COVID-19 affected the food behavior of different age groups in Chinese households

The COVID-19 pandemic brought profound changes to all corners of society and affected people in every aspect of their lives. This survey-based study investigated how household food related matters such as food sourcing and consumption behaviors of 2,126 Chinese consumers in different age groups changed approximately two months into the COVID-19 quarantine. A new food sourcing mechanism, community-based online group grocery-ordering (CoGGO), was widely adopted by households, particularly among the youngest group studied (18–24 years of age). The same group showed a higher confidence in the food supply system during the quarantine and a greater propensity for weight gain while staying-at-home. The more mature age group (≥35 years of age) showed heightened vigilance and awareness, with fewer grocery-shopping trips, a higher tendency for purchasing extra food, and less tendency to waste food. Survey findings of the new food-sourcing mechanism, attitudes to food, and changes in behavior among different age groups provide valuable insights to guide policies and management interventions to address matters pertaining to food supply and distribution, food access and household food security, and food waste reduction.

Spatial Dimension of Transport Exclusion Related to Statutory Trade Restriction—The Use of ITS Tools in Studies of Sustainable Urban Development

The problem of statutory restrictions of the freedom to conduct business activities is a subject addressed by many researchers. On the other hand, there is little research into the spatial aspect of this phenomenon and its impact on the quality of life of the inhabitants of urban centres in terms of their exclusion from one of the key motivations for travelling, namely shopping trips. The main purpose of the article is to determine the impact of the introduction of a statutory restriction on Sunday trading on sustainable urban development in terms of identifying areas excluded from free access to such services within a large urban settlement in Poland. Our studies on accessibility by car utilised data from ITS systems, the assumptions of the probabilistic Huff Model, and methods to determine market catchment areas. The data used in the study were based on the results of a questionnaire survey. The research procedure was conducted for eight scenarios that covered two periods (March 2019 and November 2020) on trading and non-trading Sundays. The conducted research shows that changes in the temporal accessibility of grocery shops in Łódź within the analysed periods are noticeable for trading and non-trading Sundays. In both cases, accessibility by private car is decidedly worse on non-trading Sundays. Transport exclusion from accessibility to grocery shops applies, in particular, to residents of peripheral areas of the city and is further compounded by the statutory Sunday retail restrictions implemented nationwide.

How COVID-19 Pandemic Affected Urban Trips? Structural Interpretive Model of Online Shopping and Passengers Trips during the Pandemic

Changing people’s shopping behavior from face-to-face to online shopping during the COVID-19 pandemic led to reduced shopping trips, and this decrease directly affects traffic congestion and air pollution. Identifying the factors influencing the increase of online shopping behavior during the pandemic can be helpful for policymakers in the post-COVID-19 era. This study aims to discover the effect of factors related to the COVID-19 pandemic and demographic characteristics on shopping attitude and, consequently, on shopping trips. Based on the interviews of ten experts, factors associated with COVID-19 and demographic characteristics are selected as influential factors on shopping attitude and shopping trips. For pairwise comparisons between these factors, a web-based questionnaire was designed and given to thirty experts. The relationship between all factors is examined using interpretive structural modeling (ISM) and Microscopic–Macroscopic (MICMAC) analysis. In addition, to prioritize factors, the IAHP model is employed. Based on the results, five levels of influential factors affect shopping attitude, which affects shopping trips: level 1, age and gender; level 2, income and education; level 3, the household size and the COVID-19 awareness; level 4, COVID-19 attitude and COVID-19 practice; and level 5, norm subject and shopping personal control.

Consumption Inequality and the Frequency of Purchases

We document a decline in the frequency of shopping trips in the United States since 1980 and consider its implications for the measurement of consumption inequality. A decline in shopping frequency as households stock up on storable goods (i.e., inventory behavior) will lead to a rise in expenditure inequality when the latter is measured at high frequency, even when underlying consumption inequality is unchanged. We find that most of the recently documented rise in expenditure inequality in the United States since the 1980s can be accounted for by this phenomenon. Using detailed micro data on spending, which we link to data on club/warehouse store openings, we directly attribute much of the reduced frequency of shopping trips to the rise in club/warehouse stores. (JEL D12, D31, D63, D91, E21)

The Interaction between E-Shopping and Shopping Trips: An Analysis with 2017 NHTS

Advances in information and communication technologies (ICT) have dramatically changed the nature of shopping and the way people travel. As this technology becomes deeply rooted in people’s lives, understanding the interplay between this way and personal travel is becoming increasingly important for planners. Using travel diary data from the 2017 National Household Travel Survey (NHTS) data for structural equation modeling (SEM) analysis, it revealed the interaction between e-shopping and shopping trips and the factors that affect this bidirectional relationship. Results show that e-shopping motivates shopping trips, and in-store shopping inhibits online shopping. It can be obtained that the increase of one standard deviation of e-shopping will increase the shopping trip by 0.17 standard deviation. When shopping trips increase by one standard deviation, e-shopping behavior also decreases by 0.12 standard deviation. The results also demonstrated that e-shopping and shopping travel behavior is heterogeneous across a variety of exogenous factors such as personal attributes, household characteristics, geography, travel distance/duration, and travel mode. Identifying the interaction may help formulate better transportation policies and lay the foundation for travel demand management strategies to reduce the stress on the transportation system and meet individual travel needs.

