Online Grocery Research Articles

SNAP online purchasing and the healthfulness of food purchases

AbstractThis paper investigates the effects of the SNAP Online Purchasing Pilot expansion (SNAP OPP) on SNAP households' online grocery shopping behaviors and the healthfulness of their food‐at‐home purchases. We explore quasi‐experimental estimates of the impact of online purchasing by leveraging a unique natural experiment: the staggered introduction of the SNAP OPP across US states. The analysis combines data on household food‐at‐home purchases around the time of the policy expansion with a dynamic difference‐in‐differences empirical strategy. The results indicate that the SNAP OPP increased the frequency of online grocery shopping, associated spending, and the healthfulness of food‐at‐home purchases among SNAP households.

Elderly Consumers’ Online Grocery Shopping Continuance After COVID-19: A Combined Importance-Performance Map Analysis (cIPMA) Method

As the global population ages, China—home to the world’s largest ageing population—experienced a notable surge in online grocery shopping (OGS) among the elderly during the COVID-19 pandemic. However, concerns remain about whether this trend will persist post-pandemic and what strategies could sustain this market. Based on 284 responses analysed using PLS-SEM, our findings reveal that consumer trust, return policy leniency, performance expectancy, imitating others, and effort expectancy positively influence the intention to continue purchasing groceries online. In contrast, facilitating conditions do not significantly impact continuance intention, while social influence is marginally insignificant. Fear of COVID-19 negatively affects the intention to continue. We propose that signalling theory offers stronger explanatory power than UTAUT and herding behaviour in predicting elderly consumers’ OGS continuance intention. Building trust through user-friendly, straightforward platforms and flexible return policies may be an effective strategy to motivate and sustain elderly consumers’ long-term engagement with OGS platforms.

“From expectations to frustrations”: Dissecting negative experiences to understand negative word-of-mouth in online grocery services

“From expectations to frustrations”: Dissecting negative experiences to understand negative word-of-mouth in online grocery services

Understanding Heterogeneity in Intended Frequency of Online Grocery Shopping Across Life Stages and Lifestyle

Understanding Heterogeneity in Intended Frequency of Online Grocery Shopping Across Life Stages and Lifestyle

Differences in Digital Health Use of Rural-Urban Medicare Beneficiaries.

Digital health inequities appear to exist between rural-urban older adults, a problem exacerbated by the COVID-19 pandemic. This study investigated the differences in digital health use (DHU) between rural-urban Medicare beneficiaries using the 2021 National Health and Aging Trends Study. Led by the Senior Technology Acceptance Model, separate multiple linear regression models examined the relationship between DHU, social determinants, and technology readiness by residence. The results showed that Black urban older adults were more likely to engage in DHU than their White counterparts, and men across both samples were more likely to partake in DHU than women. Tablet access best predicted rural DHU, whereas computer access best predicted urban DHU. Online grocery shopping was the most significant technology experience for rural residents, whereas online banking led for urban residents. Nurses and other health professionals can introduce digital health applications in clinic or at bedside to build older adults' technology experience. To improve digital health equity, the policies and implementation of digital interventions should consider locality, device ownership, and user interface familiarity of Medicare beneficiaries.

The Role of Smart Stores in Transforming the Traditional Retail Industry

This paper provides a review of the digital revolution of grocery shopping, with emphasis on the technological advancements that have reshaped consumer experiences in the last decades. Analyzing academic studies and current data from websites, the research offers a review of the development of grocery shopping from ancient times to new, technology-based methods. The review classifies advancements into two major categories: in-store and online grocery shopping. In-store shopping has evolved from conventional interactions to the use of self-service checkouts, scanners in hands, mobile applications, and artificial intelligence-based solutions such as augmented reality and face recognition. This paper overviews the first area, which is in-store technological solutions. This research focuses on emphasizing the grocery shopping revolution from a technological point of view, showcasing the most notable digital achievements, and describing the potential of future development in the field. Key Words: grocery,food,shopping,AI, online shopping.

