Comparé aux services traditionnels du secteur tertiaire, les services facilités par les technologies de l'information et des communications (ITeS, à partir du sigle en anglais, IT-enabled Services) suscitent un intérêt croissant de clients et fournisseurs d'une part du fait de l’automatisation des processus et d'autre part grâce aux nouveaux canaux de communication (Internet, réseaux mobiles, …) que ces services supportent. De ce fait, les ITeS co-créent de la valeur ajoutée due à la collaboration entre les clients et les fournisseurs lors de la conception et la livraison de services. Cet enrichissement des services traditionnels conduit à une remise à plat des méthodes actuelles de conception de biens et de services. En effet, elles ne permettent pas de répondre aux exigences imposées par ce contexte de collaboration multidisciplinaire qui intègrent les entreprises, les technologies de l'information et de la communication et les acteurs sociaux. Les caractéristiques intrinsèques des services (à savoir, l'intangibilité, l'inséparabilité, la périssabilité, la simultanéité) et leur nature sociotechnique requière à la fois une méthodologie de conception globale dirigée par les exigences des clients en vue de leur satisfaction et une approche systémique prenant en compte la dimension collaborative, le cycle de vie des services et les changements organisationnels, métiers et technologiques. Pour faire face à ces enjeux, nous proposons une méthodologie descendante pour modéliser et concevoir un système de services dirigé par les exigences des clients et supportant la collaboration entre tous les acteurs afin de permettre la co-création de ce système. Notre méthodologie repose sur une approche pluridisciplinaire et offre un ensemble de modèles interconnectés (modèle de référence de service, modèle d’exigence et modèle de collaboration) ce qui permet d’une part de donner de la flexibilité au système et de la rendre adaptable en cas de changements des exigences et d’autre part de supporter la collaboration entre tous les acteurs. Le modèle de référence offre une description des différentes dimensions du système de services (ontologique, caractéristiques et systémique) et explicite ainsi les connaissances liées aux domaines différents. En se basant sur le modèle d’exigences, les besoins du client sont spécifiés dans un langage commun et compréhensible par tous les acteurs. Ceci permet leur propagation dans tout le cycle de vie de service et leur diffusion à tous les acteurs. Le modèle de collaboration préconise une approche guidée par les données - une approche opposée aux processus métiers collaboratifs traditionnels - ce qui favorise l'interopérabilité technique et sémantique et augmente la stabilité du système face aux changements. Enfin, La collaboration s’appuie sur les canaux de communication qui engendrent des flux d'objets métiers selon lesquels des règles d'affaires sont générées afin d’invoquer les composants logiciels sous-jacents. / Compared to traditional business services, IT-enabled services provide more value to customers and providers by enabling traditional business services with Information and Communication Technologies (ICT) and delivering them via e-channels (i.e., Internet, Mobile networks). Although IT-enabled service systems help in co-creating value through collaboration with customers during service design and delivery, they raise challenges when we attempt to understand, design and produce innovative and intelligent IT-enabled services from a multi-disciplinary perspective by including businesses, technology and people for value addition and increasing benefits. Due to their social-technical nature and characteristics (i.e., Intangibility, Inseparability, Perishability, Simultaneity), IT-enabled services also lack common methods to systemize services driven by customer requirements and their satisfactions and co-produce them through ad-hoc collaboration. In this thesis, we propose a middle-out methodology to model, design and systemize advanced IT-enabled service driven by customer requirements and collaboration among all actors to jointly co-create service systems. From a multi-disciplinary perspective, the methodology relies on a multi-view models including a service system reference model, a requirement model and a collaboration model to ensure system flexibility and adaptability to requirement changes and take into account joint efforts and collaboration of all service actors. The reference model aims at a multi-disciplinary description of services (ontological, systematical and characteristic-based descriptions), and formalizing business knowledge related to different domains. As for the requirement model, customer needs are specified in common expressiveness language understandable by all service actors and made possible its top-down propagation throughout service lifecycle and among actors. The collaboration model advocates a data-driven approach, which increases busi-ness, technical and semantic interoperability and exhibits stability in comparison to business processes centric approaches. Finally, the collaboration hinges on de-livery channels expressed as data flows and encapsulating business artifacts as per which business rules are generated to invoke underlying software components.

