Search Results (65)

To enhance the performance of online food delivery (OFD) services, it is essential to strengthen consumers’ intentions to use OFD apps, which are the core interface of this business. Accordingly, this study aims to identify the cognitive mechanisms that shape consumers’ intentions to use OFD apps and explore strategies to encourage their adoption. To achieve this, the study develops a research model that incorporates segmented dimensions of service convenience as key motivational factors, along with variables from the Technology Acceptance Model (TAM). A survey was conducted among OFD consumers in China, and the proposed research model was empirically tested using data from 478 valid responses. The analysis revealed that all six dimensions of service convenience serve as significant motivational drivers of OFD app usage. Furthermore, the study demonstrates that consumers’ coupon proneness and user-generated online reviews have significant moderating effects that reinforce the mechanism by which consumers adopt and use OFD apps. The findings and implications discussed in this study are expected to provide valuable insights and practical guidance for formulating effective strategies to promote more active consumer engagement with OFD apps in the future. Full article

The evidence on e-commerce rapidly adopting and expanding has led to a high degree of changes in consumer behavior, with food delivery platforms playing a pivotal role in the digital economy. The current study highlights the interplay between consumer perception, consumer acceptance, and electronic word of mouth (e-WOM) assessed in the context of the food delivery chain. By integrating latent variables, such as trust, consumer purchase intentions, perceived usefulness, and psychological distance, the current study explores the role of e-WOM in influencing consumer perception and acceptance within the food delivery services. Data collection and analysis implied a qualitative approach by issuing an online survey and gathering 835 valid responses, further quantitatively assessed through structural equation modelling. The data reveal the validity of the two general hypotheses, according to which consumer acceptance is positively connected to consumer perception, to which the influence of electronic word of mouth was added. The current study stresses the importance for food delivery chains to gain insight and implement strategies based on its electronic peers’ online suggestions and recommendations. The current research actively contributes to the theoretical discourse on food delivery chain management related to the electronic consumers’ experience, in order to competitively position it on electronic markets as well as the food delivery global industry. Full article

The COVID-19 pandemic has reshaped various aspects of life, influencing consumer behaviors and economic activities worldwide. This paper delves into the shifts in consumer preferences and shopping patterns for gardening products and services during and after the pandemic era. Through nationwide online surveys conducted from 2020 to 2022, we analyze changes in time spent and expenses on gardening and identify key demographic and pandemic-related factors influencing these behaviors during the pandemic era. We employed both generalized and standard ordered logistic regression models to assess the impact of various variables on the ordinal dependent variable. The findings reveal a significant surge in both time spending on home gardening activities and money invested in gardening products and services, especially among individuals who considered gardening beneficial for well-being and as a family activity. Notably, the preference for online shopping and mail delivery for gardening supplies emerged as a prominent trend during the pandemic, accompanied by a significant increase in the purchase of fruit plants, vegetable plants, and seeds, indicating that primary motivation for gardening was self-food consumption. These insights provide valuable guidance for businesses in the green industry, informing production, marketing practices, and economic recovery efforts post-COVID-19. Full article

This paper presents a review of the technologies and services associated with online grocery shopping. The progress in the field of online grocery shopping has been very rapid in recent years. Hence, there was a need to systematize knowledge about the latest various solutions used in this topic. The authors searched the internet, focusing on websites of different supermarkets, shops, and other services that offer online shopping, as well as reviewed scientific papers. Based on the collected material, the authors created four thematic parts, which include: (1) supermarket services; (2) dedicated grocery delivery services and farm-to-table; (3) shopping in Virtual Reality and the metaverse; smart devices and (4) AI in food ordering—the last part includes smart devices, such as smart refrigerators, ovens, their functionality, and the services connected with them. The authors refer to 243 sources. The research includes the three following objectives: (1) exploring and presenting the emerging applied ways of online grocery shopping, (2) exploring and presenting the latest technological advances related to the digitalization of grocery shopping, (3) discussing the upcoming technologies, services, and methods in online grocery shopping. This paper provides knowledge about a wide range of solutions offered by both supermarkets and stores (e.g., shopping applications, VR applications, metaverse shopping) and other companies (e.g., deliveries, product tracking), highlighting the numerous functions available thanks to smart devices (e.g., voice control, own shopping lists, control of products, their quantities and expiration dates, management of user preferences, and many more). This paper also discusses social issues related to the presented solutions, such as their influence on consumer behavior, barriers to adoption, and the associated challenges. Full article

