Online Grocery Shopping: Exploring the Influence of Income, Internet Access, and Food Prices

Online Grocery Shopping: Exploring the Influence of Income, Internet Access, and Food Prices

1. Introduction

Interest in online grocery shopping has grown modestly for years; however, the COVID-19 pandemic led to an exponential increase in consumer interest [1,2]. Online grocery shopping refers to the purchase of groceries or food over the internet and then having these products delivered to consumer homes or these being picked up in a store or warehouse [1]. Academic literature on online grocery shopping has existed for decades. Influential studies in the field can be traced back to the late 1990s and early 2000s with studies on the type of people who bought groceries online [3,4], operations management in online grocery shopping [5,6], creating value in online grocery shopping [7], theoretical approaches for analyzing online grocery shopping behavior [8], and the success potential of online grocery shopping [9,10], among other things. Nevertheless, online grocery shopping was not always destined for success, in part because the perishable nature of food, particularly fresh foods, is fundamentally different from that of other types of products, such as clothing or electronics. According to Ring and Tigert [11], several early online grocery retailers failed due to the higher operating costs compared to brick-and-mortar grocery stores, the lack of profitability, and the small size of the target market at the time.
However, all this began to change in recent years as the operating costs of running online retail significantly dropped [12]. Also, COVID-19 and the restraints implemented to control the virus spread led to a significant boost in online grocery shopping [13,14]. Before the COVID-19 pandemic, studies showed an increasing but limited interest in online grocery shopping in several parts of the world. For example, a 2016 Nielsen study of 30,000 online consumers in 63 countries showed that only 9% of people in Europe and North America and 7% in Latin America, the Middle East, and Africa had ever purchased fresh groceries online [15]. Additional studies by Gallup [16] revealed that 81% of adults in the United States (US) never order groceries online, and 88% never order meal preparation kits with fresh foods online. Nevertheless, due to the restrictions imposed to contain the spread of COVID-19, 79% of shoppers in the US had ordered groceries online [17]. This growth is similar in other countries such as China [18] and in other parts of the world [1,2,19,20]. Research has revealed that the majority of consumers plan to continue online grocery shopping in the future, regardless of the COVID-19 pandemic circumstances [21]. For example, the data for 2022 show that the volume of online grocery shopping increased by 66% in Russia, while the number of orders increased by 75% [22].
Online grocery shopping has been envisaged as a business practice to promote sustainable development [23,24]. Online grocery shopping can become a potent tool to promote sustainable transportation and develop sustainable cities [25]. It is considered a potential solution to urban traffic congestion by consolidating several consumer shopping excursions into a solitary delivery route [26]. Prior research indicates that online grocery shopping may result in carbon dioxide and energy reductions ranging from 17 to 90 percent [25,27,28]. Sustainability practices may be enhanced by using a variety of last-mile delivery vehicles [29], including electric cars, tricycles, and bicycles [30,31]. Potentially, this might mitigate external impacts, including but not limited to traffic jamming, pollution, and land usage [32].
Furthermore, studies show that online grocery shopping can potentially ease the struggles of disadvantaged groups, such as the elderly community and people with mobility challenges [33]. Also, online grocery shopping has been championed as a way to overcome the structural barriers to food access faced by low-income families, who may live disproportionately far from physical grocery stores or lack personal vehicles to use to go shopping [34]. It can also promote healthy eating habits by limiting impulse buying unhealthy foods as a behavior, which is more prevalent in physical grocery shops [35]. Nevertheless, a crucial challenge of the premise of these studies is that the majority of the previous research, going back several decades, shows that it is wealthy people or people with higher levels of income—not low-income people—who disproportionately buy groceries online [1,3,4,36]. Moreover, in recent years, studies have begun to highlight the impact of the cost/price of food and internet connection on online grocery shopping behavior [37,38]. However, some recent studies have challenged the impact of these factors. For example, Frank and Peschel [39] stated that higher-income individuals were less likely to shop for groceries online. Zheng et al. [40] revealed that price does not increase the frequency of online grocery shopping. As a result of these studies, it can be stated that there is some inconsistency in the literature about the role of the aforementioned factors in online grocery shopping. Also, little is known about the impact of income, internet connection, and food prices on online grocery shopping at the regional, district, city, and country levels.
Nonetheless, studies show that online grocery shopping can be influenced by a range of other issues, including situational factors such as the presence of a baby in the family, the health of the consumer, distance to a physical shop, mobility challenges, and the working situation of the consumer [33,41,42]. Other influencers include social norms or subjective influence, time-saving, trust, price value, prior shopping experience, attitude, perceived usefulness, and perceived ease of use, among other things [2,20,39,43,44]. However, the impact of income, internet connection, and food prices are particularly important because they strike at the heart of the potential for online grocery shopping as a tool for addressing systemic food inequality. While the promise of online grocery shopping for low-income families remains undisputed, it is not exactly clear whether they can afford it. Disparities in vital facilitating conditions such as internet access remain very high for low-income families and communities [45,46], and in recent years, a growing body of literature suggests income might play a stronger role than earlier realized in people’s overall online shopping behavior [47,48,49].
Therefore, in this study, we aim to empirically investigate the relationship between online grocery shopping and income, internet connection, and the price of food. We developed a linear regression model using fixed effects, panel data on online grocery sales in 16 regions of Russia, and corresponding panel data on median income, mobile internet connection, and the food price index. We also examined whether food prices can moderate the impact of income. To the best of our knowledge, this paper represents one of few studies to examine the impact of income, internet connection, and food prices on online grocery shopping at the macro/meso level. While other studies have concentrated on the impact of these factors on individuals and households [1,36,37], our paper arguably provides a more definitive analysis of the topic by investigating regional data in regions with a combined population of over 44 million people. As such, this paper makes the following contributions. First, by examining the macro-level data, we provide robust evidence to guide the policy formulation process for Russia’s online grocery shopping. Second, we extend the debate on online grocery shopping by empirically demonstrating that income, internet access, and food prices not only pose a challenge for individuals and households but for regions as well. Third, we provide a reality check on the role of online grocery shopping in improving food access by showing that in spite of its potential, deep-rooted socio-economic challenges remain a problem even within online grocery shopping. The following sections present the literature review, methodology, results, discussion/conclusion, and limitations.

