無人商店與傳統商店商業模式之研究-以人工智慧的觀點為例

人工智慧的時代來臨，是這幾年來的熱門話題。人工智慧應用所帶來的商業模式轉變影響了包含產品訂價、預測性客戶服務、廣告定位、搜索引擎、語音識別、客戶細分、銷售預測、內容管理。人工智慧在最初以推論及探索的方式推進，因為網路和大數據的普及，至今演化成能夠深度學習並作出預測。隨著顧客消費模式的改變，零售業也融合人工智慧的技術，逐漸走向新零售的時代。對零售業者來說，人工智慧可以提供更好的效率、更快的決策、降低風險並實現自動化。這樣消費模式的改變，也對整個零售市場造成衝擊，影響層面從消費行為中的環境、商品、流程到商業模式中的物流、金流、商流及資訊流，以及運用人工智慧與大數據分析後對消費者是否能創造更好的滿意度和價值。本研究是利用個案研究法中的次級資料搜集和社會調查法，探討貼近日常生活中的傳統商店在轉變成應用人工智慧技術的無人商店後，商業模式是否變得較有效率，以及對於消費者在顧客滿意度上會不會有顯著差異。本研究針對顧客滿意度部分實施發放問卷及次級資料搜集，問卷部分在網路進行發放，共回收有效問卷86份；商業模式四流則使用個案分析法中的次級資料搜集。本研究結論指出，無人商店與傳統商店在顧客滿意度方面是否有所提升是不成立，而商業模式之四流應用在無人商店證實比傳統商店來得更有效率。但因種種環境或內部因素而使無人商店無法持續獲利導致營運不善，針對此部分在最後結論及建議有提出並比較差異性和建議方向。

關鍵字

人工智慧；顧客滿意度；商業模式；無人商店

並列摘要

The coming of the era of artificial intelligence can be said to be a hot topic in the past two years.The impact of the transformation in business model affected by artificial intelligence applications includes product pricing, predictive customer service, advertising targeting, search engines, voice recognition, customer segmentation, sales forecasting, and content management. Artificial intelligence, which was initially developed as a form of inference and exploration, has evolved to be able to learn deeply and make predictions because of the popularity of the Internet and big data.Along with the change of consumer consumption pattern, the retail industry also integrates the artificial intelligence technology, and gradually moves towards the new retail era. For retailers, AI can provide greater efficiency, faster decision-making, reduced risk, and automation. Such changes in consumption patterns also have an impact on the whole retail market, affecting from the environment, commodities and processes in consumption behaviors to the logistics, fund flow, business flow and information flow in business models, as well as whether the application of artificial intelligence and big data analysis can create better satisfaction and value for consumers. This study uses the secondary data collection and social survey method in case study method to explore whether the business model of traditional stores, which close to the daily life, becomes more efficient after they are transformed into unmanned stores using artificial intelligence technology, and whether there is significant difference in customer satisfaction for consumers.In this study, questionnaires and secondary data collection were conducted for customer satisfaction. The questionnaires were distributed online, and a total of 86 valid questionnaires were collected. The four-flow (logistics, fund, business, information) in business model uses secondary data collection in case study method. This study concludes that it is not true that unmanned stores and traditional stores have improved customer satisfaction, and that the four-flow application of the business model in unmanned stores proves to be more efficient than traditional stores. However, due to a variety of environmental or internal factors, unmanned stores cannot make continuous profits and lead to poor performance. As for this part, comparative differences and suggested directions to be proposed in final conclusions and suggestions.