Amplification or Mitigation? The Role of Online Grocery Shopping in the Relationship Between Food Environment and the Healthfulness of Food Purchases

ABSTRACTThis paper investigates the role of online grocery shopping in shaping the relationship between the food environment and household food choices, with a focus on disadvantaged groups. We employ fixed‐effect models with instrumental variables using consumer data from 2015 to 2019. We find that online grocery services may exacerbate nutrition inequality associated with food environment disparities. While a higher density of food stores enhances the healthfulness of food purchases among online grocery shoppers, it has no impact on those who do not use online grocery shopping. However, a higher density of convenience stores negatively impacts food healthfulness for nononline grocery shoppers, while having no significant effect on adopters. Moreover, the adoption of online grocery shopping affects food purchases differently depending on the local food environment: it tends to reduce the healthfulness of food purchase in less favorable food environments but improves it in more favorable ones.

Store fulfillment with autonomous mobile robots and in-store customers

Omnichannel services, such as buy-online-pickup-in-store, curbside pickup, and ship-from-store, have shifted the order-picking tasks previously completed by in-store customers doing their shopping to the retailer’s responsibility. To fulfill these orders, many retailers have deployed a store fulfillment strategy, where online orders are picked from brick-and-mortar retail store shelves. We focus on the design of operations inside a store where in-store customers collaborate with autonomous mobile robots (AMRs) to pick up online orders. Due to the uncertainty of in-store customers’ availability and their willingness to participate, the problem of synchronizing in-store customers with AMRs is highly stochastic. Thus, we model the stochastic order-picking problem with uncertain synchronization times of in-store customers and AMRs as a Markov Decision Process to determine how a retailer should dynamically assign tasks to a set of AMRs and dedicated pickers. We develop a heuristic solution framework that generates a set of initial assignments and routes for heterogeneous picking resources and dynamically updates them as the actual synchronization times between AMRs and in-store customers unfold. We analyze multiple strategies to generate the initial set of task assignments and routes as well as update such decisions based on the system state. To guide on whether the proposed approach is economically and operationally viable, we conduct extensive computational experiments using actual online grocery orders and empirical shopping behavior data. We illustrate the feasibility of such a policy to achieve similar picking performance as the status quo and through an economic analysis show that deploying dedicated pickers and AMRs aided by in-store customers in a store environment are economically viable.

Using a human-centered design framework and behavioral economic interventions to increase fruit and vegetable purchases in an online grocery store: Study design and methodologies.

Using a human-centered design framework and behavioral economic interventions to increase fruit and vegetable purchases in an online grocery store: Study design and methodologies.

Novel Approaches to Analyze Consumer Behavior and Policies to Promote Sustainable Consumption

ABSTRACTTechnological advancements, such as online grocery shopping, have significantly transformed consumer retail environments and experiences. Effectively studying consumer behavior in these new environments requires the use of novel methodological approaches, which will also aid in developing interventions to encourage sustainable consumption. This paper begins by providing an overview of the current literature on novel approaches to analyzing consumer behavior, then provides an empirical application by examining consumer decision‐making pathways within an online grocery shopping platform. Specifically, the paper focuses on exploring the consumers' digital footprints, such as page visits, product additions and removals, and interactions with information labels to identify patterns and interests in consumer responses to healthy and sustainable consumption. Findings highlight the potential benefits of integrating consumer search tracking data with environmental design to facilitate informed and conscious food choices.

Prevalence of online food delivery platforms, meal kit delivery, and online grocery use in five countries: an analysis of survey data from the 2022 International Food Policy Study.