3. Materials and Methods

The Russian administrative system is divided into 8 main federal administrative districts (okrug), which are then subdivided into more than 80 subjects or constituent entities referred to as regions (oblasts), territories (krais), republics, federal cities, autonomous regions, and autonomous districts. These subjects are all constitutionally equal and will hereinafter be collectively referred to as regions in this paper. Due to the controversies surrounding certain regions in Russia and the fact that some of them are not internationally recognized, we chose to use a sample of all regions instead of the total number. We utilized a two-stage sampling strategy to decide on which regions to include in this study. The first stage consisted of a stratified sampling approach by dividing the pool of regions into eight strata following the official divisions of the federal administrative district. Then, we used a purposive sample to select two regions in each stratum, accounting for factors like population size, ethnic composition, level of urbanization, political structure, and level of development. The result was a final representative sample size of 16 regions covering the breadth of Russia and providing a diverse mix of ethnicities, sizes, and wealth. The list of included regions is provided in both Figure 1 and Table 1.
Figure 1 shows the regions included in the study sample. The regional data on online grocery shopping were retrieved from the analytics page of the Association of E-Commerce Companies of Russia [80] on 13 September 2023. AKIT uses arguably the most robust methodology for collecting e-commerce data in Russia. Their methodology includes analyzing the figures for e-commerce sales via electronic payment systems—including credit cards—which make up close to 90% of the overall payment methods for e-commerce in Russia. They also analyze sales data from companies and data from fiscal operators, among others. Furthermore, the data on Russian regions’ income level, food prices, and internet connection were retrieved from the Federal State Statistical Service—Rosstat [81]. Median income was chosen as the primary measure of income level because studies show that it provides a more accurate reflection of the actual incomes of people than other measures, such as per capita income, which has been criticized for failing to capture the living standards of people accurately [82,83,84].
In addition, data on the number of connected mobile devices per 1000 people—here-after referred to as mobile internet—were used to represent internet connection. Mobile internet was chosen ahead of fixed internet because Russian consumers overwhelmingly and almost exclusively order online groceries using their mobile phones [85]. Then, the food price index was used to analyze the impact of food prices. Since there are no data to provide a comparative tracking of food prices in online and brick-and-mortar stores, the role of food prices was to examine whether more/less people shop online when the price of food increases. Moreover, in Russia, grocery prices online are largely similar to those in shops because several brick-and-mortar supermarkets are also dominant in online grocery shopping, and they offer no specific discounts for ordering online [86].
All included data were longitudinal panel data covering a three-year period from 2019 to 2021, as presented in Table 1. The mean of the sample data was utilized for the three-year period of the study. The analysis covered a three-year period due to the available data at the time of analysis. While data on online grocery shopping were available from 2018 to 2022, the annual data on the independent variables only covered the period from 2019, and there were none for 2022. Furthermore, it was necessary to decide whether a random or fixed effect was appropriate for the regression. Fixed effect was chosen ahead of random effect for several reasons. First, fixed effect is recommended as the more robust approach to panel data structures such as ours [87,88,89,90,91]. Second, we also decided to use fixed effects after using one of the most popular methods to decide between fixed and random effects: the Hausman test (Table 2) [92,93]. Regional online grocery sales were taken as the dependent variable, while the median income, mobile internet, and the food price index were taken as the explanatory or independent variables. Furthermore, we examined whether the price of food can moderate the impact of median income on online grocery shopping. The results of our analysis are presented in the results section. Following this, a robustness test on the normality of the residuals was conducted using the Kolmogorov–Smirnov method [94].