The objective of this study was to investigate how perceived benefits and risks affect perceived value, as well as to examine the relationship between perceived value, consumer–brand relationships, and loyalty. The study examines the moderating effects of environmental, social, and governance (ESG) performance on the abovementioned relationships by applying a value-based adoption model. An online survey was conducted with consumers who used a food-delivery-service platform, totaling 754 participants. The SPSS 27 statistical package and SmartPLS 4.0 were used to test the research hypotheses, as well as to verify the moderating effects. The results indicate that product quality and specialization have positive effects on perceived value; however, delivery convenience does not. The analysis also found that perceived risk factors associated with delivery-service platforms, specifically, delivery risk, delivery security, and product heterogeneity, have positive effects on perceived value. These results imply that perceived value is linked to consumer perceptions of perceived benefits or risks and is closely related to the formation of customer–brand relationships with delivery platform companies. In addition, it was found that consumer–brand relationships formed in this way act as a decisive factor in the formation of corporate brand loyalty. ESG activity was found to play an important role in moderating the relationship between product quality and specialization, which are factors regarding perceived benefits and value. The ESG performance of delivery-service platforms plays a moderating role in the relationship between perceived value, consumer–brand relationships, and brand loyalty. The results of this study contribute to the development of strategic guidelines for marketers seeking to establish delivery-service platforms. Full article

Nowadays, mobile–mobile interaction is becoming a fundamental methodology for human–human networking services since mobile devices are the most common interfacing equipment for recent smart services such as food delivery, e-commerce, ride-hailing, etc. Unlike legacy ways of human interaction, on-site and in-person mutual recognition between a service provider and a client in mobile–mobile interaction is not trivial. This is because of not only the avoidance of face-to-face communication due to safety and health concerns but also the difficulty of matching up the online user using mobiles with the real person in the physical world. So, a novel mutual recognition scheme for mobile–mobile interaction is highly necessary. This paper comes up with a novel cyber-physical secure communication scheme relying on the digital twin paradigm. The proposed scheme designs the digital twin networking architecture on which real-world users form digital twins as their own online abstraction, and the digital twins authenticate each other for a smart service interaction. Thus, inter-twin communication (ITC) could support secure mutual recognition in mobile–mobile interaction. Such cyber-physical authentication (CPA) with the ITC is built on the dynamic BLE beaconing scheme with accurate proximity detection and dynamic identifier (ID) allocation. To achieve high accuracy in proximity detection, the proposed scheme is conducted using a wide variety of data pre-processing algorithms, machine learning technologies, and ensemble techniques. A location-dependent ID exploited in the CPA is dynamically generated by the physical user for their own digital twin per each mobile service. Full article

The current study examined consumers’ sustainable behavior in the context of eco-friendly drone food delivery services. It thus focused on the cognitive triggers, normative factors, and affective triggers in forming pro-environmental intentions. This study more specifically developed a comprehensive framework that included cognitive triggers, which included environmental awareness, ascribed responsibility, biospheric value, environmental concern, and perceived effectiveness, personal norm, and affective triggers, which included positive anticipated emotion and negative anticipated emotion, subjective norm, and pro-environmental intentions. The 312 samples were randomly extracted through an online survey company in Korea, which targeted individuals who have dined out within the last six months. A theoretical model that included mediation and causal hypotheses was proposed and tested by conducting structural equation modeling. The data analysis results indicated that the four dimensions of the cognitive triggers, such as ascribed responsibility, biospheric value, environmental concern, and perceived effectiveness, positively affect personal norm, and consequently have a positive effect on positive anticipated emotion. In addition, subjective norm aids in regards to enhancing personal norm and pro-environmental intentions. The study consequently contributes knowledge that addresses the acknowledged research gap and provides practical suggestions for green marketing strategies in regards to promoting the services. Full article

