本研究旨在如何透過創新的營銷模式，如電子醫藥行銷及電子醫藥平台，來解決跨國製藥廠在台灣面臨的困境。本研究以個案公司為研究對象，透過傳統策略規劃流程來做策略分析、策略擬定及策略執行。策略分析主要在分析內外部環境，外部環境，先透過五力分析來確認製藥產業的吸引力及哪一項競爭力是跨國製藥廠最需重視的，接著討論醫業環境的演變及對傳統營銷模式的衝擊。內部分析，主要針對個案公司做情勢分析，透過個案公司的組織目標、BCG矩陣分析模型、核心競爭力、品牌權益市場調查、高涉入購買決策過程分析、SWOT分析、商業模式和4C（四種交換成本）處分析來判斷情勢。從分析的結果來確認主要問題及機會，然後根據主要問題及機會來擬定相對策略，最後分析執行行動方案的成效來驗證策略的正確性。 / This study explores how the innovative marketing and sales model (such as eDetailing and Physician Digital Platform) can help to overcome the obstacles that international pharmaceutical company has been facing in Taiwan. This research is a case study for an international pharmaceutical company. The study is mainly focused on Taiwan’s pharma division. They study is structured in 3 major sections – strategy analysis, strategy defining and strategy execution. For the analysis, it focuses on analyzing external and internal environment. For the external environment, first apply the 5-force theory to identify the attractiveness of the industry and which competitive forces should be focused on. Then it discusses the evolution of the pharmaceutical industry in Taiwan and how it impacts the traditional sales model. The internal analysis focuses on the case study of the company. Use tools and models such as BCG Matrix, core competency, brand equity market research, buying process, SWOT, business model and 4 Costs model to analyze the studied company’s situation. Through the analysis, identify the key problem and opportunity and make corresponding strategies. At the final section, validate the strategy’s effectiveness through analyzing the execution of the innovative marketing and sales model initiatives.

This thesis is focused on evaluation of the service quality in selected retail outlets or shops. The main goal of this thesis was to evaluate the level of customer service while engaged in the transaction of selling pre-selected goods in selected retail outlets. Based on the results of this evaluation, a sub-goal of this thesis was to either validate or to disprove the given hypotheses. As an introduction I define basic terms of service quality, customer satisfaction with a service, marketing Research and mystery shopping. . After depicting the basic theoretical principles of mystery shopping, I moved on to the practical (hands-on) portion of my thesis where I evaluate retail outlets for pre-selected company. Evaluation is carried out by using mystery shopping. After conclusion of mystery shopping, the data was analyzed and synthesized, which allowed me to evaluate the results and draw appropriate conclusions, proposal and recommendation to the pre-selected company.

This work is focused on marketing communication in the pharmaceutical industry. The theoretical part contains a description of the pharmaceutical market, a brief analysis of the marketing mix with a detailed focus on the individual instruments of promotion (personal selling, advertising, direct marketing, public relations and sales support). It also contains partial laws, regulations, standards which are used in marketing communication. The practical part contains an analysis of marketing communication practices of selected pharmaceutical manufacturer with a focus on medicine or drug Motilium. Following analysis and comparison of different tools of communication mix together with value of the costs of activities, as well as proposed ways to improve marketing communication process and recommendation.

The master´s thesis deals with the promotion of the firm called efF creative ateliér, that works in printing industry. This work is focused on analysis of marketing environment in and out of the firm and recognizes particular forms of marketing communication. On the basis of these analyses a new promotion for firm is suggested.

The concepts of 'data warehousing' and 'on-line analytical processing' have seen a growing interest in the research and commercial product community. Today, the trend moves away from complex centralized data warehouses to distributed data marts integrated in a common conceptual schema. However, as the first part of this paper demonstrates, there are many problems and little solutions for large distributed decision support systems in worldwide operating corporations. After showing the benefits and problems of the distributed approach, this paper outlines possibilities for achieving performance in distributed online analytical processing. Finally, the architectural framework of the prototypical distributed OLAP system CUBESTAR is outlined.

In the area of online analytical processing (OLAP), the concept of multidimensional databases is receiving much popularity. Thus, a couple of different multidimensional data models were proposed from the research as well as from the commercial product side, each emphasizing different perspectives. However, very little work has been done investigating guidelines for good schema design within such a multidimensional data model. Based on a logical reconstruction of multidimensional schema design, this paper proposes two multidimensional normal forms. These normal forms define modeling constraints for summary attributes describing the cells within a multidimensional data cube and constraints to model complex dimensional structures appropriately. Multidimensional schemas compliant to these normal forms do not only ensure the validity of analytical computations on the multidimensional database, but also favor an efficient physical database design.

Proper management of multidimensional aggregates is a fundamental prerequisite for efficient OLAP. The experimental OLAP server CUBESTAR whose concepts are described, was designed exactly for that purpose. All logical query processing is based solely on a specific algebra for multidimensional data. However, a relational database system is used for the physical storage of the data. Therefore, in popular terms, CUBESTAR can be classified as a ROLAP system. In comparison to commercially available systems, CUBESTAR is superior in two aspects. First, the implemented multidimensional data model allows more adequate modeling of hierarchical dimensions, because properties which apply only to certain dimensional elements can be modeled context-sensitively. This fact is reflected by an extended star schema on the relational side. Second, CUBESTAR supports multidimensional query optimization by caching multidimensional aggregates. Since summary tables are not created in advance but as needed, hot spots can be adequately represented. The dynamic and partition-oriented caching method allows cost reductions of up to 60% with space requirements of less than 10% of the size of the fact table.

Data marts storing pre-aggregated data, prepared for further roll-ups, play an essential role in data warehouse environments and lead to significant performance gains in the query evaluation. However, in order to ensure the completeness of query results on the data mart without to access the underlying data warehouse, null values need to be stored explicitly; this process is denoted as negative caching. Such null values typically occur in multidimensional data sets, which are naturally very sparse. To our knowledge, there is no work on shrinking the null tuples in a multi-dimensional data set within ROLAP. For these tuples, we propose a lossless compression technique, leading to a dramatic reduction in size of the data mart. Queries depending on null value information can be answered with 100% precision by partially inflating the shrunken data mart. We complement our analytical approach with an experimental evaluation using real and synthetic data sets, and demonstrate our results.

This paper reflects the results of the evaluation phase of building a data production system for the retail research division of the GfK, Europe's largest market research company. The application specific requirements like end-user needs or data volume are very different from data warehouses discussed in the literature, making it a real data warehouse. In a case study, these requirements are compared with state-of-the-art solutions offered by leading software vendors. Each of the common architectures (MOLAP, ROLAP, HOLAP) was represented by a product. The result of this comparison is that all systems have to be massively tailored to GfK's needs, especially to cope with meta data management or the maintenance of aggregations.

This paper reflects the results of the evaluation phase of building a data production system for the retail research division of the GfK, Europe's largest market research company. The application specific requirements like end-user needs or data volume are very different from data warehouses discussed in the literature, making it a real data warehouse. In a case study, these requirements are compared with state-of-the-art solutions offered by leading software vendors. Each of the common architectures (MOLAP, ROLAP, HOLAP) was represented by a product. The result of this comparison is that all systems have to be massively tailored to GfK's needs, especially to cope with meta data management or the maintenance of aggregations.