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Click and collect (or grocery pickup) represents a growing part of the channel strategy of traditional off-line retailers. The aim of this study is to understand how customers develop their perceptions toward this new channel. In other words, what are the key factors explaining the long-term value creation for each “click and collect” system depending on consumers’ profiles?

On the basis of a quantitative survey of 479 respondents, this research uses confirmatory analyses based on the partial least square path modeling.

Based on the structural model, the study finds that the customers’ relations, website and pickup station are the most important factors creating value for customers whatever the internet grocery shopping model. The global conceptual model has been implemented under many variations to test the age effect and the kind of click and collect model. It is made evident that customers’ benefits vary regarding the kind of click and collect model and the age of customers.

This research allows a better understanding of the performance of the click and collect system by looking at the key factors that maximize the customers’ value and those that decrease it. Results precisely show variations of those factors according to the customer’s profile and the click and collect model.

This quantitative paper studies customer behaviors toward their usual retailer and their relationship with them. To do so, segmented approaches of the causal model are retained to provide specific recommendations.

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.

Historically supply and demand have set the rent level for shops. Turnover rents were brought over from America in the 1980s as a way for landlords to benefit from the tenant's success without having to wait for the next rent review. In addition, from a property management viewpoint, landlords soon realised the benefit of having access to the turnover information of each store as it meant landlords could easily see who and which category of goods was doing well and who was failing. However, in the 2010s, there has been a huge change in shopping habits with many retailers adopting a business model that incorporates online transactions into the use of the physical store with, for example, click and collect. As a result, some landlords are beginning to see turnover rents as redundant for retailers with strong e-commerce strategies as they are only able to capitalise on the sales that happen in the physical store. Other landlords see the turnover information as crucial for running their centres and are searching for new ways to include all relevant sales, online and in-store in the lease. This briefing discusses the issues and challenges brought about by this change in retail practices.

This practice briefing is based on a series of interviews with the principal stakeholders in the retail market.

This briefing is a review of the UK retail market at the end of the 2010s and offers insights into the market going forward.

This briefing looks at how the change in sales technique used by retailers to encourage online sales will affect the future of the turnover rent leasing model used in UK shopping centres and other retailing locations.

Landlords are seeking to adopt leasing strategies where they have access to the turnover information without any loss of profit. This briefing identifies leasing models that will, with the agreement and partnership of the tenant allow agreements that include factors such as the halo effect, click and collect and multi-channel in-store purchases in the rent.

The purpose of this paper is to apply a multi-criteria decision-making (MCDM) framework to evaluate distribution strategies for an e-tailer. An application of MCDM method, the hybrid DANP–VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model, is used for e-tailers’ distribution strategy evaluation. The choice of distribution strategies under various dimensions is evaluated.

The authors used a hybrid MCDM model to solve the decision-making framework, which combines Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based analytic network process and VIKOR method. Data were collected from the experts (e-tail manager, logistics manager, operations manager and distribution center (DC) manager) using two questionnaires, first for the influential relationship among the criteria and dimensions and second for a performance rating of each alternative (distribution strategies) against each criterion.

DANP with VIKOR method prioritizes the distribution strategies in the following order: DC shipment, drop shipment, click and collect, store shipment and click and reserve. Performance gap was calculated based on the VIKOR method to provide distribution strategies to an e-tailer under different situations. The authors infer that in developing country, product characteristics and transportation have a major influence on deciding the distribution strategy.

Decision-making framework will provide e-tail mangers a knowledge-based understanding to select the distribution strategy under the different situations related to the performance, product, e-tailer and external characteristics for smooth order fulfillment process. The insights developed by this research provide a framework for rational decision making in distribution strategy selection in e-business.

This is the first kind of a study which offers a decision framework for e-tail managers on how to choose distribution strategies under different situations which are related to the performance, product, e-tailer and external characteristics.

The omni-channel strategy provides a holistic experience during shopping by integrating online and offline channel services. In this digitalized realm, customers are more dependent on online elements for shopping. However, physical stores are still their first choice for apparel shopping. The introduction of interactive technology is one of the key elements to provide an online experience in the physical store. The purpose of this paper is to identify the impact of interactive technologies on purchase intention and its role.

This study has been conducted in Delhi using 573 customers who are using interactive technologies for shopping. A self-developed questionnaire was used to collect the data. Data was analysed using structural equation modelling through smart partial least square 3.

The results show that 46% change in purchase intention was due to mobile point of sale/digital wallet, tablet/i-pad/digital signage, smartphone and click and collect/ship from store technology. However, there was no impact of the smart mirror and in-store Wi-Fi technology on purchase intention.

This study focuses on various technologies which provide online experience at physical stores. This study offers new insights for the theoretical and business framework of omni-channel brands. These technologies could be used as key performance indicators of omni-channel retailing in future.

The objective of this piece of qualitative research is to identify the key success factors (KSFs) of the grocery “click and drive” (or drive or drive‐in) model developed by French grocery retail companies and to understand the basis of their competitive advantages.

The authors compare the conclusions of a review of the literature with an analysis of the various grocery drive‐in approaches developed in France. These approaches are studied by applying a multi‐method qualitative perspective comprising semi‐structured interviews with managers and e‐consumer focus groups.

The research confirms – with the exception of the quality of customer reception, which is particularly valued by managers and consumers – the main key success factors identified in the literature, and reveals a real consensus among the main operators on those KSFs and on the nature of the kind of core competences required in order to obtain competitive advantages.

