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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.

This study investigates the factors influencing re-usage intention of online and mobile grocery shopping among young adult consumers in South Africa.

Data were collected from selected young adult participants using a stratified probability sampling strategy. Smart PLS was used to analyse the data.

The findings of the study indicate that perceived usefulness (PU), peer review (PR) and attitude (ATT) positively influence continuance intention (CI).

In line with the available literature, there are few prior post-adoption studies that delineate the influence of individual characteristics on digital commerce usage activities. There is high mobile penetration as a result of positive digital commerce and mobile application usage and adoption, creating the need to investigate and better understand the drivers behind, not just adoption and usage, but continued use of digital commerce platforms and applications. Since the sample size is relatively small, further future research studies can test the same model with bigger sample sizes to assess generalisability of the results in different locations.

This study adds to the current literature by concentrating on the extent to which systems and marketing elements influence young adult customers' intention to continue using online and mobile grocery shopping platforms in South Africa.

The study adds value from a theoretical standpoint, contributing to the antecedent factors of the technology acceptance model (TAM), theory of reasoned action (TRA) and stimulus-organism-response (S-O-R) model and giving marketing academics insights into what aspects drive re-use of online and mobile grocery shopping and on what should be the focus.

The pandemic impacted consumers' shopping processes, leading them to approach the online channel for grocery shopping for the first time. The paper contributes to the retailing literature by identifying different grocery shopper segments willing to switch online moved by heterogeneous motivations. Integrating the technology acceptance model 2 (TAM-2) and the protection motivation theory (PMT), this study identifies technology-related and Covid-related motivations jointly impacting channel switching.

A mixture regression model was estimated on the 370 valid questionnaires, filled out by Italian shoppers, delivering four internally consistent segments.

The results reveal the existence of four segments willing to switch towards the online channel for grocery shopping in the aftermath of the pandemic. Utilitarian shoppers would switch online as they consider the online channel useful and easy to use. Responsive shoppers will prefer the online channel driven by the fear of being infected in-store. Novel enthusiasts show interest in the online channel to not catch the virus and cope with emotional fear, although they consider online shopping as an enjoyable and useful activity as well. Smart shoppers consider online shopping as an easy-to-use alternative for their grocery purchases.

This paper identifies technology-related and Covid-related motivations jointly impacting shoppers' channel switching to online and presents a novel method – i.e. mixture regression – allowing for the identification of shopper segments motivated by different reasons, both emotional and utilitarian, to switch towards the online channel for their grocery shopping. Among other motivations, the fear of Covid-19 is identified as a relevant motivation to switch to online.

Twenty-first century online retailing has reshaped the retail landscape. Grocery shopping is emerging as the next fastest growing category in online retailing in the UK, having implications for the channels we use to purchase goods. Using Sainsbury’s data, the authors create a bespoke set of grocery click&collect catchments. The resultant catchments allow an investigation of performance within the emerging channel of grocery click&collect. The paper aims to discuss these issues.

The spatial interaction method of “Huff gravity modeling” is applied in a semi-automated approach, used to calculate grocery click&collect catchments for 95 Sainsbury’s stores in England. The catchments allow investigation of the spatial variation and particularly rural-urban differences. Store and catchment characteristics are extracted and explored using ordinary least squares regression applied to investigate “demand per day” (a confidentiality transformed revenue value) as a function of competition, performance and geodemographic factors.

The findings show that rural stores exhibit a larger catchment extent for grocery click&collect when compared with urban stores. Linear regression finds store characteristics as having the greatest impact on demand per day, adhering to wider retail competition literature. Conclusions display a need for further investigation (e.g. quantifying loyalty).

New insights are contributed at a national level for grocery click&collect, as well as e-commerce, multichannel shopping and retail geography. Areas for further investigation are identified, particularly quantitatively capturing brand loyalty. The research has commercial impact as the catchments are being applied by Sainsbury’s to decide the next 100 stores and plan for the next five years of their grocery click&collect offering.

