中國大陸智能售貨機產業營運模式與經營績效之探討

Abstract

「新零售」的概念在2016年阿里巴巴的雲栖大會後，開始被熱烈討論，伴隨著物聯網(IOT)、人工智能(AI)、移動互聯網與移動支付的日漸普及，讓原來就具備「無人零售」基因的「自動售貨機」，經過技術賦能成為「智能售貨機」，使其較容易規模化落地，並達到數據化、連鎖化和在線化的新零售型態。 目前智能售貨機已布建較多場景，遍及中國大陸各地城市，並且包含品牌商與運營商等，有多家廠商進入，演化出不同的營運模式。本研究之主要目的為探討進入以飲料機為主的智能售貨機零售通路廠商，其營運模式與投放位置分析，以及與經營績效之關係，希冀對後續進入的廠商，有合適的方案。 本研究利用設備商系統提供，篩選總計10,000台智能售貨機設備的數據作為樣本，並從中獲取營運模式與投放位置資料，而經營績效的年交易額，為2018年1月至2018年12月連續12個月的數據；為方便比較與分析，選取使用率最高的飲料機。此外，本研究採用單因子變異數分析、迴歸分析、Scheffe多重檢定、Welch’s t檢定、Games-Howell多重檢定等統計方法來分析資料。 本研究利用SPSS統計軟體進行分析，結果發現相異的營運模式對經營績效會有影響，且採取「模式一」的經營績效表現最佳、「模式三」的經營績效表現次之；不同的投放場景對經營績效會有影響，「封閉場景」與「開放場景」其經營績效表現較佳；不同的投放區域對經營績效會有影響，「華北城市」因為冬季時間長不利於飲料銷售，其經營績效表現最差；在採取相異的營運模式時，如果搭配不同的投放場景，對經營績效確實有影響；在採取相異的營運模式時，如果搭配不同的投放區域，也是對經營績效有影響。 本研究對後續營運者的建議有八，一是採取會員體系有助於提升用戶複購，二是重視用戶互動可以拉升交易額，三是機器應優先投放在封閉場景，四是如考慮廣告效果、機器亦可投放在開放場景，五為只銷售飲料的機器應避免投放在華北城市，六是進入智能售貨機零售通路的廠商要有客製化售賣系統的能力，七是品牌商如直接運營智能售貨機通路則經營績效較佳，八為All in智能化成為智能售貨機運營的基本原則。

The concept of "new retailing" has been warmly discussed since the Computing Conference held by Alibaba Group in 2016. With the increasing popularity of Internet of Things (IOT), Artificial Intelligence (AI), Mobile Internet and Mobile Payment, the vending machines with the original gene of "self-service retailing" has been enabled to become an "intelligent vending machine" through technology, making it easier to land on a large scale and achieve the new retailing forms of data-oriented, chaining, and on-line. At present, intelligent vending machines have been deployed in many scenarios, covering cities all over the cities in Mainland China, including brand traders and operators. Many vendors have entered and evolved into different modes of operation. The main purpose of this study is to explore the retailing channel of vendors of intelligent vending machines which is mainly based on the beverage machines, the analysis of their operation mode and position for deploying, as well as the relationship with performance, in the hope of providing suitable solutions for the follow-up vendors. In this study, the data of 10,000 intelligent vending machines provided by the equipment element system were screened as samples, and the data of operation mode and position for deploying was obtained. The annual turnover of operation performance was from the data of 12 months from January 2018 to December 2018. For convenience of comparison and analysis, the drink machine with the highest utilization rate was selected. In addition, this study used single factor analysis of variance, regression analysis, Scheffe multiple test, Welch's test, Games-Howell multiple test and other statistical methods to analyze data. In this study, SPSS statistical software was used to analyze the results. It was found that different operating modes had an impact on performance, and the best performance was achieved in mode one, followed by mode three; different positions for deploying had an impact on performance and closed scenarios and open scenarios had better performance; different regions had an influence on performance. Because the long winter is not conducive to beverage sales in North China, and its performance is the worst; If different operating models are adopted, and different scenarios for deploying are matched, it does have an impact on performance; when different operating models are adopted and matched with different areas for deploying, it also has an impact on performance. There are eight suggestions for the follow-up operators in this study. Firstly, adopting membership system to help enhance the repeat purchases of users; secondly, attaching importance to interaction with users to boost transaction volume; thirdly, machines should be put in closed scenarios first; fourthly, considering its advertising effects, machines can also be put in open scenarios; fifthly, machines only selling drinks should be avoided to deploy the cities of North China; sixth, manufacturers of intelligent vending machines entering the retailing channels should have the ability of customized sales system. Seventh, brand operators who directly operate intelligent vending machine channels have better performance. Eighth, all-in intellectualization has become the basic principle of intelligent vending machine operation.