A change of perceived innovativeness for contactless food delivery services using drones after the outbreak of COVID-19

Risks of Drone Use in Light of Literature Studies

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.

Application of the extended value-belief-norm (VBN) theory to understand consumers' intention to use autonomous delivery vehicles (ADVs)

Emissions from transportation fuel vehicles are polluting the environment more than ever before. Currently, autonomous delivery vehicles (ADVs) are welcomed by logistics service providers and lots of consumers in general for their significant contribution in reducing environmental pollution and increasing delivery efficiency. However, there is a lack of in-depth research on consumers' willingness to adopt ADVs, despite the fact that ADVs are innovative delivery method in the field of last-mile delivery. The purpose of the study is to expand the existing knowledge of consumers' adoption behaviors by developing and testing the extended Value-Belief-Norm (VBN) theory in autonomous delivery literature. In particular, the study adds subjective norms and COVID-19 risk into the original VBN model as a theoretical framework to gain a comprehensive understanding of the consumer decision-making processes with respect to their intentions to use ADVs. Structural equation modeling is conducted using data from a web-based survey of 561 consumers through an online sample platform. The results of the study demonstrated that both subjective norms and COVID-19 risk are all related with consumers' intention to use ADVs. The casual chain hypotheses of the extend VBN theory mentioned in our study are all supported. The results of the study make significant theoretical and managerial contributions to the field of last-mile delivery and the adoption behaviors of emerging technologies.

Do consumers continue to use O2O food delivery services in the post-pandemic era? Roles of sedentary lifestyle

Online-to-offline food delivery (O2OFD) services have become popular worldwide, and consumers' O2OFD usage and sedentary behavior have increased during the COVID-19 pandemic. However, whether consumers will continue to use O2OFD in the post-pandemic era is uncertain, and the relationship between sedentary lifestyle and O2OFD usage is poorly understood to date. Therefore, this study aims to investigate consumers' continued intention to use O2OFD in the post-pandemic era and their subsequent use behavior, as well as to explore the roles of sedentary lifestyle. A research model based on the unified theory of acceptance and use of technology 2 (UTAUT2), integrating network externalities and including sedentary lifestyle, was proposed. A two-stage online survey was conducted in China, with 409 eligible responses used in the data analysis. The results indicate that habit, perceived network size, and perceived complementarity were the main predictors of continued intention, whereas habit and continued intention were the primary determinants of use behavior. Sedentary lifestyle was positively related to O2OFD use behavior and moderated the effects of habit and continued intention on use behavior. In addition to its theoretical contributions, this study has implications for public policies, marketing strategies, and consumer well-being.

Extending UTAUT2 with knowledge to test Chinese consumers' adoption of imported spirits flash delivery applications

Despite the rapid growth in sales of imported spirits in the Chinese market, consumers are struggling to easily buy high-quality imported spirits with favorable price. The imported spirits flash delivery applications are proposed to provide Chinese consumers with high-quality services delivered within a few hours. This study extends UTUAT2 with knowledge, risk and innovativeness to identify factors influencing Chinese consumers' use of flash delivery services for imported spirits. With the help of service providers, 315 valid questionnaires were collected and an empirical study was carried out. Findings suggest that social influence, habit, innovativeness and knowledge all have significant effects on usage. In particular, knowledge has significant moderating effects on relationships between social influence, habit, innovativeness and usage. This research is supposed to help imported spirits flash delivery providers to further expand the market, and will be of great help to the investment decisions of multinational spirits manufacturers in China.

