Advancing technologies and constantly changing market needs induce competition between organizations and force enterprises to adopt better management methods to improve operational performance to survive and make profits. Knowledge management has been widely recognized as one of the effective methods to achieve the above objective. Previous researches of knowledge management chiefly focused on qualitative approaches, and largely stressed key success factors of knowledge management, such as the infrastructure of information technology, the design of the knowledge management system, deployment of motivation schemes, and the like. Among them, the knowledge spiral of socialization, externalization, connection, and internalization are the core of researches and discussions. However, early studies only disclosed the necessary cyclical phenomenon of knowledge management. A quantitative method revealing how the existing knowledge can support the creation of new knowledge or upgrade current knowledge remains non-existent. To bridge this gap, this study proposes a mathematical model which can quantify the supporting effects of the existing knowledge on the creation of new knowledge. The model evaluates knowledge from the perspectives of complexity (knowledge type/knowledge area) and depth (knowledge level), and the results of the example illustrate that the proposed model can be an effective method of measuring the usefulness of the existing knowledge.
The most crucial factor that survives enterprises under stiff competition is the success of new product development project; thus, the new product development project selection has become the vital concerns of R&D managers. The initial stage of the project is filled with uncertainties and complexities, which significantly deteriorate the success of product development and product launch. Previous researches focus on helping enterprises determine a set of good product ideas; however, when proceeding to the product development stage after the fuzzy front end, a best product idea should be selected to form a new product development project to create anticipated profits and develop competitive advantage. Therefore, this study proposes a potential project selection model, which combines optimal aggregation method and effective fuzzy weighted average to assist decision maker to achieve the best consistency of fuzzy judgments, and generates a single synergistic index project fuzzy synthetic rating that considers both risk and performance. The project fuzzy synthetic rating index is then used to help make the project Go-Kill decision, and the remaining survival projects are next prioritized to filter the best project. This model can efficiently assist R&D managers in dealing with both uncertainties and complexities when making new product development project screening decision and can reduce decision bias and produce new product development project with the highest possibility of generating expected profit.
Operations management within an enterprise requires teamwork from its members, as the efficacy developed by teamwork often far exceeds the sum of individual contributions. Project management is the most effective management method for the development of teamwork. A majority of previous researches in project management are focused on the managerial techniques, while neglecting the communications issues discovered in the aspect of member behaviors; however, the communication performance of the project members is one of the key factors contributing to the success or failure of the project. This study intends to focus on the communications among members in the project team, explore the leading influencing factors, and then develop a quantitative communication model for project management to evaluate the performance of project communication. Finally, this study uses the LINGO software to solve the mathematical programming model, and further obtain the best communication performance value based on two conditions, including communication in normal time and urgent time, thereby assisting the top management in selecting the most appropriate approach in project communications.
Purpose -This paper aims to construct for the first time a link between the project members' assignment and personality balance. Design/methodology/approach -This study develops a project assignment quantitative model that maximizes the team's personality balance while meeting the capability requirements. Findings -The findings indicate that a more balanced project team that contributes to project performance can be obtained before project starts. Research limitations/implications -This paper is limited to the exploration of Belbin's personality types. However, it offers a generic approach that can be applied to other personality categorization. Practical implications -The paper helps practitioners form a personality balanced project team to improve the project performance by reducing the complexity of project communication and problem solving. Originality/value -The paper develops for the first time a project assignment model that considers both capability and personality and allocates project personnel in such a way that the most suitable personnel is selected from a group of qualified capable candidates, to increase the possibility of success for the project.
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