5. Discussion and Conclusions

The use of online grocery shopping has been seen as a viable business strategy to ad-dress systematic inequities in food availability. It has also been envisaged to promote sustainable development as it can address urban traffic congestion [26] and reduce carbon dioxide and energy consumption [25,27,28], traffic jamming, and pollution [32].
The impact of income, internet connection, and food prices on online grocery shopping has been established in several prior studies [1,34,37,50]. However, prior research has largely examined the impact of these factors on online grocery shopping at the individual or household level [1,36,37]. Macro/meso-level analysis enables the observation of patterns and trends over a larger population scale in comparison to individual or household level analysis [110]. The utilization of macro/meso-level analysis empowers organizations to gain insights into customer behavior at a significant magnitude. Consequently, this paper contributes to the existing literature by being one of the few studies—to the best of our knowledge—to examine the impact of income, internet connection, and food prices at the macro/meso level. Therefore, the present study offered considerable evidence to inform the policy-making process for online grocery shopping through an analysis of the macro/meso-level data. Furthermore, the study provided empirical evidence that regions (not just individuals and households) are confronted with challenges related to income, internet availability, and food prices.
In this study, we examined 16 Russian regions with a combined population size of 44 million people and utilized panel data covering a period of three years. Following a fixed effects linear regression analysis, our results revealed that income has a statistically significant impact on the level of online grocery shopping in the examined regions with a β of approximately 0.86 (Table 5), whereas although internet connection and food prices showed a positive relationship (β = 0.0117; β = 0.0252), the relationship was not statistically significant. Overall, with an R-squared value of approximately 76%, our result demonstrates considerable significance.
The results of the current study suggest that a higher income positively correlates with online grocery sales. This is in alignment with those of several prior studies [1,36,40,51,59,61,62,63,64]. However, the majority of the prior research has focused on individual or household income, whereas the current research considered regional income. This suggests that a higher regional income is likely to lead to higher online grocery sales in Russia. This also underscores that Russian regions with a higher income are likely to lead in online grocery shopping sales, whereas regions with a lower income are likely to fall behind in online grocery sales. Therefore, policy-makers should pay attention to lower-income regions to encourage online grocery sales.
The current study found a positive but insignificant relationship between regional food prices and online grocery sales. Nevertheless, this result is consistent with the prior research [35,38,40,65,66,67]. It implies that affordability due to income level is a more potent influencer of online grocery shopping than the daily prices of food. This insignificant relationship suggests that although better food prices can encourage online grocery sales, other factors (like income) can be potentially more significant in influencing online grocery shopping. This implies that deep-seated socio-economic challenges continue to be an issue in the realm of online grocery shopping, notwithstanding the potential of technology to encourage online sales. Furthermore, due to the dominance of traditional brick-and-mortar companies like X5 Group and VkusVill in Russia’s online grocery shopping, the prices in shops and online are largely the same [71,72]. As a result, consumers in Russia do not obtain a price advantage by grocery shopping online.
Similarly, this study reported a positive but insignificant relationship between inter-net connection and online grocery sales. This can be explained by the relatively high penetration rate of internet access in Russia. As such, internet connection in Russia might not be a barrier as it once was. Also, a number of prior studies show that the main divide in internet access is largely between rural–urban and wealthy–poorer areas, not between regions/states [37]. Therefore, internet connection is a less significant factor in influencing online grocery sales in Russia.
Furthermore, the majority of previous studies in several parts of the world have revealed that lockdowns and health risks had a significant positive impact on online grocery shopping [1,2,21]. Similar to several previous studies, we found a substantial increase in the level of online shopping in Russia during the peak of the COVID-19 pandemic in 2020 and 2021 (Table 1 and Figure 2). This result is also supported by the prior research on online grocery sales in Russia [13,74,75,76,77].
In addition, a number of managerial and practical implications can be derived from our research. First, online grocery shopping can facilitate sustainable development; therefore, countries should formulate policies to encourage their people to buy online. Further, nations should make efforts to make people aware of the potential of online grocery shopping to promote sustainability practices. Second, since income retains a very significant impact on online grocery shopping, retailers must place the affordability of products at the core of attracting and retaining consumers. Previous studies have recommended promoting cost-saving options to increase grocery shopping online [12]. We suggest that these cost-saving strategies can include providing targeted discounts to people from lower-income households, such as those on the Supplemental Nutrition Assistance Program (SNAP) or those facing disproportionate inequality in accessing in-store grocery shops. However, simply offering these services is not enough. Managers should also communicate the price advantage of online grocery shopping in marketing campaigns, among other things.