Online food retail use is rapidly increasing in popularity, and offers user-friendly apps, and new food delivery models, including online food delivery platforms, online grocery retailers, and online meal kit delivery. We aimed to: (1) quantify the prevalence of online food retail platform use by adults across Australia, Canada, Mexico, the United Kingdom and the United States, and to (2) assess the associations between sociodemographic and behavioural factors and use of online food retail platforms. A cross-sectional online survey was conducted with adults as part of the 2022 International Food Policy Survey (n = 19,877). We described the frequency of use and number of meals ordered using different online food retail and delivery platforms. Logistic regression models were fitted to assess associations between the use of online food retail and delivery platforms, and sociodemographic and behavioural factors (including age, sex, household composition, BMI, income adequacy, ethnicity, cooking skills, nutrition knowledge, and frequency of food preparation). Online ordering was more prevalent in Mexico (72%), and in the United States (62%) in comparison with Australia, Canada, or the United Kingdom (45-56%). Overall, across all countries, 58% of participants used online retail and delivery platforms, most commonly online orders from restaurants (36% of participants), online supermarkets (28%), online meal kits (14%), online only grocery stores (11%), and online convenience stores (11%). The odds of using online restaurants was significantly higher for men (OR: 1.23, 95% CI: 1.14-1.33) and participants aged 18-29 (compared to those 60 years or older) (OR: 6.10, 95% CI: 5.34-7.00). Participants aged 18-29 also had the highest odds of using online convenience stores (OR: 7.51, 95% CI: 5.71-9.88). Participants living with primary school aged children had higher odds of using online supermarkets compared to those without children (OR: 2.56, 95% CI: 2.22-2.94). A substantial proportion of people are buying food online. Efforts to improve population diets need to ensure that online food retail platforms support good health and nutrition.

Analytical Study of Factors Impacting Online Grocery Shopping by Urban Consumers through Mobile-Commerce using Structural Equation Modelling Approach

The online purchase of the products from different segments is capturing interest of the buyers. Mobile-Commerce with its intuitive user interface provide buyer more flexibility and personalized experience. The objective of this research is to understand the factors significantly impacting online grocery shopping using M-Commerce. The study is descriptive in nature based on the primary data of 123 respondents. The data collected was quantitative in nature based on various factors to examines the cognizance of internet and its adoption helps the buyers to make the right decision of buying the groceries online. The factors are analysed using Structural Equation Modelling. The findings of the study shows that there exists a strongest relationship between the Perceived Trust and buying behaviour since Perceived Trust to buying intention (β = 0.547, p < 0.01) and buying intention to buying decision (β = 0.501, p < 0.01) for purchase of groceries online, followed by Perceived Usefulness to buying intentions (β = 0.381, p < 0.01), Perceived Ease of Used to buying intentions (β = 0.291, p < 0.01). Also, it is seen that Perceived Ease of Use also have direct impact the buying decision (β = 178, p < 0.05).

Which Consumers Change Their Food Choices in Response to Carbon Footprint Labels? The Role of Political Ideology and Other Socio-Demographic Factors.

Background/Objectives: The effectiveness of eco-labels in encouraging more sustainable food choices varies across studies. We investigate whether consumers' characteristics may explain this heterogeneity in the context of carbon footprint labeling by studying the moderating role of sociodemographic factors (age, gender, ethnicity, occupation), socioeconomic status (education and subjective socioeconomic position), place of residence (rural to urban), and political ideology. Methods: We manipulated the proportion of carbon-labeled products in two incentive-compatible and pre-registered choice experiments. The first (n = 715) asked consumers to shop for instant meal products in an online grocery store containing a food category's complete product assortment. The second (n = 1233) forced consumers to make tradeoffs between product preferences and carbon emissions in two consecutive food choices for cut fruit products, one without and another with carbon labels. To capture potential lasting effects, we collected purchase intention data from the same respondents several months after the labeling exposure in both studies. Results: Across both studies, increasing the proportion of products with a carbon label led liberals and centrists to choose lower-emission foods but had minimal or no impact on conservatives (although it never backfired). None of the other individual characteristics moderated the effects of labeling after controlling for political ideology. However, a young age, a low subjective socioeconomic position, and an urban residence indirectly improved responsiveness to labeling by predicting a more liberal political ideology. The labeling effects observed for liberals persisted for four months but not longer. Conclusions: These findings demonstrate the critical moderating role of political ideology and provide actionable insights to improve the targeting and design of sustainability interventions.