Challenges for contactless online food delivery services during the COVID-19 pandemic in Taiwan: Moderating effects of perceived government response

The COVID-19 pandemic has affected numerous industries worldwide, altered consumer behavior, and increased demand for contactless online food delivery (OFD) services. COVID-19 information from the government may influence the public's information-seeking behavior regarding OFD services. Thus, exploring the relationship between contactless OFD and consumer perceptions of the government response during the pandemic is essential. This paper probed the effects exerted by three behavioral beliefs, namely health consciousness, self-efficacy, and perceived benefits, on consumers' intention and attitude toward contactless online food delivery (OFD) services. This study explored the moderating impact exerted by perceived government response to the COVID-19 pandemic on the relationship between attitude and intention toward OFD services. The study results indicated that self-efficacy and perceived benefits positively influenced the respondents' attitude toward contactless OFD services. Health consciousness negatively influenced their attitude toward these services. The respondents' attitude toward contactless OFD services to be positively related to their behavioral intention toward such services. Perceived government response to COVID-19 moderated the relationship between respondents' attitude and behavioral intention toward contactless OFD services. Based on the study findings, some suggestions are provided for governments, other relevant agencies, and OFD service providers herein.

The effect of hotel employee resilience during COVID-19: The moderation role of perceived risk and challenge stressors

The effect of hotel employee resilience during major crises lacks sufficient empirical investigation. This research aimed to develop a conceptual model of hotel employee resilience effects on turnover intentions and service quality with belief restoration as mediation and challenge stressors and perceived risk as moderation variables. A questionnaire survey was conducted with 28 star-rated hotels (including two 3-star, fifteen 4-star, and eleven 5-star hotels) in southeastern, northeastern, central, and western China against the background of the COVID-19 pandemic, and with operational (e.g., front office, food and beverage, housekeeping) and administrative (e.g., human resource, sales, finance) departments. A total of 1318 valid questionnaires were collected. The results showed that: (1) employee resilience predicted employee service quality positively and turnover intentions negatively; (2) belief restoration partially mediated the impact of employee resilience on service quality and turnover intentions; and (3) perceived risk and challenge stressors had diverse moderation effects (e.g., U-shaped, linear) in the impacts of resilience, and they were important external and internal situational factors that influenced the impact of employee resilience. This research revealed the effects and situational conditions of hotel employee resilience during a major crisis, which provides a theoretical basis for establishing hotel crisis response strategies.

ICT applications and the COVID-19 pandemic: Impacts on the individual's digital data, digital privacy, and data protection

A prominent move amid the COVID-19 pandemic is related to the wide use of ICT applications for various reasons. Such services are context-specific and sector-specific, but we see transformative directions leading to digital data collection, monitory, and management platforms. For now, these have been beneficial to evaluate trends and issues related to the pandemic. Some aggregated data could also help decision-making processes, which are helpful to contain such disruptive events. However, the main concern is the use of the individual's data and information, which means we may shift to micro-management and eventual controlling tools that could harm data protection processes. Undoubtedly, the use of ICTs during the COVID-19 pandemic has been primarily positive at multiple scales, but we have to evaluate the pros and cons before accepting all data collection processes. Such ICT-mediated platforms and/or applications must remain beneficial to all and avoid breaching the individual's data protection. This short communication paper first introduces ICT applications during the COVID-19 before providing an overview and further analysis of the situation of the ICT applications. Afterward, it discusses issues of data privacy, data collection, and data use, which are the backbone of ICT applications. The discussions highlight that future research in this area could look into associated issues related to digital privacy, data-driven approaches, and data protection regulations.

CRNet: a multimodal deep convolutional neural network for customer revisit prediction

Since mobile food delivery services have become one of the essential issues for the restaurant industry, predicting customer revisits is highlighted as one of the significant academic and research topics. Considering that the use of multimodal datasets has gained notable attention from several scholars to address multiple industrial issues in our society, we introduce CRNet, a multimodal deep convolutional neural network for predicting customer revisits. We evaluated our approach using two datasets [a customer repurchase dataset (CRD) and mobile food delivery revisit dataset (MFDRD)] and two state-of-the-art multimodal deep learning models. The results showed that CRNet obtained accuracies and Fi-Scores of 0.9575 (CRD) and 0.9436 (MFDRD) and 0.9730 (CRD) and 0.9509 (MFDRD), respectively, thus achieving higher performance levels than current state-of-the-art multimodal frameworks (accuracy: 0.7417-0.9012; F1-Score: 0.7461-0.9378). Future research should aim to address other resources that can enhance the proposed framework (e.g., metadata information).

