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The purpose of this paper is to explore factors and their impacts influencing online grocery shopping intentions among customers in the post COVID-19 situation. Moreover, the study aims at evaluating the mediating roles of shopping habits during COVID-19 between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

Based on a review of the literature and collection of 401 useable valid responses, the study was conducted through structured questionnaires applying personal interview technique. The subsequent analysis was conducted through partial least squares structural equation modeling (PLS-SEM) using Smart PLS 3.3.3.

The study findings revealed that perceived usefulness, perceived ease of use and shopping habits during COVID-19 have a significant influence on post COVID-19 online grocery shopping intentions. Also, the study has uncovered that perceived usefulness and perceived ease of use significantly influence shopping habits during COVID-19 among customers. Furthermore, the current study has revealed that hopping habit during COVID-19 significantly mediates the relationship between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

The study findings have provided practical suggestions of developing and improving technological platforms to attract new customers for online grocery shopping. Further, the study suggests that online grocery retailers should apply adjusted pricing strategies using coupons and discount offers.

This paper investigates factors and its impacts on online grocery shopping intentions in post COVID-19 context. Therefore, the study uncovers the factors that add value to understanding customers' post COVID-19 online grocery shopping intentions by integrating perceived usefulness, perceived ease of use and shopping habits during COVID-19.

This research aims to fill the research gaps regarding customer preferences for digitalisation to create value for retailers and customers, as well as focus on retail change and shopping behaviour in grocery retail stores in the emerging market.

This paper contributes to the research in this area by evaluating customers' and retailers' attitudes towards digital transformation in retailing through interviews. Methodologically, 200 questionnaires were gathered, and data were analysed with the partial least squared structural equation modelling method.

The findings of this study reveal that the effect of digital transformation in the retail industry will be more apparent in an emerging market.

The paper's originality consists in understanding the future retail structure in an emerging market. Notably, focussing on business-to-consumer businesses appears helpful in distinguishing between behavioural (buying) intention and online buying behaviour (actual usage) in an emerging market.

Consumer choice theory (CCT) and the law of diminishing marginal utility help to explain shoppers that value less and prioritize needs. Additional units provide a marginal return on investment. Buying more does not mean equivalent gains for additional money spent. The researchers developed and validated the necessity shopper scale (NSS) to study need-focused shoppers.

The researchers followed standard psychometric practices to create and validate the NSS. The researchers performed item development, data collection, exploratory analysis, confirmatory factor analysis, and predictive validity analysis using survey data (N = 1,266).

Discriminant and convergent validity analyses demonstrated that the measure was distinct from existing measures. Predictive validity analysis found necessity shoppers (NS) are more likely to buy one over buy one get one half off (BOGOHO). NS were associated with a higher connection to community/group (CTCG). Higher hyperopia (i.e. disinclination to indulgence) with necessity shopping beliefs heightened this CTCG. A higher CTCG was associated with a greater likelihood to select BOGOHO.

NS (more connected to others) buy more to share with others, while buying just enough for themselves. Social connections are long-term investments involving more people and more needs to fulfill. Brands marketed with communal values and able to enhance social connections are discussed as implications to encourage NS to buy more.

This paper aims to examine the impact of the COVID-19 pandemic on the private label food products, specifically assessing the stability and changes in factors influencing purchasing decisions, and comparing pre-pandemic and post-pandemic datasets.

The study employs the Extra Tree Classifier method, a robust quantitative approach, to analyse data collected from questionnaires distributed among two distinct consumer samples. This methodological choice is explicitly adopted to provide a clear classification of factors influencing consumer preferences for private label products, surpassing conventional qualitative methods.

Despite the profound disruptions caused by the COVID-19 pandemic, this research underscores the persistent hierarchy of factors shaping consumer choices in the private label food market, showing an overall stability in consumer behaviour. At the same time, the analysis of individual variables highlights the positive increase in those related to product quality, health, taste, and communication.

The use of online surveys for data collection may introduce a self-selection bias, and the non-probabilistic sampling method could limit the generalizability of the results.

