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This study seeks to explore the idea that consumers select a particular shopping mode – i.e. bricks and mortar versus online outlet – based on their perceptions about whether a product or service is best bought from one or the other. It aims to posit that this perception is associated with the importance allocated to various shopping motivation dimensions.

Data for this study were collected using a self‐administered mail survey from 689 internet‐enabled US households. They represent a 28 percent response from 2,500 households that received the survey. Extensive non‐response analysis ruled out serious bias in the data.

The results from this empirical study suggest that different shopping motivations indeed influence perceptions of service type and shopping mode congruence differently. In addition, the results also suggest that services are more likely to be associated with the online shopping mode, whereas more tangible products are likely to be associated with bricks and mortar stores.

The findings have significant implications for services retail managers of both bricks and mortar and online service outlets in the areas of segmentations, targeting, and retail mix strategies. Apparently, consumers also tend to group related services or products into homogeneous shopping baskets based on their perception of congruence between the product or service and the shopping mode – online versus bricks and mortar store. These findings should help a manager plan for retailing mix strategies, catering to various shopping motivation dimensions, thus enhancing consumer satisfaction. In addition, the results hold important implications in the areas of segmentation and targeting decisions.

To measure the extent to which wine buyers behave differently when purchasing wine online vs in two brick and mortar stores. The article aims to extend the use of the Double Jeopardy principle and empirical-based methodology to the wine category in a European retailing context.

Customer loyalty data of two brick and mortar stores and the website orders of a Belgian retailer have been gathered for a one-year period. Data have been analysed based on three specific wine attributes: country of origin, grape variety and brand. Double Jeopardy measurements have been calculated for each of these attributes.

This study enlarges the scope of use of the Dirichlet principles. All three hypotheses derived from the Double Jeopardy patterns across all attributes are confirmed. From the perspective of these principles, we demonstrated that wine buyers do not behave differently in brick and mortar vs online stores.

Very few studies have analysed and understood wine buyers' behaviour using actual purchasing data from retail stores, and none have been released comparing online and brick and mortar stores owned by the same retail brand. From that perspective, our study demystifies the way people really buy, and confirms what has been found in other product categories.

Brick-and-mortar store is an essential channel to deliver a seamless shopping experience and meet customer's dynamic needs in omni-channel retailing. This paper aims to understand customers' expectations of the integrated stores and develop a measurement scale to assess in-store service quality in omni-channel retailing.

Grounded theory methodology (GTM) is employed to obtain a clear picture of consumer expectations and preferences regarding the omni-channel brick-and-mortar integrated stores. Then, an integrated store service quality scale is proposed, refined and validated using a questionnaire survey and structural equation model (SEM).

The measurement scale is set to include seven dimensions: in-store environment, in-store technology, product information consistency, employee assistance, personalization, channel availability and instant gratification and return. The relationships among these seven dimensions and customer satisfaction and loyalty are also verified. According to SEM, product information consistency is more important for customer satisfaction while personalization contributes more to customer loyalty. The results demonstrate that by analysing the seven dimensions, retailers can better understand customers and further improve service quality.

This paper proposes a sufficient measurement scale for in-store service quality and fills the gap in omni-channel retailing by capturing its integration attribute.

The advent of grocery sales through online channels necessitates that bricks-and-mortar retailers redefine their logistics networks if they want to compete online. Because the general understanding of such bricks-and-clicks logistics systems for grocery is still limited, the purpose of this paper is to analyze the internal logistics networks used to serve customers across channels by means of an exploratory study with retailers from different contexts.

A total of 12 case companies from six European countries participated in this exploratory study. Face-to-face interviews with managers were the primary source for data collection. The heterogeneity of the sample enabled the authors to build a typology of logistics networks in grocery retailing on multiple channels and to understand the advantages of different warehousing, picking, internal transportation and last-mile delivery systems.

