以模糊偏好關係建立零售業服務創新評估模式

Using Fuzzy Preference Relations to Development the Service Innovation Evaluation Model for Retailers

在實際的決策環境下，決策者會根據個人的語意偏好來表達他們的評估結果。因此，如果對於不同決策者的多語意偏好影響未加以考慮，很有可能會造成評估結果與實際決策過程的落差。為了有效降低群體決策的語意認知偏誤，本研究發展出「模糊多語意偏好模式」。模式採兩階段評估流程，第一階段著重在整體語意偏好資訊的建立，並將個別模糊語意資訊予以整合；第二階段則採用模糊偏好關係法進行服務創新型態評選，使決策者在服務創新評估過程，所產生的模糊認知能獲得有效的詮釋。最後，本研究以連鎖量販店作為實證對象，探討在不同市場狀態與服務支援的情境組合下，服務創新型態的選擇評估，以及服務創新發展策略。

Innovative developments in service industries seem to be difficult to be explained in terms of traditional innovation theories and typologies. The main emphasis of innovation research is on new products and production processes, especially in manufacturing. Relatively few studies have focused on innovations in services. This bias in the innovation literature probably restricts our perception of the challenge to the management represented by innovations in service firms. For example, to distinguish the product from the process innovations, is it necessary to provide any deeper understanding of the factors responsible for the successful development of service innovations? Owing to the process character of many services and the close interaction between the producers and the customers in the service delivery process, the boundary between the product and the process in services is not clearly definable. In addition, the assessment and development of service products is not an easy decision, involving a host of complex considerations. The decision making of service innovations is a knowledge-intensive activity with its raw material and diverse services. The decision sequence refers to making preference decisions (e.g. evaluation, prioritization, selection) on available alternatives in terms of multiple, usually conflicting, criteria. However, the decision makers may have vague knowledge about the preference degree of one alternative over another, and cannot estimate their preferences with exact numerical values. Furthermore, it is too complex or too illdefined to be amenable for description in conventional quantitative expressions. It is more suitable to provide their preferences by means of fuzzy linguistic variables rather than numerical ones. However, alternatives evaluations with fuzzy linguistic often assume that the linguistic preference formations have been given in many practical applications. Though the given linguistic data can simplify the computational technique and the aggregation of the linguistic preference information, it is unable to really understand the decision makers’ subjective cognitions experienced by the concept of the interval purpose. The decision makers may have diverse cultural, educational backgrounds and value systems, their preference would be expressed in different ways. It is valuable to integrate the cognitive difference of preference attitudes among the decision makers for improving the decision quality.. The cross impacts of the service innovations in three kinds of market situations and service supportings which are evaluated by the integrated model of fuzzy multi-linguistic preference, and we can obtain the positioning analysis of service innovations. The conclusions drawn from the study are as follows: 1. Under the “service procedure supporting”, it is necessary to adopt the service innovation of “multi-unit organization” to improve the existing business scope to the new market. Besides, in order to attract new consumers, it is served for the service innovative idea of “design changes” that may be bringing the considerable profits for the retail business. If the retail business aims at attracting new consumers and extending the new markets at the same time, the reengineering for the “new combinations of services” and “design changes” are essential to conduct the revolution of theses different forms of new services. 2. Under “technological innovations supporting”, the innovative activities are the same as the “service procedure supporting” when the retail business would attract new consumers and extend new markets. The difference between the two supportings is that non-dominance degree values of “new combinations of services” and “design changes” under service procedure supporting become better than the supporting under the technological innovations supporting. This also implicates that the retail business has to put more resource and fund cost in serving the innovative activities to be consistent with the customers’ requirements of new consumers and new markets. 3. Under “entity’s facility supporting”, if the retail business can transfer the innovative activity of “new combination of services” to the activity project of “technological innovations supporting”, it may satisfy existing consumers and new markets, and attract the joining of new consumers to increase the company’s super profits. The innovative activity of “multi-unit organization” satisfying new consumers and existing markets also can be transferred to “technological innovations supporting” to take the chance of extending new markets. 4. The non-dominance degree values in the “existing consumers and existing markets” obviously are shown on the low side with the reciprocation of each service supporting. This also indicates that current service activities should be improved and innovated further to the direction of new consumers and new markets by the retail business.