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PurposeMeal ordering apps (MOAs) have transformed the customers' dining habits, particularly during mobility restrictions of the COVID-19 pandemic. Under the theoretical cover of the extended stimulus–organism–response (SOR) model, this paper attempts to explore the critical antecedents and outcomes of customer MOA engagement which predict the continuous purchase intentions using these apps. A multigroup analysis is conducted to investigate the difference between the hypothesized relationships between the Chinese and Indonesian consumers.Design/methodology/approachA mixed-method approach, including a systematic literature review, an open-ended essay (qualitative) with 139 MOA users and an online survey (quantitative) with 1,207 MOA users in total, was used for hypotheses testing.FindingsThe structural equation model results revealed that customer MOA experience factors such as mobile online reviews (MR), food quality (FQ), restaurant reputation (RR), service quality and system quality (SyQ) are the absolute positive factors that influence customer MOA cognitive, affective and behavioral engagement, which in turn affect continuous purchase intentions. The multigroup analysis results reveal that Chinese customers prioritized MR and FQ for customer MOA engagement (cognitive, affective and behavioral). Comparatively, Indonesian customers placed most importance on RR and SyQ.Originality/valueConsidering a market-specific setting and based on the extended SOR framework, this study is one of the first to take a comprehensive look at the critical antecedents and outcome of multidimensional customer MOA engagement in the developing countries' (China and Indonesia) online to offline meal delivery context. Further, this study investigates the customer continuous purchase intentions as an outcome of MOA engagement during the COVID-19 pandemic. The findings also reveal the differences in consumer behavior across the two developing but culturally diverse countries samples during the pandemic.
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This study presents and discusses the home delivery services in stochastic queuing-inventory modeling (SQIM). This system consists of two servers: one server manages the inventory sales processes, and the other server provides home delivery services at the doorstep of customers. Based on the Bernoulli schedule, a customer served by the first server may opt for a home delivery service. If any customer chooses the home delivery option, he hands over the purchased item for home delivery and leaves the system immediately. Otherwise, he carries the purchased item and leaves the system. When the delivery server returns to the system after the last home delivery service and finds that there are no items available for delivery, he goes on vacation. Such a vacation of a delivery server is to be interrupted compulsorily or voluntarily, according to the prefixed threshold level. The replenishment process is executed due to the (s,Q) reordering policy. The unique solution of the stationary probability vector to the finite generator matrix is found using recursive substitution and the normalizing condition. The necessary and sufficient system performance measures and the expected total cost of the system are computed. The optimal expected total cost is obtained numerically for all the parameters and shown graphically. The influence of parameters on the expected number of items that need to be delivered, the probability that the delivery server is busy, and the expected rate at which the delivery server's self and compulsory vacation interruptions are also discussed.
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Freight transportation in urban areas represents an essential activity from the standpoint of economic development;in recent years, the spread of e-commerce (also accelerated by COVID-19) has contributed to increasing the demand for freight distribution over short distances. In most cities, the approaches and measures are often based on new technologies. Nevertheless, today there are contexts wherein delivery operations represent critical tasks to be solved. Furthermore, low accessibility areas, such as small islands, present further problems due to their exclusive dependence on maritime links (and often low-reliability services). This paper tackles this topic, formulating and solving a distribution problem by linking shipping services with last-mile distribution operated by means of an automatic delivery service (parcel lockers). A test application is proposed by considering the small island of Lipari in the archipelago of the Aeolian islands (Sicily, Southern Italy). The results show that such a type of service could reduce the user's waiting time when compared to traditional home deliveries.
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The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles (EVs) that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, unmanned aerial vehicles (UAVs) have also gradually and more recently been widely used for military and civilian purposes. The recent literature estimated that UAVs will become the major means of transport for goods delivery services before 2040, and the development of passenger UAVs will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping, and charging stations to refill the battery of UAVs. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of UAVs. It may even be very possible that a large number of UAVs need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of UAVs. Although studies have proposed the method of that employing moving EVs along with wireless charging technology in order to provide electricity to UAVs with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options should be provided to fit the individual need of each UAV. In view of this, this work attempts to meet the mission characteristics and needs of various UAVs by providing an adaptive flight path and charging plan attached to individual UAVs, as well as reducing the power load of the renewable power generation during the peak period. We ran a series of simulations for the proposed flight path and charging mechanism to evaluate its performance. The simulation results revealed that the solutions proposed in this work can be used by UAV operators to fit the needs of each individual UAV.