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40537-022-00674-4.

A Thematic Review on Using Food Delivery Services during the Pandemic: Insights for the Post-COVID-19 Era

The food delivery service is the most typical and visible example of online-to-offline (O2O) commerce. More consumers are using food delivery services for various reasons during the COVID-19 pandemic, making this business model viral worldwide. In the post-pandemic era, offering food delivery services will become the new normal for restaurants. Although a growing number of publications have focused on consumer behavior in this issue, no review paper has addressed current research and industry trends. Thus, this paper aims to review the literature published from 2020 to the present (October 2022) on consumers' use of food delivery services during the pandemic. A thematic review was conducted, with 40 articles searched from Scopus and Web of Science being included. Quantitative findings showed current research trends, and thematic analyses formed eight themes of factors influencing consumer behavior: (1) technical and utilitarian factors, (2) system-related attributes, (3) emotional and hedonic factors, (4) individual characteristics, (5) service quality, (6) risk-related factors, (7) social factors, and (8) food-related attributes. The paper also emphasizes COVID-19-related influences and suggests promising future research directions. The results offer insights into industry practices and starting points for future research.

COVID or VOID: A systematic literature review of technology adoption and acceptance in hospitality and tourism since the breakout of COVID-19

The purpose of this study was twofold. The first goal was to review and synthesize research pertaining to ‘technology acceptance and COVID-19’ from the years 2020, 2021, and early August 2022 in the realm of hospitality and tourism. The second goal was to dwell on the relevant technology adoption studies in order to provide a critical analysis and extract insights for future research theoretically and practically. A systematic literature review was performed. Findings indicate that some constructs were not properly used like perceived enjoyment and some constructs were overlooked like perceived interaction. Additionally, besides technology features, the characteristics of consumers need to be investigated to reveal the true underpinnings of the technology adoption behavioral process. However, inquiries regarding consumers’ traits need to be expanded beyond basic demographics (e.g. age and gender). The paper systematically garnered technology acceptance research from the COVID-19 era in order to provide insights for future research directions in the post-COVID era. This work identified a lack of consensus over the theoretical underpinnings of technology acceptance research among tourism hospitality researchers. The study revealed the narrow research lenses focusing on particular empirical domains, mainly hotels, restaurants, and museums, and overlooking other contexts (e.g. airports, stations, within-city transportation, and events).

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

Antecedents and consequences of healthiness in café service: Moderating effect of health concern

This study aims to examine the antecedents of consequences of healthiness in the café business context. Additionally, this study attests to the moderating effect of one's concern for health (health concern) between healthiness and attitude. To attain a more vivid response, this research selected Starbucks coffeehouse as a case study. Hygiene, healthiness, and nutritional disclosure are the determinants of healthiness in the café business area. The consequences of healthiness are attitude and purchase intention for café products. Health concern is the moderating variable between healthiness and attitude in the context of café businesses. In order to test the association between attributes, a survey was used. Amazon Mechanical Turk was chosen to recruit survey participants. The valid observation for data analysis was 455 participants. For hypothesis testing, a structural equation model was implemented. Regarding the results, health concern is positively influenced by hygiene and organicness, but healthiness is negatively affected by nutritional disclosure. Moreover, it was found that health concern significantly moderates the relationship between healthiness and attitude, and attitude exerts a positive effect on purchase intention.

Estimating the Impact of COVID-19 Pandemic on Customers’ Dining-Out Activities in South Korea

This study classified the types of dining-out activities into three categories: visiting restaurants, using delivery services, and using take-out services to understand how customers’ various dining-out activities were carried out during the COVID-19 pandemic. The study used the Theory of Planed Behavior (TPB) model to analyze the structural relationship between the main factors and three dining-out activities. An online survey method was used to distribute and collect survey link addresses through respondents’ SNS and e-mail and a data analysis was performed on the final 429(85.8%) effective samples. A paired t-test and structural equation modeling (SEM) were used to investigate customers’ dining-out activities. This study is of significant contribution in that it compared and analyzed customers’ various dining-out activities using the TPB model, laid the theoretical foundation for related research, and suggested ways to help related industry workers establish marketing strategies under the pandemic.