Bricks-and-mortar grocery retailers are leveraging their existing logistics structures to fulfill online orders. Logistics networks are mostly determined by the question of where to split case packs into customer units. In non-food logistics, channel integration is mostly seen as beneficial, but in grocery retailing, this depends heavily on product, market and retailer specifics. The data from the heterogeneous sample reveal six distinct types for cross-channel order fulfillment.

The qualitative analysis of different design options can serve as a decision support for retailers developing logistics networks to serve customers across channels.

The paper shows the internal and external factors that drive the decision-making for omni-channel (OC) logistics networks for previously store-based grocery retailers. Thereby, it makes a step toward building a contingency and configuration theory of retail networks design. It discusses in particular the differences between grocery and non-food OC retailing, last-mile delivery systems and market characteristics in the decision-making of retail networks design.

The purpose of this study is to analyse the level of adoption of in-store analytics by brick-and-mortar retailers. Web analytics technology has been widely adopted by online retailers, and the technology to gather similar information in physical stores is already available. This study explores how such technology is valued and adopted by retailers.

This study is based on interviews and a focus group of 21 retail executives using a semi-structured interview methodology. An in-store analytics service was defined, along with specific key performance indicators (KPIs) and use cases to structure respondents' feedback.

Although noteworthy differences have been found in the value of KPIs and use cases by type of business, the main finding is that none of the respondents reached the stage of a brick-and-mortar data-driven company. In-store analytics services are in the early stages of Rogers' (1983) model of diffusion of innovations. Three main reasons are presented: lack of technology knowledge, budget priority and a data culture inside the companies.

The results should encourage scholars to further investigate the drivers accelerating the adoption of these technologies. Practitioners and solution providers should strive for improvement in the simplicity of their solutions.

This study is the first to analyse the level of adoption of in-store analytics from the perspective of retailers.

Grounded on the concept of a value trade-off, the authors of this study seek to address the question of why some people visit an offline store before purchasing online. The authors offer a novel perspective by identifying and describing the perceived value drivers (benefits and sacrifices) associated with showrooming in the context of the branded apparel segment.

Data collected from 318 showrooming customers were analysed in the context of the proposed perceived value framework using the structural equation modelling method.

The results showed that enhanced product evaluation, monetary savings, smart shopper feelings and perceived enjoyment (positively) and search costs and online risk (negatively) influenced consumers' showrooming value perceptions as benefits and sacrifices associated with showrooming. Only perceived consumption delay emerged as insignificant. As expected, perceived showrooming value was identified as an important driver of showrooming intentions.

The application of this paper's findings is limited to the branded apparel segment. The model can be tested in other sectors with a larger sample size to gain deeper insights.

The findings can be utilized by brick-and-mortar retailers to retain showrooming customers.

The authors of the current research work contribute to a better understanding of showrooming by adopting a perceived-value-based perspective, which offers an alternative yet effective route for understanding showrooming.

The purpose of this paper is to investigate customer loyalty in the online-to-offline (O2O) model by conceptualizing and measuring emotion and cognition.

An online survey was used to collect 514 questionnaire responses. The data were analyzed using structural equation modeling.

Three emotional factors influence two cognitive factors, which in turn affect customer loyalty. The type of message source acts as a moderator. In addition to pleasure and arousal, dominance is a key factor of emotion. The effects of social enhancement and store environment on customer loyalty reflect the O2O model’s integration of online and offline environments.

The moderating role of the type of message source implies that marketers of brick-and-mortar stores can promote positive offline experiences to attract online customers and then encourage these customers to disseminate personal messages in their social circles. By attracting online customers through appealing m-services and retaining these customers through favorable store environments, marketers can maximize the utility of the O2O model.

Three emotional factors and two cognitive factors are conceptualized to predict customer loyalty in the O2O model. This study shows that the relationships between cognitive factors and customer loyalty are moderated by the type of message source. When check-in activity messages are sent by friends, the perception of social enhancement can lead to greater customer loyalty. In contrast, when check-in activity messages are sent by unfamiliar sources, customer loyalty is driven more by cognition of the store environment than by online interaction. The findings enrich existing knowledge of the O2O model and m-services, and have implications for researchers and marketers.