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Current awareness of epidemic threats and critical experiences of the COVID-19 pandemic require extension of the management model in the smart city, especially in the field of mobility and transport services, with monitoring of epidemic hazards. This paper addresses the issue of epidemic hazards, a new challenge in smart cities, and customer delivery services. The novel DHI methodology for epidemic hazards assessment is presented and applied to compare customer delivery services in aspects of SARS-CoV-2 epidemic hazards. The case studies presented a detailed analysis of epidemic hazards on the basis of process algorithms and dedicated quantitative scales to assess factors influencing the mechanisms of virus transmission. The developed DHI methodology and the results obtained for transport services constitute important cognitive knowledge for the administrative personnel in smart city.
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The COVID-19 pandemic has significantly strained online food delivery services (OFDS) globally. This has challenged OFDS businesses to redesign and deploy technologies to meet customer demand. The purpose of this article is to identify the optimal factors contributing to customer experience with OFDS services during a black swan event such as the COVID-19 pandemic. We followed a four-step research design to identify the optimal factors for OFDS. First, we identified the major episodes in the OFDS process. Second, these episodes were evaluated by customers using the sequential incidence technique. Third, we used an orthogonal design to analyze the episodes at different levels based on customer preferences. Finally, we used the Taguchi approach to calculate the signal-to-noise ratios and identify the optimal factors and their preferred levels. We classify the optimal factors into customer-oriented and service-provider-oriented propositions. The option to select the delivery person and delivery conditions was found to be the most optimal customer-oriented attribute. We discuss the theoretical and managerial implications of the study and suggest major avenues for digital transformations in OFDS for better customer experience. IEEE
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The COVID-19 pandemic and movement control order that started in 2020 has changed the shopping behavior to online shopping. This also increases in-home delivery services by the shipping providers. However, since the virus can be transmitted through surface transmission, the buyer is advised to avoid touching surfaces and clean or sanitize surfaces regularly with standard disinfectants to prevent the spread. In addition, with an increase in the parcel delivery process, missing parcels also will be one of the main problems that the buyer will be facing. This study has developed a smart parcel box with sanitizer to overcome the issues stated above. Smart in this context refers to the notification that the buyer will get once the parcel is placed inside the parcel box, the box itself will be locked once the parcel is in and only can be opened by the authorized user. This study utilizes the Arduino IDE software to control the operation of the locks and notifications. The notifications are linked to the Blynk Application that needs to be installed on the buyer's smartphone. The software is also coded to run the motor that controls the standard disinfectants that will be sprayed on the parcel for a few seconds. The results indicate one solution for the online shopping addicts to shop while avoiding the spread of COVID-19 viruses. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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A plethora of courier services are available in Bangladesh which are more expensive, less effective and takes ages to deliver the product. Besides, in the ongoing COVID-19 pandemic situation, it's onerous to move from one place to another, and if a person wants to send a product, he/she needs to go to the courier office. Moreover, many people need to move from their house for attending office, meetings, and traveling from one district to another district for special purposes. In this paperwork, a system is introduced to reduce the cost and time to send a product from one place to another place. Basically, an application is developed to meet the people who want to send a product and another one who want to carry the product. For carrying the product one can easily earn money. After scrutinizing the cost of courier services in Bangladesh, an algorithm is introduced to calculate the carrying cost of the product and an algorithm is also developed for product security.
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Drones operate on electric batteries and not on gasoline, so the eco-friendly role of drones has recently attracted a lot of attention. Thus, this study was designed in order to investigate differences in behavioral intentions, such as intention to use, word-of-mouth, and willingness to pay more, according to demographic characteristics and past experiences in the field of eco-friendly drone food delivery services. Data were collected from 422 potential consumers of eco-friendly drone food delivery services in South Korea. The data analysis results indicated that females are more willing to pay extra than males are, respondents who were in their 50s had higher word-of-mouth intention than other generations, marital status showed significant differences in willingness to pay more and intentions to use, and there was a difference in willingness to pay more and word-of-mouth with regards to monthly income. In addition, respondents who had previously heard of drone food delivery services had higher averages with willingness to pay more and intentions to use as opposed to respondents who had not heard of them, and respondents who had experience controlling drones were willing to pay additional fees when they used eco-friendly drone food delivery services. The results of this study would be a great assistance for executives who will operate eco-friendly drone food delivery services.
