Online Ordering Research Articles

Predicting E-commerce customer satisfaction: Traditional machine learning vs. deep learning approaches

The rapid growth of e-commerce has increased the need for retailers to understand and predict customer satisfaction to support data-driven managerial decisions. This study analyzes online consumer behavior through a comparative machine learning modeling approach to forecast future customer satisfaction based on review ratings. Using a large dataset of over 100 k online orders from a major retailer, traditional machine learning models including random forest and support vector machines are benchmarked against deep learning techniques like multi-layer perceptrons. The predictive models are assessed for their ability to accurately predict customer satisfaction scores for the next orders based on key e-commerce features including delivery time, order value, and location. The findings demonstrate that the random forest model can predict future satisfaction with 92% accuracy, outperforming deep learning. The analysis further identifies core drivers of satisfaction such as delivery time and order accuracy. These insights enable retail managers to make targeted improvements, like optimizing logistics, to increase customer loyalty and revenue. This study provides a framework for leveraging predictive analytics and machine learning to unlock data-driven insights into online consumer behavior and satisfaction for superior retail decision-making. The focus on generalizable insights across a major retailer enhances the practical applicability of the machine learning approach for the retail sector.

Integrated operations strategies for shared and privately-owned autonomous vehicles: A deep reinforcement learning framework

The shared autonomous vehicle (SAV), combining shared mobility and vehicle automation, will play a pivotal role in urban transportation. Effectively matching SAVs to stochastic customer demand poses a significant challenge, particularly when addressing microscopic multi-AV coordination to prevent conflicts and congestion within a network. To tackle this issue, we propose a novel traffic control scheme called the Integrated Operation Framework for Order Matching and AV Coordination (I-OFOMAC). This scheme introduces a third-party coordinator responsible for integrating online order matching for the SAV platform and real-time AV coordination for the road manager. Our approach utilizes an offline deep reinforcement learning method to train a state value neural network, which facilitates strategic order matching. Additionally, a neural network approximating bisimulation metrics is trained to enhance exploration and accelerate learning. To achieve scalability in network-level AV coordination, we adopt a scheduled transportation scheme. The coordinator solves the I-OFOMAC during each decision epoch, optimizing order matching and AV coordination. The I-OFOMAC aims to balance the goals of minimizing AV travel delay and maximizing SAV service revenue. We conduct extensive simulation studies in the realistic Wangjing network to evaluate the proposed I-OFOMAC scheme. Compared to two-step benchmark frameworks that implement order matching and AV coordination sequentially, the I-OFOMAC achieves an average increase of 13.28% in platform revenue (ranging from 2% to 22.53%) and a 4.48% reduction in average PAV travel delay (ranging from −6.55% to 20.17%).

Gypsy: AI-Powered Virtual Assistant for Windows OS

The proposed virtual assistant software, powered by AI, is specifically crafted for users operating Windows computers to enhance the efficiency and safety of their tasks with minimal input. This innovative design allows users to swiftly and effortlessly accomplish various everyday computer-based activities. Examples include streamlined online ordering, accessing desktop and web applications, conducting web searches, setting reminders, obtaining live directions, reading notes, checking weather forecasts, translating words, performing mathematical calculations, setting alarms, receiving the latest news, and sending emails and WhatsApp messages, among other functionalities. Furthermore, the project incorporates the ability to recognize both voice and text input commands. Users can interact with the system through voice commands captured by the computer's microphone, which are then converted into text output. This conversion facilitates the system in comprehending the input and executing the requested task. The tool is seamlessly integrated with the Internet and the Windows operating system, ensuring the delivery of the desired functions and results in response to user queries.

VARDARA: An Online IOT Based Water Delivery Application

This paper presents a novel online water and delivery system, "VARDARA," designed to address the pressing need for convenient and efficient water distribution. Our solution integrates an intuitive Android application with smart IoT vehicles to enable seamless online ordering and timely delivery of water. By optimizing delivery routes and leveraging IoT technology, we ensure quicker and more environmentally friendly deliveries, bridging the gap between e-commerce and efficient water distribution. This innovative approach enhances customer convenience and contributes to sustainable resource management. Key Words: water, delivery, online, IoT, efficiency, sustainability.