<div>Accurate prediction of electricity demand is a critical step in balancing the grid. Many factors influence electricity demand. Among these factors, climate variability has been the most pressing one in recent times, challenging the resilient operation of the grid, especially during climatic extremes. In this dissertation, fundamental challenges related to accurate characterization of the climate-energy nexus are presented in Chapters 2--4, as described below. </div><div><br></div><div>Chapter 2 explores the cost of neglecting the role of humidity in predicting summer-time residential electricity consumption. Analysis of electricity demand in the CONUS region demonstrates that even though surface temperature---the most widely used metric for characterising heat stress---is an important factor, it is not sufficient for accurately characterizing cooling demand. The chapter proceeds to show significant underestimations of the climate sensitivity of demand, both in the observational space as well as under climate change. Specifically, the analysis reveals underestimations as high as 10-15% across CONUS, especially in high energy consuming states such as California and Texas. </div><div><br></div><div>Chapter 3 takes a critical look at one of the most widely used metrics, namely, the Cooling Degree Days (CDD), often calculated with an arbitrary set point temperature of 65F or 18.3C, ignoring possible variations due to different patterns of electricity consumption across different regions and climate zones. In this chapter, updated values are derived based on historical electricity consumption data across the country at the state level. Chapter 3 analysis demonstrates significant variation, as high as +-25%, between derived set point variables and the conventional value of 65F. Moreover, the CDD calculation is extended to account for the role of humidity, in the light of lessons learnt in the previous chapter. Our results reveal that under climate change scenarios, the air-temperature based CDD underestimates thermal comfort by as much as ~22%.</div><div><br></div><div>The predictive analytics conducted in Chapter 2 and Chapter 3 revealed a significant challenge in characterizing the climate-demand nexuses: the ability to capture the variability at the upper tails. Chapter 4 explores this specific challenge, with the specific goal of developing an algorithm to increase prediction accuracy at the higher quantiles of the demand distributions. Specifically, Chapter 4 presents a data-centric approach at the utility level (as opposed to the state-level analyses in the previous chapters), focusing on high-energy consuming states of California and Texas. The developed algorithm shows a general improvement of 7% in the mean prediction accuracy and an improvement of 15% for the 90th quantile predictions.</div>

Quality drives customer satisfaction, improved business performance, and safer products. Reducing waste and variation is critical to the financial success of organizations. Today, it is common to see Lean and Six Sigma used as the two main strategies in improving Quality. As advancements in information technologies enable the use of big data, defect reduction and continuous improvement philosophies will benefit and even prosper. Predictive Quality Analytics (PQA) is a framework where risk assessment and Machine Learning technology can help detect anomalies in the entire ecosystem, and not just in the manufacturing facility. PQA serves as an early warning system that directs resources to where help and mitigation actions are most needed. In a world where limited resources are the norm, focused actions on the significant few defect drivers can be the difference between success and failure

Accuracy in turbulence modeling remains a hurdle in the widespread use of Computational Fluid Dynamics (CFD) as a tool for furthering fluids dynamics research. Meanwhile, computational power remains a significant concern for solving real-life wall-bounded flows, which portray a wide range of length and time scales. The tools for turbulence analysis at our disposal, in the decreasing order of their accuracy, include Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), and Reynolds-Averaged Navier Stokes (RANS) based models. While DNS and LES would remain exorbitantly expensive options for simulating high Reynolds number flows for the foreseeable future, RANS is and continues to be a viable option utilized in commercial and academic endeavors. In the first part of the present work, flow over the back-step test case was solved, and parametric studies for various parameters such as re-circulation length (X_r), coefficient of pressure (C_p), and coefficient of skin friction (C_f) are presented and validated with experimental results. The back-step setup was chosen as the test case as turbulent modeling of flow past backward-facing step has been pivotal to understand separated flows better. Turbulence modeling is done on the test case using RANS (k-ε and k-ω models), and LES modeling, for different values of Reynolds number (Re ∈ {2, 2.5, 3, 3.5} × 10⁴) and expansion ratios (ER ∈ {1.5, 2, 2.5, 3}). The LES results show good agreement with experimental results, and the discrepancy between the RANS results and experimental data was highlighted. The results obtained in the first part reveal a pattern of under-prediction noticed with using RANS-based models to analyze canonical setups such as the backward-facing step. The LES results show close proximity to experimental data, as mentioned above, which makes it an excellent source of training data for the machine learning analysis outlined in the second part. The highlighted discrepancy and the inability of the RANS model to accurately predict significant flow properties create the need for a better model. The purpose of the second part of the present study is to make systematic efforts to minimize the error between flow properties from RANS modeling and experimental data, as seen in the first part. A machine learning model was constructed in the second part of the present study to predict the eddy viscosity parameter (μt) as a function of turbulent kinetic energy (TKE) and dissipation rate (ε) derived from LES data, effectively working as an ad hoc eddy-viscosity based turbulence model. The machine learning model does not work well with the flow domain as a whole, but a zonal analysis reveals a better prediction of eddy viscosity than the whole domain. Among the zones, the area in the vicinity of the re-circulation zone gives the best result. The obtained results point towards the need for a zonal analysis for the better performance of the machine learning model, which will enable us to improve RANS predictions by developing a reduced order turbulence model.

