| 摘要: | 本研究旨在透過Schmitt及Fairchid研究架構之體驗模組理論為基礎，探討中式高級餐廳花藝風格偏好與消費者體驗之相關情形並將此研究結果，提供中式高級餐廳業者，作為餐廳空間設計及花店業者花藝設計研究發展之應用。
本研究係採量化研究方式，透過「立意抽樣」發放問卷，施測樣本730份，實際回收713份有效樣本，有效回收率為97.67%。使用之研究工具包括：「個人背景因素」、「中式高級餐廳花藝風格偏好量表」「消費者體驗量表」。施測結果以統計套裝軟體 SPSS for Windows 20.0進行結果分析，透過描述性統計、獨立樣本t檢定、單因子變異數分析、雪費法、皮爾森積差相關及一般多元迴歸分析進行資料之統計分析。
綜合實證分析結果：（1）性別、年齡、月收入、中國花、東洋花可以顯著的預測感官體驗（2）中國花、東洋花、歐式花可以顯著的預測情感體驗（3）教育程度、中國花、東洋花、歐式花可以顯著的預測思考體驗（4）教育程度、月收入、中國花、東洋花、歐式花可以顯著的預測行動體驗（5）年齡、中國花、東洋花、歐式花可以顯著的預測美感體驗（6）中式高級餐廳花藝風格與消費者體驗各構面皆成顯著正相關（7）性別、年齡、月收入、教育程度、中國花、東洋花及歐式花七個與消費者體驗相關預測變項能顯著預測各種消費者體驗。
Based on experiential modular theory of research frameworks-Schmitt and Fairchid, this study aims to discuss the correlation between floral design style preferences of high-class Chinese restaurants and customer experience, then provide research results to restaurateurs of high-class Chinese restaurants as references of restaurant design and floral shops’ research & development of floral design.
This study adopts quantitative research method and purposive sampling to issue 730 questionnaires; the number of valid questionnaires recovered is 713, which means the effective return rate is 97.67%. Research tools used in this study include Personal Background Factors, High-Class Chinese Restaurants’ Floral Design Style Preference Scale and Customer Experience Scale; the research results are analyzed by statistical package software SPSS for Windows 20.0. Data is statistically analyzed by Descriptive Statistics, Independent-Samples t Test, one-way ANOVA, Sche-ffe's Method,Pearson Product-Moment Correlation and Multiple Stepwise Regression Analysis.
Results after comprehensive empirical analysis are as follows:
(1)Sex, age, monthly income, Chinese flowers and Japanese flowers can significantly predict sensual experience.
(2)Chinese flowers, Japanese flowers and European flowers can significantly predict emotional experience.
(3)Educational background, Chinese flowers, Japanese flowers and European flowers can significantly predict thinking experience.
(4)Educational background, monthly income, Chinese flowers, Japanese flowers and European flowers can significantly predict action experience.
(5)Age, Chinese flowers, Japanese flowers and European flowers can significantly predict aesthetic experience.
(6)High-class Chinese restaurants’ floral design style preference has significant positive correlation with all aspects of customer experience.
(7)Seven predictor variables (including sex, age, monthly income, educational background, Chinese flowers, Japanese flowers and European flowers) related to customer experience can significantly predict all kinds of customer experience. |
