研究一利用歷史研究法對蒙特梭利教學法的擴散過程進行研究，將蒙特梭利教學法的擴散分為三階段，透過三階段成功、失敗與成功三種不同結果，發現不同的初始狀態變數情況，主要是再創造可能性與體制開放與自由度，將導致創新擴散的不同結果。研究二新概念擴散實驗進行兩階段實驗設計，操弄五項自變數進行重複多因子實驗，共取得二十八個實驗數據；比較不同變數情境與採用結果，除了驗證初始狀態變數對創新擴散的影響外，也發現自變數間存在明顯的交互關係。研究三進行蝴蝶蘭產業創新擴散個案研究，比較台糖進入蝴蝶蘭產業前後的創新擴散過程，以及蝴蝶蘭、嘉德利雅蘭，以及國蘭三種蘭屬的發展過程。隨著三項實證研究的進行，變數內涵逐漸豐富化，證據力也進一步強化。在研究三結束後得到修正後的觀念性架構，成為本論文的結論。 在結論部分，本研究有三大主張。首先，系統的初始狀態，包括創新導入者的網路位置、體制自由與開放性、再創造可能性、創新內涵豐富性、擴散誘因與採用人數等六項因素，將影響創新擴散成功的可能性。其次，創新擴散過程中包含許多的演化與正向回饋機制。最後，創新擴散是一個自我組織的過程，系統秩序從低一層次成員之間的互動自然突現，而非走向無序；但在自我組織過程中，秩序的出現有賴於中央協調機制（標準版本）；同時系統需要不斷輸入的能源，使其維持在自我組織行為出現的臨界點之上，這些能源通常來自於新採用者所帶來的量與質的效果。 / This dissertation applies a new perspective, complexity theory, to discuss the diffusion of “conceptual innovation”. Here conceptual innovation indicates a paradigm-like innovation with various content. By using “metaphor”, I treat diffusion as a self-organization process, and adopted important concepts from complexity theory, such as initial conditions, positive feedback, and self-organization, and then develop a dynamic process model of innovation diffusion. In this dissertation, a multi-method research design is adopted. To draw on the strength of each and offset the weakness of the others, three empirical studies were conducted. First study, the pilot study of this dissertation, is concerning the diffusion process of Montessori method, in which the different result of three diffusion stages was compared. Second, a laboratory experimental study simulating diffusion process of a new concept has been conducted. In each experiment, a new concept was announced and counted the number of adopters. Each experiment has different scenario design that is one specific combination of all variables, and then the number of adopters was compared. Third, the diffusion process of Phalaenopsis (Moth Orchid) industrial innovations was studied, in which the development process of early/late stage and three category orchids was compared. This dissertation concludes with the following findings. First, innovation diffusion is a dynamic, nonlinear complex process; factors in initial conditions will influence the result of innovation diffusion. Secondly, evolution and positive feedback effects work continuously all through the diffusion process. Finally, diffusion of conceptual innovation is a self-organization process, which depends on energy injecting into the system continuously and the existence of central coordination mechanism in the system.

Financial reporting fraud leads to not only significant investment risks for external stockholders, but also financial crises for the capital market. Although the issue of fraudulent financial reporting has drawn much attention, relevant research is much less than issues of predicting financial distress or bankruptcy. Furthermore, one purpose of exploring the financial reporting fraud with various forms is to obtain a better understand of the corporate through investigating its financial and corporate governance indicators. This study addresses the challenge with proposing an approach with the following four phases: (1) to identify a set of financial and corporate governance indicators that are significantly correlated with the financial reporting fraud; (2) to use the Growing Hierarchical Self-Organizing Map (GHSOM) to cluster the normal and fraud listed corporate data; (3) to extract knowledge about the financial reporting fraud through observing the hierarchical relationship displayed in the trained GHSOM; and (4) to make the justification of the extracted knowledge. The proposed approach is feasible because researchers claim that the GHSOM can discover the hidden hierarchical relationship from data with high dimensionality.