<p>  This paper explored the application of three machine learning models focused on predictive motor maintenance. Logistic Regression, Sequential Minimal Optimization (SMO), and NaïveBayes models. A comparative analysis of these models illustrated that while each had an accuracy greater than 95% in this study, the Logistic Regression Model exhibited the most reliable operation.</p>

論文摘要 賦能雖是九○年代才興起的管理概念，但卻已造成了組織與管理學者們的研究熱潮。有關賦能的定義，由於學者研究的旨趣各異以致眾說紛紜，然其精義則在於使組織成員更具有能力與活力，而不只是授予必要的權力而已。筆者認為，賦能乃是指創造一個環境，在此環境中組織各階層的員工在其責任範圍內對品質的標準、服務，以及機關的效能等方面具有實質的影響力；再者，每一個人都具有無限之潛力且是樂於工作的，祇要能適當的激發其內在的動機和鼓勵其應用所具備的豐富知識，並授與其在責任範圍內對所擔任之職務有實質的權力，則其潛能將發揮得淋漓盡致，並能擔當重責大任。由於賦能與授權間之被誤解與濫用，使得此兩者的定義早已晦澀不明。實則賦能與授權還是有所區別的，首先賦能的權力是來自於個人本身，權力的增加是透過學習而得來，組織中的權力關係是非零和的；而授權的權力是來自於組織中的職位，權力的增加是來自於層級節制的關係，組織中的權力關係是零和的。賦能所增加的是員工的能力與創造力；授權所增加的是成員的控制幅度。賦能是內在的，係釋放原先屬於個人的權力，此種權力是不能被剝奪也不是從外面賦予增加的；授權則 是外在的。此外，賦能使得員工有結合新任務擴展知識與責任的能力，並非今日人們所談論的授權而已。而賦能亦使員工對工作有擁有威，工作擁有威的產生乃是因為員工經過適當的指導、鼓勵之後，使其成為負責決定政策與規劃的人員之一。因此，賦能的範圍與深度遠超過授權。 賦能的作用，是希望透過對組織中個人層面的賦能，增加個人的能力、活力、創造力，進而實現組織層面的高績效的追求。所以，賦能的目的在個人層面與組織層面是一體兩面的。賦能有多種模式，不論係階段抑或過程模式，吾人可知其並非像變戲法那般的簡單，在實行的過程中必須有各種主客觀因素的配合、高層管理者的大力支持、為員工提供實用的訓練讓員工有學習和成長的機會、實際的授予權力、提供員工解決問題時所需要的資源等等；且經過持續不斷的努力與進行，否則將無法克盡其功。 組織施行賦能策略時可能面臨的問題包括：(一)在一般大型組織中不易實施；(二)機關上下人員間觀點之不同；(三)從事賦能策略時所遭受到的限制，計有： 1.管理者的角色，採取賦能的管理策略，對於組織而言是一項變革，而任何一項變革的開始是要能得到管理者的支持，否則就不易成功，因而管理者在從事賦能時，必須有以下的作法：(1)管理者的承諾、奉獻與企圖；(2)管理者對部屬的信賴與信任；(3)管理者要有豐富的學識、經驗以及溝通的技巧；(4)選擇正確的領導策略及具有遠見。 2.組織的層級節制：在層級節制之下，賦能成員、鼓勵參與、擴大溝通都有其基本的限制，例如，強調服從使得由下而上的管理方式成為不可能，且與賦能的精神相違背。而在另外一方面，造成成員以遵守法規、服從上級為主要目標，不但不能增進個人的創造力，同時亦不易達成組織的目標，形成所謂的「目標置換」的弊病。 3.組織既有的程序、政策、與規則：組織既有的法規，會造成在變革上的阻礙，以遵守現有的程序、法規為目的，而忽略變革的目的，即是在手段目的的連鎖上，只重「工具理性」而忽略「實質理性」。 4.其他的限制：諸如，(1)組織文化的配合程度；(2)實施賦能之後，人人參與，人人平等，外人不易瞭解職位的高低及工作範圍；因此，機關首長害怕採用賦能；(3)實施賦能之後，組織所強調的「創業家精神」，未必能適用於每個人身上。(4)實施賦能時，機關投資在人員的甄選與訓練上的成本較高。 組織施行賦能管理策略問題的解決之道，一般而言，可分為：(一)對員工賦能的策略，分為1.讓員工參與組織不斷改進的計畫與策略；2.訓練員工具備解決問題與決策的能力；3.明定參與感及賦能的提昇為組織的任務；4.建立組織及員工的目標；5.為員工設立一套以顧客為導向的績效評量指標；6.提高每位成員的參與威及加強其能力。(二)創造一個賦能的組織，有下列原則可遵循：1.職位設計要能提供員工「自主權」和「責任感」、「多樣化」、以及同時具有挑戰性；2.形成自我導向的工作團隊；3.提供員工必要的技能訓練；4.提供員工人際關係和問題解決能力的訓練；5.從監督者的角色走到人人是領導者，並對領導者提供訓練；6.全員瞭解並接受共同的願景與價值觀，去引導決策的制定；7.人力資源體系的支援與配合;8.隨著責任感的加重逐步提高授權賦能量。(三)如何在賦能的同時避免失控，一般而言，任何機關組織可利用其組織中的下列系統來避免在賦能時可能造成的失控：1.診斷控制系統：確保重要目標有效達成；2.價值觀系統：塑造並溝通正確的價值觀；3.界限系統，建立遊戲規 則，指出員工必須避免的行為及陷阱；4.交互控制系統：讓高階主管針對策略的不確定性及競爭環境的變化，掌握威脅和機會點，做好事前的因應輿準備。