The state of interactive digital technology is evolving rapidly and has shifted the ways in which customers shop dramatically. This trend heightens the need for research that examines the latest interactive digital technology tools adopted in fashion retailing. In response, the purpose of this paper was to examine fashion retailers’ incorporation of new interactive digital technology – in both online and offline retailing formats, and including new hybrid contexts – and its results in providing new experiential quality that contributes strongly to engage with customers.

The paper first reviews the literature and then proposes the research questions. This is followed by exploratory substantiation of those propositions with the findings from case studies that examined the new interactive digital technology implemented by six leading fashion retailers.

Various digital technology tools implemented in brick-to-click, click-to-brick and brick-and-mortar retailing offer customers a variety of experiential qualities that allow them to co-create products, engage in emotion-driven sensational and personalized shopping experiences and seamless shopping virtually, all of which derive from interactive digital technology implemented to enhance customer engagement.

This research examined the implementation of interactive digital technologies across the full spectrum of the fashion retail settings above. This paper makes an original contribution by adopting a customer-centric perspective and assessing the advantages technology provides to customer’s engagement quality in shopping, which differs from the traditional firm-centric perspective that views technology as a way to innovate retailers’ operations.

This exploratory study aims to examine the prevalent triggers that motivate a premium brand purchase in an online vs offline retail format.

A binary logit analysis is used to build a predictive model to assess the likelihood of the premium brand consumer seeking an online or an offline platform. Demographic and usage-based profile of the two set of consumers is established through a chi-square analysis.

Three hundred and forty six urban consumers of premium branded apparels residing in two Indian Metros were studied. A predictive model with 89.6% accuracy was validated for distinguishing premium brand buyers who shop at brick-and-mortar store or online platforms. Quality and finish were factors sought by the online buyer, whereas autotelic need, pleasurable shopping experience and social approval were important triggers for an in-store purchase.

The study posits divergent demographics and motivational drivers that led to an online vs offline purchase. Though interesting and directional, the study results need to be examined across geographies and categories for establishing the generalizability of the findings.

The study findings indicate that premium brand manufacturers can devise an omni-channel strategy that is largely tilted toward the online platform, as the quality conscious and brand aware consumer is confident and thus open to an online purchase. The implication for the physical outlet on the other hand is to ensure exclusive store atmospherics and knowledgeable but non-intrusive sales personnel.

The study is unique as it successfully builds a predictive model to forecast online vs offline purchase decisions among urban millennials.

This study aims to investigate the moderating effects of brick-and-mortar (BM) store characteristics and customer satisfaction on the relationship between ship-to-store (STS) retailing and BM store performance in an emerging economy. The purpose is to explore how BM store characteristics and customer satisfaction influence online buying behaviour when customers visit the stores to pick up their products.

This study collected secondary longitudinal data from 615 BM stores from one of Brazil's largest retailers and performed a panel-data regression analysis using the following moderating variables: customer satisfaction with BM stores, BM store's size, convenience and inventory transparency.

Customer satisfaction with BM stores moderates the effect of STS transactions on the revenue per store. Results also show that BM store's convenience, size and inventory transparency moderate STS online customers' impact on BM store cross-sales.

The STS strategy can increase online and BM store performance. Some BM store characteristics and customer satisfaction influence online customers to buy more products when they visit BM stores to pick up their products, providing a more complex model for the relationship between STS strategy and BM store performance.

Companies in emerging economies can use the BM store more strategically in combination with the STS strategy to increase overall retailer performance. By managing some BM store characteristics, managers can improve retail sales.

This study demonstrates how new moderating factors expand the understanding of the relationship between online and physical retailing in emerging economies. Also, the panel data regression results control for extraneous variables and provide more robust evidence of the relationships observed.