Joint optimization of inventory replenishment and rationing policies for an omnichannel store with both in-store and online demands

Boosted by the COVID-19 pandemic, omnichannel retail has become a popular retail model and is expected to further grow. We study inventory replenishment and rationing of a product in an omnichannel store that fulfils both in-store and online demands. Both demands follow Poisson process. As each in-store demand must be satisfied immediately whereas each online order has a delivery time window, the two demand classes have different behaviors facing stockout: offline demand is lost while online order is backlogged with backorder cost charged only if it is delivered late. The inventory replenishment and rationing between the two demand classes in this omnichannel inventory system are controlled by a continuous review (Q, r) policy and a critical level policy, respectively. The intertwined nature of inventory replenishment and rationing in this system makes its analytical cost evaluation and its joint optimization of the two policies challenging. After deriving an analytical formula for evaluating the expected cost of the system, two heuristic algorithms are proposed to jointly optimize the two policies. Numerical experiments on randomly generated instances demonstrate that the multi-start local search algorithm and the scatter search algorithm can obtain a near-optimal solution quickly with percentage cost gap no larger than 0.81% and 0.18%, respectively, and the critical level policy can yield cost savings up to 10.91% compared to the first-come, first-served policy. Finally, a sensitivity analysis is conducted to evaluate the influences of system parameters on the optimal critical level.

ECOMMERCE WEBSITE ,

Electronic Commerce is process of doing business through computer networks. A person sitting on his chair in front of a computer can access all the facilities of the The main advantage of e-commerce over traditional commerce is the user can browse online shops, compare prices and Internet to buy or sell the products. Unlike traditional commerce that is carried out physically with effort of a person to go & get products, ecommerce has made it easier for human to reduce physical work and to save time. E-Commerce which was started in early 1990’s has taken a great leap in the world of computers, but the fact that has hindered the growth of e-commerce is security. Security is the challenge facing e-commerce today & there is still a lot of advancement made in the field of security.The main advantage of e-commerce over traditional commerce is the user can browse online shops, compare prices and order merchandise sitting at home on their PC. Key Words: empower leraning,dynamic website, professional goals

Dynamic joint strategy of channel encroachment and logistics choice considering trade-in service and strategic consumers

As Internet technology develops rapidly, consumers’ consumption habits gradually shift from offline to online, and they are growing more strategic. In order to cater to strategic consumers, offline durable goods firms providing trade-in service are faced with practical issues of making dynamic strategies about whether establishing online channels and adopting which logistics service between self-logistics and third-party logistics (TPL) to deliver online orders. To tackle these problems, this study considers three scenarios and analyzes dynamic joint strategy of channel encroachment and logistics choice for a durable goods firm who owns an offline channel and offers trade-in service to strategic consumers via constructing a two-period game model. Results show that the firm’s dynamic joint strategy of channel encroachment and logistics choice will be affected by fixed operating cost, logistics service level difference and self-logistics cost. Moreover, trade-in service will have huge impacts on channel encroachment and logistics choice strategy. At last, when considering cap-and-trade policy, the service level of self-logistics and the cost of shipping used products, the optimal dynamic joint strategy of channel encroachment and logistics choice remains viable.

Modern Trends in Digitalization of the Restaurant Business

The relevance of studying the issues of digitalization of the restaurant business is due to the need to search for strategic directions and key factors in the digital transformation of restaurant services, assessing modern consumer demands and global market development trends.The purpose of the work is to study the main trends in the digitalization of restaurant business organizations.The objectives of the study are to analyze promising areas of digitalization of the restaurant business, assess the market for online food delivery, self-service points and the use of digital technologies.Methodology. Methods of comparative and statistical analysis, induction and deduction were used as research methodsResults. It was revealed that the main directions of digitalization of the restaurant business are online orders and delivery of ready-made food, the development of self-service points, automation of the value chain, as well as the promotion of restaurant services using digital technologies. Despite the fact that automation of the restaurant business began before the COVID-19 pandemic, it served as a catalyst for the transition of restaurant services to the virtual space. However, the reactive approach of restaurant business organizations did not allow the formation of an effective strategy for the digital transformation of restaurant business organizations. The growth of digitalization of the industry is due to digital channels for promoting services that require significant investments, available only to large market players; for non-chain restaurants, this segment of the digital market is not yet available in full, which is a limiting factor in the development of the entire industry.Conclusions. The results obtained during the research allowed us to formulate theoretical and practical recommendations aimed at developing a strategic understanding of the planning processes and implementation of digital technologies in the activities of restaurant business organizations.