Drone Usage for Medicine and Vaccine Delivery during the COVID-19 Pandemic: Attitude of Health Care Workers in Rural Medical Centres

Rural areas are often difficult to access reliably with medicine and vaccines. This study aimed to examine rural health care workers’ attitude towards drone delivery for medicine and vaccines and the factors that influenced it. Health care workers from four rural health care facilities were sampled. Participants self-reported their demographic information, attitude towards medicine and vaccine delivery using drones, perception of benefits and risks of using drones, and perceived leadership innovativeness through an online or a pen-and-paper questionnaire. A total of 272 health care workers (mean age = 36.19, SD = 8.10) from all of the sites participated in this study. More than half of the study participants agreed or strongly agreed that using a drone to deliver medicine and vaccines is a good idea (54.2%, 95% CI [47.5, 60.8]), a wise idea (54.6%, 95% CI [47.9, 61.2]), and is desirable (52.5%, 95% CI [45.7, 59.0]). Males (β = 0.223), workers from the Obstetrics and Gynaecology department (β = 0.135), a lower perceived delivery risk (β = −0.237), and higher leadership innovativeness (β = 0.336) predicted positive attitudes towards drone usage. Assistant medical officers (β = −0.172) had a negative attitude. There is a need to further understand the roles of occupation and leadership innovativeness in predicting health care workers’ attitude towards drone usage, as these differences could be embedded within their roles in the health care system.

Drone routing problem model for last-mile delivery using the public transportation capacity as moving charging stations

The fast and cost-efficient delivery of goods ordered online is logistically a challenging problem. Many firms are looking for ways to cut delivery times and costs by exploring opportunities to take advantage of drone technology. Deploying drones as a promising technology is more efficient from both environmental and economic perspectives in last-mile delivery. This paper considers a last-mile delivery system in which a set of drones are operated in coordination with public transportation system to deliver a set of orders to customer locations. A mathematical model based on Vehicle routing Problem (VRP) is extended to solve this problem. A real-world case inspired by Bremen 2025 transportation paradigm is also developed to validate the developed mathematical formulation. Results show that the sequence of visiting customers and public transport stations highly impacts the remaining charge and efficiency of drone tour planning. Also, using public transport vehicles, which enables drones to charge their battery or to approach customers, can reduce the number of drones required for satisfying the demands in a service area. The results show that there are high potentials to save energy for drone-enabled last-mile delivery by using the public transportation network.

Optimal Model and Algorithm of Medical Materials Delivery Drone Routing Problem under Major Public Health Emergencies

To reduce distribution risk and improve the efficiency of medical materials delivery under major public health emergencies, this paper introduces a drone routing problem with time windows. A mixed-integer programming model is formulated considering contactless delivery, total travel time, and customer service time windows. Utilizing Dantzig–Wolfe decomposition, the proposed optimization model is converted into a path-based master problem and a pricing subproblem based on an elementary shortest path problem with resource constraints. We embed the pulse algorithm into a column generation framework to solve the proposed model. The effectiveness of the model and algorithm is verified by addressing different scales of Solomon datasets. A case study on COVID-19 illustrates the application of the proposed model and algorithm in practice. We also perform a sensitivity analysis on the drone capacity that may affect the total distribution time. The experimental results enrich the research related to vehicle routing problem models and algorithms under major public health emergencies and provide optimized relief distribution solutions for decision-makers of emergency logistics.