上述四種系統設計的目的在使組織中的管理者能於賦能的過程中找出平衡點，以避免失控。 在組織施行賦能策略時一些原則或步驟必須遵守，方可事半功倍：1.使員工有能力(或賦能)必須藉著給予員工明確的責任來達成；2.賦能必須藉著給予員工權力來達成；3.賦能必須藉著設立優異的標準來達成；4.賦能必須藉著給予員工訓練與發展來達成；5.賦能必須藉著給予員工知識與資訊來達成；6.賦能必須藉著回饋來達成；7.賦能必須藉著對員工的承認而達成；8.賦能必須藉著信任員工來達成；9.賦能必須藉著允許員工失敗來達成；10.賦能必須藉著給予員工尊重而達成。 最後下列的許多問題，可作為後續的研究者在未來繼續從事有關賦能的研究之用，茲將其說明如下： (一)賦能在現存舊有的機關抑或新成立的機關中，較易實施成功？(二)賦能在何種型式的機關中較易實施成功？例如，公家機關、私人機構、抑或非營利機構中較易實施成功？(三)賦能在何種規模的機關中較易實施成功？例如在大型的機關(200人以上)、中型機關(200人以下50人以上)、抑或小型機關(50人以下)較易成功；(四)賦予員工能力時，使用一種抑或同時使用多種干預方法較易成功；(五)從事機關中的賦能活動，是始自於機關中的某一部門抑或整個機關較易成功；(六)從事機關中的賦能活動，是採用機關內部的諮詢專家或是外部的、抑是同時採用內外部的專家較易成功？(七)機關中的賦能活動在有工會的機關抑或無工會的機關中從事較易成功？ 第一章 緒論…………………………………………………… 1 第一節 研究動機與目的…………………………………… 1 第二節 研究方法與限制…………………………………… 5 第三節 研究範圍與章節安排及研究架構……………… 6 第二章 賦能策略之文獻探討……………………………… 10 第一節 賦能之涵義………………………………………… 10 壹 有關賦能的研究文獻…………………………… 10 貳 賦能的意義………………………………………… 17 第二節 賦能之作用……………………………………… 23 第三節 賦能與授權之區別……………………………… 28 第四節 賦能概念之發展…………………………………… 32 壹 管理思潮及管理方式之轉變…………………….. 32 貳 組織採行多樣化管理之趨勢…………………… 40 參 全面品質管理(TQM)對賦能觀念之啟發………… 44 肆 多樣化管理與全面品質管理之關係……………… 51 第五節 賦能模式之探討…………………………………… 54 第三章 賦能策略的實際作法之探討……………………… 71 第一節 從組織文化的層面而言………………………… 71 第二節 從工作團隊的層面而言………………………… 78 第三節 從組織結構的層面而言………………………… 98 第四節 從組織目標建立的層面而言…………………… 100 第五節 組織施行賦能策略的問題與解決之道………… 109 第四章 賦能策略在組織中應用之探討…………………… 120 第一節 組織施行賦能策略之理由………………………. 120 第二節 應用組織發展中之干預技術施行賦能………….. 135 第三節 組織施行賦能策略之程序………………………. 140 第四節 賦能策略與領導…………………………………… 147 壹 領導的意義………………………………………… 147 貳 領導效能…………………………………………… 149 參 領導的研究途徑…………………………………… 150 肆 賦能與權變領導的關係…………………………… 162 伍 領導者的賦能行為之六項條件…………………… 165 陸 有效領導的賦能策略…………………………… 171 第五章 結論與建議…………………………………………… 178 第一節 論文回顧與發現…………………………………… 178 第二節 實務應用與後續研究建議……………………… 193 參考書目………………………………………………………… 198 圖目次 圖1-1 本文研究架構…………………………………………… 8 圖2-1 賦予活力型的管理模式……………………………… 44 圖2-2 賦能過程的五個階段………………………………… 58 圖2-3 賦能的階段及其重要作法…………………………… 61 圖2-4 領導者在四個階段中所扮演的角色………………… 63 圖2-5 賦能之層級水準………………………………………… 65 圖2-6 賦能的過程模式………………………………………… 67 圖3-1 賦能的程度……………………………………………… 80 圖3-2 目標層級………………………………………………… 108 圖4-1 新任務的成果與結果………………………………… 124 圖4-2 組織性無力感的模式………………………………… 125 圖4-3 領導效能研究的四種途徑…………………………… 151 圖4-4 費德勒的權變領導理論………………………………… 155 圖4-5 費氏權變論中的因果關係圖…………………………… 156 圖4-6 郝賽與布蘭查的情境領導論關係圖………………… 157 圖4-7 領導的途徑-目標論中之因果關係………………… 158 圖4-8 途徑目標理論的詳細模型圖………………………… 159 圖4-9 賦能的六項條件………………………………………… 167 表目次 表2-1 組織的類型……………………………………………… 26 表2-2 高績效組織特性之研究成果彙整表………………… 28 表2-3 賦能與授權之區別……………………………………… 31 表2-4 管理方法的改變………………………………………… 33 表2-5 組織中之涉入與賦能之關係………………………… 38 表2-6 傳統組織與被賦能組織的重要不同點……………… 40 表3-1 透過四個階段整合組織文化的過程………………… 77 表3-2 文化整合的每一個階段中個體的行為及思考的差異性………………………………………………………. 