Journal of Retailing最新文献

Anecdotal evidence indicates a notable shift in online consumer expectations, emphasizing a desire for an enjoyable online shopping experience, beyond convenience and efficiency. This insight thus prompts key questions: Should retailers emphasize efficiency-related or experience-related website attributes, and in which contexts might one priority be superior to the other for encouraging consumer loyalty? The present study provides initial insights into the evolution of the effectiveness of different website attributes and heterogeneity in their effects. Using a rich data set, spanning vastly different contexts and time periods, the authors detect new, evolving patterns by which different website attributes relate to customer loyalty. Experience-related attributes have become more important than efficiency-related attributes in recent years, with some noteworthy contingencies, such that they are especially impactful for services (vs. products) and in cultures with long-term (vs. short-term), high (vs. low) self-indulgence, and high (vs. low) masculinity orientations. The increasing importance of experience-related attributes is driven by cultures with a low (vs. high) uncertainty avoidance. These insights in turn offer practical implications for retailers navigating the challenges associated with designing their websites to drive customer loyalty.

Retailers traditionally use a number system to match a product or service to a customer, ensuring that the customer receives the right product (e.g., a specific hot drink). However, some retailers have started to match an order by using a customer's name. Six studies, including an incentive-compatible experiment and field study, examine whether, when, and why order identification by a customer's name can either benefit or harm retailers. In contrast to prior research suggesting a negative effect of using a customer's name in marketing communications (e.g., online ads), the current research demonstrates a positive effect of identifying an order by name, which we refer to as the “Starbucks effect.” This positive effect, however, is mitigated or even backfires under specific circumstances. The results suggest that managers can use customers’ names while avoiding the use of numbers to increase customer preference for stores and service satisfaction, but with caution, especially in situations where privacy concerns may arise, even when the customer is only asked for their first name and could provide a fake name.

Hard discounters are increasingly selling national brands that previously were only sold through conventional retailers. While this trend is gaining traction across various product categories and countries, the marketing literature has provided scant empirical evidence on the market-response effects of these brands at hard discounters, while conceptual perspectives remain conflicting.

Using an empirics-first approach, the authors address this gap by offering a rich set of First Insights into the price and line-length elasticities of national brands at hard discounters, compared to conventional retailers. They analyze data from over 1,200 national-brand listings across eight European hard discounters and 84 product categories in six countries. They examine two primary differentials: the national brands’ price and line length relative to private labels within the same format (within-store gaps) and compared to their own offering in the other format (between-store gaps).

Similar to conventional retailers, price adjustments at hard discounters have a much more pronounced impact on national-brand sales than changes in line length. However, other findings at hard discounters diverge markedly from those commonly observed at conventional retailers. At hard discounters, consumers exhibit similar responsiveness to changes in both within-store and between-store gaps, unlike in conventional retail settings where within-store reference points are typically more influential than their between-store counterparts. While national brands’ responsiveness to within-store gaps is roughly the same at hard discounters and conventional retailers, their responsiveness to between-store gaps is more than twice as pronounced at hard discounters. While these findings are consistent across four product classes, they show less stability across the six countries, highlighting the need for future research to explore country-specific boundary conditions.

Retailers are increasingly using digital signage to promote price discounts. Our research explores a crucial question: Does displaying price discounts on digital screens, in addition to traditional displays, influence customer spending on discounted products? Through two field experiments in grocery stores involving 7,009 customers, we found that promoting price discounts on digital screens has a significant impact on the sales of discounted products located farther from digital screens (i.e., products outside the department in which the screens are located). However, promoting discounted products near screens (i.e., products in the department) do not have a significant effect on sales. Retailers should consider promoting discounted products on digital screens while considering the product's distance from the screen. For products near screens, traditional printed displays might be sufficient to drive sales. This unique insight can guide retailers and brand manufacturers in optimizing their in-store marketing strategies. Our study offers a valuable starting point for future research on the effects of digital signage on retail sales.

Retailers encounter consequential choices when categorizing products on a (virtual) shelf display. This research disentangles the impact of two of these categorization schemes, namely attribute-based and benefit-based product categorizations. In an attribute-based categorization, products are grouped based on similar product features; whereas in a benefit-based categorization, products are grouped based on their ability to solve various consumer problems. Across eight studies (two of which were conducted in field settings; N_total = 3418), we show that a benefit-based (vs. attribute-based) product categorization enhances mental imagery of product use, which in turn increases the anticipated consumption value, and ultimately the number of products that consumers choose to buy. Our findings also demonstrate that the effect of a benefit-based (vs. attribute-based) categorization is attenuated when consumers are already encouraged to engage in mental imagination (i.e., in the presence of imagery appeals in the store), or when they have high imagery abilities. Finally, we show that the effect of benefit (vs. attribute)-based categorization is stronger (weaker) for narrower (broader) categorizations. While this work contributes to a novel and extended view of research on product categorization and mental imagery, it also presents substantial managerial implications for retailers.

In recent years, the emergence of highly successful digital multi-brand retailers has facilitated an omnichannel distribution strategy to become the norm for brands. Rather than relying solely on these multi-brand retailers, it is necessary for companies’ omnichannel strategy to establish strong brand-owned direct-to-consumer (D2C) webstores. To help D2C brands make decisions regarding distribution channel choices, this paper investigates the circumstances under which customers prefer brands’ D2C webstores over digital multi-brand retailers and how these circumstances vary across phases of the customer journey. The results from an extensive experimental study demonstrate that, depending on the customer journey, brands’ D2C webstores can compete with digital multi-brand retailers, particularly in product categories characterized by deep assortments, the need for extensive product information, exclusive products, or a high degree of personalization.

Retailers rely on virtual assistants (VAs), such as Amazon's Alexa and chatbots, to deliver 24/7 customer service at low costs, as well as novel shopping opportunities. Despite improved VA capabilities due to artificial intelligence (AI), many retailers still struggle to convince customers to become repeat users of VAs. Therefore, to establish recommendations for how to facilitate VA use, this meta-analysis extracts 2,766 correlations from 244 independent samples of customers interacting with VAs. The results suggest that customer-, VA-, and shopping occasion–related factors all influence technology use. Price value is the strongest driver, followed by support, social influence, and anthropomorphism. Performance risk, competence, and trust matter to lesser extents. These factors exert strong indirect effects by triggering two customer responses: cognitive and emotional. Negative emotions emerge as a particularly important mediator. Finally, several VA types enhance or weaken the noted effects, including whether they are intelligent/less intelligent, commercial/noncommercial, voice-/text-based, and avatar-/non-avatar-based. The results suggest no one-size-fits-all approach applies for VAs, because their performance varies across customer responses. The current meta-analysis provides in-depth guidance for retailers seeking to select appealing VAs.