The comparison of the real profitability of “drive‐in” sales outlets and a more precise evaluation of the advantages of an integrated multi‐channel approach would provide more accurate results. Moreover, the authors have limited this study to an analysis of the French experience. The research implies that French grocery retailers should develop, along with a more differentiated logistical system, an improved approach to customer relations marketing. Moreover, it implies that “click and drive” outlets enable traditional grocery retailers to sharpen their competitive edge.

This article provides an original analytical approach to the identification of the critical success factors of large grocery retailers developing drive‐in services. In answering this research question, the study should also help large grocery retailers to achieve their development objectives and counter the stagnation of traditional retail formats, especially the hypermarket.

Omni-channel shopping affords consumers a variety of delivery options to receive products based on their preferred times and locations. By considering consumers' contributions (physical, social and attentive efforts) in co-creating delivery services, this study investigates their preferences for parcel delivery.

A scenario-based questionnaire survey is conducted for data collection in Singapore (n = 483). Furthermore, a multinomial logistic regression is performed to assess consumers' choice mode of delivery among five alternatives, that is attended home delivery, unattended home delivery, automated self-collection locker, attended pickup point and click-and-collect.

Compared to attended home delivery, consumers who choose the alternatives are found to be more willing to contribute physical effort but less interested in responding attentively to informational updates. Efforts required for social interactions discourage consumers from choosing attended deliveries, prompting unattended alternatives (e.g. home delivery and self-collection) as more attractive choices. Additionally, socio-demographic factors and product value also influence consumers' preferences.

This study contributes to the literature by integrating the theoretical concept of consumer logistics into omni-channel studies, providing a new approach to examining consumers' channel behaviour. With detailed profiling that links product value and consumers' socio-demographics to their choice mode of delivery, the authors create practical insight into the optimal design of omni-channel distribution systems that best harness consumers' voluntary contributions.

This paper aims to initially explore the effects of online retailing on corporate real estate strategies today, examining current trends and the approaches of leading edge retailers in this evolving marketplace. The UK has the greatest proportion of online sales worldwide.

Context is provided through existing literature, and the methodology considers specific case studies. Information from financial reports, websites and evidence directly from retailers is derived to examine selected sectoral responses (food shopping, fashion retailing and department stores) to online shopping. The research considers the interface between the virtual and physical retail landscapes.

The Internet is undeniably driving change, and large retailers have responded by embracing multi-channel sales strategies in which the adapted physical store remains a central element.

The case studies are arguably limited in their market assessment by examining only large retailers, but it is these retailers who occupy much of the real estate space in shopping centres. Data on Internet sales and retail space of individual retailers are not publicly available. This paper offers a qualitative introduction into ongoing research on the evolution of Internet retailing today.

For large retailers, a multi-channel corporate sales strategy is enhanced by physical stores that can act as showrooms and collection points and enhance consumer service. Multiple retailers have a competitive advantage in the form of store networks and a recognisable brand that they can exploit to capture the sales opportunities the Internet offers.

The paper is the first to collate and analyse corporate real estate strategic responses to online retailing.

Analysis of the publisher's behavior plays a vital role in identifying fraudulent publishers in the pay-per-click model of online advertising. However, the vast amount of raw user click data with missing values pose a challenge in analyzing the conduct of publishers. The presence of high cardinality in categorical attributes with multiple possible values has further aggrieved the issue.

In this paper, gradient tree boosting (GTB) learning is used to address the challenges encountered in learning the publishers' behavior from raw user click data and effectively classifying fraudulent publishers.

The results demonstrate that the GTB effectively classified fraudulent publishers and exhibited significantly improved performance as compared to other learning methods in terms of average precision (60.5 %), recall (57.8 %) and f-measure (59.1%).

The experiments were conducted using publicly available multiclass raw user click dataset and eight other imbalanced datasets to test the GTB's generalizing behavior, while training and testing were done using 10-fold cross-validation. The performance of GTB was evaluated using average precision, recall and f-measure. The performance of GTB learning was also compared with eleven other state-of-the-art individual and ensemble classification models.

The main purpose of this research is to investigate acceptability of different delivery methods in e-grocery (home delivery, pick-up from store, pick-up from locker) and the respective willingness of customers to pay for them using a stated preference ranking experiment.

Data collected involved two countries (Greece and UK) with different level of e-grocery development and two different distribution conditions (weekly and urgent order). Rank-ordered logit model is used to analyse the ranking experiment and calculate the willingness-to-pay (WTP) measures. Delivery mode, cost and time window are used as independent variables.

Results indicated that home delivery and picking-up from locker appear to be clearly preferable than picking-up from store. However, home delivery seems to hold a stronger competitive position over the other delivery methods, especially in the weekly order and in the UK market. The pick-up from locker option appears to be a competitive delivery mode for consumers who are cost sensitive and shop under urgent conditions. Willingness to use and pay for picking-up from locker increases significantly in the context of same-day delivery.

The information provided in this study will help retailers to design and implement distribution schemes that can meet consumers' preferences for e-grocery. WTP differences among the consumer groups and the distribution conditions examined can have a considerable impact on the evaluation of marketing and pricing strategies applied by e-retailers.

Consumer preference and the respective WTP for different delivery methods in e-grocery, especially for the pick-up from locker option, have not been systematically investigated.