77 表4-1 賦能表過程中的領導策略與成員行為反應………… 172 / Empowerment is generally defined as enabling employees in the organizations to have more capability,vitality,and creativity,rather than given them necessary authority.It is also a process of transforming individuals(that is,employees in organization) full of sense of powerlessness into persons who have much more power of self-control and sense of task ownship.This ownship derives from employees' being able to take more responsibility for doing planning and making decisions after they are properly directed and motivated (that is,empowered) .Beside,empowerment is also a key to success in the process of reinventing government.The reason is that the nations' competiveness,in large part,hinges on government employees' potential,vitality,and creativity.This three important abilities,in turn,can be enhanced by effecting the empowerment strategy. There are many distinctions between empowerment and delegation.The most significant ones follows are:1.in the case of empowerment authority comes from employee's self;increase in authority are through learning;the power relationship in organizations are non-zero-sum;empowerment adds to employee's abilities and creativity;empowerment is intrinsic which means releasing power originally belonging to individuals which is undeprivable and can not be offered added onto from outside;empowerment enables employees to take on new tasks,expand knowledge and responsibility.2.in the case of delegation authority is vested in positions;increase in authority are through scalar chain;thus the power relationship is zero-sum;delegation add to employee's span of controll;delegation is extrinsic,which means power is rendered from outside. According the author some principles or guidelines should be followed when empowerment strategies are to be implemented in organizations they are:1.Power through responsibility.2.Power through authority.3.Power through standards of excellence.4.Power through trainning and development.5.Power through knowledge and information.6.Power through feedback.7.Power through recognition.8.Power through Trust.9.Power through permission to fail.10.Power through respect.

