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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.

The purpose of this paper is to investigate how grocery retailers configure their online fulfilment centres (OFC) as they move towards an omni-channel structure and what contextual factors influence their decisions.

An exploratory case study with three grocery retailers in the Nordic countries was conducted. The study investigates the current OFC configurations and identifies nine important contextual factors.

This study shows the importance of understanding the changes that omni-channel retailing entails for an OFC configuration. Nine contextual factors were identified. Several of the factors are found in previous theory, but this paper extends the knowledge of how they affect the configuration of an OFC in grocery retail. The changes in, for example, order characteristics create different requirements for picking, packing, sorting and shipping when compared with traditional distribution centres (DC). Although representing a separate flow for online fulfilment, OFC configuration depends on how the other logistics flows from the DC to stores are designed.

To support further theory development, nine contextual factors and their relationship to OFC configurations are proposed.

This study provides managerial value in two ways. First, grocery retailers with one or more OFCs can benchmark existing solutions using the empirical case descriptions. Second, the findings provide grocery retailers with knowledge of how to configure an OFC.

The literature lacks a holistic approach towards how grocery retailers configure their OFCs and what factors affect these decisions. This study provides the first in-depth analysis of how the omni-channel context affects the configuration of all the aspects of an OFC.

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.

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 purpose of this paper is to investigate the role of the retailer’s brand strength as a potential predictor of loyalty. It also examines the role of customer satisfaction (CS) to the retailer’s loyalty as well as its impact on the retailer’s brand strength.

The study was conducted in the grocery context and in a market under recession using the European Customer Satisfaction Index (ECSI) model. Data were collected through a telephone survey from 2,000 participants responsible for the household grocery shopping with a quota of 250 respondents from each of the leading grocery retailers in Greece. A formative measurement model was developed and the collected data were analyzed using partial least square path modeling.

The findings revealed that the strength of the retailer’s brand and CS influence retail loyalty and that brand strength mediate the strength of CS to loyalty. Results also suggested that the expectations and the perceptions toward the retailer’s product offering are the most important drivers of CS and loyalty. Thus, the study has proved the importance of the functional store attributes to CS and loyalty in the grocery store setting.

Research examining the suitability of the ECSI model in the grocery setting and in a market under economic crisis is scarce. This paper addresses these shortcomings by examining a customer loyalty model which incorporates the brand strength construct and investigates the role of brand strength as a potential predictor of loyalty as well as the role of CS in the brand strength and loyalty.

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 success of last-mile delivery is dependent on consumer acceptance of such services, yet little is known about unattended delivery experience. This paper's purpose is to provide empirically based understanding of customer experience dimensions in unattended home delivery.

Using an engaged scholarship approach, this field study investigated nine households that actively used an unattended delivery service for a period of six to nine months. Empirical data were collected primarily from in-depth interviews.

The study demonstrates that unattended delivery experience is a multidimensional construct that comprises consumers' cognitive, emotional, behavioral, sensorial, physical and social responses to the service. The empirical evidence provides rich descriptions of each customer experience dimension, and the research offers a framework and propositions on unattended delivery experience.

The results guide and support managers in assessing and developing delivery services using a consumer-centric approach to enhance customer experience.

This research is one of the first to address unattended delivery experience by providing a comprehensive, empirically grounded framework. The results provide a foundation for future investigations of last-mile delivery experience dimensions.

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.

This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study examines the influence of hard apple cider attributes and consumer characteristics on consumer preferences for local hard apple cider.

Data from a 2019 survey of 875 Tennessee consumers regarding their preferences for a local hard apple cider were obtained. Probit estimates were used to calculate the premium consumers were willing to pay for a locally made hard apple cider and factors influencing this premium. A multivariate probit was used to ascertain factors influencing the importance of attributes (e.g. heirloom apples, sweetness/dryness, sparking/still and no preservatives added) on local hard apple cider preference.

Consumers would pay a $3.22 premium for local hard apple cider compared with a $6.99 reference product. Local foods preferences, urbanization, weekly purchases of other alcoholic beverages and shopping venues influenced premium amounts. Other important attributes were sweetness/dryness and no preservatives. Influence of consumer demographics suggests targeted marketing of local ciders could be successful.

Few studies examine consumer preferences for hard apple ciders. This study represents a cross-sectional analysis of the premium consumers would pay for local hard apple ciders and the importance of other hard apple cider attributes.