Sidewalk autonomous delivery robots for last-mile parcel delivery

The dynamics of e-commerce, combined with the growing number of users and the increasing volume of last-mile consignments, are driving current developments in logistics. As online commerce continues to grow, so does the need for active service providers to deliver courier, express, and parcel (CEP) shipments on time. Autonomous last-mile delivery is said to have the potential to transform the way we receive goods. As these autonomous delivery technologies continue to develop and become more widespread, it is possible to foresee a future where autonomous delivery vehicles seamlessly navigate our roads and sidewalks, bringing our online orders to our doorsteps faster and more efficiently than ever. After a general classification of sidewalk autonomous delivery robots (SADRs), this paper examines how far the development and implementation of these vehicles have progressed and which developments offer the greatest opportunities for ecological and economic use in the future.

E-fulfillment cost management in omnichannel retailing: An exploratory study

The purpose of this study is twofold: investigating how omnichannel (OC) retailers manage e-fulfillment costs and establishing how these costs relate to the evolution of OC retailers' e-fulfillment strategies. Experts in e-fulfillment from 34 European OC retailers across various sectors participated in an exploratory survey. The study's results reveal that although e-fulfillment costs significantly influence the evolution of e-fulfillment strategies, many OC retailers fulfilling online orders from retail stores or traditional warehouses remain unaware of the actual costs of e-fulfillment. Activities other than picking and last-mile delivery, such as inbound logistics and storage, are poorly controlled. Furthermore, complex cost metrics such as cost-to-serve—the total cost associated with delivering a specific order to a specific customer—are predominantly found among OC retailers operating fulfillment centers (FCs) in their e-fulfillment distribution networks. This underscores the need for all OC retailers to accurately assess e-fulfillment costs at multiple levels, which will be crucial for optimizing order preparation, tailoring pricing strategies, and achieving profitability, especially when operating hybrid e-fulfillment strategies where online orders are prepared in multiple facilities. As the largest study on e-fulfillment costs to date, it highlights the importance of advancing e-fulfillment cost management systems among OC retailers and adopting an approach that encompasses all e-fulfillment activities. Future research should delve into the key challenges of developing these systems, considering the operational realities of each OC retailer.

Enhancing E-Commerce Warehouse Management

E-commerce has revolutionized the retail industry, necessitating efficient warehouse management systems to handle the increasing volume of online orders. This paper explores various strategies, technologies, and challenges associated with e-commerce warehouse management. It examines the significance of effective warehouse operations in meeting customer expectations, optimizing inventory, and minimizing costs. Furthermore, it discusses emerging technologies such as automation, robotics, and artificial intelligence (AI) in streamlining warehouse processes. Challenges such as scalability, labor management, and sustainability are also addressed, providing insights into future directions for e-commerce warehouse management.

From hot pot to high tech: Haidilao’s transformation through digital technologies for sustainable business in the restaurant industry

The pandemic has brought many challenges to the restaurant industry but highlighted the importance of embracing digital transformation that enhances organisations’ competitive advantage and sustainable business. The success story of Haidilao, a popular hot pot restaurant, inspires those striving to overcome difficulties and learn from their digital transformation journey. By staying adaptable, proactive and customer-focused, Haidilao has leveraged digital platforms to offer new and innovative services, such as an online ordering and delivery, an intelligent kitchen, an innovative WeChat strategy and even a Cloud Video Conferencing Service to enhance the attractiveness of the dining experience. Haidilao’s story demonstrates the power of innovation and customer-centricity in driving successful digital transformations for sustainable business in the restaurant industry.

