中國大陸學生家長對校園出入門禁採人臉辨識驗證方式的持續使用意圖

Abstract

來自市調公司Markets and Markets的報告中點出，2022年人臉辨識的全球市場，預期將成長至77.6億美元，對照2017年的40.5億美元，成長率將高達52%，顯示市場普遍看好及其發展前景將帶動相關應用的加速成長。近年不只是科技大廠關注，企業與政府單位更是在金融、零售、醫療、安防等領域皆已有導入的案例，人臉辨識的高度應用將進而影響人類既有的生活模式及改變經濟體制及產業樣貌。目前社會大眾仍對人臉辨識系統有負面看法，應用於校園出入門禁時，有家長稱侵犯學生隱私，也有家長擔心學生個資洩漏、經費不足及使用規範不清楚等疑慮。面對家長的各種看法，如何針對不同人格特質的家長，增加其科技創新意識及排解其網路危險信念，使學生家長感受出入門禁之人臉辨識系統的感知價值，終而提升其使用意圖，實為當前重要之研究課題。 本研究選用便利抽樣的形式進行調查，以中國大陸學生家長為研究對象，共回收380份有效問卷，利用結構方程模式檢定研究假設。研究結果發現：1.神經質人格特質對網路危險信念有顯著正向相關。2.神經質人格特質對科技創新意識有顯著負向相關。3.外向性人格特質對網路危險信念有顯著負向相關。4.外向性人格特質對科技創新意識有顯著正向相關。5.網路危險信念對感知價值有顯著負向相關。6.科技創新意識對感知價值有顯著正向相關。7.感知價值對使用意圖有顯著正向相關。The wide application of face recognition may become key to changing human life patterns. At present, the public still has a negative view of the face recognition system. When it is applied to the entrance and exit ban on campus, some parents say that they violate the privacy of students, and some parents are worried about the leakage of students' resources, insufficient funds, and unclear usage regulations. Faced with the various views of parents, how to target parents with different personality traits to increase their technological innovativeness and resolve their beliefs about online dangers, so that parents of students can feel the perceived value of the face recognition system for entry ban, and ultimately enhance their intentions to use, It is an important research topic at present. In this study, a convenient sampling method was used to investigate, and parents of mainland students were used as the research object. A total of 380 valid questionnaires were collected, and the structural equation model was used to verify the research hypothesis. The results of the study found that: 1. Neuroticism can positively predict dangerous beliefs in virtual world; 2. Neuroticism can negatively predict technological innovativeness; 3. Extraversion can negatively predict dangerous beliefs in virtual world; 4. Extraversion predict technological innovativeness; 5. Dangerous beliefs in virtual world can negatively predict perceived value; 6. Technological innovativenesss can positively predict perceived value; 7. Perceived value can positively predict usage intentions.