The current research underscores the significant impact of income on influencing online grocery sales. Despite the potential influence of internet connection and food prices, income continues to be a substantial determinant in shaping online grocery sales. With this research, we hope to lead toward a consensus on the impact of income on online grocery shopping, not only among individuals or households but also among communities, cities, and regions. Furthermore, policy-makers in various nations should also address the socio-economic challenges that hinder the growth of online grocery shopping. This will facilitate the achievement of sustainable development in those nations by encouraging the use of online food shopping.

Limitations and Future Research

The findings and conclusions of this study should be considered exploratory. The findings of this study may not reinforce definitive conclusions to the research on online grocery shopping. However, this study provides a foundation/base for future studies to build upon.

This paper examines the absolute sale revenues of online shopping in regions and the regions’ median income, mobile internet connection, and food price index. The current study data only cover the period 2019–2021 as the most recent data available from the statistical agency Rosstat span up to 2021. This might not completely reflect the conditions of online grocery shopping in Russia at the present time. However, it provides a robust picture of the past and future trends in online grocery shopping in the country. Future research can also collect covering a longer timeframe. Additionally, future research may gather more current data to better depict the current state of online grocery shopping.

The current research does not include any analysis of individual interest in online grocery shopping. Quantitative analysis regarding the extent of public interest in online grocery shopping and the factors’ determining purchase was not conducted since such matters fall beyond the scope of the existing research. It also does not include the shopping frequency or the number of shoppers in online grocery stores. Therefore, the paper does not explain whether wealthy regions buy more expensive groceries online, which might not be entirely unique to online grocery shopping. This represents an interesting avenue for future research. As such, future studies can consider the impact of having a higher disposable income on online grocery shopping, the price differences in the average purchased products in regions with high and low median incomes, or the impact of population size on online grocery sales. Future research can also conduct a quantitative investigation into the level of public interest in online grocery shopping and the factors’ determining the purchase of products online. Further, the purpose of the food price index in this study was not to provide a comparative analysis between the prices of food in online stores and those in brick-and-mortar stores. Instead, the current study analysis chose to investigate whether changes in the general price of food can spur an overall increase/decrease in online grocery shopping. Consequently, future studies can consider looking into the influence of the cost of living and inflation on online grocery shopping.

Furthermore, since this paper is specifically focused on regional-level analysis, future studies can consider the impact of income in individual and country-level studies. This can enable an international comparative analysis at the country level and a deeper analysis of individual differences. Also, future studies can consider the impact of income across various product categories in online grocery shopping, such as fresh groceries, packaged food, beverages, pastries, or groceries with a longer shelf life. This might contribute to our understanding of customer behavior in buying groceries online across different product categories, hence enhancing the research findings. The impact of income on nutritional choices via online grocery shopping can also be examined in future research.

In addition, this study is limited to regions in a single country (Russia), whose social, cultural, and economic reality might be different from nations in other parts of the world. The results should be carefully interpreted to reflect this. Further research may involve collecting regional data from multiple nations to analyze the effects of the factors identified in this study on online grocery shopping. This will help to generalize the research findings. Future research can also investigate the level of interest in the population in online grocery shopping and the factors that determine the purchase of products online. Also, future studies can consider examining the rural–urban differences in the variables in this study. This can provide a better understanding of the influence of factors such as internet access and potentially facilitate the generalization of the present research findings.

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