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With the emergence of a number of food ordering applications in the market, it has become equally challenging for customers to choose from the available applications. The objective of this study is to determine the level of awareness about online food ordering applications among customers. Further, the study evaluates the factors affecting customer perception towards online food ordering applications in Punjab. The study also determines the influence of demographic variables on the buying behavior of customers on online food ordering apps. The primary research data was collected through a structured questionnaire from 485 respondents who prefer ordering food through virtual applications, and SPSS software was used for analysis. Factor analysis was employed to find out the behavior of respondents towards food delivery applications. ANOVA was applied to check the impact of demographics on customer perception. The study identified eight factors affecting customer perception towards food ordering applications, i.e., discounts and offers, perceived ease of use, customer support, convenient operating hours, reliability, restaurant choice and variety, alternative mode of payment and serviceability of which 'discounts and offers' was found to be the most important factor. Further, the findings of the study revealed a significant role of demographic variables such as age, education, occupation and income in affecting customers buying behavior towards food ordering applications.
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• Assess the reliability of an online food delivery system as a performance index. • Investigate with non-integer multiple orders, time, and space limitations. • Construct a multistate online food delivery network as its gig economy. • Determine minimal capacity vectors without knowing minimal paths in advance. • Conduct sensitivity analysis for more managerial insights on the MOFN. In recent years, especially during the outbreak of COVID-19, there have witnessed the emergence of online food delivery (OFD) services that allow customers to place orders via Internet-connected devices to obtain door-to-door delivered meals. In this service, on-time delivery to the right customer with high-quality fresh meals is deemed the primary factor. This paper investigates the reliability of OFD through its ability to meet customer needs in a specific context. During the delivery process, the courier receives the food at the store, packs it into a delivery box, and then delivers it to the customer. Note that, the delivery boxes are limited in space. Customers prefer having their orders delivered within a given time threshold. Thus, reliability is defined as the probability to complete non-integer and multiple orders under a limited time and space. Besides, the OFD system belongs to the gig economy, which allows couriers to select their shifts and working regions. Hence, the capacity of each region, which indicates the number of available couriers, is regarded as multistate. We, thus, construct the OFD system as a multistate online food delivery network (MOFN). Under the limitation of time and space, all feasible minimal capacity vectors are determined to compute the reliability. With the proposed investigation, managers can understand their MOFN's ability to meet specific customer demands. Accordingly, they can make appropriate adjustments for better performance. [ABSTRACT FROM AUTHOR] Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Since early 2020, the COVID-19 outbreak has disrupted various supply chains including the on-demand food delivery sector. As a result, this service industry has witnessed a tremendous spike in demand that is affecting its delivery operations at the downstream level. Previous research studies have explored one-to-one and many-to-one solutions to the virtual food court delivery problem (VFCDP) to optimize on-demand food delivery services in different cities. However, research efforts have been limited to multiple restaurant orders from only one customer which does not apply to traditional systems where multiple customers request on-demand food delivery from multiple restaurants. This study rigorously analyses multiple restaurants to multiple customers (Many-to-many) food delivery simulation models in ideal weather conditions that are constrained with multiple key performance indicators (KPIs) such as delivery fleet utilization (the number of couriers utilized over the fleet size), average order delivery time, and fuel costs. This research also benchmarks the on-demand food delivery queueing methodologies using system dynamics and agent-based simulation modeling where three on-demand food delivery routing methodologies are simulated including First-in-First-Out (FIFO), Nearest, and Simulated Annealing using AnyLogic. The results suggest that the Many-to-many (Nearest) method outperforms other delivery routing methods which would have positive implications on optimizing existing food delivery systems and managerial decisions.
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The demand for online food delivery has increased considerably throughout the world during the COVID-19 pandemic. Consumers' habits in searching for information on and making decisions about ready-to-eat food have changed remarkably during this time. The purpose of this research is to explore consumers' use of online food delivery services (OFDS) during the pandemic via applications (apps) and the moderating role played by the consumers' perceived trust in the information. Data were collected from 246 users through e-mail and structural equation modeling using PLS-3 was used to analyze the data. We have shown 12 recent insights into OFDAs behavioral intention. We found that information and food service attributes influence the perceived usefulness of OFDS and ultimately shape the respondents' intention to use it. Behavioral intention toward OFDS and perceived trust have a considerable influence on the use of OFDA. This research offers insights into the effects of the pandemic on the food delivery market and shows the dynamics of the interrelationships among various information- and restaurant-related attributes that lead to actual use.