Review Paper: CafeEase : Online Food Ordering System

With the rapid digitization of the food industry, online food ordering systems have become an integral part of modern dining experiences. This research paper explores the various facets of online food ordering systems, aiming to enhance the overall user experience through a comprehensive analysis and the development of an innovative design framework. The study begins by conducting a critical review of existing online food ordering platforms, assessing their strengths, weaknesses, and user feedback. By leveraging user-centered design principles, the research identifies key challenges such as user interface complexity, order accuracy, and delivery efficiency. Through a combination of user surveys, usability testing, and data analytics, the paper provides valuable insights into user preferences, behavior patterns, and expectations. Subsequently, the research introduces a novel design framework that integrates cutting-edge technologies, including artificial intelligence, machine learning, and personalized recommendation systems. This framework aims to address identified challenges and elevate the user experience by streamlining the ordering process, enhancing menu navigation, and ensuring accurate order fulfillment. Additionally, the proposed framework prioritizes accessibility, inclusivity, and responsiveness across various devices to cater to a diverse user base. In conclusion, this research paper offers a comprehensive examination of online food ordering systems, proposing an innovative design framework to address existing challenges and enhance the overall user experience. The findings aim to guide future developments in the field, fostering a seamless and enjoyable online dining experience for users worldwide. Key Words: Online Ordering System,,User-friendly interface, Hassle Free Environment, Queless Ordering System

Channel selection strategy: based on buy online and pick up in-store cooperation

PurposeThis paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What is the impact of BOPSC on their optimal price and sales volume of products? (2) When should an online retailer and an offline retailer conduct the BOPSC strategy with each other?Design/methodology/approachThe paper first establishes two game models to explore the equilibriums of online and offline retailers in non-BOPSC and BOPSC. Then the condition for online and offline retailers to implement BOPSC strategy are determined. Furthermore, the applicability of the BOPSC strategy is enhanced by incorporating numerical analysis.FindingsThe study’s findings reveal that BOPSC strategy will not always beneficial to online and offline retailers, which depends on the total cost of online shopping and the product valuation of consumers. BOPSC strategy leads to the increase of prices and online orders, and the demand of offline retailer is eroded. Moreover, BOPS cooperation between different retailers is easier to achieve than omni-channel integration strategy. When the convenience difference between offline shopping and BOPSC pick-up is moderate, the effectiveness of BOPSC strategy can be improved.Originality/valueThis study has the following two main contributions: Firstly, the authors investigate the effects of BOPSC strategy on the prices of online and offline retailers. The study results show that the BOPSC strategy alleviates price competition and promotes a win–win situation between online retailers and offline retailers. Secondly, this paper mainly studies the cooperative behavior between online and offline retailers and reveals the optimal conditions for online and offline retailers to adopt BOPSC strategy. It can help small- and medium-sized online and offline retailers to choose suitable products for BOPSC strategy, so as to achieve the purpose of increasing profit.

Tech-Savvy Stationery Smart Desk Accessories

This study presents a business strategy for a cutting-edge online ordering and delivery application for stationery that aims to provide students with a simple and effective way to buy stationery supplies. The article discusses the urgent need for a practical solution in the retail stationery sector and looks at how technology may be used to expedite the ordering and delivery procedures. The study conducts a thorough market analysis, determining the student target demographic and analyzing the most recent developments and rivals in the online stationery industry. The suggested business model is described, emphasizing the cost breakdowns, income sources, and scaling strategies. Technical details are covered in depth, including platform selections, security precautions, and scalability issues.

Online Auction System with AI

An online auction is type of an auction that takes place over the Internet. It is a popular method for buying and selling products and services. Such systems give the best price to the seller as well as the buyers. The application proposed in this paper was developed with the objective of making the system reliable, easier and fast. Through this application, anyone can sell anything on the website by sitting at home. It’s as easy as browsing the app website. Even non-technical persons can easily interact with the process of buying and selling on the application. An online auction system permits a customer to submit online orders for items and/or services from a store that serves both walk-in customers and online customers. The online auction system presents an online display of an order cut off time and an associated delivery window for items selected by the customer of any 2nd hand products. The online auction system does not settle with a credit supplier of the customer until the item selected by the customer is picked from inventory. Therefore, customers can go online to modify their order. In addition, the service window is presented to the customer as a function of the order and service type selected by the customer, and also the choice is made according to the person's preference, where the order selection is correct. When ordering goods, a virtual shopping cart is also provided by many shopping systems for holding items selected for purchase. Until a customer completes their shopping trip, successive items selected for purchase are placed into the virtual shopping cart. Virtual shopping carts may be examined at any time, and their contents can be deleted and edited at the customer’s end.