Despite retail digitisation and research efforts focussed on online and omnichannel shopping, there is insufficient knowledge regarding retail patronage formation in the grocery category, where in-store sales dominate. This study analyses the retail patronage formation in grocery in-store fill-in shopping.

The authors designed a questionnaire to measure retail patronage behaviour, consumer satisfaction (CS), store attributes evaluation and e-retail usage. Then, the authors analysed the path structure for retail patronage behaviour formation using structural equation modelling. Additionally, they performed a mediation analysis using the bootstrap method and a moderation analysis based on a chi-square difference test.

This study provides three main findings. First, the authors' model has two ways to increase Share-of-Wallet (SOW). One is to increase Share-of-Visits (SOV) and another is to increase CS amongst non-users of e-retailing. Second, the results of the moderation analysis suggest the influence of customers' use or non-use of e-retailing on SOW formation. Third, service evaluation plays an interesting role in the overall model: the lower the assessment of service, the higher the SOV; the higher the evaluation of service, the greater the CS; the greater the CS, the higher the SOV.

The authors proposed the framework for the relative retail patronage formation in grocery fill-in shopping to examine the relationship between two relative patronage indicators (SOW and SOV) in the path structure and the mediating effect of CS and the moderating effect of e-retailing usage on retail patronage formation.

In the rapidly growing e-grocery segment, unattended delivery is an emerging practice with the potential to offer a superior delivery experience. The purpose of this study is to contribute to the body of knowledge for unattended grocery delivery services by empirically identifying and describing the forms and determinants of customer expectations.

A multiple case study of potential early adopters was conducted to explore customer expectations of unattended grocery delivery services. Empirical data collected from direct observations and semi-structured interviews with ten Swedish households were coded and put through a single-case as well as a cross-case analysis revealing emerging patterns from which propositions were formed.

The iteration of theory and data in the case study resulted in a conceptual model of service expectations and determinants, containing six propositions. The study reveals a clear pattern that consumers expect to save time, gain flexibility and benefit from the ease of use of the service, while they predict sufficient security. Moreover, consumers’ desire open access features from retailers and service providers, integrated product returns service and nondescript hardware designs. The findings suggest that these service expectations are determined by personal needs, technology literacy and situational factors. The identified personal needs are stress reduction, limiting social interaction and increasing spare time.

To support further theory development, this study presents six propositions for the types, forms and determinants of customer expectations of unattended grocery delivery.

This study provides managers with up-to-date insights into customer expectations and offers guidance in designing and developing unattended grocery delivery services.

This study contains the first in-depth analysis of customer expectations of unattended grocery delivery services, which are increasingly used for last mile e-grocery delivery.

The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

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.

The Covid-19 pandemic has a strong effect on societies, business and consumers. Governments have taken measures to reduce the spread of the pandemic, such as social distancing and lockdowns. The latter has also resulted in a temporary closure of physical stores for “non-essential” retailing. Covid-19 thus has a profound impact on how people live. The period of relative isolation, social distancing and economic uncertainty changes the way we behave. New consumer behaviors span all areas of life, from how we work to how we shop to how we entertain ourselves. These shifts have important implications for retailers. This paper aims to discuss the potential structural effect on shopping behavior and retailing when Covid-19 measures are no longer needed and society moves back to a normal situation.

The paper synthesizes empirical and conceptual literature on the consequences of COVID-19 and introduces a conceptual framework along with a set of predictions that can be investigated with empirical data.

This study suggests that Covid-19 shapes both consumer needs and behavior and how retailers respond to these changes. Moreover, it suggests that this will not only affect market outcomes (i.e. retail sales and market share online) but also firm outcomes (i.e. customer experience, firm sales) and importantly the competition between online and offline retailers.

In the conceptual framework, this study aims to advance knowledge on longer-term outcomes (vs immediate outcomes such as panic buying) and how COVID-19 is changing the competitive landscape of retail.