The fear of being infected and fired: Examining the dual job stressors of hospitality employees during COVID-19

As the COVID-19 pandemic has posed grave threats to the financial and physical health of hospitality employees, this research unveils details of the dilemma experienced by hospitality employees during the pandemic, namely, their fear of becoming infected and fired. The research data were derived from a sample of 622 hospitality employees in the U.S. and analyzed using PLS-SEM as a new model of COVID-19 stressors are proposed and tested. The findings show that hospitality employees perceive the pandemic as a traumatic event that elevates their perceived job insecurity and infectious risk. It was also found that both job insecurity and infectious risk lead to increased job stress and turnover intentions, while job insecurity alone is a stronger predictor of turnover intentions. This study is among the first to examine the antecedents and consequences of the dual stressors encountered by public-facing occupations, including hospitality, during the pandemic.

An Empirical Evaluation of Customers’ Adoption of Drone Food Delivery Services: An Extended Technology Acceptance Model

A single technological advancement in the business sector tremendously changed customers’ lifestyles and consumption behavior. Drone technology is one of the main revolutions that increase business efficiency at a lower cost. However, the acceptance of emerging technologies is not rapid in developing markets. Therefore, this study aims to evaluate customers’ adoption of drone technology in the context of food delivery services. This study has used an extended technology acceptance model (TAM) to assess customers’ behavior. Product processing innovativeness, information processing innovativeness, and subjective norms have been added as additional constructs into TAM. The data of 354 customers from five different cities of Pakistan have been collected and analyzed through partial least square structural equation modeling (PLS-SEM). The results of the study revealed that all proposed hypotheses, except the positive influence of perceived ease of use on perceived usefulness, were accepted. Further, the results depict that perceived usefulness, subjective norms, and attitude were the major predictors of customers’ adoption of drone food delivery services. In addition to this, customers’ word of mouth has a greater influence and reach than other forms of marketing communication. Therefore, practitioners and marketers may consider hosting competition programs to experiment with drone food delivery systems to enhance the acceptance of this technology among the masses.

Investigating the effects of the outbreak of COVID-19 on perishable food supply chains: an empirical study using PLS-SEM

Purpose

At the end of 2019, the first case of the Corona Virus Disease (COVID-19) was reported in Wuhan city of China. The disease was declared a pandemic without imagining the magnitude of damage currently caused in all branches of the economy. One of the most affected sectors was food and mostly perishable food (PF), which are more susceptible to environmental conditions. Thus, the research examines the effect of the COVID-19 outbreak on Ecuador's perishable food supply chains (PFSCs) during the pandemic. It contributes to new results on the special issue (SI) PFSC response to event risk and uncertainty, such as those that generated the pandemic.

Design/methodology/approach

The data used are from primary information sources, which were collected through a questionnaire. The questionnaire was applied to 298 companies belonging to the sector, and later the information was processed through partial least squares structural equation model. The convergent validity, discriminate and robustness tests provide arguments for the suitability of the model. Therefore, the findings are reliable and valid for the adequate measures to improve the PFSC due to a COVID-19 outbreak.

Findings

The results show that the perception of personal risk (PPR) produced by COVID-19 has caused the companies of the PFSC to adopt preventive policies (PO) to avoid contagion and guarantee the operation of the companies. In addition, the PPR has been responsible for the alterations in the demand and price (DP) of PF. Next, PO and DP have a significant effect on PFSC, which shows the evidence favouring the malfunction of PFSC operations due to anti-contagion PO, the mismatch of DP. On the contrary, circular economy practices contribute to the excellent performance of the PFSC. Finally, the research suggests some policy implications to consider in improving the PFSC.

Originality/value

This study is the first to be carried out in Ecuador's country on the PFSC; its contribution is unprecedented and makes it a road-map to be considered to guarantee the correct functioning of the PFSCs, and it will provide policymakers with valid elements to design efficient PFSCs that better respond to unforeseen events and uncertainties. Future research will focus on analysing the management of PF consumption in Ecuador during the pandemic.

