ABSTRACT The domestic economic activity has been still in recession for several years. Besides moving outwards, the enterprises gradually decreased predominance in competition and are obliged to try every endeavor to find out any of proper management system. Hoping via applying diversified thinking model and managing skills that could revive the enterprises. Firmly, improve the management performance and promote the competence. The Balanced Scorecard¡]BSC¡^,a new management method, has been presented in such an occasion¡]by Kaplan & Norton in 1990¡^.This management system starts from erecting the company¡¦s vision and mission, further to choose his own strategy. However these strategic targets are planned to form a strategy- map, which consisting of four dimensions. Moreover in each dimension respectively to have various Key Performance Index¡]KPI¡^and those KPI will drive future performance -evaluation-indicators. Precisely speaking that BSC can transform the strategic targets into practical actions. As BSC can link strategy with execution, evaluation and learning to be a feedback loop so that performs to test strategy and adjust it to conform to the variation of external environment. Finally a company, which has applied above system will form a high-performing organization. This case study is based on the biggest domestic integrated stainless steel producer. Reviewing its constructed procedure of introducing the BSC and comparing its actual performance data of before and after applying of BSC system. At the same time, reconfirm by analyzing the outcome of questionnaires & visiting data. Hopefully, to prove applying BSC is an effective way to improve management performance. About this section, first of all, referring to data collection, to collect the questionnaires which are respondent from all of department managers and customers of case company. Secondly, to choose specific top managers of main departments of case company for deep visiting- survey. Finally, to analyze above data and get the following conclusions: 1. There are still some unrevealed problems existing in case company after the analysis of data acquired. 2. There is an only effective way to promote management performance that should be under a combination between monitoring KPI and incentive system. 3. The BSC can promote the management performance indeed. This study can offer a reference for other related steel producer or other enterprises to adopt the BSC in future. Absolutely, to construct such a system could make company act efficiently response against the impacts resulted from the fast variation of external environment and no doubt that could keep the management more flexible and more competent forever. Keywords: Balanced Scorecard Management performance Key performance index

Outsourcing is a popular name in the employ market. It is a common situation for enterprises to adopt the outsourcing system instead of hiring employees in order to achieve the goals of cost-down and elevate the competency of enterprises. Especially at the lower level technical and heavy physical- loaded industries. China Steel Corporation (CSC) has been experiencing of applying the outsourcing system on site-work over thirty years. CSC and the subcontractor are becoming a symbiosis relationship. Nevertheless, most of the documents focused on the research between the workforce flexibility and organization performance of the subcontract system, it¡¦s rare to investigate the integral job performance which are resulted from the cooperative working model in specific factory. Moreover, there are problems to be improved during the long period operation experiences under the similar symbiotic structure, such as work safety, quality, efficiency, management of manpower etc. which lead to results that are unsatisfied working performances. But there is no actual performance evaluation system to verify. This research conducts to find out the key successful factors and construct the key performance index of mechanical maintenance for job performances evaluation. It can be utilized to promote continuously for synchronizing maintenance performances of CSC and subcontractors. Eventually, enterprises¡Boutsourcing employees and subcontractors can get the best of benefits from each other. This research applies the method of Analytic Hierarchy Process (AHP) to conduct interviews from experts and questionnaires survey. It was capable to be calculated the key performance factors weight for the references of the performance evaluation standard. Furthermore, the key points of recognition of maintenance performances from supervisors were analyzed the weight differentiations of sections¡Bpositions¡Bfield experiences from the EXCEL statistic program. The final conclusions were: 1 The priority to weight Key Performance Indexes of mechanical maintenance on main hierarchy structure are management of manpower(0.346), equipment maintenance(0.27), preparation of material(0.148), working environment(0.122) , working method planning(0.113)¡C 2 The top 80 % of KPI¡¦s weight include 14 items listed as below: 2.1 promotion of reliability of equipment maintenance. 2.2 reduce the rate of resignation. 2.3 promotion of numbers of qualified for the testing of technical and operation licenses. 2.4 decreasing the waiting time of materials during the repair period. 2.5 increase periodical training hours. 2.6 elevate the level of education. 2.7 reduce accident occurring rate. 2.8 reduce the times of safety working accidents 2.9 reduce the trouble shooting time. 2.10 raise the rate of presence. 2.11 reduce the break down hours of equipments. 2.12 reduce the numbers of break down equipment. 2.13 raise amounts of equipment improvement proposals. 2.14 raise amounts of operation method improvement proposals. 3 From the individual survey analysis, it shows that there are obvious differentiation related to the management of manpower¡Bequipment maintenance¡Bworking environment. 4 Based on different sections perspectives, it shows that even though most of the sections are consistent, but having diverse recognition were found. It means that only a slice difference can be observed overall. 5 Based on different positions perspectives, it shows that different levels of authority are consistent in top two KPI indexes on main structure. the others indexes have slice differences. 6 Based on different experienced perspectives, it shows that reverse result occurred between veterans and people who are not experienced for long time of work, and the former focus on the management of manpower; the latter focus on equipment maintenance.