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The high demand and acute timeliness that characterizes instant delivery entail the challenges of high labor costs and an increase in courier traffic accidents. Autonomous delivery vehicles (ADVs) may serve as a key solution, with their attendant reduced labor input and higher efficiency. Customers play a key role in the successful implementation of ADVs on a large scale. However, understanding the factors that affect customers' intentions to use ADVs is still limited. Compared to autonomous driving, ADV customers are ultimately not the real users, who only are served by ADVs during the last leg of a trip. On account of this, the Technology Acceptance Model (TAM) may not be well-fitted for explaining the dynamics involved in ADV adoption. Within the context of ADVs, our study identified influencing factors that have not been captured by prior studies. This study incorporates infection risk, use experience, and social awkwardness into the Diffusion of Innovation (DOI) theory to explore customers' intentions to use ADVs. Data from 691 survey respondents were collected to validate the research design. The results demonstrate that compatibility, social influence, infection risk, green image, social awkwardness, and use experience all have a significantly positive impact on customers' intentions to adopt ADV services, while complexity and perceived risk both exhibited a negative impact. But no effect could be found for relative advantage, which may be because of the fact that customers only need ADVs to meet their delivery demand. This study contributes to understanding customers' adoption intentions toward ADVs, informing policymakers in formulating ADV regulations and standards, and promoting the large-scale application of ADVs in instant delivery services.
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This paper examines the use of augmented reality technology in the design of packaging for takeaway food to assist in marketing. The research is divided into three studies for progressive investigation and analysis. Study 1 collected 375,859 negative evaluations of food delivery from the Internet and explored the main reasons that may have impacted the user's evaluation by Latent Dirichlet Allocation topic modeling. Study 2 evaluated the effectiveness of augmented reality packaging by surveying 165 subjects and comparing it with traditional packaging. We conducted a survey of 1603 subjects in Study 3 and used the technology incentive model (TIM) to analyze how augmented reality technology positively impacts food delivery marketing. It has been established that packaging will influence the negative perception of consumers about buying and eating takeout food. Specifically, augmented reality technology can improve negative evaluations by providing a more conducive user experience than traditional packaging. According to our findings, augmented reality technology has improved the consumers' perception of interaction, perceived vividness, and novelty experience, and achieved the aim of promoting takeaway food retail by improving negative evaluations posted by users.
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Pooling Through the Waves JARED BULLARD MD, FRCPC Jared Bullard is an Associate Professor in the Departments of Pediatrics & Child Health and Medical Microbiology & Infectious Diseases at the Max Rady College of Medicine, Rady Faculty of Health Sciences and Associate Medical Director, Cadham Provincial Laboratory Investigator, Children's Hospital Research Institute of Manitoba, in Winnipeg. [...]NH has recently developed a pathway for internationally educated MLTs (IEMLTs), who may start as laboratory clerks or MLAs and be able to secure MLT positions once they gain CSMLS certification. Rethinking Safety DAVID GOLDFARB MD, FRCPC David Goldfarb, MD, FRCPC, is a Clinical Associate Professor in the Department of Pathology and Laboratory Medicine at the University of British Columbia, Associate Head of the Department of Pathology and Laboratory Medicine at BC Children's Hospital and BC Womens Hospital and Health Centre, and Medical Microbiologist and Pediatric Infectious Disease Physician at BC Children's Hospital in Vancouver.
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This paper examines the efficacy of telemedicine (TM) technology compared to traditional face-to-face (F2F) visits as an alternative healthcare delivery service for managing diabetes in populations residing in urban medically underserved areas (UMUPAs). Retrospective electronic patient health records (ePHR) with type 2 diabetes mellitus (T2DM) were examined from 1 January 2019 to 30 June 2021. Multiple linear regression models indicated that T2DM patients with uncontrolled diabetes utilizing TM were similar to traditional visits in lowering hemoglobin (HbA1c) levels. The healthcare service type significantly predicted HbA1c % values, as the regression coefficient for TM (vs. F2F) showed a significant negative association (B = −0.339, p < 0.001), suggesting that patients using TM were likely to have 0.34 lower HbA1c % values on average when compared with F2F visits. The regression coefficient for female (vs. male) gender showed a positive association (B = 0.190, p < 0.034), with HbA1c % levels showing that female patients had 0.19 higher HbA1c levels than males. Age (B = −0.026, p < 0.001) was a significant predictor of HbA1c % levels, with 0.026 lower HbA1c % levels for each year's increase in age. Black adults (B = 0.888, p < 0.001), on average, were more likely to have 0.888 higher HbA1c % levels when compared with White adults.
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PurposeThis study investigates the determinants influencing customers' intentions of using the foodpanda mobile app during COVID-19 pandemic.Design/methodology/approachThis study is based on review of the literature studies and 388 usable data collected from respondents having prior experiences in online food delivery (OFD) services in Dhaka city in Bangladesh. The subsequent data are analyzed through structural equation modeling using Smart PLS 3.3.3.FindingsThe findings show that perceived usefulness (PU), ease of use, convenience, attitude and fear of COVID-19 significantly impact intentions to use foodpanda mobile app (ITUFPMA) and attitude. Further, attitude partially mediates between PU, ease of use, convenience and ITUFPMA. Moreover, fear of COVID-19 moderates the strength of association between attitude and ITUFPMA.Practical implicationsThe findings of the study may be useful to OFD service operators in formulating business strategies for improving customers' foodpanda mobile app use intentions and coping with competitive business environment of sharing economy sector.Originality/valueThe study presents a unique case highlighting what are influencing customer intentions toward OFD services during COVID-19 context. The current study provides important insights for industry operators by integrating PU, ease of use, convenience, attitude and fear of COVID-19 in examining ITUFPMA during COVID-19 situation.
