IOT資訊系統導入餐飲業顧客滿意度及再購意願之研究

餐飲業導入物聯網資訊系統（IOT）及人工智慧（AI），將能有效的控管食材的統一品質，消費者之訂單能清楚的陳列，經營者亦能從系統上明白掌握目前現場的缺料或消費者喜好，亦能透過多媒體資訊與消費者互動，讓消費者清楚食材履歷及烹煮過程，使生產透明化，讓消費者吃得安心獲得更多的滿意度，使消費再購意願提升，創造出更好的營收效果。　　本研究以屏東縣廚師職業工會會員作為研究對象，並運用SPSS 20.0進行分析餐飲業IoT資訊系統、顧客滿意度及顧客再購意願之相關分析得知三者構面間有顯著之影響關係，並運用迴歸分析得知餐飲業IoT資訊系統對顧客滿意度及顧客再購意願皆具顯著之影響關係，亦得知三個構面間相互影響之關係存在。本研究之研究對象係以屏東縣廚師工會之會員進行研究分析，故樣本數及範圍略顯不足與狹隘，因此無法推斷不同的職業、地區或縣市之受訪者是否存在不同的研究結果，亦無法了解其差異性之比較，故建議未來研究者可以加入其他差異分析，進而從中發現在不同的環境下，是否會有所差異，進而得到更精確的結果。

關鍵字

顧客滿意度；再購意願

並列摘要

The catering industry introduces the Internet of Things information system （IOT） and artificial intelligence （AI）, which will be able to effectively control the unified quality of food materials, consumers' orders can be clearly displayed, and operators can also clearly grasp the current on-site shortcomings from the system. It can also interact with consumers through multimedia information, so that consumers can understand the history and cooking process of ingredients, make production transparent, let consumers eat with peace of mind and get more satisfaction, and make consumers willing to buy again Improve and create better revenue results. This study takes members of professional chef unions in Pingtung County as the research object, and uses SPSS 20.0 to analyze the IoT information system of the catering industry, customer satisfaction and customer repurchase intentions. It is found that there is a significant relationship between the three dimensions. And use regression analysis to know that the IoT information system of the catering industry has a significant impact on customer satisfaction and customer repurchase intention, and also know that there is a relationship between the three dimensions. The research object of this study is the members of Pingtung County Chefs Union for research and analysis, so the sample size and scope are slightly insufficient and narrow, so it is impossible to infer whether there are different research results for respondents in different occupations, regions or counties , and it is impossible to understand the comparison of their differences, so it is suggested that future researchers can add other difference analysis, and then find out whether there will be differences in different environments, and then get more accurate results.