A STUDY ON CONSUMER PERCEPTION AND LEVEL OF SATISFACTION ON ONLINE GROCERY MARKET SPECIAL REFERENCE TO ZEPTO

The online grocery market in India is experiencing exponential growth, driven by technological innovation and shifting consumer behavior. Zepto, a prominent player in the quick commerce segment, has gained attention with its unique 10-minute delivery promise. This study explores consumer perception and satisfaction with Zepto's services, aiming to understand the key factors that influence customer experience in this rapidly evolving sector. A structured questionnaire was administered to 103 respondents, and the data was analyzed using statistical tools such as simple percentage analysis, Chi-square test, and ANOVA. The study reveals varying levels of consumer awareness and satisfaction, highlighting both the strengths and challenges of Zepto's service model. Insights from this research are valuable for refining Zepto’s customer engagement strategies and enhancing its competitive positioning in the online grocery market.

Theoretical perspectives and conceptual framework for online grocery shopping: Adapting to environmental circumstances and influencing internal factors

Abstract In recent years, the availability of online grocery shopping (OGS) has increased globally. However, considerable uncertainty persists regarding its future development and associated economic challenges. OGS providers face a dual challenge: they must achieve sustained growth in an increasingly competitive market while ensuring long-term profitability. Consequently, some providers have been forced to downsize their workforce, exit specific markets, or undergo acquisitions by competitors. This research aims to reduce this uncertainty by offering theoretical perspectives and a conceptual framework that integrates both external and internal factors influencing OGS. Specifically, the framework accounts for environmental circumstances—comprising global, market-specific, and consumer-specific circumstances—as well as internal factors, such as strategic orientation and operational effectiveness. Applying this framework offers valuable insights for both academic research and industry practice. For scholars, it establishes a foundation for further investigation into OGS implementation. From a managerial perspective, the framework serves as a strategic tool for systematically adapting OGS to external conditions while optimizing internal operations to enhance its viability and success.

Farming Tools and Equipment Platform

Agriculture is the cornerstone of the Indian economy, contributing 17-18% to the country's GDP and supporting approximately 50% of the workforce. Rightly regarded as the backbone of the Indian economy, the agricultural sector remains one of the few areas where e-commerce has yet to make a significant impact. However, e- commerce solutions are emerging to address customer preferences and logistical challenges, driving online grocery sales globally, particularly among businesses and consumers

A Randomized Trial Using an Online Grocery Store to Evaluate a Multicomponent Digital Intervention to Improve Diet Quality.

Poor diet is a key contributor to rising rates of non-communicable diseases. This study tested the ability of an online grocery store that includes a multicomponent digital intervention identified through the Multiphase Optimization Strategy to improve the nutritional quality of shopper's purchases. A two-arm randomized controlled trial. A convenience sample of online grocery shoppers in Singapore who were the primary shoppers for their household were recruited via advertisements on Facebook and Instagram (n=328). Data were collected between January and October 2023. Participants were randomized into one of two versions of the online grocery store and asked to complete three weekly orders delivered to their homes. The arms were: (1) an online store with no intervention (Control); (2) the same online store with the multicomponent intervention, including (i) interpretive Front-of-Package nutrition labels, (ii) real-time feedback on the nutritional quality of the grocery cart, (iii) ordering of healthier products first, and (iv) offering healthier substitutes for shoppers' chosen products. The primary outcome was the weighted (by number of servings) average Nutri-Score (NS) points of the grocery cart. Secondary outcomes included the weighted average calories and select nutrients (sugar, sodium, total fat, and saturated fat) per serving. These outcomes were analysed using a linear mixed-effects model. The multicomponent intervention led to a statistically significant 4.06-point [95% CI: 3.06, 5.07] increase in the weighted average NS of the grocery cart relative to Control, which equates to improving the nutritional quality of the cart from NS grade C (30-37 points) to B (37.1-40 points). The positive intervention effects were sustained across the three shopping experiences. The multicomponent intervention improved the nutritional quality of online grocery carts over repeated orders, highlighting the potential of digital interventions to improve diet quality. This study is registered at www. gov NCT05537337.