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BACKGROUND: Food prepared out of home is typically energy-dense and nutrient-poor. Online food delivery services have become a popular way to purchase such food. The number of accessible food outlets through these services can influence how frequently they are used. Anecdotally, food outlet access through online food delivery services increased in England between 2020 and 2022, in the context of the COVID-19 pandemic. However, the extent to which this access changed is poorly understood. OBJECTIVE: We aimed to investigate monthly changes in online access to food prepared out of home in England in the context of the first 2 years of the COVID-19 pandemic compared with November 2019 and the extent to which any changes were associated with deprivation. METHODS: In November 2019 and monthly between June 2020 and March 2022, we used automated data collection to construct a data set containing information about all food outlets in England registered to accept orders through the leading online food delivery service. Across postcode districts, we identified the number and percentage of food outlets registered to accept orders and the number that was accessible. We used generalized estimating equations (adjusted for population density, the number of food outlets in the physical food environment, and rural/urban classification) to investigate the change in outcomes compared with prepandemic levels (November 2019). We stratified analyses by deprivation quintile (Q). RESULTS: Across England, the summed number of food outlets registered to accept orders online increased from 29,232 in November 2019 to 49,752 in March 2022. Across postcode districts, the median percentage of food outlets registered to accept orders online increased from 14.3 (IQR 3.8-26.0) in November 2019 to 24.0 (IQR 6.2-43.5) in March 2022. The median number of food outlets accessible online decreased from 63.5 (IQR 16.0-156.0) in November 2019 to 57.0 (IQR 11.0-163.0) in March 2022. However, we observed variation by deprivation. In March 2022, the median number of outlets accessible online was 175.0 (IQR 104.0-292.0) in the most deprived areas (Q5) compared with 27.0 (IQR 8.5-60.5) in the least deprived (Q1). In adjusted analyses, we estimated that the number of outlets accessible online in the most deprived areas was 10% higher in March 2022 compared with November 2019 (incidence rate ratios: 1.10, 95% CI 1.07-1.13). In the least deprived areas, we estimated a 19% decrease (incidence rate ratios: 0.81, 95% CI 0.79-0.83). CONCLUSIONS: The number of food outlets accessible online increased only in the most deprived areas in England. Future research might attempt to understand the extent to which changes in online food access were associated with changes in online food delivery service use and the possible implications on diet quality and health.
Subject(s)
COVID-19 , Pandemics , Humans , COVID-19/epidemiology , Food , Diet , EnvironmentABSTRACT
The novel coronavirus (COVID-19) pandemic created an environment where nearly all aspects of mobility changed to ensure the health and safety of the public. The Centers for Disease Control and Prevention (CDC) recommended that people quarantine for 14 days if they were potentially exposed to the virus, stay at least six feet apart from others, and stay at home as much as possible. Delivery via third-party restaurant app, grocery, and package delivery quickly became an essential service. This study assesses customer's changes in use and perceived quality of delivery services in Southwest Virginia, via an online stated-preference survey (n = 423). The responses were analyzed using ordered logit and generalized ordered logit models to identify which population segments had changing delivery behavior and perceptions due to the pandemic. Findings include that before the pandemic, only households with an income greater than $100,000 had a significantly higher demand for package delivery services than those making less than $25,000. During the pandemic, all income brackets had a significantly higher demand for package delivery "weekly" than households with less than a $25,000 income, with a 19.50%, 22.54%, and 45.59% greater chance of use for income levels $25,000 to $50,000, $50,000 to $100,000, and over $100,000, respectively. This trend highlights that package delivery became necessary during the pandemic. Respondents who lived within town limits were statistically significantly more likely to use third-party restaurant delivery apps at least once a week before (3.10%), during (9.20%), and after (4.50%) the pandemic compared to those outside town limits. The results also found people who lived within town limits were 7.77% more likely to be satisfied with delivery services in general than those who lived outside town limits. The findings from this paper identify expanding delivery equity gaps within the population and provide recommendations for policymakers and delivery agencies. Some limitations include that low sample size did not allow for fully segmented models and meant that the study should be considered exploratory in nature.