Many metropolitan cities motivate people to exploit public bike-sharing programs as alternative transportation for many reasons. Due to its’ popularity, multiple types of research on optimizing public bike-sharing systems is conducted on city-level, neighborhood-level, station-level, or user-level to predict the public bike demand. Previously, the research on the public bike demand prediction primarily focused on discovering a relationship with weather as an external factor that possibly impacted the bike usage or analyzing the bike user trend in one aspect. This work hypothesizes two external factors that are likely to affect public bike demand: weather and air pollution. This study uses a public bike data set, daily temperature, precipitation data, and air condition data to discover the trend of bike usage using multiple machine learning techniques such as Decision Tree, Naïve Bayes, and Random Forest. After conducting the research, each algorithm’s output is evaluated with performance comparisons such as accuracy, precision, or sensitivity. As a result, Random Forest is an efficient classifier for the bike demand prediction by weather and precipitation, and Decision Tree performs best for the bike demand prediction by air pollutants. Also, the three class labelings in the daily bike demand has high specificity, and is easy to trace the trend of the public bike system.

The poor state and failure of the basic education system in South Africa gave rise to this research. The wave of knowledge loss experienced in the last two decades is expected to carry on and will continue to deplete the basic education system’s knowledge base, severely affecting the already poor quality of education as well as the future economic growth and sustainability in South Africa. The main research objective was to establish whether future growth and sustainability in the basic education system in South Africa is achievable; which factors it is influenced by; and how knowledge continuity could impact on future growth and sustainability. A multidisciplinary approach focusing on organisational performance, knowledge management, individual and organisational behaviour and organisational development was followed. The nature of growth and sustainability and knowledge continuity in organisations was explored by following a contextualisation theory-building process. The main objective of the empirical research study was to determine by means of quantitative research the degree to which the influencing factors would enhance or impede growth and sustainability in an organisation. A quantitative survey method was followed. A questionnaire was developed and the survey was performed in 6 primary and secondary schools of the basic education system in South Africa. The questionnaire was found to be reliable with a Cronbach’s alpha of .8060. In the descriptive factor analysis process, principal component factor analysis was conducted, which described the five constructs that would influence growth and sustainability. These constructs’ dimensions produced significant intercorrelations which indicate that the dimensions are for the most part intercorrelated with each other in contributing to growth and sustainability. The multiple regression analysis indicated that knowledge loss would have an exceptionally strong impact on knowledge; and that knowledge, information and performance would significantly predict growth and sustainability. Organisations should change the focus for growth from physical assets to the development of intellectual capital, and knowledge continuity should form part of an organisations’ business strategy and mission. Knowledge continuity will only be successful if a culture conducive of trust and knowledge sharing and transfer exist, and are supported by effective and appropriate human resource practices and incentives. A structural equation model development strategy produced a knowledge continuity model aimed at enabling future growth and sustainability, based on the constructs confirmed in the factor analysis. The model indicated that there is a direct causal relationship between knowledge, information and performance with growth and sustainability. The regression analysis showed that most of the intercorrelations are significant, thus confirming the theory. The newly developed questionnaire and structural equation model should enable organisations to measure the degree to which the enhancing individual and organisational behavioural factors of growth and sustainability are in place and provide the measurement outcomes that would identify the factors that need to be focused on to improve and enable future growth and sustainability in an organisation. / Thesis (MBA)--North-West University, Potchefstroom Campus, 2013.