What is online Supplemental Nutrition Assistance Program shopping worth? An implicit wage rate approach using meal-kit pricing and time-use data

Abstract In 2023 all Supplemental Nutrition Assistance Program (SNAP) participants were allowed to start grocery shopping online. This paper provides the first answer to the question: What is online shopping worth to the SNAP participant in dollars? Using meal-kit pricing and time-use data, an implicit wage rate and dollar value distribution are estimated for time saved in home food production from online grocery shopping. We report the 95th, 75th, 50th, 25th, and 5th percentile results. We simulate saving 50%, 75%, and 90% of grocery shopping time and estimate the savings per hour per meal. For example, if online shopping saved 75% of shopping time, the median saving per hour per meal would be $2.59. If a family of four made 15 to 30 meals a month, this corresponds to an implicit 5% to 11% increase in the benefits per month due to the time saved. The implicit wage rate provides simple and elegant economic insights into many aspects of food production and consumption not obtainable by just considering the money price.

Why do consumers continue with e-grocery shopping? The role of motivations and environmental concerns in shaping behaviour

PurposeThis study investigates the impact of psychological perception on environmental pollution from over-packaging on consumer behaviours in the online grocery retail market.Design/methodology/approachThis study uses a quantitative survey to assess the impact of shopping motivations on satisfaction and behaviours in online grocery retailing, while also examining the moderating effects of psychological perceptions of environmental pollution (environmental consciousness, regret and eco-guilt).FindingsResults indicate that online grocery shopping motivations (informative, convenience and excitement) influence consumer satisfaction, which in turn enhances recommendation and repurchase intentions. Furthermore, environmental consciousness, regret and eco-guilt slightly moderate the relationship between various shopping motives and consumer satisfaction.Originality/valueThis study contributes to the understanding of how environmental considerations influence online shopping behaviour. It highlights the potential for psychological perception regarding over-packaging to drive changes in consumer behaviour.

Impact of AI on Consumers’ Purchase Intention Towards Online Grocery Shopping in India

In recent years, the rapid advancement of technology, specifically in Artificial Intelligence (AI), has considerably impacted consumer satisfaction in the e-retailing sector. The time-saving benefits and convenience of shopping in the comfort of their home with AI induce people to adopt digital technologies, reflecting a change in consumer behaviour. While existing studies have focused on examining TAM (technology acceptance model) components’ influence on technology acceptance, there is a lack of India-specific focus in studies and limited consideration of AI technologies like voice search or chatbots’ impact on purchase intention. This study extends the application of TAM components to the Indian online grocery sector. This study bridges a critical research gap by revealing the interplay between AI technologies and consumer behavior in India’s INR 760.2billion online grocery market. Using India’s grocery sector, the contribution of the study is in the recommendation of developing a technology-based consumer experience enhancement framework for online grocery platforms to effectively target consumers, particularly in regions with similar socio-economic characteristics. This study utilises the PLS-SEM (partial least squares structural equation modelling) model on 231 samples to analyse data and examine the impact of AI-driven technology on consumers’ online grocery shopping behaviour. PLS-SEM is instrumental in handling complex models with multiple constructs. This method is considered ideal for handling complex models with multiple constructs and primary research with smaller sample size. The application of this method also validated the conceptual framework by confirming strong construct reliability and validity. The analysis revealed that AI features like personalized recommendations, chatbots, and voice assistants improved the shopping experience by making it more efficient and easier. This enhanced user experience led to increased purchase intentions. This could be seen by the significant moderating role of AI technology and TAM components interaction on attitude towards AI.