The introduction of the Strategy Maps cooperate with the Balanced Scorecard(BSC) of Kaplan and Norton of 2003, the application and studying more and more on the practice and academy. In some papers mention the current BSC theory of the limit; there are no any research of interaction influence relation in BSC, Strategy goal, Performance Index and taking action etc. But it is the complicated dynamics relation between the BSC strategy action and the internal process of organization. Most of managers often pays close attention to neglecting the strategy goal long-termly in a short time, the side effect and sequelae caused by the fact that take action in strategy are influenced, form and judge the situation which feedbacks information by accident even more, namely the one that cause strategy planning is improper, then make the push benefit of the strategy goal not so good as expectancy. It can solve the problem of dynamic, If combine in BSC with the system dynamics method. Interaction mechanism and method of probing into enterprise's strategy goal and performance while measuring that the purpose of this research is here, draw the strategy map and weigh the goal and weigh the causality of the project with enterprises, Set up system dynamics model in accordance with its causality, analyze the result observed in simulation, find out the factor that drive succeeds, select the key index needed in order to finish the strategy goal. The main purpose, (1) to set up: The expansion of strategy map and Balanced Scorecard, and utilize the system dynamics method to carry on planning, simulation, procedure and tests. (2) To analyze: Through the interaction simulation of the test between performance index and strategy goal, looking for the best key performance index and the revise of policy and strategy. The research approach adopts the system dynamics method mainly, the materials which carry on case study are collected and analyzed; ' The procedure of planning, design and measurement of enterprise's strategy goal ' utilizing this research to be put in order, by the expansion of the strategy map and Balanced Scorecard, carry on the setting-up, simulation, test and analyzing of the system dynamic model. Use to propose the conclusion of this research. Study the conclusion: (1) with the causality of the BSC strategy goal project, there is influence of side effect and sequelae. (2) Imitate the execution achievement of the BSC strategy goal action scheme with the system dynamics method, can be the reference for policy planning and adjustment of the strategy. (3) With the side effect in the strategy goal causality of the Balanced Scorecard, support to conclude the performance index measurement. (4) Utilize the simulate test of system dynamics, look for the leading index in the system. (5) Study and put in order the basic system dynamics model of Balanced Scorecard. Expect that enterprises can use system dynamic to improve the whole benefit for a long time of enterprise's strategy goal to organize effectively. Lastly, to address the research result that in meaning on of managing, study limitation and the suggestion with follow-up research.

Balanced scorecard is a management system, which can be used for implementing organized strategy. Balanced scorecard, originated in America in 1990, emphasizes four-dimension performance appraising should be measured by strategy and be linked to business compensation and reward system. Likewise, Balanced scorecard is not only a performance measurement system, but also a management system linking with the strategy planning and reward system. This research is positioned as a case study focusing on one stock-published company in Security Industry and trying to analyze industry environment. In this research, Balanced scorecard can be considered as strategy-base carrying out BSC model by interview and case study . The purposes are listed as below: 1. Using Balanced Scorecard system in Security Industry company 2. Planning Key Performance Index in Security Industry company. 3. Discussing the necessity for Security Industry and suggest future direction for case company and researchers.

