The Autonomous Shopping-Guide Robot in Cashier-Less Convenience Stores

In recent years, several cashier-less convenience stores have appeared, including Amazon’s. A store without cashiers will become a trend in the near future. To substitute the employee in traditional stores, this research proposes and designs an autonomous shopping cart robot to guide customers’ purchase according to the requested shopping list to enhance their shopping experience. The core techniques of the system are the autonomous driving robot, the traffic control center for robots and the dynamic route planning algorithm. The robot is a self-propelled vehicle developed by ROS (Robot Operating System), in which we achieve the automatic driving via image recognition, April tag identification and driving direction guidance from the path planning and traffic control services. This enables the robot to lead customers to find their commodities following the preplanned route. In conjunction with the vocal service, the robot can notify the customer when arriving at each commodity, he or she plans to buy. We also design a light APP for customers to easily set up and manage their shopping list, call for the robotic shopping cart’s help, and interact with the shopping cart robot. To enhance the shopping experience of customers, we design the dynamic route planning genetic algorithm to dynamically plan the shopping route according to the customer’s request and the traffic condition. Experiments show that our genetic algorithm can provide the most stable performance and always get efficient shopping route planning in a limited time compared to other methods

Exploratory analysis of Internet of Things (IoT): revolutionizing the grocery retail industry

This dissertation has investigated the consequences of implementing Internet of Things (IoT) technologies in grocery retailing by analyzing customers' perceptions of eight prominent technologies. The objective was to investigate and explore to what degree implementing these technologies would impact the customer experience. Based on secondary research, this thesis focuses on eight prominent technologies that presumably will encounter an increasing utilization in the visible future; Self-Scanning, Smart Robots, Smart Shelves, Smart Shopping Cart, Smart Fridge, Just Walk Out, Personalized Promotion/Pricing, and Mobile Apps. The technology distribution varies across different stages in the customer journey, and research indicates that IoT has the most significant impact in the pre-purchase stage. A comprehensive exploratory survey was conducted through Amazon mTurk with a wide range of respondents (n=204), giving valuable insight into demographic differences' influence on each technology perception. The investigation uncovered vast differences in several areas such as age, attitude, and privacy. Among other findings, the age segment 35-44 is more confident towards IoT technology than the age segment 55+, and shoppers with a positive attitude towards grocery shopping have higher confidence towards the technologies than shoppers with a negative attitude. On a widespread basis, the findings revealed that all eight technologies would positively affect customer experience to a certain level. Keywords: Internet of Things, Grocery Retailing, Customer Journey, Customer Experience, Autonomous Retail

Hybrid jobs in the retail industry. Redesigning organizations, processes and work

Retail industry is changing, as a consequence of online competition, customers' behavior and technological advancements, and retail jobs are transforming as well, with a change of the skills required. The purpose of this thesis is to investigate how these jobs are changing and how they will likely become in some years

Tecnología para Tiendas Inteligentes

Trabajo de Fin de Grado en Doble Grado en Ingeniería Informática y Matemáticas, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021Smart stores technologies exemplify how Artificial Intelligence and Internet of Things can effectively join forces to shape the future of retailing. With an increasing number of companies proposing and implementing their own smart store concepts, such as Amazon Go or Tao Cafe, a new field is clearly emerging. Since the technologies used to build their infrastructure offer significant competitive advantages, companies are not publicly sharing their own designs. For this reason, this work presents a new smart store model named Mercury, which aims to take the edge off of the lack of public and accessible information and research documents in this field. We do not only introduce a comprehensive smart store model, but also work-through a feasible detailed implementation so that anyone can build their own system upon it.Las tecnologías utilizadas en las tiendas inteligentes ejemplifican cómo la Inteligencia Artificial y el Internet de las Cosas pueden unir, de manera efectiva, fuerzas para transformar el futuro de la venta al por menor. Con un creciente número de empresas proponiendo e implementando sus propios conceptos de tiendas inteligentes, como Amazon Go o Tao Cafe, un nuevo campo está claramente emergiendo. Debido a que las tecnologías utilizadas para construir sus infraestructuras ofrecen una importante ventaja competitiva, las empresas no están compartiendo públicamente sus diseños. Por esta razón, este trabajo presenta un nuevo modelo de tienda inteligente llamado Mercury, que tiene como objetivo mitigar la falta de información pública y accesible en este campo. No solo introduciremos un modelo general y completo de tienda inteligente, sino que también proponemos una implementación detallada y concreta para que cualquier persona pueda construir su propia tienda inteligente siguiendo nuestro modelo.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

Vehicle Path Planning with Multicloud Computation Services

With the development of artificial intelligence, public cloud service platforms have begun to provide common pretrained object recognition models for public use. In this study, a dynamic vehicle path-planning system is developed, which uses several general pretrained cloud models to detect obstacles and calculate the navigation area. The Euclidean distance and the inequality based on the detected marker box data are used for vehicle path planning. Experimental results show that the proposed method can effectively identify the driving area and plan a safe route. The proposed method integrates the bounding box information provided by multiple cloud object detection services to detect navigable areas and plan routes. The time required for cloud-based obstacle identification is 2 s per frame, and the time required for feasible area detection and action planning is 0.001 s per frame. In the experiments, the robot that uses the proposed navigation method can plan routes successfully