A review of early COVID-19 research in tourism: Launching the Annals of Tourism Research's Curated Collection on coronavirus and tourism

The COVID-19 pandemic has brought unparalleled impacts to the global tourism industry, thus inspiring a wave of academic research. This paper presents a review of the early literature on COVID-19 and tourism, representing 249 papers. The analysis revealed five key themes: (1) psychological effects and behavior; (2) responses, strategies, and resilience; (3) sustainable futures; (4) impact monitoring, valuation, and forecasting; and (5) technology adoption. However, this research also raises questions about theoretical contribution, methodologies, and future research potential. This article also launches the Annals of Tourism Research's Curated Collection on coronavirus and tourism. The Collection contains all past articles published in Annals of Tourism Research on the topic and will continue to grow as new articles are added.

Examining Image Congruence and Its Consequences in the Context of Robotic Coffee Shops

This study aimed to find the role of image congruence in the context of robotic coffee shops. More specifically, this study proposed that three types of image congruence including actual self-image congruence, ideal self-image congruence, and social self-image congruence aid to increase brand attitude. In addition, it was proposed that brand attitude positively affects brand attachment and brand loyalty. For this, this study collected data from 325 customers who used robotic coffee shops. The data analysis results indicated that the three types of image congruence have a positive influence on brand attitude. In addition, brand attitude was found to be an important factor affecting brand attachment and brand loyalty.

Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic

With the emerging popularity of online food delivery (OFD) services, this research examined predictors affecting customer intention to use OFD services amid the Coronavirus disease (COVID-19) pandemic. Specifically, Study 1 examined the moderating effect of the pandemic on the relationship between six predictors (perceived usefulness, perceived ease of use, price saving benefit, time saving benefit, food safety risk perception, and trust) and OFD usage intention, and Study 2 extended the model by adding customer perceptions of COVID-19 (perceived severity and vulnerability) during the pandemic. Study 1 showed that all of the predictors except food safety risk perception significantly affected OFD usage intention, but no moderation effect of COVID-19 was found. In Study 2, while perceived severity and vulnerability had no significant impact on OFD usage intention, the altered effects of socio-demographic variables during the COVID-19 pandemic were found. Theoretical and managerial implications are provided.

The impact of hotel attributes, well-being perception, and attitudes on brand loyalty: Examining the moderating role of COVID-19 pandemic

This research sought to investigate the relationships between hotel attributes, well-being perceptions, attitudes, and brand loyalty in the hotel context considering the COVID-19 pandemic. The results of the study's data analyses revealed how tangible and intangible hotel attributes improved individuals' well-being perceptions before and during the COVID-19, as well as how these perceptions in turn influenced cognitive attitudes, affective attitudes, and brand loyalty during these periods. Furthermore, the moderating role of COVID-19 was identified in the link between well-being perceptions and cognitive attitudes and in the association between cognitive attitudes and affective attitudes. In light of these findings, a discussion and insightful implications for both theory and practice were provided. Finally, the limitations of the study and future research directions were addressed.

Technological Innovation and Circular Economy Practices: Business Strategies to Mitigate the Effects of COVID-19

The Corona Virus Disease 2019 (COVID-19) has been a tough test on companies in the global food sector supply chain, exacerbating the realities and deficiencies it presents in developing economies. This situation has been reflected in the firm’s performance (F.P.) due to the lack of business conditions to respond to the current pandemic. However, in some companies, the adverse effects of COVID-19 have been counteracted due to endowment and technological capabilities. Thus, this study examined the role of technological innovation (T.I.) and business data analytics (B.D.A.) in the F.P. of foods in Ecuador during COVID-19. A questionnaire collected the information from the food firms. Then, Covariance-Based Structural Equation Modeling processed the collected information. We found that (B.D.A.) mechanisms and different levels of T.I. within the developing market significantly shape the F.P. The results showed that the B.D.A. enables circular economy (C.E.) practices and the improvement of product delivery services, which constitutes an improvement of the F.P. The COVID-19 outbreak did not significantly affect T.I., unlike what happened with B.D.A. This study concluded that firms with the most extraordinary technological production processes have been the least affected during COVID-19. This study suggested that policy measures should boost food firms’ technological endowment to improve their resilience in uncertainty and risk scenarios.