As food safety awareness rises and living standards improve, consumers have increasingly higher expectations for the efficiency and quality of cold chain logistics services. For cold chain logistics service providers, accurately understanding consumer psychology and enhancing their willingness to continue using the service—while guiding them to actively participate in green cold chain logistics practices—are necessary means to maintain competitiveness. Therefore, based on stimulus-organism-response and cognitive-affective-conative theories, this study constructs a three-stage model to explore the factors influencing consumers’ continuous consumption of online retail cold chain delivery services. This study substantiates that consumers’ intention to continue consuming proceeds through the following three stages: cognitive, affective, and conative. Specifically, the results indicate that consumer- and environment-oriented services significantly enhance consumer value and psychological empowerment, which further promotes their intention to continue using the service and participate in green practices. Moreover, psychological empowerment and perceived value fully and partially mediate the relationship between the two types of services and consumer sustainable consumption, respectively. These findings expand the research on cold chain consumption and deepen our understanding of how various factors influence consumer behavior. Full article

We explored the relationship and impact of service failures, acceptance of service recovery strategy, post-recovery satisfaction, and loyalty in the food delivery service industry. We used the convenience sampling method and adopted an online questionnaire survey on food delivery services for consumers aged 19 to above 30. Service failure, service recovery strategy acceptance, post-recovery satisfaction, and loyalty scales were explored. A total of 128 valid responses were analyzed for descriptive statistics, t-test and one-way analysis of variance, Pearson correlation analysis, and regression analysis. Missing food items was the most common and most serious service failure. Providing a refund was the most efficient service recovery strategy. If the service recovery strategy was handled properly, it effectively improved satisfaction and loyalty after service recovery was applied. If the service charge of delivery platforms increased, consumers mostly reduced the usage of the service. Therefore, delivery staff need to check whether the meal was correctly delivered. If service failures occur, active care or apologies must be made with the refund. Delivery platform must avoid increased service change and consumers would use the platform stably. Full article

Online food delivery services are rapidly growing in popularity, making customer satisfaction critical for company success in a competitive market. Accurate delivery time predictions are key to ensuring high customer satisfaction. While various methods for travel time estimation exist, effective data analysis and processing are often overlooked. This paper addresses this gap by leveraging spatial data analysis and preprocessing techniques to enhance the data quality used in Bayesian models for predicting food delivery times. We utilized the OSRM API to generate routes that accurately reflect real-world conditions. Next, we visualized these routes using various techniques to identify and examine suspicious results. Our analysis of route distribution identified two groups of outliers, leading us to establish an appropriate boundary for maximum route distance to be used in future Bayesian modeling. A total 3% of the data were classified as outliers, and 15% of the samples contained invalid data. The spatial analysis revealed that these outliers were primarily deliveries to the outskirts or beyond the city limits. Spatial analysis shows that the Indian OFD market has similar trends to the Chinese and English markets and is concentrated in densely populated areas. By refining the data quality through these methods, we aim to improve the accuracy of delivery time predictions, ultimately enhancing customer satisfaction. Full article

The unprecedented production and sharing of data, opinions, and comments among people on social media and the Internet in general has highlighted sentiment analysis (SA) as a key machine learning approach in scientific and market research. Sentiment analysis can extract sentiments and opinions from user-generated text, providing useful evidence for new product decision-making and effective customer relationship management. However, there are concerns about existing standard sentiment analysis tools regarding the generation of inaccurate sentiment classification results. The objective of this paper is to determine the efficiency of off-the-shelf sentiment analysis APIs in recognizing low-resource languages, such as Greek. Specifically, we examined whether sentiment analysis performed on 300 online ordering customer reviews using the Meaning Cloud web-based tool produced meaningful results with high accuracy. According to the results of this study, we found low agreement between the web-based and the actual raters in the food delivery services related data. However, the low accuracy of the results highlights the need for specialized sentiment analysis tools capable of recognizing only one low-resource language. Finally, the results highlight the necessity of developing specialized lexicons tailored not only to a specific language but also to a particular field, such as a specific type of restaurant or shop. Full article