PEMBERDAYAAN PEREMPUAN MELALUI PELUANG WIRAUSAHA KUDAPAN TRADISIONAL ACEH

Traditional Acehnese food is a heritage product that is consumed and served by the Acehnese people during celebrations or certain events and has a unique taste. The community service program aims to provide socialization through the identification of various MSME products and opportunities for traditional Acehnese snacks (kue seupet) to empower women in Gampong Lam Duro, Darussalam, Aceh Besar. The business entrepreneur opportunity of traditional Acehnese snack products (kue seupet) motivated the participants to make it a household business and create a village-leading culinary product to support income and family resilience. Digital marketing and online order receiving have become important to increasing sales. At the end of the community service, a cooking competition for Acehnese cuisine, "kuah pliek u" was successful and memorable, building solidarity with the participants as well as improving their creativity and cooking skills, which can be an idea for selling Acehnese traditional cuisine.

A PERCEPTION OF HOMEMAKERS’ ONLINE MENU ORDERS ON CONSUMERS’ SATISFACTION IN TANKE, ILORIN SOUTH LOCAL GOVERNMENT AREA, KWARA STATE

The study investigated perception of homemakers’ online menu orders on consumers’ satisfaction in Tanke, Ilorin South Local Government Area. Five research questions were stated and four research hypotheses tested. Structured questionnaire was used to solicit information from the respondents. The instrument was validated and found reliable at 0.75. Five-point Likert scales of Strongly Agree, Agree, Strongly Disagree, Disagree and Undecided were used to interpret the data. Frequency count, mean, standard deviation and Pearson Product-Moment Correlation (PPMC) were used to analyse the data. The findings show that majority of the respondents agreed on the types of menus available for online order with grand mean score of 3.51 and the prices of menus ordered online were within the ranges of #2,000.00 to #2,750.00 per plate. Majority of the respondents also agreed with the methods of online menu orders with mean score of 3.43 were 3.00 was the decision rule which is lesser than 3.51 and 3.43 respectively. There is no significant relationship between the types and prices of online menu orders on customers’ satisfaction. Online menu orders have proliferated and rapidly improved the traditional line-up for menu orders and the use of digital resource brings relief to individual. It was therefore recommended that more researches be conducted on technological benefits to consumers in rural areas.

Content analysis of IQOS direct mail and email marketing in the US

ObjectiveNovel nicotine and tobacco products, including heated tobacco products (HTPs) like IQOS, are growing in global popularity. IQOS was the first HTP authorized for sale by the US Food and Drug Administration, entering the US market in 2019 and being removed in 2021 due to patent-related legal challenges, with the possibility of returning in 2024. Direct marketing is one method tobacco companies use to reach consumers of these products. The purpose of this study was to investigate the content of US IQOS direct mail and email marketing. MethodsDirect marketing items were collected between September 2019 and July 2021 by seven team members in the first US IQOS test market, Atlanta, Georgia. ResultsOverall, 101 marketing items were collected, 59 of which were unique. Among the unique items that showed images of persons (“models”), 70 % showed models appearing to be from racial/ethnic minoritized groups, 86.8 % showed at least one female-presenting model, and 37.5 % showed models appearing to be young adults (18–29 years). Items often had an embedded link/URL (91.5 %) and mentioned topics such as online services (54.2 %; for example, online ordering and tutorials), user experience (49.2 %), social media (44.1 %), and purchasing locations (37.3 %). When examined for their main purpose, items focused on subjects such as store experience (37.7 %), product introduction (18.6 %), and product use (15.3 %). ConclusionsOur study highlights the importance of better understanding how novel tobacco products are marketed, which can inform policymakers’ regulatory efforts and product authorization decisions.

The role of on‐demand delivery platform in competition between manufacturer and retailer

AbstractTraditional retailers can now partner with on‐demand delivery platforms to fulfill consumers' online orders to fight against manufacturers' direct channels. However, it is hard to say whether traditional retailers benefit from cooperating with such platforms due to market encroachment and high commission fees. We build a game‐theoretic model where the manufacturer could decide whether to introduce its direct channel, and the retailer could decide whether to cooperate with the on‐demand delivery platform. We show that when the platform adopts a reasonable pricing and service policy, the retailer can earn more profit when cooperating with the platform. When consumer acceptance of the manufacturer's direct channel is high, the manufacturer should strategically introduce its direct channel even when there are no sales. We also find that the introduction of the platform lowers the retail price at the offline channel, increasing the market's total demand, consumer surplus, and social welfare. The reason lies in the effect of intensifying downstream competition and satisfying the consumer's demand in more market segments.