Practical implications suggest that managers in the private label industry should prioritize enhancing quality control, ensuring effective communication, and dynamically adapting strategies to meet evolving consumer preferences, with a particular emphasis on quality and health attributes.

This study contributes to the existing body of literature by providing insights into the profound transformations induced by the COVID-19 pandemic on consumer behaviour, specifically in relation to their preferences for private label food products.

While the monetary returns to education are well documented in the economics literature, the studies on non-monetary returns to education are scarce. The purpose of this study is to provide new insights into the non-market outcomes by exploring how education influences the food consumption choices of households and how these effects vary across different socio-economic groups using household-level calorie consumption data from Sri Lanka.

This study uses two waves of Household Income and Expenditure Surveys – 2006/2007 and 2016. The methods adopted in analysing the data were descriptive statistics and the OLS regression model.

The empirical results show that educated poor households pay less per calorie compared to non-educated poor households, highlighting the role of education in improving the ability to make better food choices and manage household budgets more economically.

This study informs policy-makers of the importance of education for formulating food and nutritional policies, which aim to raise the standard of living of resource-poor and vulnerable households in Sri Lanka as well as other developing countries with similar socio-economic conditions.

To the best of the authors' knowledge, this study is the first to explore the impact of education on the calorie consumption behaviour of people in the Sri Lankan context using nationwide household surveys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2022-0007

The coronavirus disease (COVID-19) pandemic continues to impact economic systems, with devastating consequences on livelihoods. Anecdotal evidence has predicted the adverse effects of COVID-19 on the livelihood of food system actors. Uganda experienced two lockdowns in March 2020 and June 2021 with varying government containment measures. During the first lockdown, fresh food market vending was deemed essential to meet urban food demand, and was consequently exempted from a total shutdown despite the ban on public and private transport. Thus, this study sought to examine the effect of COVID-19 containment measures on fresh food market vending businesses in Uganda.

Using primary data collected from fresh food market vendors, this study applied a pooled time-series estimation to examine the effect of the first lockdown COVID-19 containment measures on fresh food vendors' welfare.

The study revealed that COVID-19 had a significant negative impact on the income of fresh food vendors, with female vendors being the most affected. COVID-19 containment measures reduced the diversity of buyers, individual customers and the number of commodities traded in causing a greater impact on vendors' income.

The unavailability of data for vendors who did not return to the market at the time of data collection limits the scope of the study. Additionally, the absence of data for the second lockdown limited the analysis to only March 2020 lockdown period.

The empirical analysis highlights how vulnerabilities of different gender categories could be exacerbated by crises. The study provides empirical evidence of various market distortions caused by the COVID-19 pandemic and the disproportionate impact on women and men market vendors which calls for the need to integrate women's perspectives in future planning for market systems as well as advocating for gender-sensitive recovery responses.

The purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.

The literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.

The result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.

This study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.

This is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

Acknowledging previous scholarly focus on functional attributes in understanding technology acceptance behaviour, the current study aims to offer a novel perspective by integrating eight different dimensions of utilitarian and hedonic attributes to examine their influence in delivering a holistic web-based retail shopping experience.

The research model was tested and validated through data collected from 370 online shoppers across both hedonic and utilitarian product ranges. Hypotheses were tested using covariance-based structural equation modelling with multi-group analysis to examine the moderation effect.

The findings strongly support the model confirming eight new utilitarian and hedonic dimensions that influence web-based retail shopping behaviour. The findings also confirm that hedonic attributes remain important even for utilitarian product purchasing.

The key managerial implication is the demonstrated need to balance utilitarian and hedonic attributes in web-based retail platforms, where previously, there has been an overemphasis on functional features. Web-based retailers should consider the optimal blend of utilitarian (e.g. information quality) and hedonic (e.g. aesthetic) attributes in the design of a retail shopping site, irrespective of the product category.

This study integrates multiple dimensions of utilitarian and hedonic attributes into a single model and highlights the interplay of these attributes, thus extending the technology acceptance model. This paper also advances scholarship through its identification of attribute impact across different product categories.

Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.

Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).

A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.

Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.

Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.