To protect the safety of food bought from the online catering sector, the former State Food and Drug Administration of China issued two separate regulations in 2016 and 2017. Independently, the Shanghai government formulated local regulations, including the Shanghai Online Catering Service Supervision and Management Measures, to strengthen food safety supervision in this megacity with the largest catering sector in China. This study explored factors that influence consumer perceptions of the performance of online catering food safety regulations using survey data from 1050 respondents collected in 2019. The results indicate that consumers believe that Shanghai’s online catering industry has improved by varying degrees in terms of food freshness, ingredient traceability, foreign matter control, food temperature control, internal packaging hygiene and environmental protection, and satisfaction with food safety. The factors that influenced the listed features include the number and effectiveness of government-issued regulations regarding the online catering sector, effectiveness of ordering platform food safety regulations, employee training frequency, employee food safety awareness, delivery box cleanliness and courier personal hygiene, consumer trust in ordering platform services, and consumer confidence in government supervision. These factors significantly and positively affected the consumers’ perceptions of the performance of food safety regulations in the online catering sector. Full article

Changing customer experiences and conventional business models, the convergence of cutting-edge technologies like blockchain, chatbots, and the Internet of Things (IoT) has triggered revolutions across industries. Customers want personalized, easy, and meaningful interactions in today’s digital world, so traditional retail and service models are changing to online platforms and round-the-clock digital support. Blockchain-integrated chatbots give users a reliable platform for communication and transactions by utilizing the security and transparency of blockchain technology. These artificial intelligence (AI)-driven chatbots are revolutionizing digital interactions by conversing with users in natural language, managing transactions, and providing tailored support. IoT devices, on the other hand, bring in a new era of connectedness by giving commonplace things the ability to sense, process, and communicate. IoT devices optimize delivery processes and guarantee that the quality and safety criteria are satisfied in the food delivery industry. Blockchain-integrated chatbots are a disruptive force that improves delivery process efficiency, transparency, and trust when integrated with IoT devices. This study examines how blockchain, chatbots, and IoT technologies might be integrated into the food delivery sector, emphasizing the advantages and potential ramifications of doing so. Full article

The incessant evolution of online platforms has ushered in a multitude of shopping modalities. Within the food industry, however, assessing the delectability of meals can only be tentatively determined based on consumer feedback encompassing aspects such as taste, pricing, packaging, service quality, delivery timeliness, hygiene standards, and environmental considerations. Traditional text data mining techniques primarily focus on consumers’ emotional traits, disregarding pertinent information pertaining to the online products themselves. In light of these aforementioned issues in current research methodologies, this paper introduces the Bert BiGRU Softmax model combined with multimodal features to enhance the efficacy of sentiment classification in data analysis. Comparative experiments conducted using existing data demonstrate that the accuracy rate of the model employed in this study reaches 90.9%. In comparison to single models or combinations of three models with the highest accuracy rate of 7.7%, the proposed model exhibits superior accuracy and proves to be highly applicable to online reviews. Full article

In the context of an evolving socio-economic landscape and rising living standards, the online market for fresh products, encompassing fruits, vegetables, meats, dairy, and eggs, has seen substantial growth, necessitating sophisticated logistics for e-commerce home delivery. This study tackles the distinct challenges of fresh product delivery, which demand rigorous adherence to climate conditions and product mix during transport, significantly influencing the operational strategies and scheduling of delivery platforms. To address these challenges, a comprehensive mathematical model was developed to optimize fresh food home delivery scheduling, focusing on reducing spoilage rates and accommodating the dynamic impact of environmental temperature changes. The model posits assumptions of a consistent and ample supply of fresh goods, standard initial quality loss, and efficient porter assignment for multi-category order combinations. It introduces three objective functions, targeting the minimization of fresh food loss, maximization of customer satisfaction, and reduction of distributor costs. The efficacy of the model and its genetic-algorithm-based solution method was assessed through numerical analysis and case studies, illustrating that the model enhances delivery efficiency and service quality across varying temperature conditions. This substantiates the critical role of environmental temperature management in optimizing fresh food delivery, offering a robust framework for advancing logistical operations in the perishable goods sector and ensuring quality and efficiency in fresh food e-commerce delivery. Full article