The supply chains of military engines are linked by the repair loop, the foreign military sale loop and the procurement loop. Based on the discipline of the performance based logistics, fleet readiness and the low life cycle cost are the key performance requirement. To response the budget constraint from increasing the investment of defensive weapon systems because of the rising of the uncertain tension situation on the both sides of the Taiwan Strait, it is necessary to have good supply chain management. However most of the managers often ignore the side effects and sequelae caused by their actions to persue the success of their strategy resulting from the complicated dynamic relationship between the strategic actions and inbound logistic process of the engine supply chains. When the managers misinterpret the feedback information with the side effects and sequelae, improper strategy planning will be made and fail to make your goals as expectancy. System dynamics can be used as the solution for unlinear, multi-variables and complicated dynamic problems of engine logistic management because of its systematic, dynamic point of view characteristics. The research approach adopts the system dynamics and tries to construct a model with the data which carry on the case study. By the expansion of the supply chain management and life cycle cost, the model was carried on the setting-up, simulation, test and analyzing of the system dynamics and will be a mechanism of decision making. Besides, through the interactive simulation of the test between performance index and system variables, the key performance indexes were found out. At the same time some strategy should be revised based on the result of simulation. Because strategy is based on the logic of cause and effect, the correct strategy map can only be built after the test with the system dynamic model. Study the conclusion: (1) The consequence of the action plan implememtation for engine maintenance management strategy with the system dynamics test can be refered as the reference for policy planning and adjustment of the strategy. (2) Construct the mechanism of spares requirement controling to eliminate the Bullwhip effect. (3) The cost effectiveness of CIP( Component Improvement Program) and RDE( Repair Development Engineering) depends on the timing and cost of implementation. Those can be validated through the interactive simulation of the test. (4) Built up the strategy map with the extension of balanced scorecard for military engine maintenance management. It is benefitted to utilize the business dynamics and strategy map with key performance index as the outcome for decision making to improve the operating performance of corporation. Lastly, to address the research result that in meaning on of managing, study limitation and the suggestion with follow-on research.

The diploma thesis deals with risk management in a newly starting project in a company, with a special attention to risks before and after beginning of the project. Based on the analysis of the company, the proposal for risk driving is introduced

This research study focuses on the application models of Data Mining and Machine Learning covering cellular network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms have been applied on real cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: RStudio for Machine Learning and process visualization, Apache Spark, SparkSQL for data and big data processing and clicData for service Visualization. Two use cases have been studied during this research. In the first study, the process of Data and predictive Analytics are fully applied in the field of Telecommunications to efficiently address users’ experience, in the goal of increasing customer loyalty and decreasing churn or customer attrition. Using real cellular network transactions, prediction analytics are used to predict customers who are likely to churn, which can result in revenue loss. Prediction algorithms and models including Classification Tree, Random Forest, Neural Networks and Gradient boosting have been used with an exploratory Data Analysis, determining relationship between predicting variables. The data is segmented in to two, a training set to train the model and a testing set to test the model. The evaluation of the best performing model is based on the prediction accuracy, sensitivity, specificity and the Confusion Matrix on the test set. The second use case analyses Service Quality Management using modern data mining techniques and the advantages of in-memory big data processing with Apache Spark and SparkSQL to save cost on tool investment; thus, a low-cost Service Quality Management model is proposed and analyzed. With increase in Smart phone adoption, access to mobile internet services, applications such as streaming, interactive chats require a certain service level to ensure customer satisfaction. As a result, an SQM framework is developed with Service Quality Index (SQI) and Key Performance Index (KPI). The research concludes with recommendations and future studies around modern technology applications in Telecommunications including Internet of Things (IoT), Cloud and recommender systems. / Cellular networks have evolved and are still evolving, from traditional GSM (Global System for Mobile Communication) Circuit switched which only supported voice services and extremely low data rate, to LTE all Packet networks accommodating high speed data used for various service applications such as video streaming, video conferencing, heavy torrent download; and for say in a near future the roll-out of the Fifth generation (5G) cellular networks, intended to support complex technologies such as IoT (Internet of Things), High Definition video streaming and projected to cater massive amount of data. With high demand on network services and easy access to mobile phones, billions of transactions are performed by subscribers. The transactions appear in the form of SMSs, Handovers, voice calls, web browsing activities, video and audio streaming, heavy downloads and uploads. Nevertheless, the stormy growth in data traffic and the high requirements of new services introduce bigger challenges to Mobile Network Operators (NMOs) in analysing the big data traffic flowing in the network. Therefore, Quality of Service (QoS) and Quality of Experience (QoE) turn in to a challenge. Inefficiency in mining, analysing data and applying predictive intelligence on network traffic can produce high rate of unhappy customers or subscribers, loss on revenue and negative services’ perspective. Researchers and Service Providers are investing in Data mining, Machine Learning and AI (Artificial Intelligence) methods to manage services and experience. This research study focuses on the application models of Data Mining and Machine Learning covering network traffic, in the objective to arm Mobile Network Operators with full view of performance branches (Services, Device, Subscribers). The purpose is to optimize and minimize the time to detect service and subscriber patterns behaviour. Different data mining techniques and predictive algorithms will be applied on cellular network datasets to uncover different data usage patterns using specific Key Performance Indicators (KPIs) and Key Quality Indicators (KQI). The following tools will be used to develop the concept: R-Studio for Machine Learning, Apache Spark, SparkSQL for data processing and clicData for Visualization. / Electrical and Mining Engineering / M. Tech (Electrical Engineering)