本研究採用質性研究方法，以開放系統理論為架構，從組織運作的角度來探究個案學校─種籽親子實驗國民小學之日常生活和教育實踐，從而描繪出這所另類學校的學校圖像，並分析該校穩健存續的因素。本研究之研究結果如下： 一、本研究分別以「學生學習的制度」和「學校運作的制度」來描繪種籽親子實驗國民小學之學校圖像。前者包含課程學習及生活學習的各項制度，開展出師生自由自主、和諧共融的家校生活；後者敘述親師合作辦學治校，以及攸關教師成長的各項制度，開展出親師互信互賴、共同成長的家校生活。這兩個圖像共同呈現該校特殊的「家校生活」面貌：親師生皆能自在地以其本然面貌所展現的個別性，在學校共同生活。親師生和諧共融、互信互賴的基礎正在於鼓勵個人真實呈現自我的制度與文化。「家校生活」不僅意味著親師生在學校能延續著各自在家庭裡個人化的樣貌，更顯示家庭與學校之間資源互通、成員交流，學校呈現出由一個個學生家庭及教師團成員的家庭所組成的共同體。學校生活能自然融合、連結個人生活的其他面向，個別親師生因而在學校展現出一個個自主自在的完整學習個體的面貌。 二、種籽親子實驗國民小學的內部系統特性及其外部環境關係，如下數端： （一）結構系統呈現低度科層體制特性 （二）討論文化的底蘊是「支持個別差異的開放文化」與「有機體的合作文化」 （三）教師個人系統與家長、學生個人系統彼此協調而互有影響 （四）政治系統顯現個人範疇權力的運用與組織需求的轉化能解決衝突 （五）學校與地方教育主管機關互動良好但疏於經營與所在社區的關係 三、自我組織（self-organization）的組織本質是種籽親子實驗國民小學穩健存續的因素。以內部系統來看，該校的文化系統強韌並與個人系統協調，使其維持低度科層結構並得以化解組織衝突，內部系統顯現調和一致性。以學校組織的整體系統來看，該校是文化系統運作顯著的開放系統，文化系統具自主性的「調節回饋」本質，使學校形成「自我組織」，能因應內部系統與外部環境的擾動或壓力，得以穩健存續。 四、對於種籽親子實驗國民小學的建議： （一）親師生合力建構「種籽學」論述，做為自我改革學校變革的系統性基礎 （二）建立師資培育模式，踐行公共化使命 五、本研究對於國民教育的啟示： （一）朝向彈性的「自我組織」發展，學校更具創新變革能力 （二）建立有利於「自我創化教師」生成的學校環境 （三）親師生共同建構學校信念，形成「信任連結」關係為學校發展基礎 （四）以種籽親子實小的經驗看「實驗教育」的挑戰與因應 1. 「學校評鑑」方式應以協助學校發展為目的，宜更具彈性、因校制宜 2. 主管機關宜促進另類學校與一般學校深度交流或彼此成果分享 3. 種籽親子實驗國民小學的學校運作模式可為偏地小校轉型再生的參考 / This dissertation applies qualitative research method and the “open systems theory” to amplify on an alternative school picture of Seedling Experimental Elementary School, and inquiries the elements on the sustainable development of the alternative school. The results of this dissertation upon the case study on Seedling Experimental Elementary School are as follows. 1. By describing and analyzing the manners and systems of student learning and school operating, this dissertation points out that the school picture of Seedling Experimental Elementary School is home-school life of trustful coupling relationship among parents, teachers, and students. 2. The organizational characteristics of Seedling Experimental Elementary School are as below. (1) It seems as if Seedling Experimental Elementary School is a bureaucratic organization, but just at a modest rate, is not typical bureaucracy. (2) The intrinsic qualities of discussing culture are supporting individual differences and cooperation. (3) The individual systems of parents, teachers, and students are congruent. (4) Invoking individual power and transferring the need for organization can reconcile conflicts in the political system of organization. (5) Seedling Experimental Elementary School has the good relationship with the authorities, but has the aloof relationship with the local community. 3. The innate character of Seedling Experimental Elementary School is “self-organization” that can reconcile the inner systems of the school organization and embrace the challenges or stress come from outer systems. Seedling Experimental Elementary School as a self-organization can be developing steady. 4. This dissertation makes two suggestions to Seedling Experimental Elementary School. First of all, parents, teachers, and students can collectively build the “Seedling knowledge”. Secondly, Seedling Experimental Elementary School can accomplish educational mission for the public by establishing the method and program of teacher education based on “Seedling knowledge”. 5. This dissertation makes some suggestions for national education. (1) The authorities could assist schools to be “self-organization-orientated” school organizations. (2) The authorities could assist schools to cultivate teachers to be “self-creation-orientated” teachers. (3) A school principal could lead parents, teachers, and students to work up the school belief and vision, which may develop trustful coupling relationship that could be the base of school. (4) Three suggestions for experimental education: first, school evaluation for schools which are proceeding with experimental education should be flexible and expediential; secondly, the authorities can boost the communication and promote the cooperation between alternative schools and common schools; finally, the school operating model of Seedling Experimental Elementary School could be the reference and resource for the transformation of small schools in rural.

