| Summary: | 博士 === 中華大學 === 科技管理學系(所) === 99 === The rapid changes in technology, market competition, globalization, and the requirements for product differentiation are causing industries that employ product life cycle management (PLCM) to become more meticulous High-tech industries such as information technology, semiconductors, optoelectronics and aerospace are sensitive to product life cycle management, especially in relation to stage transition, timing control and price-setting. PLCM can significantly influence the corporate performance, profit acquisition and the achievement of business goals and can ultimately affect the survival and prospects for future development.
In practice, it is difficult to control the major variables in PLCM, such as the timing of stages transition, the stages sustainability period and price-setting. Even the majority of world-class companies, including those at the cutting edges of technology employ no standard mechanisms to control the product life cycle effectively. Due to this lack of controllability, most areas of management such as the human resources management, financial management, manufacturing management, R & D management, marketing strategy planning and development, have serious inefficiencies that can greatly impact the financial performance of the company and possibly its survival.
In this context, this research focuses on the urgent needs of enterprises, through primitive hypothesis influence, within the relevant theoretical framework and rigorously derives the functional models required. Additionally, we test the feasibility of these models for practical applications.
In the model formulation part, a series of quantitative models are developed with the motivation of finding both the optimal launching time and price-setting for maximizing profit. Based on the proposed models, we strongly encourage companies in PLC sensitive industries to adopt proactive forecasting system to facilitate decisions about both launching timing and pricesetting.
In the case implementation part, the proposed models are tested in several rigid cases that simulate genuine business situations. Moreover, the feasibility of this research in practical applications is confirmed by presenting several tables results composed by calculating possible parameters that meet the selected criteria. The discussion part compares the results with previous widely-cited studies involving related models. A variance analysis is performed to ascertain the feasibilities of this research for practical applications. The conclusion addresses the relative contributions of this research and the prospects for future research. Finally, encouragement is extended to others with a potential interest in continuing this both by approximating between proposed models and practical events and through empirical research.
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