The Magnitude and Determinants of Partial Redemptions of Food Benefits in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC)

Purpose: WIC provides food assistance to low-income pregnant and postpartum women, infants, and children ages 1- 4. A partial redemption (PR) occurs when a participant redeems only a portion of the prescribed benefit, thereby not obtaining the full nutritional benefit. We study the magnitude and determinants of PRs using electronic benefit transfer data. Design/Setting: Statistical analysis of all WIC transactions from Feb 2016 to Nov 2018. Subjects: Oklahoma WIC participants. Measures: The probability of a WIC household fully redeeming a food category. A random effects probit model is used to study determinants of PRs. Analysis: Estimate the marginal effects of key variables on households’ likelihood of full redemption: location—urban/rural, number of members in WIC, duration in the program, number of shopping trips, shopping venue, and prescribed foods. Results: Overall 18.5% of $ value of benefits are unredeemed, 29.3% excluding formula. Some foods have PRs > 40%. Only 17.3% of households fully redeem benefits in a given month. PRs increase with number of household members in WIC and duration of participation. PRs are lower for participants in rural locations, who shop more frequently, and who shop at WIC-specialized stores. Conclusions: Food packages with high PRs fail to impart prescribed benefits. Results pinpoint products and household characteristics associated with PRs, enabling targeted nutritional counseling and suggest food package choices need to be made with participant acceptance in mind.

Modeling Individualized Sustainable Last Mile Logistics

The online grocery trade has received an additional boost from the Covid pandemic. The delivery of such purchases places particular demands on last mile logistics since consumers demand more and more individualized delivery options, e.g., regarding the delivery arrival or the type of transport. At the same time, many consumers are becoming more environmentally conscious, so there is a need to examine further how this particular consumer behavior affects the sustainability of deliveries. This paper develops and presents a simulation model, which considers grocery delivery under different framework conditions. The examined scenarios show that a change in consumer behavior directly impacts last mile logistics systems, mainly by increasing the total number of orders and a slight reduction in emissions through improved vehicle utilization. Nevertheless, the results show that without sufficiently high utilization of delivery vehicles, shopping trips by private car may cause fewer emissions.

Qualitative Study on Factors Influencing Aging Population’s Online Grocery Shopping and Mode Choice When Grocery Shopping in Person

Given that older adults are prone to car cessation, they may also be at risk of food insecurity. Online shopping has the potential to become a key solution to this growing social issue. The objective of this study was to understand how mode use relates to food shopping patterns, and what specifically motivates older adults to choose certain travel modes for grocery shopping or to shop online. Sixty-one retired individuals were interviewed in Montreal, Canada. Participants were first asked to discuss their food shopping habits and the modes they used to purchase food. Then, participants were asked open-ended questions about beliefs from the theory of planned behavior. Participants listed advantages/disadvantages, people who approve/disapprove, and facilitating factors/barriers related to travel modes and online grocery shopping. Most participants never used online grocery shopping. Results revealed similarities in shopping styles between car drivers and online shoppers. Both were organized (prepared lists), shopped in bulk, and went on regularly timed shopping trips. Public transit (PT) and active mode users were spontaneous and irregular shoppers who viewed in-person shopping as physical and social activity opportunities. Grocery shopping using these modes could be made easier for some participants if shops offered home delivery after in-store purchases. Car drivers were more likely to adopt online services than PT or active mode users who preferred delivery after in-person shopping to reduce obstacles linked to these modes. In order for online grocery shopping to be integrated as part of one’s established habits, both travel habits and grocery shopping habits must be observed jointly.

Using betweenness metrics to investigate the geographical distribution of retailers

In retailing, a location’s accessibility and attractiveness depends on the spatial distribution of other stores and consumers. In particular, the literature shows that a place is more attractive for retailers if the generic routes taken by consumers often cross it. However, previous studies failed to consider that there are at least two possible consumer routes: job commutes from residential to workplaces and shopping trips among stores. In this paper, we analyze the impact of both consumer routes on the commercial patterns in Turin. The paper demonstrates that daily commutes to workplaces do not benefit a retailer along the trip, as much as journeys for shopping purposes do. In particular, we show that the benefits that a store can have when localized on the routes depend on the kind of goods it sells. Finally, the paper shows that stores selling homogeneous products and stores selling differentiated goods subject to comparison can differently benefit from being located in population hotspots and in commercial areas.