{"title":"RETAIL 4.0 PRINCIPLES-BASED PRIORITY TASKS OF SMARTIZING THE SHOPPING IN A CONVENCIONAL HYPERMARKET","authors":"Olena Shtovba","doi":"10.31649/ins.2023.2.8.17","DOIUrl":null,"url":null,"abstract":"Retail 4.0 is the newest approach to Industry 4.0-based retail organization. Industry 4.0 involves the industry transformation to the most robotic production, which is controlled by intelligent systems based on cyber-physical devices with usage of Internet of things, cloud information resources, big data processing, and virtual reality. The paper proposes two promising tasks for the implementation of Retail 4.0 technologies in the practices of traditional hypermarkets and supermarkets with low investments. The first task concerns the optimization of the buyer's route, and the second task concerns the optimization of the route of the store employee who completes the online order. It is assumed that the trolleys with RFID-modules and a system of radio frequency identification of the location of devices are available in a supermarket. Task of routine optimization for a buyer with a smart trolley is reduced to a generalized traveling salesman task. The possibility of dynamic adaptation of the route due to changes in the availability of aisles and stock of goods is considered. Three monetization ways of the proposed routine optimization service are proposed. They are based either on direct payment by the buyer for optimal routing service, or indirect payment through increased loyalty or the ability to promote additional products through the recommendation module. Recommendations are provided at hand, i.e. directly in the trading zone near the area of visibility to the recommending product. The second task concerns the optimal completion of online orders by store employees. In addition to the possibility of dynamic adaptation of the route, to save time, it is additionally suggested to complete two similar small orders at the same time. The principles by which it is possible to identify the most similar pairs of orders from the point of view of their picking routes have been formulated.","PeriodicalId":42407,"journal":{"name":"RISUS-Journal on Innovation and Sustainability","volume":"14 1","pages":"0"},"PeriodicalIF":0.2000,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"RISUS-Journal on Innovation and Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31649/ins.2023.2.8.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
Retail 4.0 is the newest approach to Industry 4.0-based retail organization. Industry 4.0 involves the industry transformation to the most robotic production, which is controlled by intelligent systems based on cyber-physical devices with usage of Internet of things, cloud information resources, big data processing, and virtual reality. The paper proposes two promising tasks for the implementation of Retail 4.0 technologies in the practices of traditional hypermarkets and supermarkets with low investments. The first task concerns the optimization of the buyer's route, and the second task concerns the optimization of the route of the store employee who completes the online order. It is assumed that the trolleys with RFID-modules and a system of radio frequency identification of the location of devices are available in a supermarket. Task of routine optimization for a buyer with a smart trolley is reduced to a generalized traveling salesman task. The possibility of dynamic adaptation of the route due to changes in the availability of aisles and stock of goods is considered. Three monetization ways of the proposed routine optimization service are proposed. They are based either on direct payment by the buyer for optimal routing service, or indirect payment through increased loyalty or the ability to promote additional products through the recommendation module. Recommendations are provided at hand, i.e. directly in the trading zone near the area of visibility to the recommending product. The second task concerns the optimal completion of online orders by store employees. In addition to the possibility of dynamic adaptation of the route, to save time, it is additionally suggested to complete two similar small orders at the same time. The principles by which it is possible to identify the most similar pairs of orders from the point of view of their picking routes have been formulated.