增長層級式自我組織映射網路(GHSOM)屬於一種非監督式類神經網路，為自我組織映射網路(SOM)的延伸，擅長於對樣本分群，以輔助分析樣本族群裡的共同特徵，並且可以透過族群間存在的空間關係假設來建立分類器，進而辨別出異常的資料。 因此本研究提出一個創新的對偶方法(即為一個建立決策支援系統架構的方法)分別對舞弊與非舞弊樣本分群，首先兩類別之群組會被配對，即辨識某一特定無弊群體的非舞弊群體對照組，針對這些配對族群，套用基於不同空間假設所設立的分類規則以檢測舞弊與非舞弊群體中是否有存在某種程度的空間關係，此外並對於舞弊樣本的分群結果加入特徵萃取機制。分類績效最好的分類規則會被用來偵測受測樣本是否有舞弊的嫌疑，萃取機制的結果則會用來標示有舞弊嫌疑之受測樣本的舞弊行為特徵以及相關的輸入變數，以做為後續的決策輔助。 更明確地說，本研究分別透過非舞弊樣本與舞弊樣本建立一個非舞弊GHSOM樹以及舞弊GHSOM樹，且針對每一對GHSOM群組建立分類規則，其相應的非舞弊/舞弊為中心規則會適應性地依循決策者的風險偏好最佳化調整規則界線，整體而言較優的規則會被決定為分類規則。非舞弊為中心的規則象徵絕大多數的舞弊樣本傾向分布於非舞弊樣本的周圍，而舞弊為中心的規則象徵絕大多數的非舞弊樣本傾向分布於舞弊樣本的周圍。 此外本研究加入了一個特徵萃取機制來發掘舞弊樣本分群結果中各群組之樣本資料的共同特質，其包含輸入變數的特徵以及舞弊行為模式，這些資訊將能輔助決策者(如資本提供者)評估受測樣本的誠實性，輔助決策者從分析結果裡做出更進一步的分析來達到審慎的信用決策。 本研究將所提出的方法套用至財報舞弊領域(屬於財務舞弊偵測的子領域)進行實證，實驗結果證實樣本之間存在特定的空間關係，且相較於其他方法如SVM、SOM+LDA和GHSOM+LDA皆具有更佳的分類績效。因此顯示本研究所提出的機制可輔助驗證財務相關數據的可靠性。此外，根據SOM的特質，即任何受測樣本歸類到某特定族群時，該族群訓練樣本的舞弊行為特徵將可以代表此受測樣本的特徵推論。這樣的原則可以用來協助判斷受測樣本的可靠性，並可供持續累積成一個舞弊知識庫，做為進一步分析以及制定相關信用決策的參考。本研究所提出之基於對偶方法的決策支援系統架構可以被套用到其他使用財務數據為資料來源的財務舞弊偵測情境中，作為輔助決策的基礎。 / The Growing Hierarchical Self-Organizing Map (GHSOM) is extended from the Self-Organizing Map (SOM). The GHSOM’s unsupervised learning nature such as the adaptive group size as well as the hierarchy structure renders its availability to discover the statistical salient features from the clustered groups, and could be used to set up a classifier for distinguishing abnormal data from regular ones based on spatial relationships between them. Therefore, this study utilizes the advantage of the GHSOM and pioneers a novel dual approach (i.e., a proposal of a DSS architecture) with two GHSOMs, which starts from identifying the counterparts within the clustered groups. Then, the classification rules are formed based on a certain spatial hypothesis, and a feature extraction mechanism is applied to extract features from the fraud clustered groups. The dominant classification rule is adapted to identify suspected samples, and the results of feature extraction mechanism are used to pinpoint their relevant input variables and potential fraud activities for further decision aid. Specifically, for the financial fraud detection (FFD) domain, a non-fraud (fraud) GHSOM tree is constructed via clustering the non-fraud (fraud) samples, and a non-fraud-central (fraud-central) rule is then tuned via inputting all the training samples to determine the optimal discrimination boundary within each leaf node of the non-fraud (fraud) GHSOM tree. The optimization renders an adjustable and effective rule for classifying fraud and non-fraud samples. Following the implementation of the DSS architecture based on the proposed dual approach, the decision makers can objectively set their weightings of type I and type II errors. The classification rule that dominates another is adopted for analyzing samples. The dominance of the non-fraud-central rule leads to an implication that most of fraud samples cluster around the non-fraud counterpart, meanwhile the dominance of fraud-central rule leads to an implication that most of non-fraud samples cluster around the fraud counterpart. Besides, a feature extraction mechanism is developed to uncover the regularity of input variables and fraud categories based on the training samples of each leaf node of a fraud GHSOM tree. The feature extraction mechanism involves extracting the variable features and fraud patterns to explore the characteristics of fraud samples within the same leaf node. Thus can help decision makers such as the capital providers evaluate the integrity of the investigated samples, and facilitate further analysis to reach prudent credit decisions. The experimental results of detecting fraudulent financial reporting (FFR), a sub-field of FFD, confirm the spatial relationship among fraud and non-fraud samples. The outcomes given by the implemented DSS architecture based on the proposed dual approach have better classification performance than the SVM, SOM+LDA, GHSOM+LDA, SOM, BPNN and DT methods, and therefore show its applicability to evaluate the reliability of the financial numbers based decisions. Besides, following the SOM theories, the extracted relevant input variables and the fraud categories from the GHSOM are applicable to all samples classified into the same leaf nodes. This principle makes that the extracted pre-warning signal can be applied to assess the reliability of the investigated samples and to form a knowledge base for further analysis to reach a prudent decision. The DSS architecture based on the proposed dual approach could be applied to other FFD scenarios that rely on financial numbers as a basis for decision making.