人們因科技的介入使得服務也將之改變。汽車產品服務系統中，從傳統駕駛到自動駕駛及其技術影響下，服務模式和解決方案的發展展現了重要的趨勢。本研究試圖提供一個以科學化的車駕服務框架，讓傳統汽車製造商即將轉換自動駕駛方向得以重新審視自己的服務模式和解決方案，集結使用者互動過程以擴散式創造思考展現出車駕在服務體驗上的創新，藉以制訂車駕載具的準則，讓傳統汽車加速智能化的過程。

實驗一以傳統車駕載具設計評估，人的駕駛為出發點，以感性工學之人因技術為基礎，量化數據分析，結合人類圖樣識別之認知特質，提出整合其單一要素導向與整體關係之感性分析模式，並以方向盤的設計為探討對象。根據各因素所構成的形容詞加以解釋，第一個因素對具有外觀審美比較的特質，稱為美感性因子；而第二因素包含了穩重的-輕巧的與輕薄的-沉重的2組形容詞對，這兩形容詞對具有形態、力量比較的特質，稱為操作強度因子；第三個因素包含了簡潔的-多變的、人工的-自然的等2組形容詞對，這些形容詞對具有現代主義美感評價的特質，稱為現代性因子。研究中利用線性複回歸分析進行感性工學模式的建構，並針對單一要素導向與整體模式進行績效的比較。研究結果指出，整體模式之R²皆高於單一要素導向模式，表示整合模式在變異量的解釋上優於單一要素導向模式。在古典的-時尚的(美感性因子)、穩重的-輕巧的(操作強度因子)與簡潔的-多變的、人工的-自然的(現代性因子)等形容詞對，其數值的差異較為明顯，說明整體模式能較明顯助益於消費者這些感性評價行為的預測。而其中有關現代性因子R²增加最為顯著，說明在現代性評估上，整體模式有較佳的績效。藉由分析結果的比較與測試樣本的驗證，整體模式能明顯助益於消費者感性評價行為的預測。

實驗二以Kano二維品質模式，根據Kano問卷求得各服務品質之顧客滿意度加以分析，並將最需改善之品質要素加以排序，並找出傳統車駕載具中，不可或缺的服務。最終提供車輛駕駛產品的服務品質改善與駕駛人滿意度的評比建議。以56份有效回收問卷的四門轎車潛在消費者，進行具體機能、無形加值服務二構面與基本安全機能方面、影音娛樂系統方面、資通訊系統方面、加值系統方面、主動匹配方面、自動服務系統方面、軟硬整合方面、助理輔助方面八大因素之30項產品設計的重視程度與使用後的滿意度、以及Kano屬性等進行統計分析了解個群體之間是否存在顯著差異。根據本研究結果發現，30項產品設計當中，被Kano品質屬性歸類為魅力品質為多數，共有10項，其次有7項為一元品質，有3項為必須品質，有4項為無異品質者，有6項為反向品質。企業能夠根據其產品歸類，再搭配研究提出的產品改善優先順序，即可有效的改善顧客不滿意與顧客滿意度。

Services are constantly changing with the introduction of new technologies, which affect the service systems of both conventional and autonomous driving. New theories and technologies are also key factors affecting the design and development trends of service models and solutions. Major automobile manufacturers aspire to provide customers with unique services and experiences, resulting in a growing demand for systematic approaches to characterize customer behaviors and scientific methods to accurately interpret data stored in databases. This study proposes a scientific engineering and operation framework for driving services that enables conventional automobile manufacturers to re-evaluate their service models and solutions as they expand into the domain of autonomous driving, integrating customized consumer interactions and mass production efficiency to develop new technologies, and subsequently applying these technologies to innovate their driving services, form service innovation guidelines, and accelerate the development of smart applications for the automobile industry.

The Experiment One involved a quantitative analysis of automobile design. The study used the human factors technology of Kansei engineering and the shape recognition patterns of human beings as the foundation of a Kansei model that integrated considerations of various components and overall design. The model then used the design of steering wheels as a test, to refine the model as a design tool for the integration of individual components and the overall style of a product. Three types of adjectives were applied to describe the constituent elements. The first type was esthetic factors and involve external esthetics. The second type comprised two pairs of adjectives, sturdy/delicate and lightweight/heavy, called operational strength factors because they relate to form and strength. The third type comprised simplistic/changeful and artificial/spontaneous, called modernity factors because they pertain to the modern sense of beauty of the parts. Multiple linear regression analysis was used to construct a Kansei engineering model and compare the performance of individual elements and the product as a whole. The results show that the R² values in the overall model were greater than those in the element-oriented model, indicating that the integrated model outperformed the element-oriented model in variance explanation. The differences between the numerical values of the adjective pairs classic/fashionable (esthetic factors), sturdy/delicate (operational strength factors), and simplistic/changeful and artificial/spontaneous (modernity factors) were significant, demonstrating that the overall model is useful in predicting how consumers make assessments according to emotional perceptions. The R² increase of the modernity factors was the most obvious, indicating that the overall model assesses modernity more accurately. Comparing results and verifying test samples demonstrated that the overall model is more useful in predicting consumer appraisals that are based on emotional perception.

A Kano two-dimensional model of quality was employed in Experiment Two. A Kano questionnaire was administered to analyze consumers’ perceived satisfaction concerning different service quality elements; the elements were then ranked in the order of requiring improvement to determine the elements that are essential in conventional vehicles. Finally, suggestions were proposed for improving the service quality of driving products and evaluating driver satisfaction.

A total of 56 valid questionnaires were collected from potential buyers of four-door sedans. The questionnaire evaluated respondents’ perceived value and satisfaction of 30 product elements categorized into two groups (specific functions and intangible value-added services) across eight major quality dimensions (basic safety functions, multimedia entertainment systems, information and communication systems, value-added systems, active matching, automatic service systems, hardware–software integration, and customer service and support). In addition, Kano quality categories were statistically analyzed to elucidate whether significant differences existed between groups. Using the Kano quality categories, 30 design elements were classified: 10 as “attractive,” 7 as “one-dimensional,” 3 as “must-be,” 4 as “indifferent,” and 6 as “reverse.” Enterprises can effectively reduce customer dissatisfaction and enhance customer satisfaction based on the quality category of the product and the product improvement order proposed in this study.

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