The poor state and failure of the basic education system in South Africa gave rise to this research. The wave of knowledge loss experienced in the last two decades is expected to carry on and will continue to deplete the basic education system’s knowledge base, severely affecting the already poor quality of education as well as the future economic growth and sustainability in South Africa. The main research objective was to establish whether future growth and sustainability in the basic education system in South Africa is achievable; which factors it is influenced by; and how knowledge continuity could impact on future growth and sustainability. A multidisciplinary approach focusing on organisational performance, knowledge management, individual and organisational behaviour and organisational development was followed. The nature of growth and sustainability and knowledge continuity in organisations was explored by following a contextualisation theory-building process. The main objective of the empirical research study was to determine by means of quantitative research the degree to which the influencing factors would enhance or impede growth and sustainability in an organisation. A quantitative survey method was followed. A questionnaire was developed and the survey was performed in 6 primary and secondary schools of the basic education system in South Africa. The questionnaire was found to be reliable with a Cronbach’s alpha of .8060. In the descriptive factor analysis process, principal component factor analysis was conducted, which described the five constructs that would influence growth and sustainability. These constructs’ dimensions produced significant intercorrelations which indicate that the dimensions are for the most part intercorrelated with each other in contributing to growth and sustainability. The multiple regression analysis indicated that knowledge loss would have an exceptionally strong impact on knowledge; and that knowledge, information and performance would significantly predict growth and sustainability. Organisations should change the focus for growth from physical assets to the development of intellectual capital, and knowledge continuity should form part of an organisations’ business strategy and mission. Knowledge continuity will only be successful if a culture conducive of trust and knowledge sharing and transfer exist, and are supported by effective and appropriate human resource practices and incentives. A structural equation model development strategy produced a knowledge continuity model aimed at enabling future growth and sustainability, based on the constructs confirmed in the factor analysis. The model indicated that there is a direct causal relationship between knowledge, information and performance with growth and sustainability. The regression analysis showed that most of the intercorrelations are significant, thus confirming the theory. The newly developed questionnaire and structural equation model should enable organisations to measure the degree to which the enhancing individual and organisational behavioural factors of growth and sustainability are in place and provide the measurement outcomes that would identify the factors that need to be focused on to improve and enable future growth and sustainability in an organisation. / Thesis (MBA)--North-West University, Potchefstroom Campus, 2013.

<p>From idea generation to conceptualization and development of products and technologies is a non-linear and iterative process. The work in this thesis follows a process that initiates with the review of existing technologies and products, examining their unique value proposition in the context of the specific applications for which they are designed. Next, the unmet needs of novel or emerging applications are identified that require new product or technologies. Once these user needs and product requirements are identified, the specific functions to be addressed by the product are specified. The subsequent process of design of products and technologies to meet these functions is enabled by engineering tools such as three-dimensional modelling, physics-based simulations, and manufacturing of a minimum viable prototype. In these steps, un-biased decisions have to be taken using weighted decision matrices to cater to the design requirements. Finally, the minimum viable prototype is tested to demonstrate the principal functionalities. The results obtained from the testing process identify the potential future improvements in the next generations of the prototype that would subsequently inform the final design of product. This thesis adopted this methodology to initiate the design two product-prototypes: i) an image-recognition-integrated service (IRIS) robotic hand for children and ii) cascaded multi-core vapor chamber (CMVC) for improving performance of next-generation computing systems. Minimum viable product-prototypes were manufactured to demonstrate the principal functionalities, followed by clear identification of future potential improvements. Tests of the prosthetic hand indicate that the image-recognition based feedback can successfully drive the actuators to perform the intended grasping motions. Experimental testing with the multi-core vapor chamber demonstrates successful performance of the prototype, which offers notable reduction in temperatures relative to the existing benchmark solid copper spreader. </p>