Study On Key Problems In The Process Of Customer Collaboration In Product Innovation

With the fierce competition in markets and the increasing individuation and diversification of customers’ demand, firms are gradually recognizing the importance of developing new products better and faster to than their competitors, which can help firms obtain market competitive advantage and earn more revenue. However, the rapid changes of external environment force firms to focus on not only its own resources but also external knowledge, resources and technology. Customers, as a significant element of external resources, who collaborate in product innovation, has become a new, potential and promising-application way to develop new products and this method has been used by many firms. Nevertheless, there are many problems existing during the process of customer collaboration in product innovation, such as collaborative customer selection, task and customer matching etc. Moreover, there is lack of efficient theory and methods to guide firms to apply customer collaborative product innovation, which has negative impacts on the application of this kind of product innovation way for firms.Therefore, after reviewing the existing related literatures, this paper introduces the process model of customer collaboration in product innovation based on the theories of product innovation, collaborative engineering, fuzzy mathematic and project management. Furthermore, we also researched the key issues of collaborative customer selection, product innovation task decomposition and grouping, task and customer matching and customer’s contribution measurement. Through the above study, we expect to develop a theory, methods and technology to guide the firms to apply customer collaborative product innovation.The paper includes the following aspects:Firstly, studied the process model of customer collaboration in product innovation. This paper defines and depicts the key concepts at the beginning. Then, construct the process framework of customer collaboration in product development according to its characteristics. Finally, analyze the key issues in the process model and its research framework.Secondly, researched the method of selecting collaborative innovation customers for product innovation requirements. This paper proposes some criteria to select collaborative innovation customers and constructs a house of quality model consisting of product innovation requirements and criteria. Then, the fuzzy linguistics are used to describe the importance of product innovation requirement, the independence degree of customer evaluation criteria and the correlation degree between them. To determine the weight of each criterion, an approach combining fuzzy weighted average and ?-cut, which can enables the fusion of fuzzy information expressed as linguistic variables is proposed. An approach based on data envelopment analysis approach is proposed to determine the value of the customers with respect to each criterion when the number of customers is large. The comprehensive evaluation of customers are then determined by combining the weights of evaluation criteria and the value of the customers with regard to each criterion.Thirdly, researched task decomposition and grouping model and method for customer collaboration in product innovation. The structure of collaborative innovation teams composed of customers and professionals was constructed according to the characteristics of customer collaborative product innovation. For the the characteristics of collaborative innovation team, this study proposes a way to decompose product innovation tasks. In order to measure the correlation between tasks, fuzzy numerical design structure matrix is applied and three indexes of sensibility, changeability and similarity of task requirements are proposed. In addition, this study takes the maximum of the cohesion degree in a task group and the minimum of the coupling degree between task groups as targets, build a model about tasks grouping model and double-population adaptive genetic algorithm which is used to solve this problem.Fourthly, researched matching approach and a model between product innovation task and collaborative innovation customer. This paper proposes matching strategy based on the idea of tasks grouping. Then, based on the analysis of resource attributes, ability attributes and attitude attributes of customers, we propose an approach to measure the matching degree between customers and tasks. On this basis, this study takes the maximum of fuzzy matching degree between them as target to build a matching model. By using ranking method, we can solve this problem and determine the optimal matching scheme.Fifthly, an approach for measuring collaborative innovation customer contribution for product innovation based on task decomposition is studied. This study proposes an idea and process to measure collaborative customer contribution for product innovation based on work breakdown structure. On this basis, an approach to measure customer contribution for activity is proposed. Furthermore, an integrated fuzzy extended analytical hierarchy process and data envelopement analysis is put forward to evaluating the importance of tasks quickly when the number of tasks is large. Then the contribution of customer for product innovation and tasks is determined by combining customer contribution for activities and the importance of activities and tasks.