AN INTERNET OF THINGS–BASED APPROACH TO INNOVATE CANTEEN STORES DEPARTMENT’S RETAIL OPERATIONS

In a competitive business environment, retail organizations in the Western world are capitalizing on technological tools and solutions to enhance customer experience and boost sales. Specifically, retailers that adopt Internet of Things (IoT) technologies improve customer experience and achieve cost savings. Yet such innovation is rare outside the Western world. Hence, early adopters of IoT technologies in retail operations in Pakistan could gain a competitive advantage. This study aims to create a deeper understanding of how Pakistan-based Canteen Stores Department (CSD), a retail chain mainly serving service members and their families, can use IoT technologies to significantly modernize and improve its operations and distinguish itself from competitors. To do so, this study conducts a qualitative analysis of scholarly articles on the relevant technologies and on IoT-based products offered by commercial companies. The authors also include findings from discussions with CSD customers and management. The results of the study indicate CSD can use IoT technologies to optimize store layout, offer interactive in-store mapping, automate checkout systems, implement smart shelving and digital price tagging, improve in-store promotions, enhance customer relationship management, and modernize distribution, transportation, and warehousing. The study also offers CSD management guidance on how to implement IoT technologies into retail operations at one location as a pilot.Outstanding ThesisLieutenant Commander, Pakistan NavyWing Commander, Pakistan Air ForceLieutenant Colonel, Pakistan ArmyApproved for public release. Distribution is unlimited

Technology-Based Self-Service: From Customer Productivity Toward Customer Value

The purpose of this dissertation is to investigate theconcept of customer productivity in a technology-basedself-service context (e.g., self-checkouts in grocerystores) to understand how customer productivity andcustomer value are related to each other. A preliminaryqualitative study initially explored the meaning ofcustomer productivity and the labor provided by customersin self-service shopping and TBSS environments. Based onthese exploratory insights and the extant literature, aconceptual framework was developed to identify therelationships between customer inputs into a TBSS optionand customer outputs from that option influenced bycustomer perceptions of self-service technology (SST) andcontact employee performance. Two adopter categories wereemployed for comparison purposes: enthusiastic adopters andreluctant adopters.The quantitative study utilized a survey researchdesign. After pre-testing the scale items with a largestudent sample, the latent variable structural equationmodel was tested by data collected from both enthusiastic and reluctant adopters who were customers of a largenational grocery chain.There were 27 hypotheses in total. Besides testing theproposed hypotheses, the dissertation also investigated atotal of seven potential relationships between theexploratory construct of emotional effort and the SSTperformance, contact employee performance, effort saving,time saving, quality of customer labor, quality of serviceand customer productivity.This research regarding the customer productivity andits relationship to customer value has made importantcontributions to managers and researchers by filling gapsin the productivity, retailing and services marketingliteratures.It fills certain gaps in the literature by:• introducing the new concept of customer productivityin services marketing area,• providing an understanding the concept of customerproductivity in a technology-based self-serviceenvironment,• incorporating both quantity and quality dimensionsinto inputs by customer and outputs for customer intesting multiple links toward customer productivity,• empirically testing a conceptual framework on customerproductivity,• predicting links based on the antecedents of customerproductivity, retailer support (SST and contactemployee) and the overall outcome,• establishing the link between customer productivityand customer value,• exploring the concept of emotional effort andintroducing it as a viable construct in customerproductivity,• differentiating between enthusiastic and reluctantadopters of TBSS options in general and self-checkoutsin particular.This dissertation research also provides importantimplications for managers. It contributes to the existingpractical business applications in terms of retailstrategies and tactics as concerns customers usage oftechnology-based self-service by:• presenting the emerging concept of customerproductivity as a new source of competitive advantage,• providing a unique way to create and deliver customervalue based on the concept of customer productivity –the self-productivity as perceived by customer,• differentiating between the input and output sides ofthe system for customer productivity to providefurther tactical details that can be used inimplementation phase of the crafted strategy,• differentiating between quality of customer labor andquality of service, and suggesting that thesignificant link between them can potentially be usedto develop a customer training program to acceleratethe adoption of self-checkouts by reluctant adopters,• underlining the importance of emotional effort as aviable concept that can be used as a competitive toolto increase perceived quality levels for both customerlabor and service,• providing ideas on how new generation SSTs cansuccessfully be developed based on a number ofconsequences such as contact employee performance,quality of customer labor and emotional effort,• differentiating between enthusiastic and reluctantadopters to understand what can potentially be done atstrategic and tactical levels with regard tointroducing, targeting and positioning self-checkoutsystems, other TBSS options and even technology-basedbusiness-to-business self-services

The Future for Frontline Retail Employees: Exploring the Intersection of Employee-driven Innovation and Technology Integration

This report explores the future for frontline employees in the retail sector, looking at how current trends specifically in technology integration may affect their role and how their opportunity for employee-driven innovation might be helped or hindered. Through a literature review and semistructured interviews, the research team developed a deeper understanding of the challenges facing frontline employees. A stakeholder analysis, influence map, and casual layered analysis provided system clarity. Through conducting a horizon scan, technology implementation was identified as a key driver of change. Existing and emerging trends added context. A 2x2 matrix and Dator’s Four Futures were then applied to create four unique possible futures focusing on the intersection of EDI, technology, and the role of frontline retail employees. These futures along with the insights developed through the secondary and primary research, inform recommendations to guide further exploration. We hope this work spurs conversations within the retail sector around how to better involve frontline employees as co-creators with unique perspectives and innovative ideas