Opportunities of Artificial Intelligence and Machine Learning in the Food Industry

The food processing and handling industry is the most significant business among the various manufacturing industries in the entire world that subsidize the highest employability. The human workforce plays an essential role in the smooth execution of the production and packaging of food products. Due to the involvement of humans, the food industries are failing to maintain the demand-supply chain and also lacking in food safety. To overcome these issues of food industries, industrial automation is the best possible solution. Automation is completely based on artificial intelligence (AI) or machine learning (ML) or deep learning (DL) algorithms. By using the AI-based system, food production and delivery processes can be efficiently handled and also enhance the operational competence. This article is going to explain the AI applications in the food industry which recommends a huge amount of capital saving with maximizing resource utilization by reducing human error. Artificial intelligence with data science can improve the quality of restaurants, cafes, online delivery food chains, hotels, and food outlets by increasing production utilizing different fitting algorithms for sales prediction. AI could significantly improve packaging, increasing shelf life, a combination of the menu by using AI algorithms, and food safety by making a more transparent supply chain management system. With the help of AI and ML, the future of food industries is completely based on smart farming, robotic farming, and drones.

COVID-19: breaking down a global health crisis

Coronavirus disease 2019 (COVID-19) is the second pandemic of the twenty-first century, with over one-hundred million infections and over two million deaths to date. It is a novel strain from the Coronaviridae family, named Severe Acute Respiratory Distress Syndrome Coronavirus-2 (SARS-CoV-2); the 7th known member of the coronavirus family to cause disease in humans, notably following the Middle East Respiratory syndrome (MERS), and Severe Acute Respiratory Distress Syndrome (SARS). The most characteristic feature of this single-stranded RNA molecule includes the spike glycoprotein on its surface. Most patients with COVID-19, of which the elderly and immunocompromised are most at risk, complain of flu-like symptoms, including dry cough and headache. The most common complications include pneumonia, acute respiratory distress syndrome, septic shock, and cardiovascular manifestations. Transmission of SARS-CoV-2 is mainly via respiratory droplets, either directly from the air when an infected patient coughs or sneezes, or in the form of fomites on surfaces. Maintaining hand-hygiene, social distancing, and personal protective equipment (i.e., masks) remain the most effective precautions. Patient management includes supportive care and anticoagulative measures, with a focus on maintaining respiratory function. Therapy with dexamethasone, remdesivir, and tocilizumab appear to be most promising to date, with hydroxychloroquine, lopinavir, ritonavir, and interferons falling out of favour. Additionally, accelerated vaccination efforts have taken place internationally, with several promising vaccinations being mass deployed. In response to the COVID-19 pandemic, countries and stakeholders have taken varying precautions to combat and contain the spread of the virus and dampen its collateral economic damage. This review paper aims to synthesize the impact of the virus on a global, micro to macro scale.

The Changing Patterns of Consumers' Behavior in China: A Comparison during and after the COVID-19 Pandemic

This paper has an opportunity to collect questionnaire-based data regarding respondents' life choices in China at the peak of COVID-19 outbreak (i.e., around 9-11 March 2020) and in a relatively stable period where the national pandemic was over and the lockdown policy was halted (i.e., around 25-30 March 2020). Comparing respondents' answers about their most fundamental aspects of life during and after the pandemic, including income level, expenditure structure and level, purchase method, study method, food price and quality, and dining habit, both the descriptive and econometric models reveal that Chinese consumers' life patterns were not significantly changed. These findings may imply a "new normal" where consumers stick to their new living habits that were forged during the pandemic. Therefore, policy makers have to envisage such an implicative socio-economic change (cost) brought by the implementation of a lock down policy in a long run, in addition to direct and explicit economic losses. However, improving food quality and controlling food price appear to be the strong and stable safety signals to reassure consumers in this complicated environment.